From 2745956bc01d2c58775033f2867d1e7aa4e800fb Mon Sep 17 00:00:00 2001
From: Ashwin Bharambe <ashwin.bharambe@gmail.com>
Date: Tue, 4 Nov 2025 16:22:04 -0800
Subject: [PATCH] chore(ci): remove unused recordings

Added a script to cleanup recordings. While doing this, moved the CI
matrix generation to a separate script so there is a single source of
truth for the matrix.

Ran the cleanup script as:

```
PYTHONPATH=. python scripts/cleanup_recordings.py
```

We can eventually put this as part of the pre-commit workflow to ensure
that the recordings are always up to date and that no stale recordings
are left in the repo.
---
 .github/workflows/integration-tests.yml       |   35 +-
 scripts/cleanup_recordings.py                 |  274 ++
 scripts/generate_ci_matrix.py                 |   59 +
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 tests/integration/suites.py                   |   13 +
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 ...536f34da3ce7e80eba86bec16d231aa347d00.json |   75 -
 497 files changed, 369 insertions(+), 370287 deletions(-)
 create mode 100755 scripts/cleanup_recordings.py
 create mode 100755 scripts/generate_ci_matrix.py
 delete mode 100644 tests/integration/batches/recordings/1d782697e7261920e2c21babd28d5126609fdc27c61a1d793792e713a48f6368.json
 delete mode 100644 tests/integration/batches/recordings/37b8d062efc39eaa4ac3438f5102044a29fd1e9b844ead2f066a1fb25c85672c.json
 delete mode 100644 tests/integration/inference/recordings/02bc4eaa12503edd2af031c7f243b280703e4ed17024e21641119530cc78bd0e.json
 delete mode 100644 tests/integration/inference/recordings/0483665572c6b72adda44aa0b31c105c4a5ac4da26d514c61fbd319910e1ce05.json
 delete mode 100644 tests/integration/inference/recordings/0ff4361a4687d14795386a4499d8fcc04772020ae9d840ceae4fb014f620593b.json
 delete mode 100644 tests/integration/inference/recordings/166dbff8b991d40d060f9307fc2a67fc24e29dc542fdce9611756d28403e4e86.json
 delete mode 100644 tests/integration/inference/recordings/1774e408dada8623a932f20fd67ab722cbff2a2213309d8a33ec2ed5a444e5d4.json
 delete mode 100644 tests/integration/inference/recordings/1f3149657717e1cca83f08af67b9f34993a49de31349b11ce13c5d0465ca5f6a.json
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diff --git a/.github/workflows/integration-tests.yml b/.github/workflows/integration-tests.yml
index ba2ffc5fd..328a3f6bd 100644
--- a/.github/workflows/integration-tests.yml
+++ b/.github/workflows/integration-tests.yml
@@ -23,6 +23,7 @@ on:
       - '.github/actions/setup-test-environment/action.yml'
       - '.github/actions/run-and-record-tests/action.yml'
       - 'scripts/integration-tests.sh'
+      - 'scripts/generate_ci_matrix.py'
   schedule:
     # If changing the cron schedule, update the provider in the test-matrix job
     - cron: '0 0 * * *'  # (test latest client) Daily at 12 AM UTC
@@ -44,8 +45,27 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
+  generate-matrix:
+    runs-on: ubuntu-latest
+    outputs:
+      matrix: ${{ steps.set-matrix.outputs.matrix }}
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+
+      - name: Generate test matrix
+        id: set-matrix
+        run: |
+          # Generate matrix from CI_MATRIX in tests/integration/suites.py
+          # Supports schedule-based and manual input overrides
+          MATRIX=$(python3 scripts/generate_ci_matrix.py \
+            --schedule "${{ github.event.schedule }}" \
+            --test-setup "${{ github.event.inputs.test-setup }}")
+          echo "matrix=$MATRIX" >> $GITHUB_OUTPUT
+          echo "Generated matrix: $MATRIX"
 
   run-replay-mode-tests:
+    needs: generate-matrix
     runs-on: ubuntu-latest
     name: ${{ format('Integration Tests ({0}, {1}, {2}, client={3}, {4})', matrix.client-type, matrix.config.setup, matrix.python-version, matrix.client-version, matrix.config.suite) }}
 
@@ -56,18 +76,9 @@ jobs:
         # Use Python 3.13 only on nightly schedule (daily latest client test), otherwise use 3.12
         python-version: ${{ github.event.schedule == '0 0 * * *' && fromJSON('["3.12", "3.13"]') || fromJSON('["3.12"]') }}
         client-version: ${{ (github.event.schedule == '0 0 * * *' || github.event.inputs.test-all-client-versions == 'true') && fromJSON('["published", "latest"]') || fromJSON('["latest"]') }}
-        # Define (setup, suite) pairs - they are always matched and cannot be independent
-        # Weekly schedule (Sun 1 AM): vllm+base
-        # Input test-setup=ollama-vision: ollama-vision+vision
-        # Default (including test-setup=ollama): ollama+base, ollama-vision+vision, gpt+responses
-        config: >-
-          ${{
-            github.event.schedule == '1 0 * * 0'
-              && fromJSON('[{"setup": "vllm", "suite": "base"}]')
-            || github.event.inputs.test-setup == 'ollama-vision'
-              && fromJSON('[{"setup": "ollama-vision", "suite": "vision"}]')
-            || fromJSON('[{"setup": "ollama", "suite": "base"}, {"setup": "ollama-vision", "suite": "vision"}, {"setup": "gpt", "suite": "responses"}]')
-          }}
+        # Test configurations: Generated from CI_MATRIX in tests/integration/suites.py
+        # See scripts/generate_ci_matrix.py for generation logic
+        config: ${{ fromJSON(needs.generate-matrix.outputs.matrix).include }}
 
     steps:
       - name: Checkout repository
diff --git a/scripts/cleanup_recordings.py b/scripts/cleanup_recordings.py
new file mode 100755
index 000000000..e0f62d1a2
--- /dev/null
+++ b/scripts/cleanup_recordings.py
@@ -0,0 +1,274 @@
+#!/usr/bin/env python3
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+"""
+Clean up unused test recordings based on CI test collection.
+
+This script:
+1. Resolves the CI test matrix by combining the default CI_MATRIX with scheduled overrides
+2. Uses pytest --collect-only with --json-report to gather all test IDs that run in CI
+3. Compares against existing recordings to identify unused ones
+4. Optionally deletes unused recordings
+
+Usage:
+    # Dry run - see what would be deleted
+    ./scripts/cleanup_recordings.py
+
+    # Save manifest of CI test IDs for inspection
+    ./scripts/cleanup_recordings.py --manifest ci_tests.txt
+
+    # Actually delete unused recordings
+    ./scripts/cleanup_recordings.py --delete
+"""
+
+import argparse
+import json
+import os
+import subprocess
+import tempfile
+from collections import defaultdict
+from pathlib import Path
+
+REPO_ROOT = Path(__file__).parent.parent
+from tests.integration.suites import CI_MATRIX  # noqa: E402
+
+# Additional scheduled CI configurations (keep in sync with scripts/generate_ci_matrix.py)
+ADDITIONAL_CI_CONFIGS = [
+    {"suite": "base", "setup": "vllm"},  # Weekly vLLM coverage
+]
+
+
+def load_ci_configs() -> list[dict[str, str]]:
+    """Return all (suite, setup) combinations exercised in CI."""
+
+    configs: list[dict[str, str]] = []
+    seen: set[tuple[str, str]] = set()
+
+    def add(entry: dict[str, str]) -> None:
+        suite = entry.get("suite")
+        setup = entry.get("setup")
+        if not suite or not setup:
+            raise RuntimeError(f"Invalid CI matrix entry: {entry}")
+        key = (suite, setup)
+        if key in seen:
+            return
+        seen.add(key)
+        configs.append({"suite": suite, "setup": setup})
+
+    for entry in CI_MATRIX:
+        add(entry)
+    for entry in ADDITIONAL_CI_CONFIGS:
+        add(entry)
+
+    return configs
+
+
+def collect_ci_tests(ci_configs: list[dict[str, str]]):
+    """Collect all test IDs that would run in CI using --collect-only with JSON output."""
+
+    all_test_ids = set()
+
+    for config in ci_configs:
+        print(f"Collecting tests for suite={config['suite']}, setup={config['setup']}...")
+
+        # Create a temporary file for JSON report
+        with tempfile.NamedTemporaryFile(mode="w", suffix=".json", delete=False) as f:
+            json_report_file = f.name
+
+        try:
+            # Configure environment for collection run
+            env = os.environ.copy()
+            env["PYTEST_ADDOPTS"] = f"--json-report --json-report-file={json_report_file}"
+            repo_path = str(REPO_ROOT)
+            existing_path = env.get("PYTHONPATH", "")
+            env["PYTHONPATH"] = f"{repo_path}{os.pathsep}{existing_path}" if existing_path else repo_path
+
+            result = subprocess.run(
+                [
+                    "./scripts/integration-tests.sh",
+                    "--collect-only",
+                    "--suite",
+                    config["suite"],
+                    "--setup",
+                    config["setup"],
+                ],
+                capture_output=True,
+                text=True,
+                cwd=REPO_ROOT,
+                env=env,
+            )
+
+            if result.returncode != 0:
+                raise RuntimeError(
+                    "Test collection failed.\n"
+                    f"Command: {' '.join(result.args)}\n"
+                    f"stdout:\n{result.stdout}\n"
+                    f"stderr:\n{result.stderr}"
+                )
+
+            # Parse JSON report to extract test IDs
+            try:
+                with open(json_report_file) as f:
+                    report = json.load(f)
+
+                # The "collectors" field contains collected test items
+                # Each collector has a "result" array with test node IDs
+                for collector in report.get("collectors", []):
+                    for item in collector.get("result", []):
+                        # The "nodeid" field is the test ID
+                        if "nodeid" in item:
+                            all_test_ids.add(item["nodeid"])
+
+                print(f"  Collected {len(all_test_ids)} test IDs so far")
+
+            except (json.JSONDecodeError, FileNotFoundError) as e:
+                print(f"  Warning: Failed to parse JSON report: {e}")
+                continue
+
+        finally:
+            # Clean up temp file
+            if os.path.exists(json_report_file):
+                os.unlink(json_report_file)
+
+    print(f"\nTotal unique test IDs collected: {len(all_test_ids)}")
+    return all_test_ids
+
+
+def get_base_test_id(test_id: str) -> str:
+    """Extract base test ID without parameterization.
+
+    Example:
+      'tests/integration/inference/test_foo.py::test_bar[param1-param2]'
+      -> 'tests/integration/inference/test_foo.py::test_bar'
+    """
+    return test_id.split("[")[0] if "[" in test_id else test_id
+
+
+def find_all_recordings():
+    """Find all recording JSON files."""
+    return list((REPO_ROOT / "tests/integration").rglob("recordings/*.json"))
+
+
+def analyze_recordings(ci_test_ids, dry_run=True):
+    """Analyze recordings and identify unused ones."""
+
+    # Use full test IDs with parameterization for exact matching
+    all_recordings = find_all_recordings()
+    print(f"\nTotal recording files: {len(all_recordings)}")
+
+    # Categorize recordings
+    used_recordings = []
+    unused_recordings = []
+    shared_recordings = []  # model-list endpoints without test_id
+    parse_errors = []
+
+    for json_file in all_recordings:
+        try:
+            with open(json_file) as f:
+                data = json.load(f)
+
+            test_id = data.get("test_id", "")
+
+            if not test_id:
+                # Shared/infrastructure recordings (model lists, etc)
+                shared_recordings.append(json_file)
+                continue
+
+            # Match exact test_id (with full parameterization)
+            if test_id in ci_test_ids:
+                used_recordings.append(json_file)
+            else:
+                unused_recordings.append((json_file, test_id))
+
+        except Exception as e:
+            parse_errors.append((json_file, str(e)))
+
+    # Print summary
+    print("\nRecording Analysis:")
+    print(f"  Used in CI:     {len(used_recordings)}")
+    print(f"  Shared (no ID): {len(shared_recordings)}")
+    print(f"  UNUSED:         {len(unused_recordings)}")
+    print(f"  Parse errors:   {len(parse_errors)}")
+
+    if unused_recordings:
+        print("\nUnused recordings by test:")
+
+        # Group by base test ID
+        by_test = defaultdict(list)
+        for file, test_id in unused_recordings:
+            base = get_base_test_id(test_id)
+            by_test[base].append(file)
+
+        for base_test, files in sorted(by_test.items()):
+            print(f"\n  {base_test}")
+            print(f"    ({len(files)} recording(s))")
+            for f in files[:3]:
+                print(f"      - {f.relative_to(REPO_ROOT / 'tests/integration')}")
+            if len(files) > 3:
+                print(f"      ... and {len(files) - 3} more")
+
+    if parse_errors:
+        print("\nParse errors:")
+        for file, error in parse_errors[:5]:
+            print(f"  {file.relative_to(REPO_ROOT)}: {error}")
+        if len(parse_errors) > 5:
+            print(f"  ... and {len(parse_errors) - 5} more")
+
+    # Perform cleanup
+    if not dry_run:
+        print(f"\nDeleting {len(unused_recordings)} unused recordings...")
+        for file, _ in unused_recordings:
+            file.unlink()
+            print(f"  Deleted: {file.relative_to(REPO_ROOT / 'tests/integration')}")
+        print("✅ Cleanup complete")
+    else:
+        print("\n(Dry run - no files deleted)")
+        print("\nTo delete these files, run with --delete")
+
+    return len(unused_recordings)
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Clean up unused test recordings based on CI test collection",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=__doc__,
+    )
+    parser.add_argument("--delete", action="store_true", help="Actually delete unused recordings (default is dry-run)")
+    parser.add_argument("--manifest", help="Save collected test IDs to file (optional)")
+
+    args = parser.parse_args()
+
+    print("=" * 60)
+    print("Recording Cleanup Utility")
+    print("=" * 60)
+
+    ci_configs = load_ci_configs()
+
+    print(f"\nDetected CI configurations: {len(ci_configs)}")
+    for config in ci_configs:
+        print(f"  - suite={config['suite']}, setup={config['setup']}")
+
+    # Collect test IDs from CI configurations
+    ci_test_ids = collect_ci_tests(ci_configs)
+
+    if args.manifest:
+        with open(args.manifest, "w") as f:
+            for test_id in sorted(ci_test_ids):
+                f.write(f"{test_id}\n")
+        print(f"\nSaved test IDs to: {args.manifest}")
+
+    # Analyze and cleanup
+    unused_count = analyze_recordings(ci_test_ids, dry_run=not args.delete)
+
+    print("\n" + "=" * 60)
+    if unused_count > 0 and not args.delete:
+        print("Run with --delete to remove unused recordings")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/scripts/generate_ci_matrix.py b/scripts/generate_ci_matrix.py
new file mode 100755
index 000000000..57afd6113
--- /dev/null
+++ b/scripts/generate_ci_matrix.py
@@ -0,0 +1,59 @@
+#!/usr/bin/env python3
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+"""
+Generate CI test matrix from suites.py with schedule/input overrides.
+
+This script is used by .github/workflows/integration-tests.yml to generate
+the test matrix dynamically based on the CI_MATRIX definition in suites.py.
+"""
+
+import json
+import sys
+from pathlib import Path
+
+# Add tests/integration to path
+sys.path.insert(0, str(Path(__file__).parent.parent / "tests/integration"))
+
+from suites import CI_MATRIX
+
+
+def generate_matrix(schedule="", test_setup=""):
+    """
+    Generate test matrix based on schedule or manual input.
+
+    Args:
+        schedule: GitHub cron schedule string (e.g., "1 0 * * 0" for weekly)
+        test_setup: Manual test setup input (e.g., "ollama-vision")
+
+    Returns:
+        Matrix configuration as JSON string
+    """
+    # Weekly vllm test on Sunday
+    if schedule == "1 0 * * 0":
+        matrix = [{"suite": "base", "setup": "vllm"}]
+    # Manual input for specific setup
+    elif test_setup == "ollama-vision":
+        matrix = [{"suite": "vision", "setup": "ollama-vision"}]
+    # Default: use CI_MATRIX from suites.py
+    else:
+        matrix = CI_MATRIX
+
+    # GitHub Actions expects {"include": [...]} format
+    return json.dumps({"include": matrix})
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser(description="Generate CI test matrix")
+    parser.add_argument("--schedule", default="", help="GitHub schedule cron string")
+    parser.add_argument("--test-setup", default="", help="Manual test setup input")
+
+    args = parser.parse_args()
+
+    print(generate_matrix(args.schedule, args.test_setup))
diff --git a/tests/integration/batches/recordings/1d782697e7261920e2c21babd28d5126609fdc27c61a1d793792e713a48f6368.json b/tests/integration/batches/recordings/1d782697e7261920e2c21babd28d5126609fdc27c61a1d793792e713a48f6368.json
deleted file mode 100644
index c96b0bde8..000000000
--- a/tests/integration/batches/recordings/1d782697e7261920e2c21babd28d5126609fdc27c61a1d793792e713a48f6368.json
+++ /dev/null
@@ -1,1206 +0,0 @@
-{
-  "test_id": "tests/integration/batches/test_batches.py::TestBatchesIntegration::test_batch_e2e_embeddings[emb=ollama/all-minilm:l6-v2]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "How are you?",
-        "Good morning",
-        "Have a great day"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
-        "data": [
-          {
-            "embedding": [
-              0.0069620265,
-              0.01094919,
-              0.08730505,
-              0.08677503,
-              0.026604276,
-              -0.067699,
-              0.072650306,
-              -0.025137117,
-              -0.08260308,
-              0.016288513,
-              -0.0059634144,
-              0.021893453,
-              -0.014844859,
-              0.026276434,
-              0.043832693,
-              -0.052769832,
-              0.058766205,
-              -0.12824233,
-              -0.09479588,
-              0.039485294,
-              -0.11324302,
-              0.038061623,
-              0.029431377,
-              0.11588057,
-              -0.026578259,
-              -0.004148723,
-              -0.042966843,
-              -0.007125199,
-              0.021863377,
-              -0.066874556,
-              -0.12788324,
-              0.04219816,
-              -0.08644679,
-              -0.03378584,
-              -0.0387981,
-              -0.012082744,
-              -0.01377726,
-              -0.109074354,
-              -0.015455687,
-              0.00926984,
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-              -0.030273998,
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diff --git a/tests/integration/batches/recordings/37b8d062efc39eaa4ac3438f5102044a29fd1e9b844ead2f066a1fb25c85672c.json b/tests/integration/batches/recordings/37b8d062efc39eaa4ac3438f5102044a29fd1e9b844ead2f066a1fb25c85672c.json
deleted file mode 100644
index 4487ba042..000000000
--- a/tests/integration/batches/recordings/37b8d062efc39eaa4ac3438f5102044a29fd1e9b844ead2f066a1fb25c85672c.json
+++ /dev/null
@@ -1,422 +0,0 @@
-{
-  "test_id": "tests/integration/batches/test_batches.py::TestBatchesIntegration::test_batch_e2e_embeddings[emb=ollama/all-minilm:l6-v2]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": "Hello world",
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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index 15a8ba473..000000000
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-        "model": "all-minilm:l6-v2",
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diff --git a/tests/integration/inference/recordings/2e4f0cbbc7bce72387e0abc9c8f003c863747faf23b394c790098feef0652fea.json b/tests/integration/inference/recordings/2e4f0cbbc7bce72387e0abc9c8f003c863747faf23b394c790098feef0652fea.json
deleted file mode 100644
index ed9a5b816..000000000
--- a/tests/integration/inference/recordings/2e4f0cbbc7bce72387e0abc9c8f003c863747faf23b394c790098feef0652fea.json
+++ /dev/null
@@ -1,421 +0,0 @@
-{
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-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": "Test encoding format",
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/inference/recordings/2efc033e9a1b66980245aabc44b6d7fe2509aafa52d6aa19eee2cde5245cd3b9.json b/tests/integration/inference/recordings/2efc033e9a1b66980245aabc44b6d7fe2509aafa52d6aa19eee2cde5245cd3b9.json
deleted file mode 100644
index b1e8cc975..000000000
--- a/tests/integration/inference/recordings/2efc033e9a1b66980245aabc44b6d7fe2509aafa52d6aa19eee2cde5245cd3b9.json
+++ /dev/null
@@ -1,422 +0,0 @@
-{
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-    "headers": {},
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-      "input": "Test user parameter",
-      "encoding_format": "base64",
-      "user": "test-user-123"
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-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/inference/recordings/54f1997f5ea8c22d5655cd5718f3c5c19da209925e3df713287db28e7830f02b.json b/tests/integration/inference/recordings/54f1997f5ea8c22d5655cd5718f3c5c19da209925e3df713287db28e7830f02b.json
deleted file mode 100644
index 9a6027d76..000000000
--- a/tests/integration/inference/recordings/54f1997f5ea8c22d5655cd5718f3c5c19da209925e3df713287db28e7830f02b.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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index c5bc96f11..000000000
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diff --git a/tests/integration/inference/recordings/b297beb1d35f63da20522290488dd51cc2b20b158bb1f3c65b0b6a9476d7f6be.json b/tests/integration/inference/recordings/b297beb1d35f63da20522290488dd51cc2b20b158bb1f3c65b0b6a9476d7f6be.json
deleted file mode 100644
index 2522852f9..000000000
--- a/tests/integration/inference/recordings/b297beb1d35f63da20522290488dd51cc2b20b158bb1f3c65b0b6a9476d7f6be.json
+++ /dev/null
@@ -1,421 +0,0 @@
-{
-  "test_id": "tests/integration/inference/test_openai_embeddings.py::test_openai_embeddings_different_inputs_different_outputs[openai_client-emb=ollama/all-minilm:l6-v2]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": "This is the first text",
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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-        "model": "all-minilm:l6-v2",
-        "object": "list",
-        "usage": {
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-    "is_streaming": false
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diff --git a/tests/integration/inference/recordings/d28e69b9ec21c644f32ac1a57ac99371068a68248f010f146e8a744cc8eba9af.json b/tests/integration/inference/recordings/d28e69b9ec21c644f32ac1a57ac99371068a68248f010f146e8a744cc8eba9af.json
deleted file mode 100644
index f4eb5066c..000000000
--- a/tests/integration/inference/recordings/d28e69b9ec21c644f32ac1a57ac99371068a68248f010f146e8a744cc8eba9af.json
+++ /dev/null
@@ -1,421 +0,0 @@
-{
-  "test_id": "tests/integration/inference/test_openai_embeddings.py::test_openai_embeddings_single_string[openai_client-emb=ollama/all-minilm:l6-v2]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": "Hello, world!",
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
-        "data": [
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-            "index": 0,
-            "object": "embedding"
-          }
-        ],
-        "model": "all-minilm:l6-v2",
-        "object": "list",
-        "usage": {
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-          "total_tokens": 4
-        }
-      }
-    },
-    "is_streaming": false
-  }
-}
diff --git a/tests/integration/inference/recordings/d2ba309413e85d6166f7543a879b890b4e65a5f9917a2d75c5795782ab7cbfff.json b/tests/integration/inference/recordings/d2ba309413e85d6166f7543a879b890b4e65a5f9917a2d75c5795782ab7cbfff.json
deleted file mode 100644
index 6b726d9fe..000000000
--- a/tests/integration/inference/recordings/d2ba309413e85d6166f7543a879b890b4e65a5f9917a2d75c5795782ab7cbfff.json
+++ /dev/null
@@ -1,48 +0,0 @@
-{
-  "test_id": "tests/integration/inference/test_openai_completion.py::test_openai_completion_guided_choice[txt=vllm/Qwen/Qwen3-0.6B]",
-  "request": {
-    "method": "POST",
-    "url": "http://localhost:8000/v1/v1/completions",
-    "headers": {},
-    "body": {
-      "model": "Qwen/Qwen3-0.6B",
-      "prompt": "I am feeling really sad today.",
-      "stream": false
-    },
-    "endpoint": "/v1/completions",
-    "model": "Qwen/Qwen3-0.6B"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.completion.Completion",
-      "__data__": {
-        "id": "rec-d2ba309413e8",
-        "choices": [
-          {
-            "finish_reason": "length",
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diff --git a/tests/integration/inference/recordings/d5b0723b5cea73527f33a5f3c0508ca5ff9df6fb940311653cfab6d01a56d155.json b/tests/integration/inference/recordings/d5b0723b5cea73527f33a5f3c0508ca5ff9df6fb940311653cfab6d01a56d155.json
deleted file mode 100644
index ea5efdd25..000000000
--- a/tests/integration/inference/recordings/d5b0723b5cea73527f33a5f3c0508ca5ff9df6fb940311653cfab6d01a56d155.json
+++ /dev/null
@@ -1,421 +0,0 @@
-{
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": "Hello, world!",
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/inference/recordings/e3727f6c749ab8bdee2f581300092002485023b937d72b7aa8d4c15c9204fc5c.json b/tests/integration/inference/recordings/e3727f6c749ab8bdee2f581300092002485023b937d72b7aa8d4c15c9204fc5c.json
deleted file mode 100644
index 21cc0300f..000000000
--- a/tests/integration/inference/recordings/e3727f6c749ab8bdee2f581300092002485023b937d72b7aa8d4c15c9204fc5c.json
+++ /dev/null
@@ -1,54 +0,0 @@
-{
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-    "headers": {},
-    "body": {
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-      "prompt": "I am feeling really sad today.",
-      "stream": false,
-      "extra_body": {
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-          "sadness"
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-    "model": "Qwen/Qwen3-0.6B"
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diff --git a/tests/integration/inference/recordings/e780faa88ebc38e9a74c5d5fa942921d291f73653719e73301196c0258732bf7.json b/tests/integration/inference/recordings/e780faa88ebc38e9a74c5d5fa942921d291f73653719e73301196c0258732bf7.json
deleted file mode 100644
index cebbc578e..000000000
--- a/tests/integration/inference/recordings/e780faa88ebc38e9a74c5d5fa942921d291f73653719e73301196c0258732bf7.json
+++ /dev/null
@@ -1,421 +0,0 @@
-{
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-    "headers": {},
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-      "model": "all-minilm:l6-v2",
-      "input": "This is completely different content",
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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-                "llama"
-              ],
-              "parameter_size": "1.5B",
-              "quantization_level": "Q8_0"
-            }
-          }
-        ]
-      }
-    },
-    "is_streaming": false
-  }
-}
diff --git a/tests/integration/responses/recordings/0413e144be29fe1ffbd0e6511b9ec1e76840d7147993a26057f07246640a7cea.json b/tests/integration/responses/recordings/0413e144be29fe1ffbd0e6511b9ec1e76840d7147993a26057f07246640a7cea.json
deleted file mode 100644
index b9af12b96..000000000
--- a/tests/integration/responses/recordings/0413e144be29fe1ffbd0e6511b9ec1e76840d7147993a26057f07246640a7cea.json
+++ /dev/null
@@ -1,1578 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_sequential_file_search[openai_client-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "text-embedding-3-small",
-      "input": [
-        "Llama 4 Maverick model architecture details"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "text-embedding-3-small"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
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-        "model": "text-embedding-3-small",
-        "object": "list",
-        "usage": {
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-    },
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diff --git a/tests/integration/responses/recordings/06c4f294f3afc1f4d1a0ea83547d9cd37d10ea91e526d00d4a51e09ca956f6e8.json b/tests/integration/responses/recordings/06c4f294f3afc1f4d1a0ea83547d9cd37d10ea91e526d00d4a51e09ca956f6e8.json
deleted file mode 100644
index 6d9a2fe7d..000000000
--- a/tests/integration/responses/recordings/06c4f294f3afc1f4d1a0ea83547d9cd37d10ea91e526d00d4a51e09ca956f6e8.json
+++ /dev/null
@@ -1,1575 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search_empty_vector_store[client_with_models-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "text-embedding-3-small",
-      "input": [
-        "Llama 4 Maverick model number of experts"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "text-embedding-3-small"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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-        "model": "text-embedding-3-small",
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diff --git a/tests/integration/responses/recordings/07b6475c42139e6e3f06323eeef10cba663a61796f4667367aa5084f2e2c2eb6.json b/tests/integration/responses/recordings/07b6475c42139e6e3f06323eeef10cba663a61796f4667367aa5084f2e2c2eb6.json
deleted file mode 100644
index 1905a1b34..000000000
--- a/tests/integration/responses/recordings/07b6475c42139e6e3f06323eeef10cba663a61796f4667367aa5084f2e2c2eb6.json
+++ /dev/null
@@ -1,372 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_sequential_file_search[openai_client-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_aPe1vS1v5bIwPgl789D5bfmW",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_aPe1vS1v5bIwPgl789D5bfmW",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-690481987689, score: 2.5781234969335522, attributes: {'filename': 'test_sequential_file_search.txt', 'document_id': 'file-690481987689', 'token_count': 19.0, 'metadata_token_count': 11.0} (cite as <|file-690481987689|>)\nThe Llama 4 Maverick model has 128 experts in its mixture of experts architecture.\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        },
-        {
-          "role": "assistant",
-          "content": "The Llama 4 Maverick model has 128 experts in its mixture of experts architecture <|file-690481987689|>."
-        },
-        {
-          "role": "user",
-          "content": "Can you tell me more about the architecture?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_UqyVZyvMh30eQuiKg7lJIUhQ",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model architecture\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_UqyVZyvMh30eQuiKg7lJIUhQ",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-690481987689, score: 1.9327567816402336, attributes: {'filename': 'test_sequential_file_search.txt', 'document_id': 'file-690481987689', 'token_count': 19.0, 'metadata_token_count': 11.0} (cite as <|file-690481987689|>)\nThe Llama 4 Maverick model has 128 experts in its mixture of experts architecture.\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model architecture\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        }
-      ],
-      "stream": true,
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
-                "query"
-              ]
-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
-    "body": [
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-07b6475c4213",
-          "choices": [
-            {
-              "delta": {
-                "content": "",
-                "function_call": null,
-                "refusal": null,
-                "role": "assistant",
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "MR85AdN9cL5"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-07b6475c4213",
-          "choices": [
-            {
-              "delta": {
-                "content": "The Llama ",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "PU1MvlGgbp"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-07b6475c4213",
-          "choices": [
-            {
-              "delta": {
-                "content": "4 Maverick model's architecture utilizes a mixture of experts,",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "j5k5TwcdwAGF"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-07b6475c4213",
-          "choices": [
-            {
-              "delta": {
-                "content": " comprising ",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "RY"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-07b6475c4213",
-          "choices": [
-            {
-              "delta": {
-                "content": "128 experts <|file-690481987689|>.",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "zfJzUoSQia"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-07b6475c4213",
-          "choices": [
-            {
-              "delta": {
-                "content": " Unfortunately,",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "myxQ8DZiq0bzUFn"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-07b6475c4213",
-          "choices": [
-            {
-              "delta": {
-                "content": " the retrieved data did not provide more detailed information beyond this specific aspect of the architecture.",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "tqzrfbJ9V"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-07b6475c4213",
-          "choices": [
-            {
-              "delta": {
-                "content": " Would you like me to search for additional details?",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "p8JOT5P"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-07b6475c4213",
-          "choices": [
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-              "delta": {
-                "content": null,
-                "function_call": null,
-                "refusal": null,
-                "role": null,
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-              },
-              "finish_reason": "stop",
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "tA2QeAL"
-        }
-      }
-    ],
-    "is_streaming": true
-  },
-  "id_normalization_mapping": {}
-}
diff --git a/tests/integration/responses/recordings/08f3fbf0d55f3e5a0c98b89e144663cbc5b0ea707de71feaa4c47a585d4e0073.json b/tests/integration/responses/recordings/08f3fbf0d55f3e5a0c98b89e144663cbc5b0ea707de71feaa4c47a585d4e0073.json
deleted file mode 100644
index fabc81bff..000000000
--- a/tests/integration/responses/recordings/08f3fbf0d55f3e5a0c98b89e144663cbc5b0ea707de71feaa4c47a585d4e0073.json
+++ /dev/null
@@ -1,501 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_basic_responses.py::test_response_streaming_incremental_content[client_with_models-txt=openai/gpt-4o-image_input]",
-  "request": {
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-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
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-          "role": "user",
-          "content": [
-            {
-              "type": "text",
-              "text": "what teams are playing in this image?"
-            }
-          ]
-        },
-        {
-          "role": "user",
-          "content": [
-            {
-              "type": "image_url",
-              "image_url": {
-                "url": "https://upload.wikimedia.org/wikipedia/commons/3/3b/LeBron_James_Layup_%28Cleveland_vs_Brooklyn_2018%29.jpg",
-                "detail": "auto"
-              }
-            }
-          ]
-        }
-      ],
-      "stream": true
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
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-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-08f3fbf0d55f",
-          "choices": [
-            {
-              "delta": {
-                "content": " playing",
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-                "refusal": null,
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-          "service_tier": "default",
-          "system_fingerprint": "fp_cbf1785567",
-          "usage": null,
-          "obfuscation": "p4G1M"
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-      {
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-        "__data__": {
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-          "choices": [
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-              },
-              "finish_reason": "stop",
-              "index": 0,
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-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
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-          "usage": null,
-          "obfuscation": "d4KX2ki"
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-      }
-    ],
-    "is_streaming": true
-  }
-}
diff --git a/tests/integration/responses/recordings/0a7db42a014ba0d7c7a06139842cefc624698aa63d3036cb1764474a2b01a5c7.json b/tests/integration/responses/recordings/0a7db42a014ba0d7c7a06139842cefc624698aa63d3036cb1764474a2b01a5c7.json
deleted file mode 100644
index 4c0e81ee1..000000000
--- a/tests/integration/responses/recordings/0a7db42a014ba0d7c7a06139842cefc624698aa63d3036cb1764474a2b01a5c7.json
+++ /dev/null
@@ -1,1437 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search[client_with_models-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536-llama_experts_pdf]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_Zb3UPWm2DOVVTce3d5Uo21FX",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_Zb3UPWm2DOVVTce3d5Uo21FX",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 2 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-de7f28ce49b04e58ae6e21a63745e339, score: 1.4947232325305748, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-de7f28ce49b04e58ae6e21a63745e339', 'token_count': 98.0, 'metadata_token_count': 11.0} (cite as <|file-de7f28ce49b04e58ae6e21a63745e339|>)\n,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "[2] document_id: file-de7f28ce49b04e58ae6e21a63745e339, score: 1.1417523389560924, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-de7f28ce49b04e58ae6e21a63745e339', 'token_count': 498.0, 'metadata_token_count': 11.0} (cite as <|file-de7f28ce49b04e58ae6e21a63745e339|>)\nLlama  Stack  \nLlama  Stack  Overview  \nLlama  Stack  standardizes  the  core  building  blocks  that  simplify  AI  application  development.  It  codifies  best  \npractices\n \nacross\n \nthe\n \nLlama\n \necosystem.\n \nMore\n \nspecifically,\n \nit\n \nprovides\n  \u25cf  Unified  API  layer  for  Inference,  RAG,  Agents,  Tools,  Safety,  Evals,  and  Telemetry.  \u25cf  Plugin  architecture  to  support  the  rich  ecosystem  of  different  API  implementations  in  various  \nenvironments,\n \nincluding\n \nlocal\n \ndevelopment,\n \non-premises,\n \ncloud,\n \nand\n \nmobile.\n \u25cf  Prepackaged  verified  distributions  which  offer  a  one-stop  solution  for  developers  to  get  started  quickly  \nand\n \nreliably\n \nin\n \nany\n \nenvironment.\n \u25cf  Multiple  developer  interfaces  like  CLI  and  SDKs  for  Python,  Typescript,  iOS,  and  Android.  \u25cf  Standalone  applications  as  examples  for  how  to  build  production-grade  AI  applications  with  Llama  \nStack.\n \nLlama  Stack  Benefits  \n\u25cf  Flexible  Options:  Developers  can  choose  their  preferred  infrastructure  without  changing  APIs  and  enjoy  \nflexible\n \ndeployment\n \nchoices.\n \u25cf  Consistent  Experience:  With  its  unified  APIs,  Llama  Stack  makes  it  easier  to  build,  test,  and  deploy  AI  \napplications\n \nwith\n \nconsistent\n \napplication\n \nbehavior.\n \u25cf  Robust  Ecosystem:  Llama  Stack  is  already  integrated  with  distribution  partners  (cloud  providers,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        }
-      ],
-      "stream": true,
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
-                "query"
-              ]
-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
-    "body": [
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
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-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
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-          "service_tier": "default",
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diff --git a/tests/integration/responses/recordings/0c65f0c1f494dd345cdc00d4df22b4f3be76b56834180572b58f5e619815a946.json b/tests/integration/responses/recordings/0c65f0c1f494dd345cdc00d4df22b4f3be76b56834180572b58f5e619815a946.json
deleted file mode 100644
index 689c5303d..000000000
--- a/tests/integration/responses/recordings/0c65f0c1f494dd345cdc00d4df22b4f3be76b56834180572b58f5e619815a946.json
+++ /dev/null
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-            ],
-            "index": 0,
-            "object": "embedding"
-          }
-        ],
-        "model": "text-embedding-3-small",
-        "object": "list",
-        "usage": {
-          "prompt_tokens": 10,
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-        }
-      }
-    },
-    "is_streaming": false
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-}
diff --git a/tests/integration/responses/recordings/0f79646fcf8aaf90bd27658c7c038a495eba448dfde29b58d887281ab0ffe972.json b/tests/integration/responses/recordings/0f79646fcf8aaf90bd27658c7c038a495eba448dfde29b58d887281ab0ffe972.json
deleted file mode 100644
index 5cf5a828e..000000000
--- a/tests/integration/responses/recordings/0f79646fcf8aaf90bd27658c7c038a495eba448dfde29b58d887281ab0ffe972.json
+++ /dev/null
@@ -1,629 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_sequential_file_search[openai_client-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        }
-      ],
-      "stream": true,
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
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diff --git a/tests/integration/responses/recordings/0fd12925d27e6824a956559c79b4c90723b11660134454284bddc28e2275f770.json b/tests/integration/responses/recordings/0fd12925d27e6824a956559c79b4c90723b11660134454284bddc28e2275f770.json
deleted file mode 100644
index bbd883bc2..000000000
--- a/tests/integration/responses/recordings/0fd12925d27e6824a956559c79b4c90723b11660134454284bddc28e2275f770.json
+++ /dev/null
@@ -1,219 +0,0 @@
-{
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diff --git a/tests/integration/responses/recordings/112ca0696d9265f3301cfe6b263f62aac7bc31f6f2c1191f15030f176e32c855.json b/tests/integration/responses/recordings/112ca0696d9265f3301cfe6b263f62aac7bc31f6f2c1191f15030f176e32c855.json
deleted file mode 100644
index e888274ad..000000000
--- a/tests/integration/responses/recordings/112ca0696d9265f3301cfe6b263f62aac7bc31f6f2c1191f15030f176e32c855.json
+++ /dev/null
@@ -1,736 +0,0 @@
-{
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-    "headers": {},
-    "body": {
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-      "messages": [
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-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
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-          "tool_calls": [
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-              "index": 0,
-              "id": "call_zKJ7WgvCO3tx6yB0We1qI0d8",
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-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
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-        {
-          "role": "tool",
-          "tool_call_id": "call_zKJ7WgvCO3tx6yB0We1qI0d8",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 2 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-728796232029, score: 1.4945131220963286, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-728796232029', 'token_count': 98.0, 'metadata_token_count': 11.0} (cite as <|file-728796232029|>)\n,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "[2] document_id: file-728796232029, score: 1.1415676746925796, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-728796232029', 'token_count': 498.0, 'metadata_token_count': 11.0} (cite as <|file-728796232029|>)\nLlama  Stack  \nLlama  Stack  Overview  \nLlama  Stack  standardizes  the  core  building  blocks  that  simplify  AI  application  development.  It  codifies  best  \npractices\n \nacross\n \nthe\n \nLlama\n \necosystem.\n \nMore\n \nspecifically,\n \nit\n \nprovides\n  \u25cf  Unified  API  layer  for  Inference,  RAG,  Agents,  Tools,  Safety,  Evals,  and  Telemetry.  \u25cf  Plugin  architecture  to  support  the  rich  ecosystem  of  different  API  implementations  in  various  \nenvironments,\n \nincluding\n \nlocal\n \ndevelopment,\n \non-premises,\n \ncloud,\n \nand\n \nmobile.\n \u25cf  Prepackaged  verified  distributions  which  offer  a  one-stop  solution  for  developers  to  get  started  quickly  \nand\n \nreliably\n \nin\n \nany\n \nenvironment.\n \u25cf  Multiple  developer  interfaces  like  CLI  and  SDKs  for  Python,  Typescript,  iOS,  and  Android.  \u25cf  Standalone  applications  as  examples  for  how  to  build  production-grade  AI  applications  with  Llama  \nStack.\n \nLlama  Stack  Benefits  \n\u25cf  Flexible  Options:  Developers  can  choose  their  preferred  infrastructure  without  changing  APIs  and  enjoy  \nflexible\n \ndeployment\n \nchoices.\n \u25cf  Consistent  Experience:  With  its  unified  APIs,  Llama  Stack  makes  it  easier  to  build,  test,  and  deploy  AI  \napplications\n \nwith\n \nconsistent\n \napplication\n \nbehavior.\n \u25cf  Robust  Ecosystem:  Llama  Stack  is  already  integrated  with  distribution  partners  (cloud  providers,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
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diff --git a/tests/integration/responses/recordings/127a97b42f235e9a22414005f5c941476af8e8a6a211898394fee77a0b40507f.json b/tests/integration/responses/recordings/127a97b42f235e9a22414005f5c941476af8e8a6a211898394fee77a0b40507f.json
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-          "content": "How many experts does the Llama 4 Maverick model have?"
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diff --git a/tests/integration/responses/recordings/16144567d21785fd1837a8f86258d8a972e7216dbb55427ea63edb9ae3185b0a.json b/tests/integration/responses/recordings/16144567d21785fd1837a8f86258d8a972e7216dbb55427ea63edb9ae3185b0a.json
deleted file mode 100644
index 6cbbb9b2c..000000000
--- a/tests/integration/responses/recordings/16144567d21785fd1837a8f86258d8a972e7216dbb55427ea63edb9ae3185b0a.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/16499abd50909c547f4a980a69dec75cb2931838dc1a18a16cf83bc299c056e0.json b/tests/integration/responses/recordings/16499abd50909c547f4a980a69dec75cb2931838dc1a18a16cf83bc299c056e0.json
deleted file mode 100644
index 0c905f195..000000000
--- a/tests/integration/responses/recordings/16499abd50909c547f4a980a69dec75cb2931838dc1a18a16cf83bc299c056e0.json
+++ /dev/null
@@ -1,600 +0,0 @@
-{
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-  "request": {
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-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_aPe1vS1v5bIwPgl789D5bfmW",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_aPe1vS1v5bIwPgl789D5bfmW",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-690481987689, score: 2.5781234969335522, attributes: {'filename': 'test_sequential_file_search.txt', 'document_id': 'file-690481987689', 'token_count': 19.0, 'metadata_token_count': 11.0} (cite as <|file-690481987689|>)\nThe Llama 4 Maverick model has 128 experts in its mixture of experts architecture.\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
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-        {
-          "role": "assistant",
-          "content": "The Llama 4 Maverick model has 128 experts in its mixture of experts architecture <|file-690481987689|>."
-        },
-        {
-          "role": "user",
-          "content": "Can you tell me more about the architecture?"
-        }
-      ],
-      "stream": true,
-      "tools": [
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-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
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-                "query"
-              ]
-            }
-          }
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-      ]
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-    "model": "gpt-4o"
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diff --git a/tests/integration/responses/recordings/178c316ab442673f5570334d8e1933be9d2dd0991d0dce944eeb35dd59a002de.json b/tests/integration/responses/recordings/178c316ab442673f5570334d8e1933be9d2dd0991d0dce944eeb35dd59a002de.json
deleted file mode 100644
index 06bc7a744..000000000
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-        "model": "text-embedding-3-small",
-        "object": "list",
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-}
diff --git a/tests/integration/responses/recordings/19a995f94d68e53d09f378afe7f4a27af4f029b679de5b986157dfd7fe7a4ec2.json b/tests/integration/responses/recordings/19a995f94d68e53d09f378afe7f4a27af4f029b679de5b986157dfd7fe7a4ec2.json
deleted file mode 100644
index d494439cd..000000000
--- a/tests/integration/responses/recordings/19a995f94d68e53d09f378afe7f4a27af4f029b679de5b986157dfd7fe7a4ec2.json
+++ /dev/null
@@ -1,1645 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_sequential_file_search[client_with_models-txt=openai/gpt-4o:emb=Nomic-v1.5:dim=768]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_uy4RL1d6RPGFQ0dV63O5lqgM",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_uy4RL1d6RPGFQ0dV63O5lqgM",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-562027679042, score: 0.1388247736002883, attributes: {'filename': 'test_sequential_file_search.txt', 'document_id': 'file-562027679042', 'token_count': 19.0, 'metadata_token_count': 11.0} (cite as <|file-562027679042|>)\nThe Llama 4 Maverick model has 128 experts in its mixture of experts architecture.\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        },
-        {
-          "role": "assistant",
-          "content": "The Llama 4 Maverick model has 128 experts in its mixture of experts architecture <|file-562027679042|>."
-        },
-        {
-          "role": "user",
-          "content": "Can you tell me more about the architecture?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_JqSvXCKxAfungZuECdvE91Kw",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model architecture\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_JqSvXCKxAfungZuECdvE91Kw",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-562027679042, score: 0.07784888062388627, attributes: {'filename': 'test_sequential_file_search.txt', 'document_id': 'file-562027679042', 'token_count': 19.0, 'metadata_token_count': 11.0} (cite as <|file-562027679042|>)\nThe Llama 4 Maverick model has 128 experts in its mixture of experts architecture.\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model architecture\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        }
-      ],
-      "stream": true,
-      "stream_options": {
-        "include_usage": true
-      },
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
-                "query"
-              ]
-            }
-          }
-        }
-      ]
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diff --git a/tests/integration/responses/recordings/1b0c005eb4b93c22ec7211904cab5145194ec832d8e436fee11599c1c2d80fd8.json b/tests/integration/responses/recordings/1b0c005eb4b93c22ec7211904cab5145194ec832d8e436fee11599c1c2d80fd8.json
deleted file mode 100644
index 642f35b4e..000000000
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deleted file mode 100644
index 1c356ab8e..000000000
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diff --git a/tests/integration/responses/recordings/1d05d239176af7d32d056e563fd2bc132925c86f548fde2976f19f5397e57629.json b/tests/integration/responses/recordings/1d05d239176af7d32d056e563fd2bc132925c86f548fde2976f19f5397e57629.json
deleted file mode 100644
index 76e84e54e..000000000
--- a/tests/integration/responses/recordings/1d05d239176af7d32d056e563fd2bc132925c86f548fde2976f19f5397e57629.json
+++ /dev/null
@@ -1,806 +0,0 @@
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diff --git a/tests/integration/responses/recordings/22f0ad06b093be67d13574bd2396040875395d346873bc80e68ecb5c603bc697.json b/tests/integration/responses/recordings/22f0ad06b093be67d13574bd2396040875395d346873bc80e68ecb5c603bc697.json
deleted file mode 100644
index ec2dc9c4d..000000000
--- a/tests/integration/responses/recordings/22f0ad06b093be67d13574bd2396040875395d346873bc80e68ecb5c603bc697.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/26e569a66dd1b1669a26851179956ffca286bd5f6874f975f6b369bf6bbcc521.json b/tests/integration/responses/recordings/26e569a66dd1b1669a26851179956ffca286bd5f6874f975f6b369bf6bbcc521.json
deleted file mode 100644
index 0daab7d4d..000000000
--- a/tests/integration/responses/recordings/26e569a66dd1b1669a26851179956ffca286bd5f6874f975f6b369bf6bbcc521.json
+++ /dev/null
@@ -1,1650 +0,0 @@
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diff --git a/tests/integration/responses/recordings/2ba43758466f6eb5d66af4cc1c5016b013155bf1dcf750873e2adbda644f04fa.json b/tests/integration/responses/recordings/2ba43758466f6eb5d66af4cc1c5016b013155bf1dcf750873e2adbda644f04fa.json
deleted file mode 100644
index 7ad52d611..000000000
--- a/tests/integration/responses/recordings/2ba43758466f6eb5d66af4cc1c5016b013155bf1dcf750873e2adbda644f04fa.json
+++ /dev/null
@@ -1,1576 +0,0 @@
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-        "usage": {
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diff --git a/tests/integration/responses/recordings/2f3f766a9601f4ffcde5522361da752354dbf42d982c0a98f4f1113f9cc03769.json b/tests/integration/responses/recordings/2f3f766a9601f4ffcde5522361da752354dbf42d982c0a98f4f1113f9cc03769.json
deleted file mode 100644
index e7ba883c9..000000000
--- a/tests/integration/responses/recordings/2f3f766a9601f4ffcde5522361da752354dbf42d982c0a98f4f1113f9cc03769.json
+++ /dev/null
@@ -1,219 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search[client_with_models-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536-llama_experts]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_90pCu8l9ITbz463ZJxhGGKm3",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_90pCu8l9ITbz463ZJxhGGKm3",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-36441599755, score: 2.933222791810999, attributes: {'filename': 'test_response_non_streaming_file_search.txt', 'document_id': 'file-36441599755', 'token_count': 10.0, 'metadata_token_count': 13.0} (cite as <|file-36441599755|>)\nLlama 4 Maverick has 128 experts\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        }
-      ],
-      "stream": true,
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
-                "query"
-              ]
-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
-    "body": [
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-2f3f766a9601",
-          "choices": [
-            {
-              "delta": {
-                "content": "",
-                "function_call": null,
-                "refusal": null,
-                "role": "assistant",
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "ZcjznG6Yo8S"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-2f3f766a9601",
-          "choices": [
-            {
-              "delta": {
-                "content": "The Llama ",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "otwbPJWhEZ"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-2f3f766a9601",
-          "choices": [
-            {
-              "delta": {
-                "content": "4 Maverick model has ",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "WOGpoDlX3rN1"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-2f3f766a9601",
-          "choices": [
-            {
-              "delta": {
-                "content": "128 experts <|file-36441599755|>.",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "td4Hm9RbPE"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
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-              "finish_reason": "stop",
-              "index": 0,
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-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "PMGTSWK"
-        }
-      }
-    ],
-    "is_streaming": true
-  },
-  "id_normalization_mapping": {}
-}
diff --git a/tests/integration/responses/recordings/323c7637263f3623d58c73a3584af9d9f3d3190b2a2beec72bf5c34d8c196d51.json b/tests/integration/responses/recordings/323c7637263f3623d58c73a3584af9d9f3d3190b2a2beec72bf5c34d8c196d51.json
deleted file mode 100644
index 0245c48e8..000000000
--- a/tests/integration/responses/recordings/323c7637263f3623d58c73a3584af9d9f3d3190b2a2beec72bf5c34d8c196d51.json
+++ /dev/null
@@ -1,628 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search[client_with_models-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536-llama_experts_pdf]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        }
-      ],
-      "stream": true,
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
-                "query"
-              ]
-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
-    "body": [
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-323c7637263f",
-          "choices": [
-            {
-              "delta": {
-                "content": null,
-                "function_call": null,
-                "refusal": null,
-                "role": "assistant",
-                "tool_calls": [
-                  {
-                    "index": 0,
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diff --git a/tests/integration/responses/recordings/33a4981f0e249903c4502c3e59f51b67e418a50095e3b406f92f200c62ae163c.json b/tests/integration/responses/recordings/33a4981f0e249903c4502c3e59f51b67e418a50095e3b406f92f200c62ae163c.json
deleted file mode 100644
index 7a61cda60..000000000
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-        "model": "text-embedding-3-small",
-        "object": "list",
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diff --git a/tests/integration/responses/recordings/39e480e3e6716f7e2e41be654eae0f0250ac22a51707a110eabec377358f6b8f.json b/tests/integration/responses/recordings/39e480e3e6716f7e2e41be654eae0f0250ac22a51707a110eabec377358f6b8f.json
deleted file mode 100644
index c2b46f420..000000000
--- a/tests/integration/responses/recordings/39e480e3e6716f7e2e41be654eae0f0250ac22a51707a110eabec377358f6b8f.json
+++ /dev/null
@@ -1,1578 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_sequential_file_search[client_with_models-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "text-embedding-3-small",
-      "input": [
-        "Llama 4 Maverick model architecture details"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "text-embedding-3-small"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
-        "data": [
-          {
-            "embedding": [
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diff --git a/tests/integration/responses/recordings/3d492a17827d8560d6dc397986b1cc92afe08beb65cf51b05119908a2d9000fc.json b/tests/integration/responses/recordings/3d492a17827d8560d6dc397986b1cc92afe08beb65cf51b05119908a2d9000fc.json
deleted file mode 100644
index 3f3414f0d..000000000
--- a/tests/integration/responses/recordings/3d492a17827d8560d6dc397986b1cc92afe08beb65cf51b05119908a2d9000fc.json
+++ /dev/null
@@ -1,1321 +0,0 @@
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diff --git a/tests/integration/responses/recordings/4098e0793b9af1624c0ba2b016b5829c93365504599a8a95ddb444a6c8e39aa5.json b/tests/integration/responses/recordings/4098e0793b9af1624c0ba2b016b5829c93365504599a8a95ddb444a6c8e39aa5.json
deleted file mode 100644
index 0dd6fc6b8..000000000
--- a/tests/integration/responses/recordings/4098e0793b9af1624c0ba2b016b5829c93365504599a8a95ddb444a6c8e39aa5.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/4525315e8eab433996daef916a629ab2526233d66a616ff0b391e9b2d4d1dd27.json b/tests/integration/responses/recordings/4525315e8eab433996daef916a629ab2526233d66a616ff0b391e9b2d4d1dd27.json
deleted file mode 100644
index 8962fad83..000000000
--- a/tests/integration/responses/recordings/4525315e8eab433996daef916a629ab2526233d66a616ff0b391e9b2d4d1dd27.json
+++ /dev/null
@@ -1,894 +0,0 @@
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diff --git a/tests/integration/responses/recordings/4eb6e076a5b400260dc58a211bf90a9bd9bb6c940c4d88aba912ae87a8f66816.json b/tests/integration/responses/recordings/4eb6e076a5b400260dc58a211bf90a9bd9bb6c940c4d88aba912ae87a8f66816.json
deleted file mode 100644
index f586f4e61..000000000
--- a/tests/integration/responses/recordings/4eb6e076a5b400260dc58a211bf90a9bd9bb6c940c4d88aba912ae87a8f66816.json
+++ /dev/null
@@ -1,250 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search[client_with_models-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536-llama_experts_pdf]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_Zb3UPWm2DOVVTce3d5Uo21FX",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_Zb3UPWm2DOVVTce3d5Uo21FX",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 2 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-433408948870, score: 1.4947232325305748, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-433408948870', 'token_count': 98.0, 'metadata_token_count': 11.0} (cite as <|file-433408948870|>)\n,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "[2] document_id: file-433408948870, score: 1.1417523389560924, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-433408948870', 'token_count': 498.0, 'metadata_token_count': 11.0} (cite as <|file-433408948870|>)\nLlama  Stack  \nLlama  Stack  Overview  \nLlama  Stack  standardizes  the  core  building  blocks  that  simplify  AI  application  development.  It  codifies  best  \npractices\n \nacross\n \nthe\n \nLlama\n \necosystem.\n \nMore\n \nspecifically,\n \nit\n \nprovides\n  \u25cf  Unified  API  layer  for  Inference,  RAG,  Agents,  Tools,  Safety,  Evals,  and  Telemetry.  \u25cf  Plugin  architecture  to  support  the  rich  ecosystem  of  different  API  implementations  in  various  \nenvironments,\n \nincluding\n \nlocal\n \ndevelopment,\n \non-premises,\n \ncloud,\n \nand\n \nmobile.\n \u25cf  Prepackaged  verified  distributions  which  offer  a  one-stop  solution  for  developers  to  get  started  quickly  \nand\n \nreliably\n \nin\n \nany\n \nenvironment.\n \u25cf  Multiple  developer  interfaces  like  CLI  and  SDKs  for  Python,  Typescript,  iOS,  and  Android.  \u25cf  Standalone  applications  as  examples  for  how  to  build  production-grade  AI  applications  with  Llama  \nStack.\n \nLlama  Stack  Benefits  \n\u25cf  Flexible  Options:  Developers  can  choose  their  preferred  infrastructure  without  changing  APIs  and  enjoy  \nflexible\n \ndeployment\n \nchoices.\n \u25cf  Consistent  Experience:  With  its  unified  APIs,  Llama  Stack  makes  it  easier  to  build,  test,  and  deploy  AI  \napplications\n \nwith\n \nconsistent\n \napplication\n \nbehavior.\n \u25cf  Robust  Ecosystem:  Llama  Stack  is  already  integrated  with  distribution  partners  (cloud  providers,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        }
-      ],
-      "stream": true,
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
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-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
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-  "response": {
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-        "__data__": {
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-        "__data__": {
-          "id": "rec-4eb6e076a5b4",
-          "choices": [
-            {
-              "delta": {
-                "content": "4 Maverick model is a Mixture-of-Experts (MoE)",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
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-              },
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-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
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-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "2LBRj2itsMHM"
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-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-4eb6e076a5b4",
-          "choices": [
-            {
-              "delta": {
-                "content": " model with ",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
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-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
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-        "__data__": {
-          "id": "rec-4eb6e076a5b4",
-          "choices": [
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-              "delta": {
-                "content": "128 experts <|file-433408948870|>.",
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diff --git a/tests/integration/responses/recordings/50209c4013650ac6b04e2ac8a5dc865d7e6b17a175e6674499c870797be5951e.json b/tests/integration/responses/recordings/50209c4013650ac6b04e2ac8a5dc865d7e6b17a175e6674499c870797be5951e.json
deleted file mode 100644
index 957ef40aa..000000000
--- a/tests/integration/responses/recordings/50209c4013650ac6b04e2ac8a5dc865d7e6b17a175e6674499c870797be5951e.json
+++ /dev/null
@@ -1,320 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_sequential_file_search[client_with_models-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_qzY7B7EArJwpMqLVer8kcAey",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_qzY7B7EArJwpMqLVer8kcAey",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-d7cee10212814cfcb75cc091eee11688, score: 2.5781234969335522, attributes: {'filename': 'test_sequential_file_search.txt', 'document_id': 'file-d7cee10212814cfcb75cc091eee11688', 'token_count': 19.0, 'metadata_token_count': 11.0} (cite as <|file-d7cee10212814cfcb75cc091eee11688|>)\nThe Llama 4 Maverick model has 128 experts in its mixture of experts architecture.\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        },
-        {
-          "role": "assistant",
-          "content": "The Llama 4 Maverick model has 128 experts in its mixture of experts architecture <|file-d7cee10212814cfcb75cc091eee11688|>."
-        },
-        {
-          "role": "user",
-          "content": "Can you tell me more about the architecture?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_1ALB4oPNgIKUK5psXuwbr75h",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model architecture details\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_1ALB4oPNgIKUK5psXuwbr75h",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-d7cee10212814cfcb75cc091eee11688, score: 1.932386575539943, attributes: {'filename': 'test_sequential_file_search.txt', 'document_id': 'file-d7cee10212814cfcb75cc091eee11688', 'token_count': 19.0, 'metadata_token_count': 11.0} (cite as <|file-d7cee10212814cfcb75cc091eee11688|>)\nThe Llama 4 Maverick model has 128 experts in its mixture of experts architecture.\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model architecture details\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        }
-      ],
-      "stream": true,
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
-                "query"
-              ]
-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
-    "body": [
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
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diff --git a/tests/integration/responses/recordings/53ee2f8e45e7a4aa0c39a3f2691d544dfeefbc3678e08d4add8140f9127f50a1.json b/tests/integration/responses/recordings/53ee2f8e45e7a4aa0c39a3f2691d544dfeefbc3678e08d4add8140f9127f50a1.json
deleted file mode 100644
index 326ff043b..000000000
--- a/tests/integration/responses/recordings/53ee2f8e45e7a4aa0c39a3f2691d544dfeefbc3678e08d4add8140f9127f50a1.json
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diff --git a/tests/integration/responses/recordings/62eb194000dcab5aeb873eed2403c963fca80beab1f1f2fafc6d8a18c6b4df6e.json b/tests/integration/responses/recordings/62eb194000dcab5aeb873eed2403c963fca80beab1f1f2fafc6d8a18c6b4df6e.json
deleted file mode 100644
index 4924e152b..000000000
--- a/tests/integration/responses/recordings/62eb194000dcab5aeb873eed2403c963fca80beab1f1f2fafc6d8a18c6b4df6e.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/635f9971c8d6855fb581204bf37e5d0577d3d38e286c5796aed6f72ebdbbca53.json b/tests/integration/responses/recordings/635f9971c8d6855fb581204bf37e5d0577d3d38e286c5796aed6f72ebdbbca53.json
deleted file mode 100644
index de948e2b0..000000000
--- a/tests/integration/responses/recordings/635f9971c8d6855fb581204bf37e5d0577d3d38e286c5796aed6f72ebdbbca53.json
+++ /dev/null
@@ -1,732 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search[openai_client-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536-llama_experts]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_9Ofp0Uepi3uOnEmuFtm9yvCU",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_9Ofp0Uepi3uOnEmuFtm9yvCU",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-78420035045, score: 2.933222791810999, attributes: {'filename': 'test_response_non_streaming_file_search.txt', 'document_id': 'file-78420035045', 'token_count': 10.0, 'metadata_token_count': 13.0} (cite as <|file-78420035045|>)\nLlama 4 Maverick has 128 experts\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        }
-      ],
-      "stream": true,
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
-                "query"
-              ]
-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
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diff --git a/tests/integration/responses/recordings/6a31576af40e49e15e7a4db15b683147ac002ada7a4680ef5085688f18ff5fcf.json b/tests/integration/responses/recordings/6a31576af40e49e15e7a4db15b683147ac002ada7a4680ef5085688f18ff5fcf.json
deleted file mode 100644
index a6393387d..000000000
--- a/tests/integration/responses/recordings/6a31576af40e49e15e7a4db15b683147ac002ada7a4680ef5085688f18ff5fcf.json
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-            "index": 0,
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-        "model": "text-embedding-3-small",
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diff --git a/tests/integration/responses/recordings/6bc34054dd782e9c2100053a55bad1b5973ae19f8e75c847bef36d71fccd804e.json b/tests/integration/responses/recordings/6bc34054dd782e9c2100053a55bad1b5973ae19f8e75c847bef36d71fccd804e.json
deleted file mode 100644
index 6c2242c9c..000000000
--- a/tests/integration/responses/recordings/6bc34054dd782e9c2100053a55bad1b5973ae19f8e75c847bef36d71fccd804e.json
+++ /dev/null
@@ -1,952 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search[client_with_models-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536-llama_experts_pdf]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_Zb3UPWm2DOVVTce3d5Uo21FX",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_Zb3UPWm2DOVVTce3d5Uo21FX",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 2 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-433408948870, score: 1.4947232325305748, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-433408948870', 'token_count': 98.0, 'metadata_token_count': 11.0} (cite as <|file-433408948870|>)\n,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "[2] document_id: file-433408948870, score: 1.1417523389560924, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-433408948870', 'token_count': 498.0, 'metadata_token_count': 11.0} (cite as <|file-433408948870|>)\nLlama  Stack  \nLlama  Stack  Overview  \nLlama  Stack  standardizes  the  core  building  blocks  that  simplify  AI  application  development.  It  codifies  best  \npractices\n \nacross\n \nthe\n \nLlama\n \necosystem.\n \nMore\n \nspecifically,\n \nit\n \nprovides\n  \u25cf  Unified  API  layer  for  Inference,  RAG,  Agents,  Tools,  Safety,  Evals,  and  Telemetry.  \u25cf  Plugin  architecture  to  support  the  rich  ecosystem  of  different  API  implementations  in  various  \nenvironments,\n \nincluding\n \nlocal\n \ndevelopment,\n \non-premises,\n \ncloud,\n \nand\n \nmobile.\n \u25cf  Prepackaged  verified  distributions  which  offer  a  one-stop  solution  for  developers  to  get  started  quickly  \nand\n \nreliably\n \nin\n \nany\n \nenvironment.\n \u25cf  Multiple  developer  interfaces  like  CLI  and  SDKs  for  Python,  Typescript,  iOS,  and  Android.  \u25cf  Standalone  applications  as  examples  for  how  to  build  production-grade  AI  applications  with  Llama  \nStack.\n \nLlama  Stack  Benefits  \n\u25cf  Flexible  Options:  Developers  can  choose  their  preferred  infrastructure  without  changing  APIs  and  enjoy  \nflexible\n \ndeployment\n \nchoices.\n \u25cf  Consistent  Experience:  With  its  unified  APIs,  Llama  Stack  makes  it  easier  to  build,  test,  and  deploy  AI  \napplications\n \nwith\n \nconsistent\n \napplication\n \nbehavior.\n \u25cf  Robust  Ecosystem:  Llama  Stack  is  already  integrated  with  distribution  partners  (cloud  providers,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        }
-      ],
-      "stream": true,
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
-                "query"
-              ]
-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
-    "body": [
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-6bc34054dd78",
-          "choices": [
-            {
-              "delta": {
-                "content": "",
-                "function_call": null,
-                "refusal": null,
-                "role": "assistant",
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "4vldG6YkUnH"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-6bc34054dd78",
-          "choices": [
-            {
-              "delta": {
-                "content": "The",
-                "function_call": null,
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diff --git a/tests/integration/responses/recordings/714a7d73a6ab1eec33454d4e95af0d6dd9eaef568213109d5e847c7e00b97bc7.json b/tests/integration/responses/recordings/714a7d73a6ab1eec33454d4e95af0d6dd9eaef568213109d5e847c7e00b97bc7.json
deleted file mode 100644
index 4d6d409e2..000000000
--- a/tests/integration/responses/recordings/714a7d73a6ab1eec33454d4e95af0d6dd9eaef568213109d5e847c7e00b97bc7.json
+++ /dev/null
@@ -1,1060 +0,0 @@
-{
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-          "content": "How many experts does the Llama 4 Maverick model have?"
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-          "tool_calls": [
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-              "id": "call_zKJ7WgvCO3tx6yB0We1qI0d8",
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-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
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-          "role": "tool",
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-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 2 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-728796232029, score: 1.4945131220963286, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-728796232029', 'token_count': 98.0, 'metadata_token_count': 11.0} (cite as <|file-728796232029|>)\n,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "[2] document_id: file-728796232029, score: 1.1415676746925796, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-728796232029', 'token_count': 498.0, 'metadata_token_count': 11.0} (cite as <|file-728796232029|>)\nLlama  Stack  \nLlama  Stack  Overview  \nLlama  Stack  standardizes  the  core  building  blocks  that  simplify  AI  application  development.  It  codifies  best  \npractices\n \nacross\n \nthe\n \nLlama\n \necosystem.\n \nMore\n \nspecifically,\n \nit\n \nprovides\n  \u25cf  Unified  API  layer  for  Inference,  RAG,  Agents,  Tools,  Safety,  Evals,  and  Telemetry.  \u25cf  Plugin  architecture  to  support  the  rich  ecosystem  of  different  API  implementations  in  various  \nenvironments,\n \nincluding\n \nlocal\n \ndevelopment,\n \non-premises,\n \ncloud,\n \nand\n \nmobile.\n \u25cf  Prepackaged  verified  distributions  which  offer  a  one-stop  solution  for  developers  to  get  started  quickly  \nand\n \nreliably\n \nin\n \nany\n \nenvironment.\n \u25cf  Multiple  developer  interfaces  like  CLI  and  SDKs  for  Python,  Typescript,  iOS,  and  Android.  \u25cf  Standalone  applications  as  examples  for  how  to  build  production-grade  AI  applications  with  Llama  \nStack.\n \nLlama  Stack  Benefits  \n\u25cf  Flexible  Options:  Developers  can  choose  their  preferred  infrastructure  without  changing  APIs  and  enjoy  \nflexible\n \ndeployment\n \nchoices.\n \u25cf  Consistent  Experience:  With  its  unified  APIs,  Llama  Stack  makes  it  easier  to  build,  test,  and  deploy  AI  \napplications\n \nwith\n \nconsistent\n \napplication\n \nbehavior.\n \u25cf  Robust  Ecosystem:  Llama  Stack  is  already  integrated  with  distribution  partners  (cloud  providers,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
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diff --git a/tests/integration/responses/recordings/78574bdf4f6ef71a5f3675e80daae8d935595b8d4e14002bc1b73629cba1427a.json b/tests/integration/responses/recordings/78574bdf4f6ef71a5f3675e80daae8d935595b8d4e14002bc1b73629cba1427a.json
deleted file mode 100644
index 6ec48dd74..000000000
--- a/tests/integration/responses/recordings/78574bdf4f6ef71a5f3675e80daae8d935595b8d4e14002bc1b73629cba1427a.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/78f9446cb2483639d2d49d73e5774b17078adbf2f522081ad08befd8a79eb96d.json b/tests/integration/responses/recordings/78f9446cb2483639d2d49d73e5774b17078adbf2f522081ad08befd8a79eb96d.json
deleted file mode 100644
index 90a74c300..000000000
--- a/tests/integration/responses/recordings/78f9446cb2483639d2d49d73e5774b17078adbf2f522081ad08befd8a79eb96d.json
+++ /dev/null
@@ -1,501 +0,0 @@
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diff --git a/tests/integration/responses/recordings/7aaabdcbe9e3cdc8215c09ab8da13ce2bcdb1d7cfc05c79bbc1e3024323cd992.json b/tests/integration/responses/recordings/7aaabdcbe9e3cdc8215c09ab8da13ce2bcdb1d7cfc05c79bbc1e3024323cd992.json
deleted file mode 100644
index 4b629525c..000000000
--- a/tests/integration/responses/recordings/7aaabdcbe9e3cdc8215c09ab8da13ce2bcdb1d7cfc05c79bbc1e3024323cd992.json
+++ /dev/null
@@ -1,1028 +0,0 @@
-{
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-    "headers": {},
-    "body": {
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-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
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-              "index": 0,
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-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
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-        {
-          "role": "tool",
-          "tool_call_id": "call_9Ofp0Uepi3uOnEmuFtm9yvCU",
-          "content": [
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-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
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-              "type": "text",
-              "text": "[1] document_id: file-e85154cb613142a9a2ea335cc345e772, score: 2.933222791810999, attributes: {'filename': 'test_response_non_streaming_file_search.txt', 'document_id': 'file-e85154cb613142a9a2ea335cc345e772', 'token_count': 10.0, 'metadata_token_count': 13.0} (cite as <|file-e85154cb613142a9a2ea335cc345e772|>)\nLlama 4 Maverick has 128 experts\n"
-            },
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-              "text": "END of knowledge_search tool results.\n"
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-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
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diff --git a/tests/integration/responses/recordings/813ac454f8df150f6a9918ddd8a68279f2e21c8948779350810cdf51987ed559.json b/tests/integration/responses/recordings/813ac454f8df150f6a9918ddd8a68279f2e21c8948779350810cdf51987ed559.json
deleted file mode 100644
index 1887967a4..000000000
--- a/tests/integration/responses/recordings/813ac454f8df150f6a9918ddd8a68279f2e21c8948779350810cdf51987ed559.json
+++ /dev/null
@@ -1,219 +0,0 @@
-{
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-          "content": "How many experts does the Llama 4 Maverick model have?"
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diff --git a/tests/integration/responses/recordings/816a62894f78f439f800f50431b565c19c73f68de45ec7f96b1c1fd4a7beb4bc.json b/tests/integration/responses/recordings/816a62894f78f439f800f50431b565c19c73f68de45ec7f96b1c1fd4a7beb4bc.json
deleted file mode 100644
index ba63a62a1..000000000
--- a/tests/integration/responses/recordings/816a62894f78f439f800f50431b565c19c73f68de45ec7f96b1c1fd4a7beb4bc.json
+++ /dev/null
@@ -1,1911 +0,0 @@
-{
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-          "content": "How many experts does the Llama 4 Maverick model have?"
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-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-5217982280, score: 2.57802841833685, attributes: {'filename': 'test_sequential_file_search.txt', 'document_id': 'file-5217982280', 'token_count': 19.0, 'metadata_token_count': 11.0} (cite as <|file-5217982280|>)\nThe Llama 4 Maverick model has 128 experts in its mixture of experts architecture.\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        },
-        {
-          "role": "assistant",
-          "content": "The Llama 4 Maverick model has 128 experts in its mixture of experts architecture <|file-5217982280|>."
-        },
-        {
-          "role": "user",
-          "content": "Can you tell me more about the architecture?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
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-              "index": 0,
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-          "tool_call_id": "call_65UIUP8qaZGeNNTjOTONwYKj",
-          "content": [
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-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
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-              "text": "[1] document_id: file-5217982280, score: 1.9325686555844606, attributes: {'filename': 'test_sequential_file_search.txt', 'document_id': 'file-5217982280', 'token_count': 19.0, 'metadata_token_count': 11.0} (cite as <|file-5217982280|>)\nThe Llama 4 Maverick model has 128 experts in its mixture of experts architecture.\n"
-            },
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-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model architecture\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
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diff --git a/tests/integration/responses/recordings/818fcb5332bf6025c6550a3c5acffc75d16dbe1fe0d904783b52c844593463ab.json b/tests/integration/responses/recordings/818fcb5332bf6025c6550a3c5acffc75d16dbe1fe0d904783b52c844593463ab.json
deleted file mode 100644
index 08d4808d8..000000000
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diff --git a/tests/integration/responses/recordings/81c187746f90357a29cacca14e867cfc23e3587c73e96f498accfee4a04a213a.json b/tests/integration/responses/recordings/81c187746f90357a29cacca14e867cfc23e3587c73e96f498accfee4a04a213a.json
deleted file mode 100644
index 8ed24e9bb..000000000
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diff --git a/tests/integration/responses/recordings/82a37bb569542fe6d1187aeeb101e1c1df907e6f92420e69d7d69c5b24c3905f.json b/tests/integration/responses/recordings/82a37bb569542fe6d1187aeeb101e1c1df907e6f92420e69d7d69c5b24c3905f.json
deleted file mode 100644
index 864e6a30d..000000000
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diff --git a/tests/integration/responses/recordings/831d92084691c9d83aa1ca0cb6b5019f9acfb2630062f6db261b253398216bb9.json b/tests/integration/responses/recordings/831d92084691c9d83aa1ca0cb6b5019f9acfb2630062f6db261b253398216bb9.json
deleted file mode 100644
index 09dab5251..000000000
--- a/tests/integration/responses/recordings/831d92084691c9d83aa1ca0cb6b5019f9acfb2630062f6db261b253398216bb9.json
+++ /dev/null
@@ -1,732 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
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-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_9Ofp0Uepi3uOnEmuFtm9yvCU",
-          "content": [
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-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-78420035045, score: 2.933222791810999, attributes: {'filename': 'test_response_non_streaming_file_search.txt', 'document_id': 'file-78420035045', 'token_count': 10.0, 'metadata_token_count': 13.0} (cite as <|file-78420035045|>)\nLlama 4 Maverick has 128 experts\n"
-            },
-            {
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-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
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diff --git a/tests/integration/responses/recordings/832c09ecdc6c122794ae00ce7e758b933654f257da29944b17f8c4e62d5ebf90.json b/tests/integration/responses/recordings/832c09ecdc6c122794ae00ce7e758b933654f257da29944b17f8c4e62d5ebf90.json
deleted file mode 100644
index b7748446d..000000000
--- a/tests/integration/responses/recordings/832c09ecdc6c122794ae00ce7e758b933654f257da29944b17f8c4e62d5ebf90.json
+++ /dev/null
@@ -1,1087 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_Zb3UPWm2DOVVTce3d5Uo21FX",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_Zb3UPWm2DOVVTce3d5Uo21FX",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 2 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-433408948870, score: 1.4947232325305748, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-433408948870', 'token_count': 98.0, 'metadata_token_count': 11.0} (cite as <|file-433408948870|>)\n,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "[2] document_id: file-433408948870, score: 1.1417523389560924, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-433408948870', 'token_count': 498.0, 'metadata_token_count': 11.0} (cite as <|file-433408948870|>)\nLlama  Stack  \nLlama  Stack  Overview  \nLlama  Stack  standardizes  the  core  building  blocks  that  simplify  AI  application  development.  It  codifies  best  \npractices\n \nacross\n \nthe\n \nLlama\n \necosystem.\n \nMore\n \nspecifically,\n \nit\n \nprovides\n  \u25cf  Unified  API  layer  for  Inference,  RAG,  Agents,  Tools,  Safety,  Evals,  and  Telemetry.  \u25cf  Plugin  architecture  to  support  the  rich  ecosystem  of  different  API  implementations  in  various  \nenvironments,\n \nincluding\n \nlocal\n \ndevelopment,\n \non-premises,\n \ncloud,\n \nand\n \nmobile.\n \u25cf  Prepackaged  verified  distributions  which  offer  a  one-stop  solution  for  developers  to  get  started  quickly  \nand\n \nreliably\n \nin\n \nany\n \nenvironment.\n \u25cf  Multiple  developer  interfaces  like  CLI  and  SDKs  for  Python,  Typescript,  iOS,  and  Android.  \u25cf  Standalone  applications  as  examples  for  how  to  build  production-grade  AI  applications  with  Llama  \nStack.\n \nLlama  Stack  Benefits  \n\u25cf  Flexible  Options:  Developers  can  choose  their  preferred  infrastructure  without  changing  APIs  and  enjoy  \nflexible\n \ndeployment\n \nchoices.\n \u25cf  Consistent  Experience:  With  its  unified  APIs,  Llama  Stack  makes  it  easier  to  build,  test,  and  deploy  AI  \napplications\n \nwith\n \nconsistent\n \napplication\n \nbehavior.\n \u25cf  Robust  Ecosystem:  Llama  Stack  is  already  integrated  with  distribution  partners  (cloud  providers,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
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diff --git a/tests/integration/responses/recordings/835f83febec3613e8a1c009f6b6c016141d64654669e52c8afac2d3909c727f7.json b/tests/integration/responses/recordings/835f83febec3613e8a1c009f6b6c016141d64654669e52c8afac2d3909c727f7.json
deleted file mode 100644
index 2bbc672f6..000000000
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diff --git a/tests/integration/responses/recordings/84ee2161b38281c6f20a2db28a3a16626ec30a9022eec6327fdba016c3b8d4a0.json b/tests/integration/responses/recordings/84ee2161b38281c6f20a2db28a3a16626ec30a9022eec6327fdba016c3b8d4a0.json
deleted file mode 100644
index e0fc0cb22..000000000
--- a/tests/integration/responses/recordings/84ee2161b38281c6f20a2db28a3a16626ec30a9022eec6327fdba016c3b8d4a0.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/84f3ac4d8f92d4fc884b329f0b516b18e13a02230eb82befeac5bba5b936a99e.json b/tests/integration/responses/recordings/84f3ac4d8f92d4fc884b329f0b516b18e13a02230eb82befeac5bba5b936a99e.json
deleted file mode 100644
index 15749138c..000000000
--- a/tests/integration/responses/recordings/84f3ac4d8f92d4fc884b329f0b516b18e13a02230eb82befeac5bba5b936a99e.json
+++ /dev/null
@@ -1,732 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
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-              "id": "call_90pCu8l9ITbz463ZJxhGGKm3",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
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-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_90pCu8l9ITbz463ZJxhGGKm3",
-          "content": [
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-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-36441599755, score: 2.933222791810999, attributes: {'filename': 'test_response_non_streaming_file_search.txt', 'document_id': 'file-36441599755', 'token_count': 10.0, 'metadata_token_count': 13.0} (cite as <|file-36441599755|>)\nLlama 4 Maverick has 128 experts\n"
-            },
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-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
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diff --git a/tests/integration/responses/recordings/8574e8f6c619214a65f433b5f7b6dddf2943ab918fde536ace2deb0091e8e7da.json b/tests/integration/responses/recordings/8574e8f6c619214a65f433b5f7b6dddf2943ab918fde536ace2deb0091e8e7da.json
deleted file mode 100644
index fe5320a5d..000000000
--- a/tests/integration/responses/recordings/8574e8f6c619214a65f433b5f7b6dddf2943ab918fde536ace2deb0091e8e7da.json
+++ /dev/null
@@ -1,894 +0,0 @@
-{
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deleted file mode 100644
index a3295342c..000000000
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index e82f77da6..000000000
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+++ /dev/null
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diff --git a/tests/integration/responses/recordings/8ce76cb00986647bbb2175d73915eee068824175e094bf70e5d0fe4711550632.json b/tests/integration/responses/recordings/8ce76cb00986647bbb2175d73915eee068824175e094bf70e5d0fe4711550632.json
deleted file mode 100644
index 1fb3cd0e3..000000000
--- a/tests/integration/responses/recordings/8ce76cb00986647bbb2175d73915eee068824175e094bf70e5d0fe4711550632.json
+++ /dev/null
@@ -1,631 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
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-          "tool_call_id": "call_UVmJRK8x8PZSXaGMP8YkWUTN",
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-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-753491389399, score: 0.1388247736002883, attributes: {'filename': 'test_sequential_file_search.txt', 'document_id': 'file-753491389399', 'token_count': 19.0, 'metadata_token_count': 11.0} (cite as <|file-753491389399|>)\nThe Llama 4 Maverick model has 128 experts in its mixture of experts architecture.\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
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-        {
-          "role": "assistant",
-          "content": "The Llama 4 Maverick model has 128 experts in its mixture of experts architecture <|file-753491389399|>."
-        },
-        {
-          "role": "user",
-          "content": "Can you tell me more about the architecture?"
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-      ],
-      "stream": true,
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-              "properties": {
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-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
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-    "model": "gpt-4o"
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diff --git a/tests/integration/responses/recordings/8e0e96f0c8e383b40a3889911d2167b05ac000411c0008f23b75b21d979b846d.json b/tests/integration/responses/recordings/8e0e96f0c8e383b40a3889911d2167b05ac000411c0008f23b75b21d979b846d.json
deleted file mode 100644
index a3cf619e5..000000000
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diff --git a/tests/integration/responses/recordings/9303128e4af555495750ef8bf042b6f0940445a217e011c6204a183f51eba35c.json b/tests/integration/responses/recordings/9303128e4af555495750ef8bf042b6f0940445a217e011c6204a183f51eba35c.json
deleted file mode 100644
index 450dfc291..000000000
--- a/tests/integration/responses/recordings/9303128e4af555495750ef8bf042b6f0940445a217e011c6204a183f51eba35c.json
+++ /dev/null
@@ -1,660 +0,0 @@
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diff --git a/tests/integration/responses/recordings/931f6a8f837e39d34c6355aa92a5d795b2c42314cdab60c0a3e69d31769aa29d.json b/tests/integration/responses/recordings/931f6a8f837e39d34c6355aa92a5d795b2c42314cdab60c0a3e69d31769aa29d.json
deleted file mode 100644
index ab60d7ee4..000000000
--- a/tests/integration/responses/recordings/931f6a8f837e39d34c6355aa92a5d795b2c42314cdab60c0a3e69d31769aa29d.json
+++ /dev/null
@@ -1,428 +0,0 @@
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diff --git a/tests/integration/responses/recordings/9bab7e0eaff090d1924a92fb3637eb59db7eb30a1344b9f6b4cdc0fbc405700e.json b/tests/integration/responses/recordings/9bab7e0eaff090d1924a92fb3637eb59db7eb30a1344b9f6b4cdc0fbc405700e.json
deleted file mode 100644
index 90b30eb91..000000000
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diff --git a/tests/integration/responses/recordings/9d4488f127623f1ac2b73fd88ba1fe624fdc346efd40a6b0408be9e159bb741b.json b/tests/integration/responses/recordings/9d4488f127623f1ac2b73fd88ba1fe624fdc346efd40a6b0408be9e159bb741b.json
deleted file mode 100644
index 4a80410aa..000000000
--- a/tests/integration/responses/recordings/9d4488f127623f1ac2b73fd88ba1fe624fdc346efd40a6b0408be9e159bb741b.json
+++ /dev/null
@@ -1,485 +0,0 @@
-{
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-                "content": " \n\n",
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diff --git a/tests/integration/responses/recordings/a221946e51170a96f1da7cc49426ad30333bcadf9ff79c28caf7eed2cca90976.json b/tests/integration/responses/recordings/a221946e51170a96f1da7cc49426ad30333bcadf9ff79c28caf7eed2cca90976.json
deleted file mode 100644
index 72e42c099..000000000
--- a/tests/integration/responses/recordings/a221946e51170a96f1da7cc49426ad30333bcadf9ff79c28caf7eed2cca90976.json
+++ /dev/null
@@ -1,3118 +0,0 @@
-{
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-        ",  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   "
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-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "text-embedding-3-small"
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diff --git a/tests/integration/responses/recordings/a3679b147eb7a264ff9d1d404f80c7e6caf68b5b0819ffdb20d830d9a4ac01ff.json b/tests/integration/responses/recordings/a3679b147eb7a264ff9d1d404f80c7e6caf68b5b0819ffdb20d830d9a4ac01ff.json
deleted file mode 100644
index 48d79b0d2..000000000
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diff --git a/tests/integration/responses/recordings/a5c2d46fdd20a6c1ec59a005059f30aa7f0f01ce2d655146a52589168aa6c990.json b/tests/integration/responses/recordings/a5c2d46fdd20a6c1ec59a005059f30aa7f0f01ce2d655146a52589168aa6c990.json
deleted file mode 100644
index 12e7004ce..000000000
--- a/tests/integration/responses/recordings/a5c2d46fdd20a6c1ec59a005059f30aa7f0f01ce2d655146a52589168aa6c990.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/a8d230449cbd412fb6e8503d36be50464fdd81bf0b0511a259997323c2847a63.json b/tests/integration/responses/recordings/a8d230449cbd412fb6e8503d36be50464fdd81bf0b0511a259997323c2847a63.json
deleted file mode 100644
index f551ec5c4..000000000
--- a/tests/integration/responses/recordings/a8d230449cbd412fb6e8503d36be50464fdd81bf0b0511a259997323c2847a63.json
+++ /dev/null
@@ -1,501 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_basic_responses.py::test_response_streaming_basic[client_with_models-txt=openai/gpt-4o-image_input]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": [
-            {
-              "type": "text",
-              "text": "what teams are playing in this image?"
-            }
-          ]
-        },
-        {
-          "role": "user",
-          "content": [
-            {
-              "type": "image_url",
-              "image_url": {
-                "url": "https://upload.wikimedia.org/wikipedia/commons/3/3b/LeBron_James_Layup_%28Cleveland_vs_Brooklyn_2018%29.jpg",
-                "detail": "auto"
-              }
-            }
-          ]
-        }
-      ],
-      "stream": true
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
-    "body": [
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-a8d230449cbd",
-          "choices": [
-            {
-              "delta": {
-                "content": "",
-                "function_call": null,
-                "refusal": null,
-                "role": "assistant",
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_cbf1785567",
-          "usage": null,
-          "obfuscation": "EM8pD84HPZ9"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-a8d230449cbd",
-          "choices": [
-            {
-              "delta": {
-                "content": "The",
-                "function_call": null,
-                "refusal": null,
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diff --git a/tests/integration/responses/recordings/aa12bef744323396e0b385f349b77b3636e695370c53821fb87e135f387c95ec.json b/tests/integration/responses/recordings/aa12bef744323396e0b385f349b77b3636e695370c53821fb87e135f387c95ec.json
deleted file mode 100644
index 4a9414dd5..000000000
--- a/tests/integration/responses/recordings/aa12bef744323396e0b385f349b77b3636e695370c53821fb87e135f387c95ec.json
+++ /dev/null
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-            "index": 0,
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-        ],
-        "model": "text-embedding-3-small",
-        "object": "list",
-        "usage": {
-          "prompt_tokens": 10,
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-    "is_streaming": false
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-}
diff --git a/tests/integration/responses/recordings/b5ba164d766f544b0f95d4a9c153a0eb22f259ea97dbd3a2d3ba909a23af9c21.json b/tests/integration/responses/recordings/b5ba164d766f544b0f95d4a9c153a0eb22f259ea97dbd3a2d3ba909a23af9c21.json
deleted file mode 100644
index 5b807b388..000000000
--- a/tests/integration/responses/recordings/b5ba164d766f544b0f95d4a9c153a0eb22f259ea97dbd3a2d3ba909a23af9c21.json
+++ /dev/null
@@ -1,1575 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search[client_with_models-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536-llama_experts]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "text-embedding-3-small",
-      "input": [
-        "Llama 4 Maverick has 128 experts"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "text-embedding-3-small"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
-        "data": [
-          {
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-            ],
-            "index": 0,
-            "object": "embedding"
-          }
-        ],
-        "model": "text-embedding-3-small",
-        "object": "list",
-        "usage": {
-          "prompt_tokens": 10,
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-        }
-      }
-    },
-    "is_streaming": false
-  }
-}
diff --git a/tests/integration/responses/recordings/b6484b82fd6d6cd548e7b31637994cf2bf1d630699b33ff6e5161b880156e840.json b/tests/integration/responses/recordings/b6484b82fd6d6cd548e7b31637994cf2bf1d630699b33ff6e5161b880156e840.json
deleted file mode 100644
index 86bec634b..000000000
--- a/tests/integration/responses/recordings/b6484b82fd6d6cd548e7b31637994cf2bf1d630699b33ff6e5161b880156e840.json
+++ /dev/null
@@ -1,291 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_sequential_file_search[client_with_models-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_zS2WxgXWetjnlPt2MzH9Asrc",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
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diff --git a/tests/integration/responses/recordings/b7c02d59e1fa664de53afecc490f0bb6d7889a12817d450089650c31351a05d0.json b/tests/integration/responses/recordings/b7c02d59e1fa664de53afecc490f0bb6d7889a12817d450089650c31351a05d0.json
deleted file mode 100644
index aa550551f..000000000
--- a/tests/integration/responses/recordings/b7c02d59e1fa664de53afecc490f0bb6d7889a12817d450089650c31351a05d0.json
+++ /dev/null
@@ -1,1301 +0,0 @@
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diff --git a/tests/integration/responses/recordings/b847ae54cba58bd5c0cf754003ee488abbedd3859880f5b22813058ac59efcb9.json b/tests/integration/responses/recordings/b847ae54cba58bd5c0cf754003ee488abbedd3859880f5b22813058ac59efcb9.json
deleted file mode 100644
index 1bf18f31a..000000000
--- a/tests/integration/responses/recordings/b847ae54cba58bd5c0cf754003ee488abbedd3859880f5b22813058ac59efcb9.json
+++ /dev/null
@@ -1,447 +0,0 @@
-{
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-  "request": {
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-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": [
-            {
-              "type": "text",
-              "text": "what teams are playing in this image?"
-            }
-          ]
-        },
-        {
-          "role": "user",
-          "content": [
-            {
-              "type": "image_url",
-              "image_url": {
-                "url": "https://upload.wikimedia.org/wikipedia/commons/3/3b/LeBron_James_Layup_%28Cleveland_vs_Brooklyn_2018%29.jpg",
-                "detail": "auto"
-              }
-            }
-          ]
-        }
-      ],
-      "stream": true
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
-    "body": [
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-        "__data__": {
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-        "__data__": {
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-              "delta": {
-                "content": " Nets",
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-                "refusal": null,
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-              "finish_reason": "stop",
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-    "is_streaming": true
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diff --git a/tests/integration/responses/recordings/b86c1bd4ac858dd4d109a784f0ffdc07c4f4c697e788009446318289104b55dc.json b/tests/integration/responses/recordings/b86c1bd4ac858dd4d109a784f0ffdc07c4f4c697e788009446318289104b55dc.json
deleted file mode 100644
index 8a53d0bc6..000000000
--- a/tests/integration/responses/recordings/b86c1bd4ac858dd4d109a784f0ffdc07c4f4c697e788009446318289104b55dc.json
+++ /dev/null
@@ -1,1082 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search[client_with_models-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536-llama_experts]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_90pCu8l9ITbz463ZJxhGGKm3",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_90pCu8l9ITbz463ZJxhGGKm3",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-40b9ece5067845d498f085845de6b1cc, score: 2.933222791810999, attributes: {'filename': 'test_response_non_streaming_file_search.txt', 'document_id': 'file-40b9ece5067845d498f085845de6b1cc', 'token_count': 10.0, 'metadata_token_count': 13.0} (cite as <|file-40b9ece5067845d498f085845de6b1cc|>)\nLlama 4 Maverick has 128 experts\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        }
-      ],
-      "stream": true,
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
-                "query"
-              ]
-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
-    "body": [
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-b86c1bd4ac85",
-          "choices": [
-            {
-              "delta": {
-                "content": "",
-                "function_call": null,
-                "refusal": null,
-                "role": "assistant",
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "CnAYONBkk9n"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-b86c1bd4ac85",
-          "choices": [
-            {
-              "delta": {
-                "content": "The",
-                "function_call": null,
-                "refusal": null,
-                "role": null,
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diff --git a/tests/integration/responses/recordings/c4915bdee5a93d3c0426367bd29868d84fb3e4b26c372407f177a4812bd90ea7.json b/tests/integration/responses/recordings/c4915bdee5a93d3c0426367bd29868d84fb3e4b26c372407f177a4812bd90ea7.json
deleted file mode 100644
index 021cc4661..000000000
--- a/tests/integration/responses/recordings/c4915bdee5a93d3c0426367bd29868d84fb3e4b26c372407f177a4812bd90ea7.json
+++ /dev/null
@@ -1,250 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search[openai_client-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536-llama_experts_pdf]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_zKJ7WgvCO3tx6yB0We1qI0d8",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_zKJ7WgvCO3tx6yB0We1qI0d8",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 2 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-728796232029, score: 1.4945131220963286, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-728796232029', 'token_count': 98.0, 'metadata_token_count': 11.0} (cite as <|file-728796232029|>)\n,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "[2] document_id: file-728796232029, score: 1.1415676746925796, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-728796232029', 'token_count': 498.0, 'metadata_token_count': 11.0} (cite as <|file-728796232029|>)\nLlama  Stack  \nLlama  Stack  Overview  \nLlama  Stack  standardizes  the  core  building  blocks  that  simplify  AI  application  development.  It  codifies  best  \npractices\n \nacross\n \nthe\n \nLlama\n \necosystem.\n \nMore\n \nspecifically,\n \nit\n \nprovides\n  \u25cf  Unified  API  layer  for  Inference,  RAG,  Agents,  Tools,  Safety,  Evals,  and  Telemetry.  \u25cf  Plugin  architecture  to  support  the  rich  ecosystem  of  different  API  implementations  in  various  \nenvironments,\n \nincluding\n \nlocal\n \ndevelopment,\n \non-premises,\n \ncloud,\n \nand\n \nmobile.\n \u25cf  Prepackaged  verified  distributions  which  offer  a  one-stop  solution  for  developers  to  get  started  quickly  \nand\n \nreliably\n \nin\n \nany\n \nenvironment.\n \u25cf  Multiple  developer  interfaces  like  CLI  and  SDKs  for  Python,  Typescript,  iOS,  and  Android.  \u25cf  Standalone  applications  as  examples  for  how  to  build  production-grade  AI  applications  with  Llama  \nStack.\n \nLlama  Stack  Benefits  \n\u25cf  Flexible  Options:  Developers  can  choose  their  preferred  infrastructure  without  changing  APIs  and  enjoy  \nflexible\n \ndeployment\n \nchoices.\n \u25cf  Consistent  Experience:  With  its  unified  APIs,  Llama  Stack  makes  it  easier  to  build,  test,  and  deploy  AI  \napplications\n \nwith\n \nconsistent\n \napplication\n \nbehavior.\n \u25cf  Robust  Ecosystem:  Llama  Stack  is  already  integrated  with  distribution  partners  (cloud  providers,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
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-      ],
-      "stream": true,
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
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-    "model": "gpt-4o"
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-        "__data__": {
-          "id": "rec-c4915bdee5a9",
-          "choices": [
-            {
-              "delta": {
-                "content": "4 Maverick model is a Mixture-of-Experts (MoE)",
-                "function_call": null,
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-              },
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-        "__data__": {
-          "id": "rec-c4915bdee5a9",
-          "choices": [
-            {
-              "delta": {
-                "content": " model with ",
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-                "refusal": null,
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-              },
-              "finish_reason": null,
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-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
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-        "__data__": {
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-          "choices": [
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-              "delta": {
-                "content": "128 experts <|file-728796232029|>.",
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-  "id_normalization_mapping": {}
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diff --git a/tests/integration/responses/recordings/c4a6ed09dda5f325b9e3f0438076a88e5e33846d0e0397cf3bec099568ecced3.json b/tests/integration/responses/recordings/c4a6ed09dda5f325b9e3f0438076a88e5e33846d0e0397cf3bec099568ecced3.json
deleted file mode 100644
index 2d49eff34..000000000
--- a/tests/integration/responses/recordings/c4a6ed09dda5f325b9e3f0438076a88e5e33846d0e0397cf3bec099568ecced3.json
+++ /dev/null
@@ -1,763 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search[openai_client-txt=openai/gpt-4o:emb=Nomic-v1.5:dim=768-llama_experts]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_k76vUrLo0Ew7O3OJ5pSSGER9",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_k76vUrLo0Ew7O3OJ5pSSGER9",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-378093378930, score: 0.12350204991476797, attributes: {'filename': 'test_response_non_streaming_file_search.txt', 'document_id': 'file-378093378930', 'token_count': 10.0, 'metadata_token_count': 13.0} (cite as <|file-378093378930|>)\nLlama 4 Maverick has 128 experts\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
-          ]
-        }
-      ],
-      "stream": true,
-      "stream_options": {
-        "include_usage": true
-      },
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
-                "query"
-              ]
-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
-    "body": [
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-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
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-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
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-        }
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-        "__data__": {
-          "id": "rec-c4a6ed09dda5",
-          "choices": [
-            {
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-                "content": "The",
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diff --git a/tests/integration/responses/recordings/c5527a312f1dd5d7026dcfd0f492a6e2cf81fce399049503c8004cf577349506.json b/tests/integration/responses/recordings/c5527a312f1dd5d7026dcfd0f492a6e2cf81fce399049503c8004cf577349506.json
deleted file mode 100644
index 643a6b321..000000000
--- a/tests/integration/responses/recordings/c5527a312f1dd5d7026dcfd0f492a6e2cf81fce399049503c8004cf577349506.json
+++ /dev/null
@@ -1,501 +0,0 @@
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diff --git a/tests/integration/responses/recordings/c793f433223698108d14485dd0ab99a50f0ebde9b68c04602d51f589bfacfa0f.json b/tests/integration/responses/recordings/c793f433223698108d14485dd0ab99a50f0ebde9b68c04602d51f589bfacfa0f.json
deleted file mode 100644
index 84e477ccb..000000000
--- a/tests/integration/responses/recordings/c793f433223698108d14485dd0ab99a50f0ebde9b68c04602d51f589bfacfa0f.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/cca4ac0eab9f1f1fdf3c6a7f21b076332d01d55de8b13ac35ee0414ac7537ba8.json b/tests/integration/responses/recordings/cca4ac0eab9f1f1fdf3c6a7f21b076332d01d55de8b13ac35ee0414ac7537ba8.json
deleted file mode 100644
index 684bdf64d..000000000
--- a/tests/integration/responses/recordings/cca4ac0eab9f1f1fdf3c6a7f21b076332d01d55de8b13ac35ee0414ac7537ba8.json
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diff --git a/tests/integration/responses/recordings/ccc45dcf18e3f5ac43b449612889959e6bccf650c4d135a6a1330ddc37c2405b.json b/tests/integration/responses/recordings/ccc45dcf18e3f5ac43b449612889959e6bccf650c4d135a6a1330ddc37c2405b.json
deleted file mode 100644
index c01e02da8..000000000
--- a/tests/integration/responses/recordings/ccc45dcf18e3f5ac43b449612889959e6bccf650c4d135a6a1330ddc37c2405b.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/ccf305c14285e6c5788c9126f13bc02f786a1562614596c8ac5ffa38cb49e0a1.json b/tests/integration/responses/recordings/ccf305c14285e6c5788c9126f13bc02f786a1562614596c8ac5ffa38cb49e0a1.json
deleted file mode 100644
index 79a3c7bcf..000000000
--- a/tests/integration/responses/recordings/ccf305c14285e6c5788c9126f13bc02f786a1562614596c8ac5ffa38cb49e0a1.json
+++ /dev/null
@@ -1,767 +0,0 @@
-{
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-          "tool_calls": [
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-              "text": "knowledge_search tool found 2 chunks:\nBEGIN of knowledge_search tool results.\n"
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-              "type": "text",
-              "text": "[1] document_id: file-383513632278, score: 0.09107262839224209, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-383513632278', 'token_count': 98.0, 'metadata_token_count': 11.0} (cite as <|file-383513632278|>)\n,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
-              "type": "text",
-              "text": "[2] document_id: file-383513632278, score: 0.058223047015159325, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-383513632278', 'token_count': 498.0, 'metadata_token_count': 11.0} (cite as <|file-383513632278|>)\nLlama  Stack  \nLlama  Stack  Overview  \nLlama  Stack  standardizes  the  core  building  blocks  that  simplify  AI  application  development.  It  codifies  best  \npractices\n \nacross\n \nthe\n \nLlama\n \necosystem.\n \nMore\n \nspecifically,\n \nit\n \nprovides\n  \u25cf  Unified  API  layer  for  Inference,  RAG,  Agents,  Tools,  Safety,  Evals,  and  Telemetry.  \u25cf  Plugin  architecture  to  support  the  rich  ecosystem  of  different  API  implementations  in  various  \nenvironments,\n \nincluding\n \nlocal\n \ndevelopment,\n \non-premises,\n \ncloud,\n \nand\n \nmobile.\n \u25cf  Prepackaged  verified  distributions  which  offer  a  one-stop  solution  for  developers  to  get  started  quickly  \nand\n \nreliably\n \nin\n \nany\n \nenvironment.\n \u25cf  Multiple  developer  interfaces  like  CLI  and  SDKs  for  Python,  Typescript,  iOS,  and  Android.  \u25cf  Standalone  applications  as  examples  for  how  to  build  production-grade  AI  applications  with  Llama  \nStack.\n \nLlama  Stack  Benefits  \n\u25cf  Flexible  Options:  Developers  can  choose  their  preferred  infrastructure  without  changing  APIs  and  enjoy  \nflexible\n \ndeployment\n \nchoices.\n \u25cf  Consistent  Experience:  With  its  unified  APIs,  Llama  Stack  makes  it  easier  to  build,  test,  and  deploy  AI  \napplications\n \nwith\n \nconsistent\n \napplication\n \nbehavior.\n \u25cf  Robust  Ecosystem:  Llama  Stack  is  already  integrated  with  distribution  partners  (cloud  providers,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
-            {
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-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
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diff --git a/tests/integration/responses/recordings/cd95ef741031a85ce04075ba9be7d2abf1d76f63d49edfa6b32a9845e0527c03.json b/tests/integration/responses/recordings/cd95ef741031a85ce04075ba9be7d2abf1d76f63d49edfa6b32a9845e0527c03.json
deleted file mode 100644
index be6e2ef6e..000000000
--- a/tests/integration/responses/recordings/cd95ef741031a85ce04075ba9be7d2abf1d76f63d49edfa6b32a9845e0527c03.json
+++ /dev/null
@@ -1,1915 +0,0 @@
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diff --git a/tests/integration/responses/recordings/cf798a30233ce3791238a03421a6f032f25dd80e142bdadf59749de0360cb3ed.json b/tests/integration/responses/recordings/cf798a30233ce3791238a03421a6f032f25dd80e142bdadf59749de0360cb3ed.json
deleted file mode 100644
index 489d5f139..000000000
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diff --git a/tests/integration/responses/recordings/d07dea1671082e52174ac8d467f3e20958091c2ccc81c976e0a3f26b3f27c27e.json b/tests/integration/responses/recordings/d07dea1671082e52174ac8d467f3e20958091c2ccc81c976e0a3f26b3f27c27e.json
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index 4cdd1fe8a..000000000
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+++ /dev/null
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diff --git a/tests/integration/responses/recordings/d2efc782575c38b455293bba648feb98aa2afda700a2063a1e49433d5fe4eb4b.json b/tests/integration/responses/recordings/d2efc782575c38b455293bba648feb98aa2afda700a2063a1e49433d5fe4eb4b.json
deleted file mode 100644
index d2dc6fddb..000000000
--- a/tests/integration/responses/recordings/d2efc782575c38b455293bba648feb98aa2afda700a2063a1e49433d5fe4eb4b.json
+++ /dev/null
@@ -1,631 +0,0 @@
-{
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-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
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-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
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diff --git a/tests/integration/responses/recordings/d30a3a9a90ea3ba6ea62417aec80e79ee502a2e75b58f7c87ee65c446200af0e.json b/tests/integration/responses/recordings/d30a3a9a90ea3ba6ea62417aec80e79ee502a2e75b58f7c87ee65c446200af0e.json
deleted file mode 100644
index d48bf37ae..000000000
--- a/tests/integration/responses/recordings/d30a3a9a90ea3ba6ea62417aec80e79ee502a2e75b58f7c87ee65c446200af0e.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/d8147a3e034d24f0e677a3a86e73140dff5fccb15ba824434cc899992390a1ca.json b/tests/integration/responses/recordings/d8147a3e034d24f0e677a3a86e73140dff5fccb15ba824434cc899992390a1ca.json
deleted file mode 100644
index 1cb94c66c..000000000
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diff --git a/tests/integration/responses/recordings/da9a93d127e1b0f7cc09445fdb876987dc481bd94343d6f1694b6d9e4f9110d0.json b/tests/integration/responses/recordings/da9a93d127e1b0f7cc09445fdb876987dc481bd94343d6f1694b6d9e4f9110d0.json
deleted file mode 100644
index 376ef812e..000000000
--- a/tests/integration/responses/recordings/da9a93d127e1b0f7cc09445fdb876987dc481bd94343d6f1694b6d9e4f9110d0.json
+++ /dev/null
@@ -1,639 +0,0 @@
-{
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-    "body": {
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-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_qzY7B7EArJwpMqLVer8kcAey",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
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-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_qzY7B7EArJwpMqLVer8kcAey",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-d7cee10212814cfcb75cc091eee11688, score: 2.5781234969335522, attributes: {'filename': 'test_sequential_file_search.txt', 'document_id': 'file-d7cee10212814cfcb75cc091eee11688', 'token_count': 19.0, 'metadata_token_count': 11.0} (cite as <|file-d7cee10212814cfcb75cc091eee11688|>)\nThe Llama 4 Maverick model has 128 experts in its mixture of experts architecture.\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
-            }
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-        },
-        {
-          "role": "assistant",
-          "content": "The Llama 4 Maverick model has 128 experts in its mixture of experts architecture <|file-d7cee10212814cfcb75cc091eee11688|>."
-        },
-        {
-          "role": "user",
-          "content": "Can you tell me more about the architecture?"
-        }
-      ],
-      "stream": true,
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-            "description": "Search for information in a database.",
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-              "properties": {
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-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
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-              ]
-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
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diff --git a/tests/integration/responses/recordings/dbcdb09c1f7f98873b0ea708de87c3f85bc1306aa4e0055e80bbb12501e25135.json b/tests/integration/responses/recordings/dbcdb09c1f7f98873b0ea708de87c3f85bc1306aa4e0055e80bbb12501e25135.json
deleted file mode 100644
index 10111258e..000000000
--- a/tests/integration/responses/recordings/dbcdb09c1f7f98873b0ea708de87c3f85bc1306aa4e0055e80bbb12501e25135.json
+++ /dev/null
@@ -1,660 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        }
-      ],
-      "stream": true,
-      "stream_options": {
-        "include_usage": true
-      },
-      "tools": [
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diff --git a/tests/integration/responses/recordings/dd15c72fb6ea6fb773e09158983926f8769c43aced7ec3b1047e0dad70ea3bfd.json b/tests/integration/responses/recordings/dd15c72fb6ea6fb773e09158983926f8769c43aced7ec3b1047e0dad70ea3bfd.json
deleted file mode 100644
index 11ec3f487..000000000
--- a/tests/integration/responses/recordings/dd15c72fb6ea6fb773e09158983926f8769c43aced7ec3b1047e0dad70ea3bfd.json
+++ /dev/null
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-        "model": "text-embedding-3-small",
-        "object": "list",
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diff --git a/tests/integration/responses/recordings/de9dba9d7fe3da6201ae41b7c61fe75f5910a8175dd46e47966a21eae3de7626.json b/tests/integration/responses/recordings/de9dba9d7fe3da6201ae41b7c61fe75f5910a8175dd46e47966a21eae3de7626.json
deleted file mode 100644
index 12c5dcfad..000000000
--- a/tests/integration/responses/recordings/de9dba9d7fe3da6201ae41b7c61fe75f5910a8175dd46e47966a21eae3de7626.json
+++ /dev/null
@@ -1,628 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search_empty_vector_store[openai_client-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        }
-      ],
-      "stream": true,
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
-                "query"
-              ]
-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
-    "body": [
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-de9dba9d7fe3",
-          "choices": [
-            {
-              "delta": {
-                "content": null,
-                "function_call": null,
-                "refusal": null,
-                "role": "assistant",
-                "tool_calls": [
-                  {
-                    "index": 0,
-                    "id": "call_cwXITZNuapCLvGBx3jpcLCgS",
-                    "function": {
-                      "arguments": "",
-                      "name": "knowledge_search"
-                    },
-                    "type": "function"
-                  }
-                ]
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
-          "model": "gpt-4o-2024-08-06",
-          "object": "chat.completion.chunk",
-          "service_tier": "default",
-          "system_fingerprint": "fp_f64f290af2",
-          "usage": null,
-          "obfuscation": "w"
-        }
-      },
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-de9dba9d7fe3",
-          "choices": [
-            {
-              "delta": {
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diff --git a/tests/integration/responses/recordings/e0ef89da13c3b389e85bbf1fd7e9b113a256b2d1196c6abf60af8b1d38c2a802.json b/tests/integration/responses/recordings/e0ef89da13c3b389e85bbf1fd7e9b113a256b2d1196c6abf60af8b1d38c2a802.json
deleted file mode 100644
index 8eb5c3ae1..000000000
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+++ /dev/null
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-            "index": 0,
-            "object": "embedding"
-          }
-        ],
-        "model": "text-embedding-3-small",
-        "object": "list",
-        "usage": {
-          "prompt_tokens": 10,
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-      }
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-    "is_streaming": false
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-  "id_normalization_mapping": {}
-}
diff --git a/tests/integration/responses/recordings/e522998b44d864c192a5c90c85999743d019e08d4a1e7eee1a5ebefb89fc5cf5.json b/tests/integration/responses/recordings/e522998b44d864c192a5c90c85999743d019e08d4a1e7eee1a5ebefb89fc5cf5.json
deleted file mode 100644
index 62570dcf7..000000000
--- a/tests/integration/responses/recordings/e522998b44d864c192a5c90c85999743d019e08d4a1e7eee1a5ebefb89fc5cf5.json
+++ /dev/null
@@ -1,1299 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search_empty_vector_store[client_with_models-txt=openai/gpt-4o:emb=Nomic-v1.5:dim=768]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_n64EzCBu9K9VmDVOpVCOz92n",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_n64EzCBu9K9VmDVOpVCOz92n",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 0 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query.\n"
-            }
-          ]
-        }
-      ],
-      "stream": true,
-      "stream_options": {
-        "include_usage": true
-      },
-      "tools": [
-        {
-          "type": "function",
-          "function": {
-            "name": "knowledge_search",
-            "description": "Search for information in a database.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "query": {
-                  "type": "string",
-                  "description": "The query to search for. Can be a natural language sentence or keywords."
-                }
-              },
-              "required": [
-                "query"
-              ]
-            }
-          }
-        }
-      ]
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "gpt-4o"
-  },
-  "response": {
-    "body": [
-      {
-        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
-        "__data__": {
-          "id": "rec-e522998b44d8",
-          "choices": [
-            {
-              "delta": {
-                "content": "",
-                "function_call": null,
-                "refusal": null,
-                "role": "assistant",
-                "tool_calls": null
-              },
-              "finish_reason": null,
-              "index": 0,
-              "logprobs": null
-            }
-          ],
-          "created": 0,
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diff --git a/tests/integration/responses/recordings/e6f2729dc72958e5a1a69fe1554af0febb3b87b1b8a7387f24cd16a0911e8e5a.json b/tests/integration/responses/recordings/e6f2729dc72958e5a1a69fe1554af0febb3b87b1b8a7387f24cd16a0911e8e5a.json
deleted file mode 100644
index 627270bc9..000000000
--- a/tests/integration/responses/recordings/e6f2729dc72958e5a1a69fe1554af0febb3b87b1b8a7387f24cd16a0911e8e5a.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/e7777f594336f5ad72b1c9b12db316808a248f008a07ea177c5c88c746004e04.json b/tests/integration/responses/recordings/e7777f594336f5ad72b1c9b12db316808a248f008a07ea177c5c88c746004e04.json
deleted file mode 100644
index f57b20355..000000000
--- a/tests/integration/responses/recordings/e7777f594336f5ad72b1c9b12db316808a248f008a07ea177c5c88c746004e04.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/f2f10c24b29fa4f7e587dbf4b0aca59fd6e607aa47cd0ebf96e08e072f3bd79c.json b/tests/integration/responses/recordings/f2f10c24b29fa4f7e587dbf4b0aca59fd6e607aa47cd0ebf96e08e072f3bd79c.json
deleted file mode 100644
index 62343e88d..000000000
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diff --git a/tests/integration/responses/recordings/f3e202bf262f7ac3cea613bee3dbca0676e82e83074c5c0947dfa38faaad3672.json b/tests/integration/responses/recordings/f3e202bf262f7ac3cea613bee3dbca0676e82e83074c5c0947dfa38faaad3672.json
deleted file mode 100644
index 8166827b8..000000000
--- a/tests/integration/responses/recordings/f3e202bf262f7ac3cea613bee3dbca0676e82e83074c5c0947dfa38faaad3672.json
+++ /dev/null
@@ -1,600 +0,0 @@
-{
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-    "body": {
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-      "messages": [
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-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
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-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
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-              "index": 0,
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-              "function": {
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-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
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-          "role": "tool",
-          "tool_call_id": "call_zS2WxgXWetjnlPt2MzH9Asrc",
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-              "type": "text",
-              "text": "knowledge_search tool found 1 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-5217982280, score: 2.57802841833685, attributes: {'filename': 'test_sequential_file_search.txt', 'document_id': 'file-5217982280', 'token_count': 19.0, 'metadata_token_count': 11.0} (cite as <|file-5217982280|>)\nThe Llama 4 Maverick model has 128 experts in its mixture of experts architecture.\n"
-            },
-            {
-              "type": "text",
-              "text": "END of knowledge_search tool results.\n"
-            },
-            {
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-              "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model number of experts\". Use them as supporting information only in answering this query. Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). Do not add extra punctuation. Use only the file IDs provided (do not invent new ones).\n"
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-        {
-          "role": "assistant",
-          "content": "The Llama 4 Maverick model has 128 experts in its mixture of experts architecture <|file-5217982280|>."
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-        {
-          "role": "user",
-          "content": "Can you tell me more about the architecture?"
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-      ],
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diff --git a/tests/integration/responses/recordings/f4c55be96a3ad64b8f72f0aa7ecb7cce1673ea05bce78c40296aee8a291baa0d.json b/tests/integration/responses/recordings/f4c55be96a3ad64b8f72f0aa7ecb7cce1673ea05bce78c40296aee8a291baa0d.json
deleted file mode 100644
index 91ad883d5..000000000
--- a/tests/integration/responses/recordings/f4c55be96a3ad64b8f72f0aa7ecb7cce1673ea05bce78c40296aee8a291baa0d.json
+++ /dev/null
@@ -1,1437 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_non_streaming_file_search[openai_client-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536-llama_experts_pdf]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
-      "messages": [
-        {
-          "role": "user",
-          "content": "How many experts does the Llama 4 Maverick model have?"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "tool_calls": [
-            {
-              "index": 0,
-              "id": "call_zKJ7WgvCO3tx6yB0We1qI0d8",
-              "type": "function",
-              "function": {
-                "name": "knowledge_search",
-                "arguments": "{\"query\":\"Llama 4 Maverick model number of experts\"}"
-              }
-            }
-          ]
-        },
-        {
-          "role": "tool",
-          "tool_call_id": "call_zKJ7WgvCO3tx6yB0We1qI0d8",
-          "content": [
-            {
-              "type": "text",
-              "text": "knowledge_search tool found 2 chunks:\nBEGIN of knowledge_search tool results.\n"
-            },
-            {
-              "type": "text",
-              "text": "[1] document_id: file-6a2838f48611448e84361f6b005972c8, score: 1.4945131220963286, attributes: {'filename': 'llama_stack_and_models.pdf', 'document_id': 'file-6a2838f48611448e84361f6b005972c8', 'token_count': 98.0, 'metadata_token_count': 11.0} (cite as <|file-6a2838f48611448e84361f6b005972c8|>)\n,  \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n  \nLlama  4  Maverick  \n Llama  4  Maverick  is  a  Mixture-of-Experts  (MoE)  model  with  17  billion  active  parameters  and  128  experts.   \n"
-            },
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diff --git a/tests/integration/responses/recordings/f5e9ed93c27b86c46dc0ce13b49223c263940984400a8abf29a462583dbf7c7f.json b/tests/integration/responses/recordings/f5e9ed93c27b86c46dc0ce13b49223c263940984400a8abf29a462583dbf7c7f.json
deleted file mode 100644
index d274f1336..000000000
--- a/tests/integration/responses/recordings/f5e9ed93c27b86c46dc0ce13b49223c263940984400a8abf29a462583dbf7c7f.json
+++ /dev/null
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diff --git a/tests/integration/responses/recordings/f71a334e7ed26b07541e0059b426fed14b3c7c040ef70a35af390db58b26289e.json b/tests/integration/responses/recordings/f71a334e7ed26b07541e0059b426fed14b3c7c040ef70a35af390db58b26289e.json
deleted file mode 100644
index 06024a0d8..000000000
--- a/tests/integration/responses/recordings/f71a334e7ed26b07541e0059b426fed14b3c7c040ef70a35af390db58b26289e.json
+++ /dev/null
@@ -1,1576 +0,0 @@
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diff --git a/tests/integration/responses/recordings/fb36a435632d5de6e5decf333a7e38e1c629713bfdcc2536d569a776a4091791.json b/tests/integration/responses/recordings/fb36a435632d5de6e5decf333a7e38e1c629713bfdcc2536d569a776a4091791.json
deleted file mode 100644
index a2cac6d79..000000000
--- a/tests/integration/responses/recordings/fb36a435632d5de6e5decf333a7e38e1c629713bfdcc2536d569a776a4091791.json
+++ /dev/null
@@ -1,894 +0,0 @@
-{
-  "test_id": "tests/integration/responses/test_tool_responses.py::test_response_sequential_file_search[client_with_models-txt=openai/gpt-4o:emb=openai/text-embedding-3-small:dim=1536]",
-  "request": {
-    "method": "POST",
-    "url": "https://api.openai.com/v1/v1/chat/completions",
-    "headers": {},
-    "body": {
-      "model": "gpt-4o",
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index f74824ff5..000000000
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diff --git a/tests/integration/responses/recordings/ffd3616510e6b4af54622460f259c291c2759701208db02841abc86d9977f74e.json b/tests/integration/responses/recordings/ffd3616510e6b4af54622460f259c291c2759701208db02841abc86d9977f74e.json
deleted file mode 100644
index 0cd1fa632..000000000
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diff --git a/tests/integration/safety/recordings/7f1fb35b3ab8fe247c03b7a174f67c86959732cacaabd8ee84d34f12032c2129.json b/tests/integration/safety/recordings/7f1fb35b3ab8fe247c03b7a174f67c86959732cacaabd8ee84d34f12032c2129.json
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-    "body": {},
-    "endpoint": "/api/ps",
-    "model": ""
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diff --git a/tests/integration/suites.py b/tests/integration/suites.py
index e1fb6a1c7..c2780325d 100644
--- a/tests/integration/suites.py
+++ b/tests/integration/suites.py
@@ -180,3 +180,16 @@ SUITE_DEFINITIONS: dict[str, Suite] = {
         default_setup="ollama-vision",
     ),
 }
+
+# CI test matrix - single source of truth for continuous integration test configurations
+# This is used by:
+# - .github/workflows/integration-tests.yml (CI jobs)
+# - scripts/cleanup_recordings.py (unused recording cleanup)
+#
+# Each entry defines a (suite, setup) pair that runs in CI.
+# Note: Special test configurations (vllm weekly tests, manual inputs) are handled in the CI workflow.
+CI_MATRIX = [
+    {"suite": "base", "setup": "ollama"},
+    {"suite": "vision", "setup": "ollama-vision"},
+    {"suite": "responses", "setup": "gpt"},
+]
diff --git a/tests/integration/telemetry/recordings/0de60cd6a6ec3dbfc4a7601e77be8083caf34f49147ad1c25efae1de3f0b25e5.json b/tests/integration/telemetry/recordings/0de60cd6a6ec3dbfc4a7601e77be8083caf34f49147ad1c25efae1de3f0b25e5.json
deleted file mode 100644
index ce518f01d..000000000
--- a/tests/integration/telemetry/recordings/0de60cd6a6ec3dbfc4a7601e77be8083caf34f49147ad1c25efae1de3f0b25e5.json
+++ /dev/null
@@ -1,57 +0,0 @@
-{
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-    "headers": {},
-    "body": {
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-      "messages": [
-        {
-          "role": "user",
-          "content": "Test OpenAI telemetry creation"
-        }
-      ],
-      "stream": false
-    },
-    "endpoint": "/v1/chat/completions",
-    "model": "llama3.2:3b-instruct-fp16"
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-        "choices": [
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-            "finish_reason": "stop",
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-            "message": {
-              "content": "I'm happy to help you with setting up and testing OpenAI's telemetry creation.\n\nOpenAI provides a feature called \"Telemetry\" which allows developers to collect data about their users' interactions with the model. To test this feature, we need to create a simple application that uses the OpenAI API and sends telemetry data to their servers.\n\nHere's an example code in Python that demonstrates how to create a simple telemetry creator:\n\n```python\nimport os\nfrom openai.api import API\n\n# Initialize the OpenAI API client\napi = API(os.environ['OPENAI_API_KEY'])\n\ndef create_user():\n    # Create a new user entity\n    user_entity = {\n        'id': 'user-123',\n        'name': 'John Doe',\n        'email': 'john.doe@example.com'\n    }\n    \n    # Send the user creation request to OpenAI\n    response = api.users.create(user_entity)\n    print(f\"User created: {response}\")\n\ndef create_transaction():\n    # Create a new transaction entity\n    transaction_entity = {\n        'id': 'tran-123',\n        'user_id': 'user-123',\n        'transaction_type': 'query'\n    }\n    \n    # Send the transaction creation request to OpenAI\n    response = api.transactions.create(transaction_entity)\n    print(f\"Transaction created: {response}\")\n\ndef send_telemetry_data():\n    # Create a new telemetry event entity\n    telemetry_event_entity = {\n        'id': 'telem-123',\n        'transaction_id': 'tran-123',\n        'data': '{ \"event\": \"test\", \"user_id\": 1 }'\n    }\n    \n    # Send the telemetry data to OpenAI\n    response = api.telemetry.create(telemetry_event_entity)\n    print(f\"Telemetry event sent: {response}\")\n\n# Test the telemetry creation\ncreate_user()\ncreate_transaction()\nsend_telemetry_data()\n```\n\nMake sure you replace `OPENAI_API_KEY` with your actual API key. Also, ensure that you have the OpenAI API client library installed by running `pip install openai`.\n\nOnce you've created the test code, run it and observe the behavior of the telemetry creation process.\n\nPlease let me know if you need further modifications or assistance!",
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diff --git a/tests/integration/telemetry/recordings/d45c9a9229e7e3f50a6eac139508babe21988649eb321b562f74061f58593c25.json b/tests/integration/telemetry/recordings/d45c9a9229e7e3f50a6eac139508babe21988649eb321b562f74061f58593c25.json
deleted file mode 100644
index b148c9e51..000000000
--- a/tests/integration/telemetry/recordings/d45c9a9229e7e3f50a6eac139508babe21988649eb321b562f74061f58593c25.json
+++ /dev/null
@@ -1,4211 +0,0 @@
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-      "messages": [
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-          "content": "Test trace openai 1"
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diff --git a/tests/integration/telemetry/recordings/dba5042d6691c2fbc29f2172c0f175e235f2829cb1c3e49781dd2b1850e28775.json b/tests/integration/telemetry/recordings/dba5042d6691c2fbc29f2172c0f175e235f2829cb1c3e49781dd2b1850e28775.json
deleted file mode 100644
index bfed48cb4..000000000
--- a/tests/integration/telemetry/recordings/dba5042d6691c2fbc29f2172c0f175e235f2829cb1c3e49781dd2b1850e28775.json
+++ /dev/null
@@ -1,59 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/0017fb171832738ab63935b610003c8fee26dcc73e8f5c5a741b8ba8870ee5cd.json b/tests/integration/vector_io/recordings/0017fb171832738ab63935b610003c8fee26dcc73e8f5c5a741b8ba8870ee5cd.json
deleted file mode 100644
index 8888e3cee..000000000
--- a/tests/integration/vector_io/recordings/0017fb171832738ab63935b610003c8fee26dcc73e8f5c5a741b8ba8870ee5cd.json
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diff --git a/tests/integration/vector_io/recordings/00382b85acc6f335afb503d9520578741f3d88c398bc544e008de88f8683e02c.json b/tests/integration/vector_io/recordings/00382b85acc6f335afb503d9520578741f3d88c398bc544e008de88f8683e02c.json
deleted file mode 100644
index a7e43201d..000000000
--- a/tests/integration/vector_io/recordings/00382b85acc6f335afb503d9520578741f3d88c398bc544e008de88f8683e02c.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
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-      "input": [
-        "Why are data structures important in computer science?"
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-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/009ed4389000cf225e39ce2cd3167249791baa941906e0325f46be5b3223c4d8.json b/tests/integration/vector_io/recordings/009ed4389000cf225e39ce2cd3167249791baa941906e0325f46be5b3223c4d8.json
deleted file mode 100644
index c508a1f08..000000000
--- a/tests/integration/vector_io/recordings/009ed4389000cf225e39ce2cd3167249791baa941906e0325f46be5b3223c4d8.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
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-      "input": [
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-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
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-        "object": "list",
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diff --git a/tests/integration/vector_io/recordings/00af71a2d4b59c7120e3972032ff25aeba47766d18eb6714743f3a95753165f5.json b/tests/integration/vector_io/recordings/00af71a2d4b59c7120e3972032ff25aeba47766d18eb6714743f3a95753165f5.json
deleted file mode 100644
index aa779f6fe..000000000
--- a/tests/integration/vector_io/recordings/00af71a2d4b59c7120e3972032ff25aeba47766d18eb6714743f3a95753165f5.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-      "input": [
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-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/00b014835d02f114ef2bcfac4d875f9043a6c697306450d04f20014d6f71ccfd.json b/tests/integration/vector_io/recordings/00b014835d02f114ef2bcfac4d875f9043a6c697306450d04f20014d6f71ccfd.json
deleted file mode 100644
index 9605d5e0b..000000000
--- a/tests/integration/vector_io/recordings/00b014835d02f114ef2bcfac4d875f9043a6c697306450d04f20014d6f71ccfd.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-    "headers": {},
-    "body": {
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-      "input": [
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diff --git a/tests/integration/vector_io/recordings/00ef6c256b56c8de003a6d779884dd80db7d67d0d4af6280fec506503425bfe1.json b/tests/integration/vector_io/recordings/00ef6c256b56c8de003a6d779884dd80db7d67d0d4af6280fec506503425bfe1.json
deleted file mode 100644
index 04161bcb0..000000000
--- a/tests/integration/vector_io/recordings/00ef6c256b56c8de003a6d779884dd80db7d67d0d4af6280fec506503425bfe1.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/013d76ece13c49b04c9ab9714671cc74f96e90db65c73e3a50a98702351df2c1.json b/tests/integration/vector_io/recordings/013d76ece13c49b04c9ab9714671cc74f96e90db65c73e3a50a98702351df2c1.json
deleted file mode 100644
index e5d251d8e..000000000
--- a/tests/integration/vector_io/recordings/013d76ece13c49b04c9ab9714671cc74f96e90db65c73e3a50a98702351df2c1.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-      "input": [
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diff --git a/tests/integration/vector_io/recordings/01a319ad65beb355edeaac4d39e620e83bfed1bbcc573b80c3117009b0c12c4a.json b/tests/integration/vector_io/recordings/01a319ad65beb355edeaac4d39e620e83bfed1bbcc573b80c3117009b0c12c4a.json
deleted file mode 100644
index 9b34a49f8..000000000
--- a/tests/integration/vector_io/recordings/01a319ad65beb355edeaac4d39e620e83bfed1bbcc573b80c3117009b0c12c4a.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_with_high_score_filter[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "Python is a high-level programming language with code readability and fewer lines than C++ or Java"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
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diff --git a/tests/integration/vector_io/recordings/01b03f60f707c31e3db6ee7474df5aad72d003eee3fca5360ad4015f0fd0e30e.json b/tests/integration/vector_io/recordings/01b03f60f707c31e3db6ee7474df5aad72d003eee3fca5360ad4015f0fd0e30e.json
deleted file mode 100644
index 478579a0f..000000000
--- a/tests/integration/vector_io/recordings/01b03f60f707c31e3db6ee7474df5aad72d003eee3fca5360ad4015f0fd0e30e.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-      "input": [
-        "machine learning and artificial intelligence"
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-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
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diff --git a/tests/integration/vector_io/recordings/02630ecc0d941bf6f878e89f4753d30018fbd020289803e4d1df6d0a0b8eaf64.json b/tests/integration/vector_io/recordings/02630ecc0d941bf6f878e89f4753d30018fbd020289803e4d1df6d0a0b8eaf64.json
deleted file mode 100644
index af41af09c..000000000
--- a/tests/integration/vector_io/recordings/02630ecc0d941bf6f878e89f4753d30018fbd020289803e4d1df6d0a0b8eaf64.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "This is a test file 0"
-      ],
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
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diff --git a/tests/integration/vector_io/recordings/0296d7587e6e0c465201c0dec1ca0d56a7d1d799703bfcb2199e96f3576d5fcc.json b/tests/integration/vector_io/recordings/0296d7587e6e0c465201c0dec1ca0d56a7d1d799703bfcb2199e96f3576d5fcc.json
deleted file mode 100644
index ec5b74108..000000000
--- a/tests/integration/vector_io/recordings/0296d7587e6e0c465201c0dec1ca0d56a7d1d799703bfcb2199e96f3576d5fcc.json
+++ /dev/null
@@ -1,424 +0,0 @@
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diff --git a/tests/integration/vector_io/recordings/02c9e90314152c1bb70af3259fb34e5ff572625e5218fbdd653c654649a91d53.json b/tests/integration/vector_io/recordings/02c9e90314152c1bb70af3259fb34e5ff572625e5218fbdd653c654649a91d53.json
deleted file mode 100644
index 0bbfdafac..000000000
--- a/tests/integration/vector_io/recordings/02c9e90314152c1bb70af3259fb34e5ff572625e5218fbdd653c654649a91d53.json
+++ /dev/null
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diff --git a/tests/integration/vector_io/recordings/03a7e73eef7e263f4ab669fa48aa157c476b6cfb054f41e50ad5a6594512ea2d.json b/tests/integration/vector_io/recordings/03a7e73eef7e263f4ab669fa48aa157c476b6cfb054f41e50ad5a6594512ea2d.json
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diff --git a/tests/integration/vector_io/recordings/04c8026448f31efabdc099b3c11824c0426a56e8449445574769849fe77d10c8.json b/tests/integration/vector_io/recordings/04c8026448f31efabdc099b3c11824c0426a56e8449445574769849fe77d10c8.json
deleted file mode 100644
index fcefd3eec..000000000
--- a/tests/integration/vector_io/recordings/04c8026448f31efabdc099b3c11824c0426a56e8449445574769849fe77d10c8.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is batch list test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/053b1a14834e439c49e37feb3b7c5f3355b7351be33c808c74367af746eb8d62.json b/tests/integration/vector_io/recordings/053b1a14834e439c49e37feb3b7c5f3355b7351be33c808c74367af746eb8d62.json
deleted file mode 100644
index 829192cfc..000000000
--- a/tests/integration/vector_io/recordings/053b1a14834e439c49e37feb3b7c5f3355b7351be33c808c74367af746eb8d62.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/05b3a368764ad1c862a511f6777c88c0cc4190b4799acdbd749f3b4caf432db0.json b/tests/integration/vector_io/recordings/05b3a368764ad1c862a511f6777c88c0cc4190b4799acdbd749f3b4caf432db0.json
deleted file mode 100644
index 6ecd4a1f5..000000000
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-{
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diff --git a/tests/integration/vector_io/recordings/062e1b768d8f879e5278243d70f2dae044c289f5dba21448939c48b3749c75cc.json b/tests/integration/vector_io/recordings/062e1b768d8f879e5278243d70f2dae044c289f5dba21448939c48b3749c75cc.json
deleted file mode 100644
index 5d303429a..000000000
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-{
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diff --git a/tests/integration/vector_io/recordings/0638a023d11222fd6cdf431c95ccbed914b37b6d212e5254ea0140441bab5aa6.json b/tests/integration/vector_io/recordings/0638a023d11222fd6cdf431c95ccbed914b37b6d212e5254ea0140441bab5aa6.json
deleted file mode 100644
index 88ffe563b..000000000
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diff --git a/tests/integration/vector_io/recordings/0838ee102f6ac2da4e71334cf0b3aadd9761b4374ae7e1f2deedff962992115d.json b/tests/integration/vector_io/recordings/0838ee102f6ac2da4e71334cf0b3aadd9761b4374ae7e1f2deedff962992115d.json
deleted file mode 100644
index 4474f79f5..000000000
--- a/tests/integration/vector_io/recordings/0838ee102f6ac2da4e71334cf0b3aadd9761b4374ae7e1f2deedff962992115d.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-    "headers": {},
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-      "input": [
-        "How do systems learn automatically?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
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diff --git a/tests/integration/vector_io/recordings/09619a00ffdff45aae1bfb5642b14cf428b37b7106a927094a852c2a3dc0f66d.json b/tests/integration/vector_io/recordings/09619a00ffdff45aae1bfb5642b14cf428b37b7106a927094a852c2a3dc0f66d.json
deleted file mode 100644
index a10e6742d..000000000
--- a/tests/integration/vector_io/recordings/09619a00ffdff45aae1bfb5642b14cf428b37b7106a927094a852c2a3dc0f66d.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_relevance[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384-test_case0]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/0a15a7415cd676f0215ffa3d0d51eee9f1f8b5a3a036492127fe074cf2db5771.json b/tests/integration/vector_io/recordings/0a15a7415cd676f0215ffa3d0d51eee9f1f8b5a3a036492127fe074cf2db5771.json
deleted file mode 100644
index 3f887998a..000000000
--- a/tests/integration/vector_io/recordings/0a15a7415cd676f0215ffa3d0d51eee9f1f8b5a3a036492127fe074cf2db5771.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file 1"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
-        "data": [
-          {
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diff --git a/tests/integration/vector_io/recordings/0a4a48cefd0b5438b08461391cb7fcb0684427b4d3098ba2daaf61560777b855.json b/tests/integration/vector_io/recordings/0a4a48cefd0b5438b08461391cb7fcb0684427b4d3098ba2daaf61560777b855.json
deleted file mode 100644
index b0f09d857..000000000
--- a/tests/integration/vector_io/recordings/0a4a48cefd0b5438b08461391cb7fcb0684427b4d3098ba2daaf61560777b855.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-      "input": [
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-    "endpoint": "/v1/embeddings",
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diff --git a/tests/integration/vector_io/recordings/0b5de416f217cbce16533ea70daf1419ff1346a8c2b95bab7174309fd102b51a.json b/tests/integration/vector_io/recordings/0b5de416f217cbce16533ea70daf1419ff1346a8c2b95bab7174309fd102b51a.json
deleted file mode 100644
index a0108280f..000000000
--- a/tests/integration/vector_io/recordings/0b5de416f217cbce16533ea70daf1419ff1346a8c2b95bab7174309fd102b51a.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is batch test file 1"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/0db99e92d8e46bf53746763050b1aa44d72aa7019356d3e3dc5fc058ae9f47b1.json b/tests/integration/vector_io/recordings/0db99e92d8e46bf53746763050b1aa44d72aa7019356d3e3dc5fc058ae9f47b1.json
deleted file mode 100644
index 26557ee12..000000000
--- a/tests/integration/vector_io/recordings/0db99e92d8e46bf53746763050b1aa44d72aa7019356d3e3dc5fc058ae9f47b1.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-      "input": [
-        "Why are data structures important?"
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-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/0e2d2a3d6eec969a4d4d17083d6cbda40abe92afd23b7d26665d1d61da57b44a.json b/tests/integration/vector_io/recordings/0e2d2a3d6eec969a4d4d17083d6cbda40abe92afd23b7d26665d1d61da57b44a.json
deleted file mode 100644
index 8a9c006b0..000000000
--- a/tests/integration/vector_io/recordings/0e2d2a3d6eec969a4d4d17083d6cbda40abe92afd23b7d26665d1d61da57b44a.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is the content of test file 1"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/0fa534534cb5cda28ab13942c953e5632e056c1e15e1674abd5a296558424fbd.json b/tests/integration/vector_io/recordings/0fa534534cb5cda28ab13942c953e5632e056c1e15e1674abd5a296558424fbd.json
deleted file mode 100644
index 9b171a3fd..000000000
--- a/tests/integration/vector_io/recordings/0fa534534cb5cda28ab13942c953e5632e056c1e15e1674abd5a296558424fbd.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-    "model": "nomic-embed-text:latest"
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diff --git a/tests/integration/vector_io/recordings/0fbf282a067bb1fe2c9fa5c96287b1a0700b6c74372d556c873dda39c603d844.json b/tests/integration/vector_io/recordings/0fbf282a067bb1fe2c9fa5c96287b1a0700b6c74372d556c873dda39c603d844.json
deleted file mode 100644
index 6f8e7c445..000000000
--- a/tests/integration/vector_io/recordings/0fbf282a067bb1fe2c9fa5c96287b1a0700b6c74372d556c873dda39c603d844.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is the content of test file 2"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/12e8cc50ddf64c88d279b944c87119026ffe2ed3000f7f4502a358632e0444ba.json b/tests/integration/vector_io/recordings/12e8cc50ddf64c88d279b944c87119026ffe2ed3000f7f4502a358632e0444ba.json
deleted file mode 100644
index 49f3586f1..000000000
--- a/tests/integration/vector_io/recordings/12e8cc50ddf64c88d279b944c87119026ffe2ed3000f7f4502a358632e0444ba.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/12fb43ca93ef574bf56958c854af7cebd9feca440786124bef31d1aed244e3a0.json b/tests/integration/vector_io/recordings/12fb43ca93ef574bf56958c854af7cebd9feca440786124bef31d1aed244e3a0.json
deleted file mode 100644
index 3758c2926..000000000
--- a/tests/integration/vector_io/recordings/12fb43ca93ef574bf56958c854af7cebd9feca440786124bef31d1aed244e3a0.json
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-{
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diff --git a/tests/integration/vector_io/recordings/1307404b09daf48cfdb89f184f0b82f584e10a08cc3bb17bd2c81379391521a6.json b/tests/integration/vector_io/recordings/1307404b09daf48cfdb89f184f0b82f584e10a08cc3bb17bd2c81379391521a6.json
deleted file mode 100644
index 43610a821..000000000
--- a/tests/integration/vector_io/recordings/1307404b09daf48cfdb89f184f0b82f584e10a08cc3bb17bd2c81379391521a6.json
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@@ -1,1596 +0,0 @@
-{
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--- a/tests/integration/vector_io/recordings/13c5190bbf76d11fb5c92215649c3a2dcaced67f9fffffa41cfad11fac332717.json
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diff --git a/tests/integration/vector_io/recordings/13c696c6d74240a70a1b05d2ca504bbf5edc772d756dec16485b5821c6013c16.json b/tests/integration/vector_io/recordings/13c696c6d74240a70a1b05d2ca504bbf5edc772d756dec16485b5821c6013c16.json
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diff --git a/tests/integration/vector_io/recordings/1521a1b6cbd87d9cec77af07f594020d09b39efc765efe4a9ab077c06bf179c3.json b/tests/integration/vector_io/recordings/1521a1b6cbd87d9cec77af07f594020d09b39efc765efe4a9ab077c06bf179c3.json
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diff --git a/tests/integration/vector_io/recordings/15db13f2dd7a3a9f4a4683f1546858be6c2b837e38e87007aa93e9e16b47d425.json b/tests/integration/vector_io/recordings/15db13f2dd7a3a9f4a4683f1546858be6c2b837e38e87007aa93e9e16b47d425.json
deleted file mode 100644
index 9e3f9d1e5..000000000
--- a/tests/integration/vector_io/recordings/15db13f2dd7a3a9f4a4683f1546858be6c2b837e38e87007aa93e9e16b47d425.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "This is a test file 1"
-      ],
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
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diff --git a/tests/integration/vector_io/recordings/178cb5a8efc255482d52e7bc074f240f7c35fae0227e7cf69a0d98b5927caf06.json b/tests/integration/vector_io/recordings/178cb5a8efc255482d52e7bc074f240f7c35fae0227e7cf69a0d98b5927caf06.json
deleted file mode 100644
index 888b5dbe6..000000000
--- a/tests/integration/vector_io/recordings/178cb5a8efc255482d52e7bc074f240f7c35fae0227e7cf69a0d98b5927caf06.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
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-  "request": {
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-    "body": {
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-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/17df655a22bff78d2c1dec1f1a9fc77b767ddab6681d09e64cfa4b13f8bd404c.json b/tests/integration/vector_io/recordings/17df655a22bff78d2c1dec1f1a9fc77b767ddab6681d09e64cfa4b13f8bd404c.json
deleted file mode 100644
index f7397ab72..000000000
--- a/tests/integration/vector_io/recordings/17df655a22bff78d2c1dec1f1a9fc77b767ddab6681d09e64cfa4b13f8bd404c.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "The secret string is foobazbar."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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diff --git a/tests/integration/vector_io/recordings/18106b39d9f90695f6ea9d2ba8b57faa0c7f568cdd6312d982873565bb57ea44.json b/tests/integration/vector_io/recordings/18106b39d9f90695f6ea9d2ba8b57faa0c7f568cdd6312d982873565bb57ea44.json
deleted file mode 100644
index 176d98c76..000000000
--- a/tests/integration/vector_io/recordings/18106b39d9f90695f6ea9d2ba8b57faa0c7f568cdd6312d982873565bb57ea44.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-      "input": [
-        "What is the secret string?"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/18a3cfa248028cec285ca25857a14f208ab554d1549db0c478310cd0bb69a115.json b/tests/integration/vector_io/recordings/18a3cfa248028cec285ca25857a14f208ab554d1549db0c478310cd0bb69a115.json
deleted file mode 100644
index b0361db91..000000000
--- a/tests/integration/vector_io/recordings/18a3cfa248028cec285ca25857a14f208ab554d1549db0c478310cd0bb69a115.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/18c9ac97c23f673e7df311d0586751f44c86cbad4def92c6e395c1b7b6aef25e.json b/tests/integration/vector_io/recordings/18c9ac97c23f673e7df311d0586751f44c86cbad4def92c6e395c1b7b6aef25e.json
deleted file mode 100644
index 1f419a672..000000000
--- a/tests/integration/vector_io/recordings/18c9ac97c23f673e7df311d0586751f44c86cbad4def92c6e395c1b7b6aef25e.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/194c309b84c1b4e4c27d4d4eb193497007e288a4a7725e5b050d455cb61cb7a8.json b/tests/integration/vector_io/recordings/194c309b84c1b4e4c27d4d4eb193497007e288a4a7725e5b050d455cb61cb7a8.json
deleted file mode 100644
index 67a0428f9..000000000
--- a/tests/integration/vector_io/recordings/194c309b84c1b4e4c27d4d4eb193497007e288a4a7725e5b050d455cb61cb7a8.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-      "input": [
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-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/19ee7e5300789c831e47099999653620ce78ae52d324736748561f337f144570.json b/tests/integration/vector_io/recordings/19ee7e5300789c831e47099999653620ce78ae52d324736748561f337f144570.json
deleted file mode 100644
index 2381edd81..000000000
--- a/tests/integration/vector_io/recordings/19ee7e5300789c831e47099999653620ce78ae52d324736748561f337f144570.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_delete_file[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is a test file 1"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/1a9a4684c3bf89061211d6001435e63237a73d20f7603bd8c71e42da1721d4b9.json b/tests/integration/vector_io/recordings/1a9a4684c3bf89061211d6001435e63237a73d20f7603bd8c71e42da1721d4b9.json
deleted file mode 100644
index 0a9a2c0e4..000000000
--- a/tests/integration/vector_io/recordings/1a9a4684c3bf89061211d6001435e63237a73d20f7603bd8c71e42da1721d4b9.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
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-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
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diff --git a/tests/integration/vector_io/recordings/1b46d16754ff22c16add7562f04bd9b2cc6ea4325d1ebff9c683ba8349346b4d.json b/tests/integration/vector_io/recordings/1b46d16754ff22c16add7562f04bd9b2cc6ea4325d1ebff9c683ba8349346b4d.json
deleted file mode 100644
index 9f43d49fe..000000000
--- a/tests/integration/vector_io/recordings/1b46d16754ff22c16add7562f04bd9b2cc6ea4325d1ebff9c683ba8349346b4d.json
+++ /dev/null
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-{
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diff --git a/tests/integration/vector_io/recordings/1b5c5e4ad05741115893e8d8bd2b0792a405c7ed6e96f610ade889855ba811d8.json b/tests/integration/vector_io/recordings/1b5c5e4ad05741115893e8d8bd2b0792a405c7ed6e96f610ade889855ba811d8.json
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diff --git a/tests/integration/vector_io/recordings/1b5e124ccc2b9a27ecf8ddd316895a25ca47835176f3fa88fc464c11ee4cd1b6.json b/tests/integration/vector_io/recordings/1b5e124ccc2b9a27ecf8ddd316895a25ca47835176f3fa88fc464c11ee4cd1b6.json
deleted file mode 100644
index 4ba758f28..000000000
--- a/tests/integration/vector_io/recordings/1b5e124ccc2b9a27ecf8ddd316895a25ca47835176f3fa88fc464c11ee4cd1b6.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_with_max_num_results[client_with_models-emb=ollama/all-minilm:l6-v2:dim=384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/1bbfdd713cbcc75ea98571495883fcde333b1db79ddc8e397bdaabdf0b2e8667.json b/tests/integration/vector_io/recordings/1bbfdd713cbcc75ea98571495883fcde333b1db79ddc8e397bdaabdf0b2e8667.json
deleted file mode 100644
index fb2d7dec6..000000000
--- a/tests/integration/vector_io/recordings/1bbfdd713cbcc75ea98571495883fcde333b1db79ddc8e397bdaabdf0b2e8667.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "What is Python programming language?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
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diff --git a/tests/integration/vector_io/recordings/1ca1f750ad91b2429c22105f81462ef64c3c1a7565229c92d3a765556edf210c.json b/tests/integration/vector_io/recordings/1ca1f750ad91b2429c22105f81462ef64c3c1a7565229c92d3a765556edf210c.json
deleted file mode 100644
index 88b4ba69c..000000000
--- a/tests/integration/vector_io/recordings/1ca1f750ad91b2429c22105f81462ef64c3c1a7565229c92d3a765556edf210c.json
+++ /dev/null
@@ -1,75 +0,0 @@
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diff --git a/tests/integration/vector_io/recordings/1da19256a5bb6e3d2030299d2711ba7f2e8a574dc54292e3d2abd38bd7d79a9b.json b/tests/integration/vector_io/recordings/1da19256a5bb6e3d2030299d2711ba7f2e8a574dc54292e3d2abd38bd7d79a9b.json
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index 265e57d46..000000000
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-        "model": "nomic-embed-text:latest",
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diff --git a/tests/integration/vector_io/recordings/1dee96193f1fad52a494264b4463b05dde47dbdd4ee01e6b6218afeffe2c5e85.json b/tests/integration/vector_io/recordings/1dee96193f1fad52a494264b4463b05dde47dbdd4ee01e6b6218afeffe2c5e85.json
deleted file mode 100644
index 09e216e31..000000000
--- a/tests/integration/vector_io/recordings/1dee96193f1fad52a494264b4463b05dde47dbdd4ee01e6b6218afeffe2c5e85.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_with_max_num_results[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
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diff --git a/tests/integration/vector_io/recordings/1e1d788daeea797802fb02b1af57f43ea13ee98d2ad790378ce5b58ae6c1b514.json b/tests/integration/vector_io/recordings/1e1d788daeea797802fb02b1af57f43ea13ee98d2ad790378ce5b58ae6c1b514.json
deleted file mode 100644
index e7a4aba45..000000000
--- a/tests/integration/vector_io/recordings/1e1d788daeea797802fb02b1af57f43ea13ee98d2ad790378ce5b58ae6c1b514.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is a test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
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diff --git a/tests/integration/vector_io/recordings/1fad47cf13dfb46ef44da46c8814378e34f8b7e1cb39d7538d942e3ae993da07.json b/tests/integration/vector_io/recordings/1fad47cf13dfb46ef44da46c8814378e34f8b7e1cb39d7538d942e3ae993da07.json
deleted file mode 100644
index fd3655fab..000000000
--- a/tests/integration/vector_io/recordings/1fad47cf13dfb46ef44da46c8814378e34f8b7e1cb39d7538d942e3ae993da07.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
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-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
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diff --git a/tests/integration/vector_io/recordings/20a72a1826742daf86202aafe0f3ee57c84b5374ba204c21845f525250177f84.json b/tests/integration/vector_io/recordings/20a72a1826742daf86202aafe0f3ee57c84b5374ba204c21845f525250177f84.json
deleted file mode 100644
index 62e6595e8..000000000
--- a/tests/integration/vector_io/recordings/20a72a1826742daf86202aafe0f3ee57c84b5374ba204c21845f525250177f84.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-      "input": [
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diff --git a/tests/integration/vector_io/recordings/21e75ec6f58e8fff4031cd8a7093bf3dbc58993bb065572d1bb3984de6fa8062.json b/tests/integration/vector_io/recordings/21e75ec6f58e8fff4031cd8a7093bf3dbc58993bb065572d1bb3984de6fa8062.json
deleted file mode 100644
index bb62a9d22..000000000
--- a/tests/integration/vector_io/recordings/21e75ec6f58e8fff4031cd8a7093bf3dbc58993bb065572d1bb3984de6fa8062.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/2282ae99f44ca555e23e48b2c766c2b4d6b64bb8466f510b581dd5a18c55e765.json b/tests/integration/vector_io/recordings/2282ae99f44ca555e23e48b2c766c2b4d6b64bb8466f510b581dd5a18c55e765.json
deleted file mode 100644
index 2921ec39f..000000000
--- a/tests/integration/vector_io/recordings/2282ae99f44ca555e23e48b2c766c2b4d6b64bb8466f510b581dd5a18c55e765.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/239a4718a8b2400ae18f8b72e5cb98706f8a05c3caf5d6e091d2e1055f8dcc4a.json b/tests/integration/vector_io/recordings/239a4718a8b2400ae18f8b72e5cb98706f8a05c3caf5d6e091d2e1055f8dcc4a.json
deleted file mode 100644
index 922631e58..000000000
--- a/tests/integration/vector_io/recordings/239a4718a8b2400ae18f8b72e5cb98706f8a05c3caf5d6e091d2e1055f8dcc4a.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is a test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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-        "model": "nomic-embed-text:latest",
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diff --git a/tests/integration/vector_io/recordings/23e4e443a0b1d196237ea84076f9952c5d4b5586256b5c1b3497d3b4f3e6ade0.json b/tests/integration/vector_io/recordings/23e4e443a0b1d196237ea84076f9952c5d4b5586256b5c1b3497d3b4f3e6ade0.json
deleted file mode 100644
index 9f8e1341b..000000000
--- a/tests/integration/vector_io/recordings/23e4e443a0b1d196237ea84076f9952c5d4b5586256b5c1b3497d3b4f3e6ade0.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_file_batch_create_and_retrieve[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is batch test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
-        "data": [
-          {
-            "embedding": [
-              0.046143305,
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diff --git a/tests/integration/vector_io/recordings/24186b97bf36e7344379d872878e0526f142ce8829e5fed340a78d562fd4af30.json b/tests/integration/vector_io/recordings/24186b97bf36e7344379d872878e0526f142ce8829e5fed340a78d562fd4af30.json
deleted file mode 100644
index 61fa5a7d6..000000000
--- a/tests/integration/vector_io/recordings/24186b97bf36e7344379d872878e0526f142ce8829e5fed340a78d562fd4af30.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
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-      "input": [
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diff --git a/tests/integration/vector_io/recordings/249fb6786c435bd92dd7a203875f061b0065e1e6531987902cd0939781c016f9.json b/tests/integration/vector_io/recordings/249fb6786c435bd92dd7a203875f061b0065e1e6531987902cd0939781c016f9.json
deleted file mode 100644
index c96ed4324..000000000
--- a/tests/integration/vector_io/recordings/249fb6786c435bd92dd7a203875f061b0065e1e6531987902cd0939781c016f9.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
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-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
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diff --git a/tests/integration/vector_io/recordings/24bd6332335675307cc18d54d66ec7f98d5ab1ee04c1172ecd9d9433c2f733fd.json b/tests/integration/vector_io/recordings/24bd6332335675307cc18d54d66ec7f98d5ab1ee04c1172ecd9d9433c2f733fd.json
deleted file mode 100644
index 8ffd85f96..000000000
--- a/tests/integration/vector_io/recordings/24bd6332335675307cc18d54d66ec7f98d5ab1ee04c1172ecd9d9433c2f733fd.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file 2"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/261f92e807d9c19cd7982434744682ab971149b8984186622c14060fc6c203e6.json b/tests/integration/vector_io/recordings/261f92e807d9c19cd7982434744682ab971149b8984186622c14060fc6c203e6.json
deleted file mode 100644
index d161878c2..000000000
--- a/tests/integration/vector_io/recordings/261f92e807d9c19cd7982434744682ab971149b8984186622c14060fc6c203e6.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_with_ranking_options[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/265614cbb84bc36e9ac14fa1548d6e14a980e97b326a31d6d8facae980de9926.json b/tests/integration/vector_io/recordings/265614cbb84bc36e9ac14fa1548d6e14a980e97b326a31d6d8facae980de9926.json
deleted file mode 100644
index 61427cf08..000000000
--- a/tests/integration/vector_io/recordings/265614cbb84bc36e9ac14fa1548d6e14a980e97b326a31d6d8facae980de9926.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_modes[ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384-keyword]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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deleted file mode 100644
index ae6de58e8..000000000
--- a/tests/integration/vector_io/recordings/2a0b0357565c4d0c081b484feea3137efaf7a5cee1755f17d08596280cfd35ec.json
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diff --git a/tests/integration/vector_io/recordings/2cb93a47143c023b72d96cef39c333322850fffa1a1bb61cac37205c16b0d39f.json b/tests/integration/vector_io/recordings/2cb93a47143c023b72d96cef39c333322850fffa1a1bb61cac37205c16b0d39f.json
deleted file mode 100644
index f14641fc3..000000000
--- a/tests/integration/vector_io/recordings/2cb93a47143c023b72d96cef39c333322850fffa1a1bb61cac37205c16b0d39f.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-      "input": [
-        "What is the secret string?"
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-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/2cd388b99641701079d8398590d2a41879dd858b7670e3de0f1a49f5b8bbfe9c.json b/tests/integration/vector_io/recordings/2cd388b99641701079d8398590d2a41879dd858b7670e3de0f1a49f5b8bbfe9c.json
deleted file mode 100644
index c6184d2a7..000000000
--- a/tests/integration/vector_io/recordings/2cd388b99641701079d8398590d2a41879dd858b7670e3de0f1a49f5b8bbfe9c.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
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-      "input": [
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-    "endpoint": "/v1/embeddings",
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diff --git a/tests/integration/vector_io/recordings/2d1459e1428a06975446b0873ff82b71108e546d0d0302f4439f0c0d06d83aa8.json b/tests/integration/vector_io/recordings/2d1459e1428a06975446b0873ff82b71108e546d0d0302f4439f0c0d06d83aa8.json
deleted file mode 100644
index 005c079bc..000000000
--- a/tests/integration/vector_io/recordings/2d1459e1428a06975446b0873ff82b71108e546d0d0302f4439f0c0d06d83aa8.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/2d32599c6c245e619d24d5bd696c184d8046898e35302c65492cd0b1c4238f2f.json b/tests/integration/vector_io/recordings/2d32599c6c245e619d24d5bd696c184d8046898e35302c65492cd0b1c4238f2f.json
deleted file mode 100644
index 968c1c5a4..000000000
--- a/tests/integration/vector_io/recordings/2d32599c6c245e619d24d5bd696c184d8046898e35302c65492cd0b1c4238f2f.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_attach_files_on_creation[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "This is a test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
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-        ],
-        "model": "nomic-embed-text:137m-v1.5-fp16",
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diff --git a/tests/integration/vector_io/recordings/2da747e09e8667b02032caf6dd44d949929477bb8c1470bd824812fbd6338fbd.json b/tests/integration/vector_io/recordings/2da747e09e8667b02032caf6dd44d949929477bb8c1470bd824812fbd6338fbd.json
deleted file mode 100644
index 86f2c942e..000000000
--- a/tests/integration/vector_io/recordings/2da747e09e8667b02032caf6dd44d949929477bb8c1470bd824812fbd6338fbd.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_with_high_score_filter[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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index 6b526e176..000000000
--- a/tests/integration/vector_io/recordings/2e2f6e34536e67cc73f37d94dfa68ecaad4f0aa10f020ac49b5b7678a0f94075.json
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diff --git a/tests/integration/vector_io/recordings/2eaeb5ff7e503ff24cae9e9adc9b50767ba0f98adc9947ea9dd51ac8a556ac78.json b/tests/integration/vector_io/recordings/2eaeb5ff7e503ff24cae9e9adc9b50767ba0f98adc9947ea9dd51ac8a556ac78.json
deleted file mode 100644
index 3d4ab0c44..000000000
--- a/tests/integration/vector_io/recordings/2eaeb5ff7e503ff24cae9e9adc9b50767ba0f98adc9947ea9dd51ac8a556ac78.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "What inspires neural networks?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/2eb418f019ea5f11c054dcdc21092845597ef4d4ff0ea41a3a44481e22b172fc.json b/tests/integration/vector_io/recordings/2eb418f019ea5f11c054dcdc21092845597ef4d4ff0ea41a3a44481e22b172fc.json
deleted file mode 100644
index aa0c30991..000000000
--- a/tests/integration/vector_io/recordings/2eb418f019ea5f11c054dcdc21092845597ef4d4ff0ea41a3a44481e22b172fc.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/2f5e886d2c158c6219eca729bba30f1684ba3e617e9e76ac181eba6e7f01c839.json b/tests/integration/vector_io/recordings/2f5e886d2c158c6219eca729bba30f1684ba3e617e9e76ac181eba6e7f01c839.json
deleted file mode 100644
index 3f74d7a05..000000000
--- a/tests/integration/vector_io/recordings/2f5e886d2c158c6219eca729bba30f1684ba3e617e9e76ac181eba6e7f01c839.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/307bb7dfec58ba06444e457140e82c0d2bf5d1c5b6a4f2f003689bbe6ca4f82b.json b/tests/integration/vector_io/recordings/307bb7dfec58ba06444e457140e82c0d2bf5d1c5b6a4f2f003689bbe6ca4f82b.json
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index 57a3a5462..000000000
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diff --git a/tests/integration/vector_io/recordings/3091dd8894f0f370f6bbbd9eec236772f54d8a5ad3e362e49b43f532139d3c5e.json b/tests/integration/vector_io/recordings/3091dd8894f0f370f6bbbd9eec236772f54d8a5ad3e362e49b43f532139d3c5e.json
deleted file mode 100644
index 8269bbd24..000000000
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diff --git a/tests/integration/vector_io/recordings/31ad2c13786917e47ca08d9ec38e7236d231371f35762365b150a4c2170498be.json b/tests/integration/vector_io/recordings/31ad2c13786917e47ca08d9ec38e7236d231371f35762365b150a4c2170498be.json
deleted file mode 100644
index d24ac8045..000000000
--- a/tests/integration/vector_io/recordings/31ad2c13786917e47ca08d9ec38e7236d231371f35762365b150a4c2170498be.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/321f0309725942dbcad18528f40cc6fe2feb7c33b9bb11cad105bc1540b36e6c.json b/tests/integration/vector_io/recordings/321f0309725942dbcad18528f40cc6fe2feb7c33b9bb11cad105bc1540b36e6c.json
deleted file mode 100644
index d8f38b03c..000000000
--- a/tests/integration/vector_io/recordings/321f0309725942dbcad18528f40cc6fe2feb7c33b9bb11cad105bc1540b36e6c.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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index 92ac54188..000000000
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diff --git a/tests/integration/vector_io/recordings/32d8755616bc747def2263c9a0de5474afbaa139eaaaa3780c648c1ac5f7afaf.json b/tests/integration/vector_io/recordings/32d8755616bc747def2263c9a0de5474afbaa139eaaaa3780c648c1ac5f7afaf.json
deleted file mode 100644
index cd982f35d..000000000
--- a/tests/integration/vector_io/recordings/32d8755616bc747def2263c9a0de5474afbaa139eaaaa3780c648c1ac5f7afaf.json
+++ /dev/null
@@ -1,75 +0,0 @@
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diff --git a/tests/integration/vector_io/recordings/3301bd83fcd7a7f300f3d7e1be2205f04315934bc4058e9efe50e3fe0bcea560.json b/tests/integration/vector_io/recordings/3301bd83fcd7a7f300f3d7e1be2205f04315934bc4058e9efe50e3fe0bcea560.json
deleted file mode 100644
index e8e6109a1..000000000
--- a/tests/integration/vector_io/recordings/3301bd83fcd7a7f300f3d7e1be2205f04315934bc4058e9efe50e3fe0bcea560.json
+++ /dev/null
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-{
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diff --git a/tests/integration/vector_io/recordings/338b25115a6ae999bd83750922367d6f00c5934bd54ca9c089ecf8d511ebda94.json b/tests/integration/vector_io/recordings/338b25115a6ae999bd83750922367d6f00c5934bd54ca9c089ecf8d511ebda94.json
deleted file mode 100644
index b5b2f2332..000000000
--- a/tests/integration/vector_io/recordings/338b25115a6ae999bd83750922367d6f00c5934bd54ca9c089ecf8d511ebda94.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_attach_file[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "The secret string is foobazbar."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
-        "data": [
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diff --git a/tests/integration/vector_io/recordings/359ec1c4a16848ba6e13bad47b2485c6802b216799f2c8672d78f28e7712fb2e.json b/tests/integration/vector_io/recordings/359ec1c4a16848ba6e13bad47b2485c6802b216799f2c8672d78f28e7712fb2e.json
deleted file mode 100644
index 574d35a35..000000000
--- a/tests/integration/vector_io/recordings/359ec1c4a16848ba6e13bad47b2485c6802b216799f2c8672d78f28e7712fb2e.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-      "input": [
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-      "encoding_format": "float"
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-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/35cbf15ba1ac9c48fb77899ed7715be0049e52f371444ef843223e350ba24e9e.json b/tests/integration/vector_io/recordings/35cbf15ba1ac9c48fb77899ed7715be0049e52f371444ef843223e350ba24e9e.json
deleted file mode 100644
index d2bb6692f..000000000
--- a/tests/integration/vector_io/recordings/35cbf15ba1ac9c48fb77899ed7715be0049e52f371444ef843223e350ba24e9e.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
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-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
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diff --git a/tests/integration/vector_io/recordings/3621ff58c95335276c6bcc53c46a69e0e8965288b40f09c2a9dc5f4985132fb0.json b/tests/integration/vector_io/recordings/3621ff58c95335276c6bcc53c46a69e0e8965288b40f09c2a9dc5f4985132fb0.json
deleted file mode 100644
index 725ffb3db..000000000
--- a/tests/integration/vector_io/recordings/3621ff58c95335276c6bcc53c46a69e0e8965288b40f09c2a9dc5f4985132fb0.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_empty[openai_client-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://localhost:11434/api/ps",
-    "headers": {},
-    "body": {},
-    "endpoint": "/api/ps",
-    "model": ""
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diff --git a/tests/integration/vector_io/recordings/39273447614383795aa3eda0f36013422d15aa783037dd4b91fb9e3f4412a04c.json b/tests/integration/vector_io/recordings/39273447614383795aa3eda0f36013422d15aa783037dd4b91fb9e3f4412a04c.json
deleted file mode 100644
index d63c4c728..000000000
--- a/tests/integration/vector_io/recordings/39273447614383795aa3eda0f36013422d15aa783037dd4b91fb9e3f4412a04c.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
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-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
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diff --git a/tests/integration/vector_io/recordings/3a09e4b610d24c272a3deb1ebbe92e695d869b7ca06ca28c2aa1db0366d365d2.json b/tests/integration/vector_io/recordings/3a09e4b610d24c272a3deb1ebbe92e695d869b7ca06ca28c2aa1db0366d365d2.json
deleted file mode 100644
index 47325c0c6..000000000
--- a/tests/integration/vector_io/recordings/3a09e4b610d24c272a3deb1ebbe92e695d869b7ca06ca28c2aa1db0366d365d2.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-      "input": [
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-      ],
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
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diff --git a/tests/integration/vector_io/recordings/3a324c86ec3e4e98d9adf70d1ead80309e21de2578f969125428a5ee21dc5bc5.json b/tests/integration/vector_io/recordings/3a324c86ec3e4e98d9adf70d1ead80309e21de2578f969125428a5ee21dc5bc5.json
deleted file mode 100644
index 0fdab0912..000000000
--- a/tests/integration/vector_io/recordings/3a324c86ec3e4e98d9adf70d1ead80309e21de2578f969125428a5ee21dc5bc5.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is the content of test file 2"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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diff --git a/tests/integration/vector_io/recordings/3cb5d608dc2afe5237df36aa7aa179ad5478bcfcaabb502aee30a71f468b60f8.json b/tests/integration/vector_io/recordings/3cb5d608dc2afe5237df36aa7aa179ad5478bcfcaabb502aee30a71f468b60f8.json
deleted file mode 100644
index 1a944c3fa..000000000
--- a/tests/integration/vector_io/recordings/3cb5d608dc2afe5237df36aa7aa179ad5478bcfcaabb502aee30a71f468b60f8.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_create_vector_store_files_duplicate_vector_store_name[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "This is a test file 1"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
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diff --git a/tests/integration/vector_io/recordings/3d4135093ecac438762c404a9387b4e0e01214e2d0c2565829b9ea38227fab80.json b/tests/integration/vector_io/recordings/3d4135093ecac438762c404a9387b4e0e01214e2d0c2565829b9ea38227fab80.json
deleted file mode 100644
index 715fef5e5..000000000
--- a/tests/integration/vector_io/recordings/3d4135093ecac438762c404a9387b4e0e01214e2d0c2565829b9ea38227fab80.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_list_files[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file 2"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
-        "data": [
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diff --git a/tests/integration/vector_io/recordings/4238dca4b781c3a26be52f96af7e6207db43ca208277c909460a23df5dd7ace6.json b/tests/integration/vector_io/recordings/4238dca4b781c3a26be52f96af7e6207db43ca208277c909460a23df5dd7ace6.json
deleted file mode 100644
index 879975335..000000000
--- a/tests/integration/vector_io/recordings/4238dca4b781c3a26be52f96af7e6207db43ca208277c909460a23df5dd7ace6.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
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-      "input": [
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-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/42e67e71def8f49274d9aa7745b38840d864e664bec3e3bbac6fdbda12fd02cb.json b/tests/integration/vector_io/recordings/42e67e71def8f49274d9aa7745b38840d864e664bec3e3bbac6fdbda12fd02cb.json
deleted file mode 100644
index 897d431f3..000000000
--- a/tests/integration/vector_io/recordings/42e67e71def8f49274d9aa7745b38840d864e664bec3e3bbac6fdbda12fd02cb.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
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-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
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diff --git a/tests/integration/vector_io/recordings/43c052d4260c99f4d757ff20b2b79d2081824d5803c12923adf9b9ee4fcfc608.json b/tests/integration/vector_io/recordings/43c052d4260c99f4d757ff20b2b79d2081824d5803c12923adf9b9ee4fcfc608.json
deleted file mode 100644
index a5afab60c..000000000
--- a/tests/integration/vector_io/recordings/43c052d4260c99f4d757ff20b2b79d2081824d5803c12923adf9b9ee4fcfc608.json
+++ /dev/null
@@ -1,424 +0,0 @@
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diff --git a/tests/integration/vector_io/recordings/441286a50ac9e0a980376eb3dbc100831888d9e06ceebc6d1ff1e7341649d6ef.json b/tests/integration/vector_io/recordings/441286a50ac9e0a980376eb3dbc100831888d9e06ceebc6d1ff1e7341649d6ef.json
deleted file mode 100644
index 91ab5c754..000000000
--- a/tests/integration/vector_io/recordings/441286a50ac9e0a980376eb3dbc100831888d9e06ceebc6d1ff1e7341649d6ef.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/4414f7fcbb374068ed40c92757f4e9dd7b5a58f3638372aa9b18acf866067442.json b/tests/integration/vector_io/recordings/4414f7fcbb374068ed40c92757f4e9dd7b5a58f3638372aa9b18acf866067442.json
deleted file mode 100644
index d974739f9..000000000
--- a/tests/integration/vector_io/recordings/4414f7fcbb374068ed40c92757f4e9dd7b5a58f3638372aa9b18acf866067442.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-    "headers": {},
-    "body": {
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-      "input": [
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-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/44d4c5e6fe563eaf3af302e34be04501eee9458f272d248d08d292a7d12152f1.json b/tests/integration/vector_io/recordings/44d4c5e6fe563eaf3af302e34be04501eee9458f272d248d08d292a7d12152f1.json
deleted file mode 100644
index 7c2980777..000000000
--- a/tests/integration/vector_io/recordings/44d4c5e6fe563eaf3af302e34be04501eee9458f272d248d08d292a7d12152f1.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_relevance[client_with_models-emb=ollama/all-minilm:l6-v2:dim=384-test_case3]",
-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "What inspires neural networks?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/4508909b1c6fdad83af2f926f0ed6e49c11ba2b6d51965fbd8766e138ba59e20.json b/tests/integration/vector_io/recordings/4508909b1c6fdad83af2f926f0ed6e49c11ba2b6d51965fbd8766e138ba59e20.json
deleted file mode 100644
index e2a2b4eb2..000000000
--- a/tests/integration/vector_io/recordings/4508909b1c6fdad83af2f926f0ed6e49c11ba2b6d51965fbd8766e138ba59e20.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_relevance[openai_client-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384-test_case0]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
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diff --git a/tests/integration/vector_io/recordings/45bbad75b64868302f532cbebcdde21a75cead9a06a69ac023ad398c13c3b280.json b/tests/integration/vector_io/recordings/45bbad75b64868302f532cbebcdde21a75cead9a06a69ac023ad398c13c3b280.json
deleted file mode 100644
index 63f4232e6..000000000
--- a/tests/integration/vector_io/recordings/45bbad75b64868302f532cbebcdde21a75cead9a06a69ac023ad398c13c3b280.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "How does machine learning improve over time?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/460027f7ab8dbb6c4eabc6ba6ed0451d84d857cfc5d4d96b794f1e52f68ab1c0.json b/tests/integration/vector_io/recordings/460027f7ab8dbb6c4eabc6ba6ed0451d84d857cfc5d4d96b794f1e52f68ab1c0.json
deleted file mode 100644
index 0cdc0bdd5..000000000
--- a/tests/integration/vector_io/recordings/460027f7ab8dbb6c4eabc6ba6ed0451d84d857cfc5d4d96b794f1e52f68ab1c0.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
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-    "headers": {},
-    "body": {
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-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
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diff --git a/tests/integration/vector_io/recordings/4705735cf4a990c9088272985084f3ad2b488a09f247ad37be0237e2ceb9965c.json b/tests/integration/vector_io/recordings/4705735cf4a990c9088272985084f3ad2b488a09f247ad37be0237e2ceb9965c.json
deleted file mode 100644
index 6c871279f..000000000
--- a/tests/integration/vector_io/recordings/4705735cf4a990c9088272985084f3ad2b488a09f247ad37be0237e2ceb9965c.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-      "input": [
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-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/47af53c5330b053101a2825113dec4ca7fe7118e7151638e40563b3290c3a421.json b/tests/integration/vector_io/recordings/47af53c5330b053101a2825113dec4ca7fe7118e7151638e40563b3290c3a421.json
deleted file mode 100644
index f908759f9..000000000
--- a/tests/integration/vector_io/recordings/47af53c5330b053101a2825113dec4ca7fe7118e7151638e40563b3290c3a421.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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deleted file mode 100644
index 444a74db0..000000000
--- a/tests/integration/vector_io/recordings/47f832568cfd9461bb323b4e33eef8552ed6fdebcf7886f33ffe64afc77c76af.json
+++ /dev/null
@@ -1,423 +0,0 @@
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diff --git a/tests/integration/vector_io/recordings/4889c5d8f71bac757978b5078ba5278d19ee58d71b2d1541de6fab43bb53c8b8.json b/tests/integration/vector_io/recordings/4889c5d8f71bac757978b5078ba5278d19ee58d71b2d1541de6fab43bb53c8b8.json
deleted file mode 100644
index 4d2cfdbce..000000000
--- a/tests/integration/vector_io/recordings/4889c5d8f71bac757978b5078ba5278d19ee58d71b2d1541de6fab43bb53c8b8.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/48b3a89f475791ce5c49a211cdfb02244a78947135111413023f16facd76fe8e.json b/tests/integration/vector_io/recordings/48b3a89f475791ce5c49a211cdfb02244a78947135111413023f16facd76fe8e.json
deleted file mode 100644
index a0db50cef..000000000
--- a/tests/integration/vector_io/recordings/48b3a89f475791ce5c49a211cdfb02244a78947135111413023f16facd76fe8e.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
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-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is a test file 1"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
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-        "model": "nomic-embed-text:latest",
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diff --git a/tests/integration/vector_io/recordings/48b722ae2dcb4988c8764bd01c4c469d2335dd03003f19b4c45b05e542f97a77.json b/tests/integration/vector_io/recordings/48b722ae2dcb4988c8764bd01c4c469d2335dd03003f19b4c45b05e542f97a77.json
deleted file mode 100644
index 28432d1a2..000000000
--- a/tests/integration/vector_io/recordings/48b722ae2dcb4988c8764bd01c4c469d2335dd03003f19b4c45b05e542f97a77.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "What is the secret string?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/4962d607edc12a614f39f4b7043e12162b14335d2a1c94b84a346c56868ede2e.json b/tests/integration/vector_io/recordings/4962d607edc12a614f39f4b7043e12162b14335d2a1c94b84a346c56868ede2e.json
deleted file mode 100644
index b986315d3..000000000
--- a/tests/integration/vector_io/recordings/4962d607edc12a614f39f4b7043e12162b14335d2a1c94b84a346c56868ede2e.json
+++ /dev/null
@@ -1,1597 +0,0 @@
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-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
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diff --git a/tests/integration/vector_io/recordings/4ae390ac58b8475d8c2d3247f44513978f91d45dabb7e2e499a4d901b37e4895.json b/tests/integration/vector_io/recordings/4ae390ac58b8475d8c2d3247f44513978f91d45dabb7e2e499a4d901b37e4895.json
deleted file mode 100644
index 5cbc8699f..000000000
--- a/tests/integration/vector_io/recordings/4ae390ac58b8475d8c2d3247f44513978f91d45dabb7e2e499a4d901b37e4895.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is a test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
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diff --git a/tests/integration/vector_io/recordings/4b8ce5031f00e754bbb6e1f55109ae8f46ac7086afb48820a36c41a3cb994cb9.json b/tests/integration/vector_io/recordings/4b8ce5031f00e754bbb6e1f55109ae8f46ac7086afb48820a36c41a3cb994cb9.json
deleted file mode 100644
index aa208aa69..000000000
--- a/tests/integration/vector_io/recordings/4b8ce5031f00e754bbb6e1f55109ae8f46ac7086afb48820a36c41a3cb994cb9.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is the content of test file 1"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/4c044ae708862abba94b8e757d05cf3c7120e1dd8484d3947a86fb29af24a8a1.json b/tests/integration/vector_io/recordings/4c044ae708862abba94b8e757d05cf3c7120e1dd8484d3947a86fb29af24a8a1.json
deleted file mode 100644
index 47f9844a0..000000000
--- a/tests/integration/vector_io/recordings/4c044ae708862abba94b8e757d05cf3c7120e1dd8484d3947a86fb29af24a8a1.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
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-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
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index bdb3883be..000000000
--- a/tests/integration/vector_io/recordings/4ccda7be2796c06ddd11bca371ef9c02c65fb498f59058588c3ba5d3cc859296.json
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diff --git a/tests/integration/vector_io/recordings/4de0996261fc32272bd04030a962aa6060b4488c54939f81c93ae081a10c7a78.json b/tests/integration/vector_io/recordings/4de0996261fc32272bd04030a962aa6060b4488c54939f81c93ae081a10c7a78.json
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diff --git a/tests/integration/vector_io/recordings/4efd4a0d6f6a60e5e3b166f4c5350002023e4382f1b87f092201b8e4137c9eef.json b/tests/integration/vector_io/recordings/4efd4a0d6f6a60e5e3b166f4c5350002023e4382f1b87f092201b8e4137c9eef.json
deleted file mode 100644
index 1d38f1e03..000000000
--- a/tests/integration/vector_io/recordings/4efd4a0d6f6a60e5e3b166f4c5350002023e4382f1b87f092201b8e4137c9eef.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_with_ranking_options[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
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diff --git a/tests/integration/vector_io/recordings/50464a97147e0cc4fa337a0a3beb038a57e93e01a16b78b750233c149d905f27.json b/tests/integration/vector_io/recordings/50464a97147e0cc4fa337a0a3beb038a57e93e01a16b78b750233c149d905f27.json
deleted file mode 100644
index de6cb995d..000000000
--- a/tests/integration/vector_io/recordings/50464a97147e0cc4fa337a0a3beb038a57e93e01a16b78b750233c149d905f27.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file 1"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/506216767e53ce1a6ef47637a97d4baa865eda04d9d92e418a7e58da7be1bc2b.json b/tests/integration/vector_io/recordings/506216767e53ce1a6ef47637a97d4baa865eda04d9d92e418a7e58da7be1bc2b.json
deleted file mode 100644
index fa799da03..000000000
--- a/tests/integration/vector_io/recordings/506216767e53ce1a6ef47637a97d4baa865eda04d9d92e418a7e58da7be1bc2b.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
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-      "input": [
-        "This is batch test file 1"
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-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/52fb3763cdc6b8897ef52bd70bb1fcaecf6ea82ee13a4097265a26c42268a9b7.json b/tests/integration/vector_io/recordings/52fb3763cdc6b8897ef52bd70bb1fcaecf6ea82ee13a4097265a26c42268a9b7.json
deleted file mode 100644
index b3a436e61..000000000
--- a/tests/integration/vector_io/recordings/52fb3763cdc6b8897ef52bd70bb1fcaecf6ea82ee13a4097265a26c42268a9b7.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-      "input": [
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diff --git a/tests/integration/vector_io/recordings/544de77e04e9f32bd2a59c17338da3131e381919b636394e6f419da932484ffe.json b/tests/integration/vector_io/recordings/544de77e04e9f32bd2a59c17338da3131e381919b636394e6f419da932484ffe.json
deleted file mode 100644
index 439e3d657..000000000
--- a/tests/integration/vector_io/recordings/544de77e04e9f32bd2a59c17338da3131e381919b636394e6f419da932484ffe.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/54f7bec4d7073965af5f612d096c1c82f2602f796edcdbf8c9813a5a3a82825b.json b/tests/integration/vector_io/recordings/54f7bec4d7073965af5f612d096c1c82f2602f796edcdbf8c9813a5a3a82825b.json
deleted file mode 100644
index 84a5692ee..000000000
--- a/tests/integration/vector_io/recordings/54f7bec4d7073965af5f612d096c1c82f2602f796edcdbf8c9813a5a3a82825b.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/55360350b02abc65d94860c6497619d1f0a4c24dd928fb995d73bbd929f79093.json b/tests/integration/vector_io/recordings/55360350b02abc65d94860c6497619d1f0a4c24dd928fb995d73bbd929f79093.json
deleted file mode 100644
index 43128e05d..000000000
--- a/tests/integration/vector_io/recordings/55360350b02abc65d94860c6497619d1f0a4c24dd928fb995d73bbd929f79093.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
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-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
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diff --git a/tests/integration/vector_io/recordings/557572691830be08e427e6b2ea96584c5a2aaad92a573f187df97295e7b5757b.json b/tests/integration/vector_io/recordings/557572691830be08e427e6b2ea96584c5a2aaad92a573f187df97295e7b5757b.json
deleted file mode 100644
index d49ae91de..000000000
--- a/tests/integration/vector_io/recordings/557572691830be08e427e6b2ea96584c5a2aaad92a573f187df97295e7b5757b.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is a test file 1"
-      ],
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
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diff --git a/tests/integration/vector_io/recordings/56571b92d8276796c890f4d6c37610fb6a2e48e3710a39d161668a56abb2735a.json b/tests/integration/vector_io/recordings/56571b92d8276796c890f4d6c37610fb6a2e48e3710a39d161668a56abb2735a.json
deleted file mode 100644
index bf18ef5a8..000000000
--- a/tests/integration/vector_io/recordings/56571b92d8276796c890f4d6c37610fb6a2e48e3710a39d161668a56abb2735a.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
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-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
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diff --git a/tests/integration/vector_io/recordings/56ca70a42e963d031a57348b903d92348289f512cf84db3b1c0fe408f807a480.json b/tests/integration/vector_io/recordings/56ca70a42e963d031a57348b903d92348289f512cf84db3b1c0fe408f807a480.json
deleted file mode 100644
index b3aacb111..000000000
--- a/tests/integration/vector_io/recordings/56ca70a42e963d031a57348b903d92348289f512cf84db3b1c0fe408f807a480.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "precomputed embedding test"
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-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/577047f4c517bbc331650dd23bccadfb5b76e55a84164f21d876862103b98b44.json b/tests/integration/vector_io/recordings/577047f4c517bbc331650dd23bccadfb5b76e55a84164f21d876862103b98b44.json
deleted file mode 100644
index e8bb49f75..000000000
--- a/tests/integration/vector_io/recordings/577047f4c517bbc331650dd23bccadfb5b76e55a84164f21d876862103b98b44.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/5788169f01e13bae211de2de2bf1092f7657f9277498d49266e9b1545535b78b.json b/tests/integration/vector_io/recordings/5788169f01e13bae211de2de2bf1092f7657f9277498d49266e9b1545535b78b.json
deleted file mode 100644
index f24d708df..000000000
--- a/tests/integration/vector_io/recordings/5788169f01e13bae211de2de2bf1092f7657f9277498d49266e9b1545535b78b.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_with_max_num_results[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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diff --git a/tests/integration/vector_io/recordings/579f7796c73c5ea991f05cd3075866d7f3a564e9fc2e8dfcd89a9d785129659f.json b/tests/integration/vector_io/recordings/579f7796c73c5ea991f05cd3075866d7f3a564e9fc2e8dfcd89a9d785129659f.json
deleted file mode 100644
index 19bf1706a..000000000
--- a/tests/integration/vector_io/recordings/579f7796c73c5ea991f05cd3075866d7f3a564e9fc2e8dfcd89a9d785129659f.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is a test file 2"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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-            ],
-            "index": 0,
-            "object": "embedding"
-          }
-        ],
-        "model": "nomic-embed-text:latest",
-        "object": "list",
-        "usage": {
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-      }
-    },
-    "is_streaming": false
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-}
diff --git a/tests/integration/vector_io/recordings/585e15d5f698479a28156373423c50bd019418121d5a66bb6fc1f2ef737dce1e.json b/tests/integration/vector_io/recordings/585e15d5f698479a28156373423c50bd019418121d5a66bb6fc1f2ef737dce1e.json
deleted file mode 100644
index d158c7b65..000000000
--- a/tests/integration/vector_io/recordings/585e15d5f698479a28156373423c50bd019418121d5a66bb6fc1f2ef737dce1e.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_with_chunks[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "What is Python programming language?"
-      ],
-      "encoding_format": "float"
-    },
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diff --git a/tests/integration/vector_io/recordings/58acdc68a1083c09c0874b88c8697fc353f6a895c6b99c86daf00cf4f76b764e.json b/tests/integration/vector_io/recordings/58acdc68a1083c09c0874b88c8697fc353f6a895c6b99c86daf00cf4f76b764e.json
deleted file mode 100644
index 9cc92a9f4..000000000
--- a/tests/integration/vector_io/recordings/58acdc68a1083c09c0874b88c8697fc353f6a895c6b99c86daf00cf4f76b764e.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/5908f48af1663d749291fac1fb0d3e534a7a446c2ffc07dab51a151694dea1be.json b/tests/integration/vector_io/recordings/5908f48af1663d749291fac1fb0d3e534a7a446c2ffc07dab51a151694dea1be.json
deleted file mode 100644
index f8022d020..000000000
--- a/tests/integration/vector_io/recordings/5908f48af1663d749291fac1fb0d3e534a7a446c2ffc07dab51a151694dea1be.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/5af7a343bbe09ce69d62b1e3dc39fa4d43ac2c803988fcb10b08cf866ce53d29.json b/tests/integration/vector_io/recordings/5af7a343bbe09ce69d62b1e3dc39fa4d43ac2c803988fcb10b08cf866ce53d29.json
deleted file mode 100644
index c710ebbe9..000000000
--- a/tests/integration/vector_io/recordings/5af7a343bbe09ce69d62b1e3dc39fa4d43ac2c803988fcb10b08cf866ce53d29.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-      "input": [
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-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
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diff --git a/tests/integration/vector_io/recordings/5b52a60a1a3e5d0ee7738e48a41cf63ed25b3b7a2b70bb98a994bbccfe9c7b3b.json b/tests/integration/vector_io/recordings/5b52a60a1a3e5d0ee7738e48a41cf63ed25b3b7a2b70bb98a994bbccfe9c7b3b.json
deleted file mode 100644
index d27639edb..000000000
--- a/tests/integration/vector_io/recordings/5b52a60a1a3e5d0ee7738e48a41cf63ed25b3b7a2b70bb98a994bbccfe9c7b3b.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/5c84cd7d51c608d95d923d44975a8ae177c6894762ee3178eb508f154fb09b0b.json b/tests/integration/vector_io/recordings/5c84cd7d51c608d95d923d44975a8ae177c6894762ee3178eb508f154fb09b0b.json
deleted file mode 100644
index 2d914954e..000000000
--- a/tests/integration/vector_io/recordings/5c84cd7d51c608d95d923d44975a8ae177c6894762ee3178eb508f154fb09b0b.json
+++ /dev/null
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-{
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diff --git a/tests/integration/vector_io/recordings/5cffe1f65b6635bd15ddb661f71e8e5c0aa7c54942150b3c77e08a61129b0ead.json b/tests/integration/vector_io/recordings/5cffe1f65b6635bd15ddb661f71e8e5c0aa7c54942150b3c77e08a61129b0ead.json
deleted file mode 100644
index cc22f71dd..000000000
--- a/tests/integration/vector_io/recordings/5cffe1f65b6635bd15ddb661f71e8e5c0aa7c54942150b3c77e08a61129b0ead.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file"
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-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/5d259394e1b583d3510c0190234475468a7e1363635493a483d0c17d3a0c6196.json b/tests/integration/vector_io/recordings/5d259394e1b583d3510c0190234475468a7e1363635493a483d0c17d3a0c6196.json
deleted file mode 100644
index 4222e0118..000000000
--- a/tests/integration/vector_io/recordings/5d259394e1b583d3510c0190234475468a7e1363635493a483d0c17d3a0c6196.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-      "input": [
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diff --git a/tests/integration/vector_io/recordings/5d49c5e43bf8b7210aefa54adb7f5eb851974d4f2b27ba59977df959d61c770c.json b/tests/integration/vector_io/recordings/5d49c5e43bf8b7210aefa54adb7f5eb851974d4f2b27ba59977df959d61c770c.json
deleted file mode 100644
index 1fbccd85a..000000000
--- a/tests/integration/vector_io/recordings/5d49c5e43bf8b7210aefa54adb7f5eb851974d4f2b27ba59977df959d61c770c.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
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-  },
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diff --git a/tests/integration/vector_io/recordings/5d49dd6ab969ee6b56212ee520a832283997c4d941fbfcbe6c62586b94f83575.json b/tests/integration/vector_io/recordings/5d49dd6ab969ee6b56212ee520a832283997c4d941fbfcbe6c62586b94f83575.json
deleted file mode 100644
index bfd95d1fd..000000000
--- a/tests/integration/vector_io/recordings/5d49dd6ab969ee6b56212ee520a832283997c4d941fbfcbe6c62586b94f83575.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
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-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
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-        "model": "all-minilm:l6-v2",
-        "object": "list",
-        "usage": {
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-    "is_streaming": false
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diff --git a/tests/integration/vector_io/recordings/5da809595a176c88b2fb6e2b1cd9af7eba4e2dbbf73151ffd920846f6f115a2f.json b/tests/integration/vector_io/recordings/5da809595a176c88b2fb6e2b1cd9af7eba4e2dbbf73151ffd920846f6f115a2f.json
deleted file mode 100644
index fc1085a74..000000000
--- a/tests/integration/vector_io/recordings/5da809595a176c88b2fb6e2b1cd9af7eba4e2dbbf73151ffd920846f6f115a2f.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is the content of test file 2"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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-            "object": "embedding"
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-        "model": "all-minilm:l6-v2",
-        "object": "list",
-        "usage": {
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-      }
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-    "is_streaming": false
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diff --git a/tests/integration/vector_io/recordings/5e5b5b2a71a5c46f4ace0549b576c303d0dfddb7a0a1515cb2915cedfcd29fb7.json b/tests/integration/vector_io/recordings/5e5b5b2a71a5c46f4ace0549b576c303d0dfddb7a0a1515cb2915cedfcd29fb7.json
deleted file mode 100644
index 868fa7dc8..000000000
--- a/tests/integration/vector_io/recordings/5e5b5b2a71a5c46f4ace0549b576c303d0dfddb7a0a1515cb2915cedfcd29fb7.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_attach_files_on_creation[openai_client-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file 1"
-      ],
-      "encoding_format": "float"
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diff --git a/tests/integration/vector_io/recordings/5ea21922d71dff5daa7379b666fb96b4d0335ff225c8ff23ef24d639ff476268.json b/tests/integration/vector_io/recordings/5ea21922d71dff5daa7379b666fb96b4d0335ff225c8ff23ef24d639ff476268.json
deleted file mode 100644
index 34a72d308..000000000
--- a/tests/integration/vector_io/recordings/5ea21922d71dff5daa7379b666fb96b4d0335ff225c8ff23ef24d639ff476268.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/5f7456304d0f3a846e98f138770648d68925964f20520efe044b12dac15c5d92.json b/tests/integration/vector_io/recordings/5f7456304d0f3a846e98f138770648d68925964f20520efe044b12dac15c5d92.json
deleted file mode 100644
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+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/6025c300d61f32b2c51ca02f21c77d87fd7c940187cc2439d5834ee942cce1ef.json b/tests/integration/vector_io/recordings/6025c300d61f32b2c51ca02f21c77d87fd7c940187cc2439d5834ee942cce1ef.json
deleted file mode 100644
index 815bca69d..000000000
--- a/tests/integration/vector_io/recordings/6025c300d61f32b2c51ca02f21c77d87fd7c940187cc2439d5834ee942cce1ef.json
+++ /dev/null
@@ -1,424 +0,0 @@
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diff --git a/tests/integration/vector_io/recordings/60470b421afa2ac7a1c23b149d00bb04ac178ed7fcf0d29c7852d00205757c14.json b/tests/integration/vector_io/recordings/60470b421afa2ac7a1c23b149d00bb04ac178ed7fcf0d29c7852d00205757c14.json
deleted file mode 100644
index d0c599026..000000000
--- a/tests/integration/vector_io/recordings/60470b421afa2ac7a1c23b149d00bb04ac178ed7fcf0d29c7852d00205757c14.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/615b44f8fe23e923f6849f9bad8d9f7531ed74ca532ab3badc178a5cc329376c.json b/tests/integration/vector_io/recordings/615b44f8fe23e923f6849f9bad8d9f7531ed74ca532ab3badc178a5cc329376c.json
deleted file mode 100644
index 51be227f1..000000000
--- a/tests/integration/vector_io/recordings/615b44f8fe23e923f6849f9bad8d9f7531ed74ca532ab3badc178a5cc329376c.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
-    "body": {
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-      "input": [
-        "Python is a high-level programming language with code readability and fewer lines than C++ or Java"
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-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/6347ac0eac4eb1dbcb2d797956cf1e8e5978ed2e912902723dcb6b88d54b2101.json b/tests/integration/vector_io/recordings/6347ac0eac4eb1dbcb2d797956cf1e8e5978ed2e912902723dcb6b88d54b2101.json
deleted file mode 100644
index 89640ddea..000000000
--- a/tests/integration/vector_io/recordings/6347ac0eac4eb1dbcb2d797956cf1e8e5978ed2e912902723dcb6b88d54b2101.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "The secret string is foobazbar."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/6393bd2d9dd6e1e73be8f2d5cc65011bb38cb115719c9e5c083a40a21cb594d4.json b/tests/integration/vector_io/recordings/6393bd2d9dd6e1e73be8f2d5cc65011bb38cb115719c9e5c083a40a21cb594d4.json
deleted file mode 100644
index c56896377..000000000
--- a/tests/integration/vector_io/recordings/6393bd2d9dd6e1e73be8f2d5cc65011bb38cb115719c9e5c083a40a21cb594d4.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is batch cancel test file 1 with substantial content"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/640b6fe648864089776d64b6b3eb9a28b427e3f3ab8f518f301ed74983a78b60.json b/tests/integration/vector_io/recordings/640b6fe648864089776d64b6b3eb9a28b427e3f3ab8f518f301ed74983a78b60.json
deleted file mode 100644
index 538d00aa2..000000000
--- a/tests/integration/vector_io/recordings/640b6fe648864089776d64b6b3eb9a28b427e3f3ab8f518f301ed74983a78b60.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/643b162dc506f28dc9b55b1ac3e3fb307f251e0f33db7d5e09df0f9aebbd5357.json b/tests/integration/vector_io/recordings/643b162dc506f28dc9b55b1ac3e3fb307f251e0f33db7d5e09df0f9aebbd5357.json
deleted file mode 100644
index 727bda16b..000000000
--- a/tests/integration/vector_io/recordings/643b162dc506f28dc9b55b1ac3e3fb307f251e0f33db7d5e09df0f9aebbd5357.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is batch list test file 1"
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-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/6691698998c504c26018a304a441513f1b26f0053262812c302130703623ea09.json b/tests/integration/vector_io/recordings/6691698998c504c26018a304a441513f1b26f0053262812c302130703623ea09.json
deleted file mode 100644
index fdcc632a0..000000000
--- a/tests/integration/vector_io/recordings/6691698998c504c26018a304a441513f1b26f0053262812c302130703623ea09.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_relevance[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384-test_case1]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/679cc4130a40a2663acfea6a2ff9ea2298fff1aedf33cfd80ce6767a7673a617.json b/tests/integration/vector_io/recordings/679cc4130a40a2663acfea6a2ff9ea2298fff1aedf33cfd80ce6767a7673a617.json
deleted file mode 100644
index 41555abf3..000000000
--- a/tests/integration/vector_io/recordings/679cc4130a40a2663acfea6a2ff9ea2298fff1aedf33cfd80ce6767a7673a617.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is the content of test file 1"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
-    "body": {
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diff --git a/tests/integration/vector_io/recordings/67b22c95e3b2707338ecc2d7637e3b1c8b4915590869d11d3da368340363699a.json b/tests/integration/vector_io/recordings/67b22c95e3b2707338ecc2d7637e3b1c8b4915590869d11d3da368340363699a.json
deleted file mode 100644
index 9ea733881..000000000
--- a/tests/integration/vector_io/recordings/67b22c95e3b2707338ecc2d7637e3b1c8b4915590869d11d3da368340363699a.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_file_batch_list_files[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is batch list test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
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diff --git a/tests/integration/vector_io/recordings/67d020b8c75fe4ba8a9bd55921bd250680aca095a5ddce1683c66727d58785be.json b/tests/integration/vector_io/recordings/67d020b8c75fe4ba8a9bd55921bd250680aca095a5ddce1683c66727d58785be.json
deleted file mode 100644
index 7cafa7593..000000000
--- a/tests/integration/vector_io/recordings/67d020b8c75fe4ba8a9bd55921bd250680aca095a5ddce1683c66727d58785be.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-      "input": [
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-      ],
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
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diff --git a/tests/integration/vector_io/recordings/6e9d59d598cba7cada45ace625323bf70896ff34f8f52af6621f055f55e41b98.json b/tests/integration/vector_io/recordings/6e9d59d598cba7cada45ace625323bf70896ff34f8f52af6621f055f55e41b98.json
deleted file mode 100644
index 235067c8c..000000000
--- a/tests/integration/vector_io/recordings/6e9d59d598cba7cada45ace625323bf70896ff34f8f52af6621f055f55e41b98.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-    "headers": {},
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-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is batch list test file 0"
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-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/72b413c0161f20c1f6bb91cb7a3d0d10721ad903d46e5bd24a4709a6beaed080.json b/tests/integration/vector_io/recordings/72b413c0161f20c1f6bb91cb7a3d0d10721ad903d46e5bd24a4709a6beaed080.json
deleted file mode 100644
index 814cd8479..000000000
--- a/tests/integration/vector_io/recordings/72b413c0161f20c1f6bb91cb7a3d0d10721ad903d46e5bd24a4709a6beaed080.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/72b50c9d5b1ccd965c432d2159e205287e2e300789aeb297cc3a42b0e74a8138.json b/tests/integration/vector_io/recordings/72b50c9d5b1ccd965c432d2159e205287e2e300789aeb297cc3a42b0e74a8138.json
deleted file mode 100644
index f03a3c44a..000000000
--- a/tests/integration/vector_io/recordings/72b50c9d5b1ccd965c432d2159e205287e2e300789aeb297cc3a42b0e74a8138.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/75b681f9a2487bfc8b1319524e98fa2e5bd3d0d1a1287134ca2364cd7edf936f.json b/tests/integration/vector_io/recordings/75b681f9a2487bfc8b1319524e98fa2e5bd3d0d1a1287134ca2364cd7edf936f.json
deleted file mode 100644
index cc3d717a6..000000000
--- a/tests/integration/vector_io/recordings/75b681f9a2487bfc8b1319524e98fa2e5bd3d0d1a1287134ca2364cd7edf936f.json
+++ /dev/null
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diff --git a/tests/integration/vector_io/recordings/7684dfce11db2e4890f7bd5bc55285f1a48c24761fa7fd723275fb76b4465188.json b/tests/integration/vector_io/recordings/7684dfce11db2e4890f7bd5bc55285f1a48c24761fa7fd723275fb76b4465188.json
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index 2db0ff9be..000000000
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deleted file mode 100644
index ba4fb5379..000000000
--- a/tests/integration/vector_io/recordings/78c36db6afff9b01753f156389093399ffe725e60cadd228299e417ab8db87a4.json
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diff --git a/tests/integration/vector_io/recordings/7a4dc8b319952ea55c62631a06f41b640aac7bbd7e313e963dcff064d6811d31.json b/tests/integration/vector_io/recordings/7a4dc8b319952ea55c62631a06f41b640aac7bbd7e313e963dcff064d6811d31.json
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diff --git a/tests/integration/vector_io/recordings/7b8564896bb03fa72e8420dcffe91f62e985a0a1be6e00e1b8e80baaaedbf4bc.json b/tests/integration/vector_io/recordings/7b8564896bb03fa72e8420dcffe91f62e985a0a1be6e00e1b8e80baaaedbf4bc.json
deleted file mode 100644
index 4f5f9e57e..000000000
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-{
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-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/7beb2caee3e80caf3d2b3c6cf303a0a3c01e890e83b0fab387c0349d3c04ea9a.json b/tests/integration/vector_io/recordings/7beb2caee3e80caf3d2b3c6cf303a0a3c01e890e83b0fab387c0349d3c04ea9a.json
deleted file mode 100644
index fcfd73050..000000000
--- a/tests/integration/vector_io/recordings/7beb2caee3e80caf3d2b3c6cf303a0a3c01e890e83b0fab387c0349d3c04ea9a.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-      "input": [
-        "What makes Python different from other languages?"
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-      "encoding_format": "float"
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-    "model": "nomic-embed-text:137m-v1.5-fp16"
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diff --git a/tests/integration/vector_io/recordings/7c963a6b5bd89f13b7383fb4ca2409bb7dcd0e2e73d29f94bba77786915821c0.json b/tests/integration/vector_io/recordings/7c963a6b5bd89f13b7383fb4ca2409bb7dcd0e2e73d29f94bba77786915821c0.json
deleted file mode 100644
index adb631cb6..000000000
--- a/tests/integration/vector_io/recordings/7c963a6b5bd89f13b7383fb4ca2409bb7dcd0e2e73d29f94bba77786915821c0.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-      "input": [
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-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/7ee0d7d0aa75ba4dd8243abaa96f2282f995fdb1aef43d10c418b6e03401e959.json b/tests/integration/vector_io/recordings/7ee0d7d0aa75ba4dd8243abaa96f2282f995fdb1aef43d10c418b6e03401e959.json
deleted file mode 100644
index 728bdc03f..000000000
--- a/tests/integration/vector_io/recordings/7ee0d7d0aa75ba4dd8243abaa96f2282f995fdb1aef43d10c418b6e03401e959.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-    "headers": {},
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-      "input": [
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diff --git a/tests/integration/vector_io/recordings/7f0c7944a68047bd4ae32c2306ad5757ae7165bf0bc49b87dcb2c21ae9a4eefd.json b/tests/integration/vector_io/recordings/7f0c7944a68047bd4ae32c2306ad5757ae7165bf0bc49b87dcb2c21ae9a4eefd.json
deleted file mode 100644
index 7bdca61f4..000000000
--- a/tests/integration/vector_io/recordings/7f0c7944a68047bd4ae32c2306ad5757ae7165bf0bc49b87dcb2c21ae9a4eefd.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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-    "body": {},
-    "endpoint": "/api/ps",
-    "model": ""
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diff --git a/tests/integration/vector_io/recordings/7f1cb222265f56ca4e3110b416355a7c842e3d4bc32efec5fa8b65a99f8a3bad.json b/tests/integration/vector_io/recordings/7f1cb222265f56ca4e3110b416355a7c842e3d4bc32efec5fa8b65a99f8a3bad.json
deleted file mode 100644
index 4a76dc0a4..000000000
--- a/tests/integration/vector_io/recordings/7f1cb222265f56ca4e3110b416355a7c842e3d4bc32efec5fa8b65a99f8a3bad.json
+++ /dev/null
@@ -1,807 +0,0 @@
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diff --git a/tests/integration/vector_io/recordings/7f4e87f64ef902317807cab5511bba64571798c892ba643f4e90fd6d303096e5.json b/tests/integration/vector_io/recordings/7f4e87f64ef902317807cab5511bba64571798c892ba643f4e90fd6d303096e5.json
deleted file mode 100644
index 3f14fce49..000000000
--- a/tests/integration/vector_io/recordings/7f4e87f64ef902317807cab5511bba64571798c892ba643f4e90fd6d303096e5.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/8158c78a51cf32f35b849dd054077757f7abbd584a52b47259fb0a903922eec0.json b/tests/integration/vector_io/recordings/8158c78a51cf32f35b849dd054077757f7abbd584a52b47259fb0a903922eec0.json
deleted file mode 100644
index d95380b90..000000000
--- a/tests/integration/vector_io/recordings/8158c78a51cf32f35b849dd054077757f7abbd584a52b47259fb0a903922eec0.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
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-      "input": [
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-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/81b1a9f421728ea0d7cebd8ee98e3884736ff73b43ca7e1380ae4021a6408c88.json b/tests/integration/vector_io/recordings/81b1a9f421728ea0d7cebd8ee98e3884736ff73b43ca7e1380ae4021a6408c88.json
deleted file mode 100644
index 8bed400ec..000000000
--- a/tests/integration/vector_io/recordings/81b1a9f421728ea0d7cebd8ee98e3884736ff73b43ca7e1380ae4021a6408c88.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "This is a test file 2"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
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diff --git a/tests/integration/vector_io/recordings/857315b4e5d12003e6001bf960d6f777c1bf17ea8d0223104e58929131c2b85a.json b/tests/integration/vector_io/recordings/857315b4e5d12003e6001bf960d6f777c1bf17ea8d0223104e58929131c2b85a.json
deleted file mode 100644
index c300d7cc9..000000000
--- a/tests/integration/vector_io/recordings/857315b4e5d12003e6001bf960d6f777c1bf17ea8d0223104e58929131c2b85a.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/8a91191497b114c296c8527508376c07e4e022018ca469b67be1cf7ca4f8dad7.json b/tests/integration/vector_io/recordings/8a91191497b114c296c8527508376c07e4e022018ca469b67be1cf7ca4f8dad7.json
deleted file mode 100644
index 4444048f2..000000000
--- a/tests/integration/vector_io/recordings/8a91191497b114c296c8527508376c07e4e022018ca469b67be1cf7ca4f8dad7.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
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-      "model": "nomic-embed-text:latest",
-      "input": [
-        "What is the secret string?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
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diff --git a/tests/integration/vector_io/recordings/8ad166a87a7d0faf81f7303dfc3987abce47f73b05cd4589e2ace9111b74017a.json b/tests/integration/vector_io/recordings/8ad166a87a7d0faf81f7303dfc3987abce47f73b05cd4589e2ace9111b74017a.json
deleted file mode 100644
index e483fab52..000000000
--- a/tests/integration/vector_io/recordings/8ad166a87a7d0faf81f7303dfc3987abce47f73b05cd4589e2ace9111b74017a.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_with_max_num_results[openai_client-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/8bff5f3199bbce23a135c3ee13686b28021c02e153f7e9afde245f92a976b201.json b/tests/integration/vector_io/recordings/8bff5f3199bbce23a135c3ee13686b28021c02e153f7e9afde245f92a976b201.json
deleted file mode 100644
index d943c40d5..000000000
--- a/tests/integration/vector_io/recordings/8bff5f3199bbce23a135c3ee13686b28021c02e153f7e9afde245f92a976b201.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "What makes Python different from C++ and Java?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
-    "body": {
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diff --git a/tests/integration/vector_io/recordings/8c1ed77a31e10ec6988db06208a667306a47ff9fc69643f51ffc31c204e02bc4.json b/tests/integration/vector_io/recordings/8c1ed77a31e10ec6988db06208a667306a47ff9fc69643f51ffc31c204e02bc4.json
deleted file mode 100644
index 40f45c283..000000000
--- a/tests/integration/vector_io/recordings/8c1ed77a31e10ec6988db06208a667306a47ff9fc69643f51ffc31c204e02bc4.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/8c4cc6bddf8e2a7e4f82cd7720ac00cb269802f01b8298fd20474d3b90c75ef8.json b/tests/integration/vector_io/recordings/8c4cc6bddf8e2a7e4f82cd7720ac00cb269802f01b8298fd20474d3b90c75ef8.json
deleted file mode 100644
index e5a663eb1..000000000
--- a/tests/integration/vector_io/recordings/8c4cc6bddf8e2a7e4f82cd7720ac00cb269802f01b8298fd20474d3b90c75ef8.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is a test file"
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-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
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diff --git a/tests/integration/vector_io/recordings/8d14acb1c48f179163ac25a18e16174725fd39decc6a0a0fdf48e79555768baf.json b/tests/integration/vector_io/recordings/8d14acb1c48f179163ac25a18e16174725fd39decc6a0a0fdf48e79555768baf.json
deleted file mode 100644
index f43a8ea93..000000000
--- a/tests/integration/vector_io/recordings/8d14acb1c48f179163ac25a18e16174725fd39decc6a0a0fdf48e79555768baf.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "What inspires neural networks?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
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diff --git a/tests/integration/vector_io/recordings/8e246925f82545d722b07dda81d265d03cbcd803987c3f7e52839f0e8ca70734.json b/tests/integration/vector_io/recordings/8e246925f82545d722b07dda81d265d03cbcd803987c3f7e52839f0e8ca70734.json
deleted file mode 100644
index 18d53028a..000000000
--- a/tests/integration/vector_io/recordings/8e246925f82545d722b07dda81d265d03cbcd803987c3f7e52839f0e8ca70734.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is batch cancel test file 0 with substantial content"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/8ef4143d60533d94e65f40f7c9bf3d5dedb83a652f62b620e4a72d1ed2649746.json b/tests/integration/vector_io/recordings/8ef4143d60533d94e65f40f7c9bf3d5dedb83a652f62b620e4a72d1ed2649746.json
deleted file mode 100644
index 9defe0777..000000000
--- a/tests/integration/vector_io/recordings/8ef4143d60533d94e65f40f7c9bf3d5dedb83a652f62b620e4a72d1ed2649746.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "The secret string is foobazbar."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/8fd70045388ac95624e6a06ccf539f50118a5c8863c10efa6ae3ae349a96b1fa.json b/tests/integration/vector_io/recordings/8fd70045388ac95624e6a06ccf539f50118a5c8863c10efa6ae3ae349a96b1fa.json
deleted file mode 100644
index ddfe5662a..000000000
--- a/tests/integration/vector_io/recordings/8fd70045388ac95624e6a06ccf539f50118a5c8863c10efa6ae3ae349a96b1fa.json
+++ /dev/null
@@ -1,75 +0,0 @@
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diff --git a/tests/integration/vector_io/recordings/905c500ff836c8f362e829181f31ae1d41e27f67a4c3c34e85c05a9de5f463fe.json b/tests/integration/vector_io/recordings/905c500ff836c8f362e829181f31ae1d41e27f67a4c3c34e85c05a9de5f463fe.json
deleted file mode 100644
index 177fec508..000000000
--- a/tests/integration/vector_io/recordings/905c500ff836c8f362e829181f31ae1d41e27f67a4c3c34e85c05a9de5f463fe.json
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-{
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diff --git a/tests/integration/vector_io/recordings/914b22e2837eb636400e1df117e8156fae80d0c68c54143bdb248673708dce89.json b/tests/integration/vector_io/recordings/914b22e2837eb636400e1df117e8156fae80d0c68c54143bdb248673708dce89.json
deleted file mode 100644
index b87c3f06f..000000000
--- a/tests/integration/vector_io/recordings/914b22e2837eb636400e1df117e8156fae80d0c68c54143bdb248673708dce89.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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index ad4611bd2..000000000
--- a/tests/integration/vector_io/recordings/919d7c178a51ecfdeb6dc98974baaef1f1fc20084f52828e02e640b354878392.json
+++ /dev/null
@@ -1,424 +0,0 @@
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diff --git a/tests/integration/vector_io/recordings/92376938790715055b6caca6610657df9aded31b68e57d6de7f1f9b941c24ffd.json b/tests/integration/vector_io/recordings/92376938790715055b6caca6610657df9aded31b68e57d6de7f1f9b941c24ffd.json
deleted file mode 100644
index a2f53ffcf..000000000
--- a/tests/integration/vector_io/recordings/92376938790715055b6caca6610657df9aded31b68e57d6de7f1f9b941c24ffd.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/9306a0b21f64fdd936685e172f220c125e364137ffdbd12013bd034cc07577ff.json b/tests/integration/vector_io/recordings/9306a0b21f64fdd936685e172f220c125e364137ffdbd12013bd034cc07577ff.json
deleted file mode 100644
index 2bc480c9a..000000000
--- a/tests/integration/vector_io/recordings/9306a0b21f64fdd936685e172f220c125e364137ffdbd12013bd034cc07577ff.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/93e42737b2b497aaf25e85aacdad49d573b52fc6f5f8d2f71c96a47eb155ccb0.json b/tests/integration/vector_io/recordings/93e42737b2b497aaf25e85aacdad49d573b52fc6f5f8d2f71c96a47eb155ccb0.json
deleted file mode 100644
index dcbed6ced..000000000
--- a/tests/integration/vector_io/recordings/93e42737b2b497aaf25e85aacdad49d573b52fc6f5f8d2f71c96a47eb155ccb0.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "machine learning and artificial intelligence"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
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diff --git a/tests/integration/vector_io/recordings/943a7db9bab0934c95417e8befe710b364496c1ee21a75258205830e1df7221b.json b/tests/integration/vector_io/recordings/943a7db9bab0934c95417e8befe710b364496c1ee21a75258205830e1df7221b.json
deleted file mode 100644
index c4338e8df..000000000
--- a/tests/integration/vector_io/recordings/943a7db9bab0934c95417e8befe710b364496c1ee21a75258205830e1df7221b.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
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-      "input": [
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/94855fa5b689f5e19ba5f7bdad71b7d893497622d5d24d057981b4ac18310d6a.json b/tests/integration/vector_io/recordings/94855fa5b689f5e19ba5f7bdad71b7d893497622d5d24d057981b4ac18310d6a.json
deleted file mode 100644
index 3b14b5b64..000000000
--- a/tests/integration/vector_io/recordings/94855fa5b689f5e19ba5f7bdad71b7d893497622d5d24d057981b4ac18310d6a.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
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-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
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diff --git a/tests/integration/vector_io/recordings/951a2cde454e88a99039a4b5dd9390f6039f5c312942529cee7839c7596320c9.json b/tests/integration/vector_io/recordings/951a2cde454e88a99039a4b5dd9390f6039f5c312942529cee7839c7596320c9.json
deleted file mode 100644
index 9a3d53dc8..000000000
--- a/tests/integration/vector_io/recordings/951a2cde454e88a99039a4b5dd9390f6039f5c312942529cee7839c7596320c9.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
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-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
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diff --git a/tests/integration/vector_io/recordings/95590b5adc9f1e988ad18650475c69d81d905027bf7c7bfa2d9e1db4499bbe30.json b/tests/integration/vector_io/recordings/95590b5adc9f1e988ad18650475c69d81d905027bf7c7bfa2d9e1db4499bbe30.json
deleted file mode 100644
index db4b6507a..000000000
--- a/tests/integration/vector_io/recordings/95590b5adc9f1e988ad18650475c69d81d905027bf7c7bfa2d9e1db4499bbe30.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
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diff --git a/tests/integration/vector_io/recordings/97187cadffb7a2aad98aafedd43e68078edc66584f1ec175e2b52c7e82d90ba9.json b/tests/integration/vector_io/recordings/97187cadffb7a2aad98aafedd43e68078edc66584f1ec175e2b52c7e82d90ba9.json
deleted file mode 100644
index 199315b3c..000000000
--- a/tests/integration/vector_io/recordings/97187cadffb7a2aad98aafedd43e68078edc66584f1ec175e2b52c7e82d90ba9.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
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diff --git a/tests/integration/vector_io/recordings/988232f3a98f7adbc71680b597271b3c225707cee8f153dc629713dbd8baa9e1.json b/tests/integration/vector_io/recordings/988232f3a98f7adbc71680b597271b3c225707cee8f153dc629713dbd8baa9e1.json
deleted file mode 100644
index 9f665e3ce..000000000
--- a/tests/integration/vector_io/recordings/988232f3a98f7adbc71680b597271b3c225707cee8f153dc629713dbd8baa9e1.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/9aa2abb14fb4eb11cfde0cb5027a9cf80194781a6133ea6e9b4998897b8888df.json b/tests/integration/vector_io/recordings/9aa2abb14fb4eb11cfde0cb5027a9cf80194781a6133ea6e9b4998897b8888df.json
deleted file mode 100644
index 2e637dc31..000000000
--- a/tests/integration/vector_io/recordings/9aa2abb14fb4eb11cfde0cb5027a9cf80194781a6133ea6e9b4998897b8888df.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/9b7dae9566293c1c4501e9b7781553e5f5a03e243b8966aecff921ce5feb2f6b.json b/tests/integration/vector_io/recordings/9b7dae9566293c1c4501e9b7781553e5f5a03e243b8966aecff921ce5feb2f6b.json
deleted file mode 100644
index 79a65cc70..000000000
--- a/tests/integration/vector_io/recordings/9b7dae9566293c1c4501e9b7781553e5f5a03e243b8966aecff921ce5feb2f6b.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
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-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
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diff --git a/tests/integration/vector_io/recordings/9c30695933702b8bb0b90a9b79c8def97ef6742dbdfd8ca22f06523a5ca97c55.json b/tests/integration/vector_io/recordings/9c30695933702b8bb0b90a9b79c8def97ef6742dbdfd8ca22f06523a5ca97c55.json
deleted file mode 100644
index cdb0099ba..000000000
--- a/tests/integration/vector_io/recordings/9c30695933702b8bb0b90a9b79c8def97ef6742dbdfd8ca22f06523a5ca97c55.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_with_high_score_filter[client_with_models-emb=ollama/all-minilm:l6-v2:dim=384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
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diff --git a/tests/integration/vector_io/recordings/a3df2e3d02fcafc4434c74e93ffba0ffd54fd87eac5d2aaf8f9b2b8315e922a3.json b/tests/integration/vector_io/recordings/a3df2e3d02fcafc4434c74e93ffba0ffd54fd87eac5d2aaf8f9b2b8315e922a3.json
deleted file mode 100644
index 03fda6ee9..000000000
--- a/tests/integration/vector_io/recordings/a3df2e3d02fcafc4434c74e93ffba0ffd54fd87eac5d2aaf8f9b2b8315e922a3.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/a51b6d8ffe6157f82c93357007be640c0df4933631566b8e4c8e13e9ad1723b9.json b/tests/integration/vector_io/recordings/a51b6d8ffe6157f82c93357007be640c0df4933631566b8e4c8e13e9ad1723b9.json
deleted file mode 100644
index ce70b22b3..000000000
--- a/tests/integration/vector_io/recordings/a51b6d8ffe6157f82c93357007be640c0df4933631566b8e4c8e13e9ad1723b9.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/a696b651a82787407df666c2965b530deef00ff9136fa587598ac1504614d187.json b/tests/integration/vector_io/recordings/a696b651a82787407df666c2965b530deef00ff9136fa587598ac1504614d187.json
deleted file mode 100644
index 8c8e4ac20..000000000
--- a/tests/integration/vector_io/recordings/a696b651a82787407df666c2965b530deef00ff9136fa587598ac1504614d187.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
-    "body": {
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-      "input": [
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-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/a8668c968c057b15c396b11e3954ddd82f666eba0901113902d42fc247219a53.json b/tests/integration/vector_io/recordings/a8668c968c057b15c396b11e3954ddd82f666eba0901113902d42fc247219a53.json
deleted file mode 100644
index b3830ecc9..000000000
--- a/tests/integration/vector_io/recordings/a8668c968c057b15c396b11e3954ddd82f666eba0901113902d42fc247219a53.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
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diff --git a/tests/integration/vector_io/recordings/a886f112c4f9091d64b9ddc6cd6eb216871537b01bb8a5e4480e735bb4ad2986.json b/tests/integration/vector_io/recordings/a886f112c4f9091d64b9ddc6cd6eb216871537b01bb8a5e4480e735bb4ad2986.json
deleted file mode 100644
index 9ea10e399..000000000
--- a/tests/integration/vector_io/recordings/a886f112c4f9091d64b9ddc6cd6eb216871537b01bb8a5e4480e735bb4ad2986.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-    "endpoint": "/v1/embeddings",
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index aa5544ebd..000000000
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diff --git a/tests/integration/vector_io/recordings/ab94b114976fc7509a3f608ebf93178b8403ed86e1b8826541704f18f1fa081a.json b/tests/integration/vector_io/recordings/ab94b114976fc7509a3f608ebf93178b8403ed86e1b8826541704f18f1fa081a.json
deleted file mode 100644
index 3a15a0b11..000000000
--- a/tests/integration/vector_io/recordings/ab94b114976fc7509a3f608ebf93178b8403ed86e1b8826541704f18f1fa081a.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/acfbf9ddad33b2acb7f4effe5071d21b0d4619f536cb8af093b6d518b4a65ba1.json b/tests/integration/vector_io/recordings/acfbf9ddad33b2acb7f4effe5071d21b0d4619f536cb8af093b6d518b4a65ba1.json
deleted file mode 100644
index 240014661..000000000
--- a/tests/integration/vector_io/recordings/acfbf9ddad33b2acb7f4effe5071d21b0d4619f536cb8af093b6d518b4a65ba1.json
+++ /dev/null
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deleted file mode 100644
index d51ddd513..000000000
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diff --git a/tests/integration/vector_io/recordings/af2bbdaa1a50cbcc09258f53bfd94f7cfd7c86023612018011dd07d3e80d422f.json b/tests/integration/vector_io/recordings/af2bbdaa1a50cbcc09258f53bfd94f7cfd7c86023612018011dd07d3e80d422f.json
deleted file mode 100644
index 9ff00b6e3..000000000
--- a/tests/integration/vector_io/recordings/af2bbdaa1a50cbcc09258f53bfd94f7cfd7c86023612018011dd07d3e80d422f.json
+++ /dev/null
@@ -1,423 +0,0 @@
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-    "is_streaming": false
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diff --git a/tests/integration/vector_io/recordings/afb1826ce440eb642cc2e213a0b69b27cf4ef1fd0cdaef95cef1a1f19b54cd72.json b/tests/integration/vector_io/recordings/afb1826ce440eb642cc2e213a0b69b27cf4ef1fd0cdaef95cef1a1f19b54cd72.json
deleted file mode 100644
index df7a314b4..000000000
--- a/tests/integration/vector_io/recordings/afb1826ce440eb642cc2e213a0b69b27cf4ef1fd0cdaef95cef1a1f19b54cd72.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "What is the capital of France?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/b03801ff92bb7b6cc494872e562ac62e07757316fd788b1b57e712dc1a56ba79.json b/tests/integration/vector_io/recordings/b03801ff92bb7b6cc494872e562ac62e07757316fd788b1b57e712dc1a56ba79.json
deleted file mode 100644
index c5accc1fd..000000000
--- a/tests/integration/vector_io/recordings/b03801ff92bb7b6cc494872e562ac62e07757316fd788b1b57e712dc1a56ba79.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
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diff --git a/tests/integration/vector_io/recordings/b1980d1314bdf6b13518da36cd669e51f54e5c269131d91b6156ab153eb9a12e.json b/tests/integration/vector_io/recordings/b1980d1314bdf6b13518da36cd669e51f54e5c269131d91b6156ab153eb9a12e.json
deleted file mode 100644
index 5691bda0b..000000000
--- a/tests/integration/vector_io/recordings/b1980d1314bdf6b13518da36cd669e51f54e5c269131d91b6156ab153eb9a12e.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_relevance[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384-test_case1]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
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-        "model": "all-minilm:l6-v2",
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diff --git a/tests/integration/vector_io/recordings/b2b2d7c8a0ff031cfdb0338794b1cd2d32bbfe8b634b02453b069ea788a3c25f.json b/tests/integration/vector_io/recordings/b2b2d7c8a0ff031cfdb0338794b1cd2d32bbfe8b634b02453b069ea788a3c25f.json
deleted file mode 100644
index 75ef1267d..000000000
--- a/tests/integration/vector_io/recordings/b2b2d7c8a0ff031cfdb0338794b1cd2d32bbfe8b634b02453b069ea788a3c25f.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/b3f9fc35d4be85f421610c60333f0c2dde2b01f41cd085428225eb809eb0c811.json b/tests/integration/vector_io/recordings/b3f9fc35d4be85f421610c60333f0c2dde2b01f41cd085428225eb809eb0c811.json
deleted file mode 100644
index c0b5fd01f..000000000
--- a/tests/integration/vector_io/recordings/b3f9fc35d4be85f421610c60333f0c2dde2b01f41cd085428225eb809eb0c811.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
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-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
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diff --git a/tests/integration/vector_io/recordings/b464a1555bc412e0019125f7d267213561e75add47b00588695a4f24228dd2af.json b/tests/integration/vector_io/recordings/b464a1555bc412e0019125f7d267213561e75add47b00588695a4f24228dd2af.json
deleted file mode 100644
index 2b0e62520..000000000
--- a/tests/integration/vector_io/recordings/b464a1555bc412e0019125f7d267213561e75add47b00588695a4f24228dd2af.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "What is the capital of France?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
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diff --git a/tests/integration/vector_io/recordings/b60f4978fe7be917e2bf7dd4303f743caa0d92d15763caeb452aac73239e0703.json b/tests/integration/vector_io/recordings/b60f4978fe7be917e2bf7dd4303f743caa0d92d15763caeb452aac73239e0703.json
deleted file mode 100644
index 199d7fac2..000000000
--- a/tests/integration/vector_io/recordings/b60f4978fe7be917e2bf7dd4303f743caa0d92d15763caeb452aac73239e0703.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/b64e87344975bc04c04c010bbffcf2878033babb996ab6ff73757ccfbe8ccd7d.json b/tests/integration/vector_io/recordings/b64e87344975bc04c04c010bbffcf2878033babb996ab6ff73757ccfbe8ccd7d.json
deleted file mode 100644
index f58e96213..000000000
--- a/tests/integration/vector_io/recordings/b64e87344975bc04c04c010bbffcf2878033babb996ab6ff73757ccfbe8ccd7d.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/b7b5be5b9bb1b27f8163464b8072639122ba0c45bfad89bf20ee909ae93f4784.json b/tests/integration/vector_io/recordings/b7b5be5b9bb1b27f8163464b8072639122ba0c45bfad89bf20ee909ae93f4784.json
deleted file mode 100644
index 66e4a6855..000000000
--- a/tests/integration/vector_io/recordings/b7b5be5b9bb1b27f8163464b8072639122ba0c45bfad89bf20ee909ae93f4784.json
+++ /dev/null
@@ -1,424 +0,0 @@
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-  "id_normalization_mapping": {}
-}
diff --git a/tests/integration/vector_io/recordings/b7da02bba5b53eba22254adf0e5086763cc6caff7fafddeefc9826e63a196098.json b/tests/integration/vector_io/recordings/b7da02bba5b53eba22254adf0e5086763cc6caff7fafddeefc9826e63a196098.json
deleted file mode 100644
index d52e34c72..000000000
--- a/tests/integration/vector_io/recordings/b7da02bba5b53eba22254adf0e5086763cc6caff7fafddeefc9826e63a196098.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is a test file 2"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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diff --git a/tests/integration/vector_io/recordings/b9c73278f1fa312444933f25385c766bdd5b774dcd880ee5e61cd3fdc63d9d5e.json b/tests/integration/vector_io/recordings/b9c73278f1fa312444933f25385c766bdd5b774dcd880ee5e61cd3fdc63d9d5e.json
deleted file mode 100644
index 46af83e50..000000000
--- a/tests/integration/vector_io/recordings/b9c73278f1fa312444933f25385c766bdd5b774dcd880ee5e61cd3fdc63d9d5e.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
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-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file 2"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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-  },
-  "id_normalization_mapping": {}
-}
diff --git a/tests/integration/vector_io/recordings/bd4fe447e7d66a348743652557150932b95a236f08d31f33da07ad526139c6d8.json b/tests/integration/vector_io/recordings/bd4fe447e7d66a348743652557150932b95a236f08d31f33da07ad526139c6d8.json
deleted file mode 100644
index 8e4d44481..000000000
--- a/tests/integration/vector_io/recordings/bd4fe447e7d66a348743652557150932b95a236f08d31f33da07ad526139c6d8.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is a test file 2"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/bdfb92af4b2d3ea2883d519ef83c27689523c9d8abfe53cfd44e96f80644b1c2.json b/tests/integration/vector_io/recordings/bdfb92af4b2d3ea2883d519ef83c27689523c9d8abfe53cfd44e96f80644b1c2.json
deleted file mode 100644
index b24101823..000000000
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+++ /dev/null
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-{
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diff --git a/tests/integration/vector_io/recordings/be19ba4e6af5ab141cb7fa2d955f8c83ee1b1fc64935e081a4ae0e63ec1e1a0d.json b/tests/integration/vector_io/recordings/be19ba4e6af5ab141cb7fa2d955f8c83ee1b1fc64935e081a4ae0e63ec1e1a0d.json
deleted file mode 100644
index 1e753dde8..000000000
--- a/tests/integration/vector_io/recordings/be19ba4e6af5ab141cb7fa2d955f8c83ee1b1fc64935e081a4ae0e63ec1e1a0d.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/be32c9233b45500fa8489ee490f8e4fb4f62fe33ba6daca56a2e68f8ab6bd110.json b/tests/integration/vector_io/recordings/be32c9233b45500fa8489ee490f8e4fb4f62fe33ba6daca56a2e68f8ab6bd110.json
deleted file mode 100644
index b6cb5d9ee..000000000
--- a/tests/integration/vector_io/recordings/be32c9233b45500fa8489ee490f8e4fb4f62fe33ba6daca56a2e68f8ab6bd110.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/be4907dad3a07c4b44bb5ff9463dcdae61612c7500bc04669cbf13c43927c87e.json b/tests/integration/vector_io/recordings/be4907dad3a07c4b44bb5ff9463dcdae61612c7500bc04669cbf13c43927c87e.json
deleted file mode 100644
index 94742c3b4..000000000
--- a/tests/integration/vector_io/recordings/be4907dad3a07c4b44bb5ff9463dcdae61612c7500bc04669cbf13c43927c87e.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
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-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file 2"
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-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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deleted file mode 100644
index fbcb45dde..000000000
--- a/tests/integration/vector_io/recordings/be8b6debd99ae0edadbf85762fd0ae2dbc53aebd13834348d5142bf249b9aa50.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/c081cad9ac0edf5f7acea76c5bc9d62d0e8181556cdfa1fc8d0870d879520e29.json b/tests/integration/vector_io/recordings/c081cad9ac0edf5f7acea76c5bc9d62d0e8181556cdfa1fc8d0870d879520e29.json
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diff --git a/tests/integration/vector_io/recordings/c165563c0bf26d6504d63f35839eed1149a569e3e3f0648e1abb03257d10c006.json b/tests/integration/vector_io/recordings/c165563c0bf26d6504d63f35839eed1149a569e3e3f0648e1abb03257d10c006.json
deleted file mode 100644
index 8ced4042e..000000000
--- a/tests/integration/vector_io/recordings/c165563c0bf26d6504d63f35839eed1149a569e3e3f0648e1abb03257d10c006.json
+++ /dev/null
@@ -1,423 +0,0 @@
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diff --git a/tests/integration/vector_io/recordings/c3c1adc7f70b7236338d292532179a65fc0b4b9b989542eafa8e2e5317b5cc47.json b/tests/integration/vector_io/recordings/c3c1adc7f70b7236338d292532179a65fc0b4b9b989542eafa8e2e5317b5cc47.json
deleted file mode 100644
index 5c66341cf..000000000
--- a/tests/integration/vector_io/recordings/c3c1adc7f70b7236338d292532179a65fc0b4b9b989542eafa8e2e5317b5cc47.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "What is the biological inspiration for neural networks?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
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diff --git a/tests/integration/vector_io/recordings/c4dc33b6ca81a4bee57e69a8afe9dfd4fc4b4213306068ab3c3f79f431a04aa3.json b/tests/integration/vector_io/recordings/c4dc33b6ca81a4bee57e69a8afe9dfd4fc4b4213306068ab3c3f79f431a04aa3.json
deleted file mode 100644
index aa486d025..000000000
--- a/tests/integration/vector_io/recordings/c4dc33b6ca81a4bee57e69a8afe9dfd4fc4b4213306068ab3c3f79f431a04aa3.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-      "input": [
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diff --git a/tests/integration/vector_io/recordings/c520d56562b8c9d7621d2f2a19935433d4c8d8c17bd0ab79db811a2e5bfa58bf.json b/tests/integration/vector_io/recordings/c520d56562b8c9d7621d2f2a19935433d4c8d8c17bd0ab79db811a2e5bfa58bf.json
deleted file mode 100644
index b0987a73f..000000000
--- a/tests/integration/vector_io/recordings/c520d56562b8c9d7621d2f2a19935433d4c8d8c17bd0ab79db811a2e5bfa58bf.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/c57d4e2d339390448d8d2ea70d270c9da9c5e08ed42b6fca33bb227b8fbda1d3.json b/tests/integration/vector_io/recordings/c57d4e2d339390448d8d2ea70d270c9da9c5e08ed42b6fca33bb227b8fbda1d3.json
deleted file mode 100644
index 979f9d79e..000000000
--- a/tests/integration/vector_io/recordings/c57d4e2d339390448d8d2ea70d270c9da9c5e08ed42b6fca33bb227b8fbda1d3.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-        "model": "all-minilm:l6-v2",
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diff --git a/tests/integration/vector_io/recordings/c5b910bee30b424762f48d2d20bdf8823e2de7f9e63fe8e085428ba4306fc7bd.json b/tests/integration/vector_io/recordings/c5b910bee30b424762f48d2d20bdf8823e2de7f9e63fe8e085428ba4306fc7bd.json
deleted file mode 100644
index 56c254f9d..000000000
--- a/tests/integration/vector_io/recordings/c5b910bee30b424762f48d2d20bdf8823e2de7f9e63fe8e085428ba4306fc7bd.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_relevance[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384-test_case0]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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diff --git a/tests/integration/vector_io/recordings/c61a30ecd0a20fce37f374ae66e8c284e2374c6dc9c85d0407666148cb130338.json b/tests/integration/vector_io/recordings/c61a30ecd0a20fce37f374ae66e8c284e2374c6dc9c85d0407666148cb130338.json
deleted file mode 100644
index f21b14449..000000000
--- a/tests/integration/vector_io/recordings/c61a30ecd0a20fce37f374ae66e8c284e2374c6dc9c85d0407666148cb130338.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
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-      "input": [
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-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/c789f41a814ae83aeb63314429951525bfae1ccd8acd000f234f62772385f25d.json b/tests/integration/vector_io/recordings/c789f41a814ae83aeb63314429951525bfae1ccd8acd000f234f62772385f25d.json
deleted file mode 100644
index c8e5b6760..000000000
--- a/tests/integration/vector_io/recordings/c789f41a814ae83aeb63314429951525bfae1ccd8acd000f234f62772385f25d.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is a test file 1"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
-    "body": {
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-        "model": "nomic-embed-text:latest",
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diff --git a/tests/integration/vector_io/recordings/c7ac41031c6144ea22dae926b10d61e6c290808526ea553d8bb1dd46a7ceb23e.json b/tests/integration/vector_io/recordings/c7ac41031c6144ea22dae926b10d61e6c290808526ea553d8bb1dd46a7ceb23e.json
deleted file mode 100644
index 2f4da8ec1..000000000
--- a/tests/integration/vector_io/recordings/c7ac41031c6144ea22dae926b10d61e6c290808526ea553d8bb1dd46a7ceb23e.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_with_high_score_filter[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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diff --git a/tests/integration/vector_io/recordings/c8403cec0956a223c5fd8018b79bcabccae052d0f772eb8e3b93e970b74783a1.json b/tests/integration/vector_io/recordings/c8403cec0956a223c5fd8018b79bcabccae052d0f772eb8e3b93e970b74783a1.json
deleted file mode 100644
index 6d8b5a659..000000000
--- a/tests/integration/vector_io/recordings/c8403cec0956a223c5fd8018b79bcabccae052d0f772eb8e3b93e970b74783a1.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is the content of test file 2"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
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diff --git a/tests/integration/vector_io/recordings/c8c5fd819e5541517feb2f5ce2365cb585f923c09505c82174b6f943d93ed0ed.json b/tests/integration/vector_io/recordings/c8c5fd819e5541517feb2f5ce2365cb585f923c09505c82174b6f943d93ed0ed.json
deleted file mode 100644
index f30a4ecfc..000000000
--- a/tests/integration/vector_io/recordings/c8c5fd819e5541517feb2f5ce2365cb585f923c09505c82174b6f943d93ed0ed.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/c8ed0fec93643f46119f52d41dac630e6509d587f06b76bc6e5a3eafddc17170.json b/tests/integration/vector_io/recordings/c8ed0fec93643f46119f52d41dac630e6509d587f06b76bc6e5a3eafddc17170.json
deleted file mode 100644
index f22b68464..000000000
--- a/tests/integration/vector_io/recordings/c8ed0fec93643f46119f52d41dac630e6509d587f06b76bc6e5a3eafddc17170.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/ca1e663fded17ca15ee64f694c7a070edf253a01b18edfa7dcee5e2a2a3a0780.json b/tests/integration/vector_io/recordings/ca1e663fded17ca15ee64f694c7a070edf253a01b18edfa7dcee5e2a2a3a0780.json
deleted file mode 100644
index ddd65e836..000000000
--- a/tests/integration/vector_io/recordings/ca1e663fded17ca15ee64f694c7a070edf253a01b18edfa7dcee5e2a2a3a0780.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is a test file"
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-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
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diff --git a/tests/integration/vector_io/recordings/cb7a804d10b478a8d370ff1cc9f7ee792738289351c69c27d17fc319f9b37bce.json b/tests/integration/vector_io/recordings/cb7a804d10b478a8d370ff1cc9f7ee792738289351c69c27d17fc319f9b37bce.json
deleted file mode 100644
index 779495f47..000000000
--- a/tests/integration/vector_io/recordings/cb7a804d10b478a8d370ff1cc9f7ee792738289351c69c27d17fc319f9b37bce.json
+++ /dev/null
@@ -1,75 +0,0 @@
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diff --git a/tests/integration/vector_io/recordings/cbaec9aea0716682ec03d89e2e1c307e91d5448b3c93ca4ef3e790954240ecb4.json b/tests/integration/vector_io/recordings/cbaec9aea0716682ec03d89e2e1c307e91d5448b3c93ca4ef3e790954240ecb4.json
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diff --git a/tests/integration/vector_io/recordings/cbfc8bf8095304fe907c29afadc847b401dd78b534a85382fe011e7a1ea78949.json b/tests/integration/vector_io/recordings/cbfc8bf8095304fe907c29afadc847b401dd78b534a85382fe011e7a1ea78949.json
deleted file mode 100644
index f2b288013..000000000
--- a/tests/integration/vector_io/recordings/cbfc8bf8095304fe907c29afadc847b401dd78b534a85382fe011e7a1ea78949.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is batch test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
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index a52e53c90..000000000
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diff --git a/tests/integration/vector_io/recordings/cf9303336f79c19949db1e44bab3d3637b4a7edb50c51c7fd3806a24bcd9fe7d.json b/tests/integration/vector_io/recordings/cf9303336f79c19949db1e44bab3d3637b4a7edb50c51c7fd3806a24bcd9fe7d.json
deleted file mode 100644
index 4cae6e558..000000000
--- a/tests/integration/vector_io/recordings/cf9303336f79c19949db1e44bab3d3637b4a7edb50c51c7fd3806a24bcd9fe7d.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "This is a test file 2"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
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diff --git a/tests/integration/vector_io/recordings/d0adabbaf5f9556efbea11aedca90cdf5e6f58c0dbe9288a739f1d253d241afa.json b/tests/integration/vector_io/recordings/d0adabbaf5f9556efbea11aedca90cdf5e6f58c0dbe9288a739f1d253d241afa.json
deleted file mode 100644
index 04e1161da..000000000
--- a/tests/integration/vector_io/recordings/d0adabbaf5f9556efbea11aedca90cdf5e6f58c0dbe9288a739f1d253d241afa.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_relevance[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384-test_case1]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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diff --git a/tests/integration/vector_io/recordings/d1747c96c0da77d861ca1e1a24924fbe12a62ee7366734738b0c777f1a792cb3.json b/tests/integration/vector_io/recordings/d1747c96c0da77d861ca1e1a24924fbe12a62ee7366734738b0c777f1a792cb3.json
deleted file mode 100644
index 8748326b9..000000000
--- a/tests/integration/vector_io/recordings/d1747c96c0da77d861ca1e1a24924fbe12a62ee7366734738b0c777f1a792cb3.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
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-      "input": [
-        "What inspires neural networks?"
-      ],
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/d19b3455f6437a862be80a2327e035d99dcafb55430077f0d367de43f8488c31.json b/tests/integration/vector_io/recordings/d19b3455f6437a862be80a2327e035d99dcafb55430077f0d367de43f8488c31.json
deleted file mode 100644
index b07befc72..000000000
--- a/tests/integration/vector_io/recordings/d19b3455f6437a862be80a2327e035d99dcafb55430077f0d367de43f8488c31.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-      "input": [
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-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/d2292098666c78ddeb9187e35478e706031cc53b6354505cb5475dfc1428c687.json b/tests/integration/vector_io/recordings/d2292098666c78ddeb9187e35478e706031cc53b6354505cb5475dfc1428c687.json
deleted file mode 100644
index acb9e1139..000000000
--- a/tests/integration/vector_io/recordings/d2292098666c78ddeb9187e35478e706031cc53b6354505cb5475dfc1428c687.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/d3b0355aeba053e46c3aa0d1a37ea1f44306df990abdff5d2f755d65dd91bc41.json b/tests/integration/vector_io/recordings/d3b0355aeba053e46c3aa0d1a37ea1f44306df990abdff5d2f755d65dd91bc41.json
deleted file mode 100644
index d147241bd..000000000
--- a/tests/integration/vector_io/recordings/d3b0355aeba053e46c3aa0d1a37ea1f44306df990abdff5d2f755d65dd91bc41.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "What makes Python different from other languages?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/d3c384fc44a5508fec866e03dc7f8db69033767367cfc689266c26a05d8f7732.json b/tests/integration/vector_io/recordings/d3c384fc44a5508fec866e03dc7f8db69033767367cfc689266c26a05d8f7732.json
deleted file mode 100644
index 8051a48cb..000000000
--- a/tests/integration/vector_io/recordings/d3c384fc44a5508fec866e03dc7f8db69033767367cfc689266c26a05d8f7732.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file"
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-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
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diff --git a/tests/integration/vector_io/recordings/d5eb538d76e0b62acedf0e8f475d1dfef7d57b6e7facb1779a5dd15b547144b3.json b/tests/integration/vector_io/recordings/d5eb538d76e0b62acedf0e8f475d1dfef7d57b6e7facb1779a5dd15b547144b3.json
deleted file mode 100644
index 1bb97e204..000000000
--- a/tests/integration/vector_io/recordings/d5eb538d76e0b62acedf0e8f475d1dfef7d57b6e7facb1779a5dd15b547144b3.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "What is the secret string?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
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diff --git a/tests/integration/vector_io/recordings/d5fb8bf6057307043bb8207aa0219d88652f0918a5520b56f8bfa0a8b2e7bc42.json b/tests/integration/vector_io/recordings/d5fb8bf6057307043bb8207aa0219d88652f0918a5520b56f8bfa0a8b2e7bc42.json
deleted file mode 100644
index 49e62fea8..000000000
--- a/tests/integration/vector_io/recordings/d5fb8bf6057307043bb8207aa0219d88652f0918a5520b56f8bfa0a8b2e7bc42.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/d6ac0ad7fd2df01a6a1809f4be3f770fc218ca68702d51da8d325db23a2d16d6.json b/tests/integration/vector_io/recordings/d6ac0ad7fd2df01a6a1809f4be3f770fc218ca68702d51da8d325db23a2d16d6.json
deleted file mode 100644
index cf8cb038c..000000000
--- a/tests/integration/vector_io/recordings/d6ac0ad7fd2df01a6a1809f4be3f770fc218ca68702d51da8d325db23a2d16d6.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "How do systems learn automatically?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
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diff --git a/tests/integration/vector_io/recordings/d714a7d06de1f6fc4a50fae14e97e04603946ec379615879856de7a2c8ea48a6.json b/tests/integration/vector_io/recordings/d714a7d06de1f6fc4a50fae14e97e04603946ec379615879856de7a2c8ea48a6.json
deleted file mode 100644
index e7975a328..000000000
--- a/tests/integration/vector_io/recordings/d714a7d06de1f6fc4a50fae14e97e04603946ec379615879856de7a2c8ea48a6.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file"
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-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
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diff --git a/tests/integration/vector_io/recordings/d74e7e352b27eff8032641831fb79602fd2b48f5bfc786d89a5512041b5c3f62.json b/tests/integration/vector_io/recordings/d74e7e352b27eff8032641831fb79602fd2b48f5bfc786d89a5512041b5c3f62.json
deleted file mode 100644
index 0bcd22c83..000000000
--- a/tests/integration/vector_io/recordings/d74e7e352b27eff8032641831fb79602fd2b48f5bfc786d89a5512041b5c3f62.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
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-      "input": [
-        "Python is a high-level programming language with code readability and fewer lines than C++ or Java"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/d7c0f2ab8feb1c356881fa40c573bf1d16a1e5ab3c49e3f207da32ac7f93cbad.json b/tests/integration/vector_io/recordings/d7c0f2ab8feb1c356881fa40c573bf1d16a1e5ab3c49e3f207da32ac7f93cbad.json
deleted file mode 100644
index 7c21f281f..000000000
--- a/tests/integration/vector_io/recordings/d7c0f2ab8feb1c356881fa40c573bf1d16a1e5ab3c49e3f207da32ac7f93cbad.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "The secret string is foobazbar."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/d9dabe864485fe4ac7220bacb73bc09f4cf1441fff75af00005372bcce53d072.json b/tests/integration/vector_io/recordings/d9dabe864485fe4ac7220bacb73bc09f4cf1441fff75af00005372bcce53d072.json
deleted file mode 100644
index be6d0246c..000000000
--- a/tests/integration/vector_io/recordings/d9dabe864485fe4ac7220bacb73bc09f4cf1441fff75af00005372bcce53d072.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-    "headers": {},
-    "body": {
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-      "input": [
-        "The secret string is foobazbar."
-      ],
-      "encoding_format": "float"
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-    "model": "nomic-embed-text:latest"
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diff --git a/tests/integration/vector_io/recordings/da1e7b0f80936e70deaa09b6678d0f2756377d5ed83818898fd4c4c67df8ade6.json b/tests/integration/vector_io/recordings/da1e7b0f80936e70deaa09b6678d0f2756377d5ed83818898fd4c4c67df8ade6.json
deleted file mode 100644
index 938e83cf0..000000000
--- a/tests/integration/vector_io/recordings/da1e7b0f80936e70deaa09b6678d0f2756377d5ed83818898fd4c4c67df8ade6.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_file_batch_cancel[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is batch cancel test file 1 with substantial content"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
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diff --git a/tests/integration/vector_io/recordings/da46b1557c5b162e15c6adb1d36a4e851b8a67093cc917a1e8dde8176172ba28.json b/tests/integration/vector_io/recordings/da46b1557c5b162e15c6adb1d36a4e851b8a67093cc917a1e8dde8176172ba28.json
deleted file mode 100644
index 5e92352ed..000000000
--- a/tests/integration/vector_io/recordings/da46b1557c5b162e15c6adb1d36a4e851b8a67093cc917a1e8dde8176172ba28.json
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diff --git a/tests/integration/vector_io/recordings/da86b5dccd827d9c7e1a922baeca746051c9eb833ea1a0748e451c21b7442d68.json b/tests/integration/vector_io/recordings/da86b5dccd827d9c7e1a922baeca746051c9eb833ea1a0748e451c21b7442d68.json
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diff --git a/tests/integration/vector_io/recordings/db5a100bc97ebce10aa7b5b1b68ae42d52885ecd3609a75d804866c67b6b709d.json b/tests/integration/vector_io/recordings/db5a100bc97ebce10aa7b5b1b68ae42d52885ecd3609a75d804866c67b6b709d.json
deleted file mode 100644
index 0f751cd3e..000000000
--- a/tests/integration/vector_io/recordings/db5a100bc97ebce10aa7b5b1b68ae42d52885ecd3609a75d804866c67b6b709d.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
-  "response": {
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deleted file mode 100644
index ef2e423cd..000000000
--- a/tests/integration/vector_io/recordings/dca19b7ef78816758fd49eae3ab1cb5de27c173361a4a1ba01eaa33599dfc268.json
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diff --git a/tests/integration/vector_io/recordings/ddab76d1d1b267c631246f89c4e4875a6cfedf7f7445ee6440dfff9879a24bec.json b/tests/integration/vector_io/recordings/ddab76d1d1b267c631246f89c4e4875a6cfedf7f7445ee6440dfff9879a24bec.json
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index 341839ec4..000000000
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diff --git a/tests/integration/vector_io/recordings/de4148bb72ba07cb93bd73dee30cc85c83935df23940549e2fb0f2262910ab31.json b/tests/integration/vector_io/recordings/de4148bb72ba07cb93bd73dee30cc85c83935df23940549e2fb0f2262910ab31.json
deleted file mode 100644
index 436da8c57..000000000
--- a/tests/integration/vector_io/recordings/de4148bb72ba07cb93bd73dee30cc85c83935df23940549e2fb0f2262910ab31.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_with_chunks[openai_client-emb=ollama/all-minilm:l6-v2:dim=384]",
-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
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diff --git a/tests/integration/vector_io/recordings/df0116b306adc5197078e76edbc58dae9c9c44186435b30eac3f312b1a954063.json b/tests/integration/vector_io/recordings/df0116b306adc5197078e76edbc58dae9c9c44186435b30eac3f312b1a954063.json
deleted file mode 100644
index 0ee6749cf..000000000
--- a/tests/integration/vector_io/recordings/df0116b306adc5197078e76edbc58dae9c9c44186435b30eac3f312b1a954063.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=ollama/all-minilm:l6-v2:dim=384-test_case2]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/e03951c7b13aa5ddad6828b30c71da7d8e9dfaeafa208db2c4308974cfbfc70a.json b/tests/integration/vector_io/recordings/e03951c7b13aa5ddad6828b30c71da7d8e9dfaeafa208db2c4308974cfbfc70a.json
deleted file mode 100644
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+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/e05734a51b5ed00dcac0aff27bc28b614936c4454e27d81855f06104346c0b5a.json b/tests/integration/vector_io/recordings/e05734a51b5ed00dcac0aff27bc28b614936c4454e27d81855f06104346c0b5a.json
deleted file mode 100644
index af2177c8c..000000000
--- a/tests/integration/vector_io/recordings/e05734a51b5ed00dcac0aff27bc28b614936c4454e27d81855f06104346c0b5a.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
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-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
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-        "object": "list",
-        "usage": {
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-    "is_streaming": false
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diff --git a/tests/integration/vector_io/recordings/e19bb342a5817d18312a1d772ff8cb3ea9e67d4dff338329bf3eed04f830e59f.json b/tests/integration/vector_io/recordings/e19bb342a5817d18312a1d772ff8cb3ea9e67d4dff338329bf3eed04f830e59f.json
deleted file mode 100644
index bd8782c6b..000000000
--- a/tests/integration/vector_io/recordings/e19bb342a5817d18312a1d772ff8cb3ea9e67d4dff338329bf3eed04f830e59f.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "The secret string is foobazbar."
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-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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-  "response": {
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diff --git a/tests/integration/vector_io/recordings/e1c0d5d8e1d9b36a58b46785d908a83c1b0ea923d060708382b29ab273069d75.json b/tests/integration/vector_io/recordings/e1c0d5d8e1d9b36a58b46785d908a83c1b0ea923d060708382b29ab273069d75.json
deleted file mode 100644
index 9c1f8c51c..000000000
--- a/tests/integration/vector_io/recordings/e1c0d5d8e1d9b36a58b46785d908a83c1b0ea923d060708382b29ab273069d75.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is batch list test file 1"
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-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/e1c1d3f7b35e7e9d9e70db857a7aaa58004ebb93634739469036487d0f59e359.json b/tests/integration/vector_io/recordings/e1c1d3f7b35e7e9d9e70db857a7aaa58004ebb93634739469036487d0f59e359.json
deleted file mode 100644
index 5a751c186..000000000
--- a/tests/integration/vector_io/recordings/e1c1d3f7b35e7e9d9e70db857a7aaa58004ebb93634739469036487d0f59e359.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is batch list test file 1"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
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diff --git a/tests/integration/vector_io/recordings/e1f83946817b6468faa6b146d57b10a4f965ea010d04c2c6abc96abe4a4341e0.json b/tests/integration/vector_io/recordings/e1f83946817b6468faa6b146d57b10a4f965ea010d04c2c6abc96abe4a4341e0.json
deleted file mode 100644
index 194da7f20..000000000
--- a/tests/integration/vector_io/recordings/e1f83946817b6468faa6b146d57b10a4f965ea010d04c2c6abc96abe4a4341e0.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-    "headers": {},
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-      "model": "nomic-embed-text:latest",
-      "input": [
-        "How do systems learn automatically?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
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diff --git a/tests/integration/vector_io/recordings/e2420f11a4b9fdecb676fd8799ab413bbba50d086ed2b1d1b177f2413bbf06cb.json b/tests/integration/vector_io/recordings/e2420f11a4b9fdecb676fd8799ab413bbba50d086ed2b1d1b177f2413bbf06cb.json
deleted file mode 100644
index 731b9896a..000000000
--- a/tests/integration/vector_io/recordings/e2420f11a4b9fdecb676fd8799ab413bbba50d086ed2b1d1b177f2413bbf06cb.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-  "request": {
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-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "The secret string is foobazbar."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
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-        "object": "list",
-        "usage": {
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diff --git a/tests/integration/vector_io/recordings/e2e6f10d12cce96a5870e05b96e7c569c18d0b751b01d84efb4db76efa7aae1c.json b/tests/integration/vector_io/recordings/e2e6f10d12cce96a5870e05b96e7c569c18d0b751b01d84efb4db76efa7aae1c.json
deleted file mode 100644
index d136efa2f..000000000
--- a/tests/integration/vector_io/recordings/e2e6f10d12cce96a5870e05b96e7c569c18d0b751b01d84efb4db76efa7aae1c.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "What is the capital of France?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/e3e9d55a4d989cec5b3a3194cd539923f7ca38b4d82f7b973662ba644b4b1731.json b/tests/integration/vector_io/recordings/e3e9d55a4d989cec5b3a3194cd539923f7ca38b4d82f7b973662ba644b4b1731.json
deleted file mode 100644
index f65edc428..000000000
--- a/tests/integration/vector_io/recordings/e3e9d55a4d989cec5b3a3194cd539923f7ca38b4d82f7b973662ba644b4b1731.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
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-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/e4ac3142b21f1640f79244721df0b797a7a297a70f2506f83e1d652ff4250c11.json b/tests/integration/vector_io/recordings/e4ac3142b21f1640f79244721df0b797a7a297a70f2506f83e1d652ff4250c11.json
deleted file mode 100644
index bbde28654..000000000
--- a/tests/integration/vector_io/recordings/e4ac3142b21f1640f79244721df0b797a7a297a70f2506f83e1d652ff4250c11.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
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-      "model": "nomic-embed-text:latest",
-      "input": [
-        "This is batch list test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
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diff --git a/tests/integration/vector_io/recordings/e7098721839eb8f15a6dccf1ebf0a1fee344905aca46ad1088debf120e28151f.json b/tests/integration/vector_io/recordings/e7098721839eb8f15a6dccf1ebf0a1fee344905aca46ad1088debf120e28151f.json
deleted file mode 100644
index a01fb55b6..000000000
--- a/tests/integration/vector_io/recordings/e7098721839eb8f15a6dccf1ebf0a1fee344905aca46ad1088debf120e28151f.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_with_max_num_results[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/ec2d107699f7ef0a0e29f5fab3abdca33d1c45d611f6a58ba69bc1e151b7c298.json b/tests/integration/vector_io/recordings/ec2d107699f7ef0a0e29f5fab3abdca33d1c45d611f6a58ba69bc1e151b7c298.json
deleted file mode 100644
index 9d79e58ca..000000000
--- a/tests/integration/vector_io/recordings/ec2d107699f7ef0a0e29f5fab3abdca33d1c45d611f6a58ba69bc1e151b7c298.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/ec4489651d4c52d34dca1c6c303182b1c46c18fa599e61a07d9adb6608ec10cf.json b/tests/integration/vector_io/recordings/ec4489651d4c52d34dca1c6c303182b1c46c18fa599e61a07d9adb6608ec10cf.json
deleted file mode 100644
index 75a29b5e1..000000000
--- a/tests/integration/vector_io/recordings/ec4489651d4c52d34dca1c6c303182b1c46c18fa599e61a07d9adb6608ec10cf.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/ed116c398340b125ae0488108c99a4bfcbc6d42c018afd2a378a2283d3e90293.json b/tests/integration/vector_io/recordings/ed116c398340b125ae0488108c99a4bfcbc6d42c018afd2a378a2283d3e90293.json
deleted file mode 100644
index 31dd61f99..000000000
--- a/tests/integration/vector_io/recordings/ed116c398340b125ae0488108c99a4bfcbc6d42c018afd2a378a2283d3e90293.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/ed11e85201f572a15902bb32f19a7cd21581442421f5818fbee4ac0cb8610fdc.json b/tests/integration/vector_io/recordings/ed11e85201f572a15902bb32f19a7cd21581442421f5818fbee4ac0cb8610fdc.json
deleted file mode 100644
index a25f83a85..000000000
--- a/tests/integration/vector_io/recordings/ed11e85201f572a15902bb32f19a7cd21581442421f5818fbee4ac0cb8610fdc.json
+++ /dev/null
@@ -1,1597 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/ee3f17985b43f36aee4512837c4f3e7dcc5c57f69a06001c325331a9c133d854.json b/tests/integration/vector_io/recordings/ee3f17985b43f36aee4512837c4f3e7dcc5c57f69a06001c325331a9c133d854.json
deleted file mode 100644
index 7d0d644c9..000000000
--- a/tests/integration/vector_io/recordings/ee3f17985b43f36aee4512837c4f3e7dcc5c57f69a06001c325331a9c133d854.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_relevance[openai_client-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384-test_case2]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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diff --git a/tests/integration/vector_io/recordings/ee4aad5aa1b20c8a0118046a0c23a5070fba0e83d0f0c0677a0af67e38b94db7.json b/tests/integration/vector_io/recordings/ee4aad5aa1b20c8a0118046a0c23a5070fba0e83d0f0c0677a0af67e38b94db7.json
deleted file mode 100644
index fa388d30f..000000000
--- a/tests/integration/vector_io/recordings/ee4aad5aa1b20c8a0118046a0c23a5070fba0e83d0f0c0677a0af67e38b94db7.json
+++ /dev/null
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diff --git a/tests/integration/vector_io/recordings/f04cbf93eb979e4da17a7f145a945991ae3dadcefa761f286095fa6751ea5982.json b/tests/integration/vector_io/recordings/f04cbf93eb979e4da17a7f145a945991ae3dadcefa761f286095fa6751ea5982.json
deleted file mode 100644
index a9ab22d3f..000000000
--- a/tests/integration/vector_io/recordings/f04cbf93eb979e4da17a7f145a945991ae3dadcefa761f286095fa6751ea5982.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/f08fedf0fab157c768d61f9bddffd83afae63e25a29f81d96ad93111e24f3d5d.json b/tests/integration/vector_io/recordings/f08fedf0fab157c768d61f9bddffd83afae63e25a29f81d96ad93111e24f3d5d.json
deleted file mode 100644
index 25c593932..000000000
--- a/tests/integration/vector_io/recordings/f08fedf0fab157c768d61f9bddffd83afae63e25a29f81d96ad93111e24f3d5d.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-        "model": "nomic-embed-text:latest",
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diff --git a/tests/integration/vector_io/recordings/f0f122e421432d5cd415ae9303fb4a232cf38865317fc737b7fc6d3ae096bcf0.json b/tests/integration/vector_io/recordings/f0f122e421432d5cd415ae9303fb4a232cf38865317fc737b7fc6d3ae096bcf0.json
deleted file mode 100644
index 01c2c31eb..000000000
--- a/tests/integration/vector_io/recordings/f0f122e421432d5cd415ae9303fb4a232cf38865317fc737b7fc6d3ae096bcf0.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_delete_file_removes_from_vector_store[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "What is the secret string?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
-        "data": [
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diff --git a/tests/integration/vector_io/recordings/f4f3ac9012ca9decf4eeefcef1826bcc2a6c2605fb4e98bff1214e5e2c278bf2.json b/tests/integration/vector_io/recordings/f4f3ac9012ca9decf4eeefcef1826bcc2a6c2605fb4e98bff1214e5e2c278bf2.json
deleted file mode 100644
index d8e7ba23f..000000000
--- a/tests/integration/vector_io/recordings/f4f3ac9012ca9decf4eeefcef1826bcc2a6c2605fb4e98bff1214e5e2c278bf2.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_modes[ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384-vector]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/f5572b0464722c4da947cd504efc5c13f78bf14184b44d9899bc63f1bee469a3.json b/tests/integration/vector_io/recordings/f5572b0464722c4da947cd504efc5c13f78bf14184b44d9899bc63f1bee469a3.json
deleted file mode 100644
index c38952bd3..000000000
--- a/tests/integration/vector_io/recordings/f5572b0464722c4da947cd504efc5c13f78bf14184b44d9899bc63f1bee469a3.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
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-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/f5591b58afc7ca9dcbd4e183cf172e7cba4ff15aca4d4ae3538fc3809d887343.json b/tests/integration/vector_io/recordings/f5591b58afc7ca9dcbd4e183cf172e7cba4ff15aca4d4ae3538fc3809d887343.json
deleted file mode 100644
index 64e84234a..000000000
--- a/tests/integration/vector_io/recordings/f5591b58afc7ca9dcbd4e183cf172e7cba4ff15aca4d4ae3538fc3809d887343.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/f6310cd6ff9871d46ac05441d4b2178dc2fd1f476a1fc213fb6b25c0c6614ed8.json b/tests/integration/vector_io/recordings/f6310cd6ff9871d46ac05441d4b2178dc2fd1f476a1fc213fb6b25c0c6614ed8.json
deleted file mode 100644
index c13880bdd..000000000
--- a/tests/integration/vector_io/recordings/f6310cd6ff9871d46ac05441d4b2178dc2fd1f476a1fc213fb6b25c0c6614ed8.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/f6a8befc1dfce931b48319e478c0286c5fd73de20a28d6991749ef662ab8a99b.json b/tests/integration/vector_io/recordings/f6a8befc1dfce931b48319e478c0286c5fd73de20a28d6991749ef662ab8a99b.json
deleted file mode 100644
index 6adcb4c11..000000000
--- a/tests/integration/vector_io/recordings/f6a8befc1dfce931b48319e478c0286c5fd73de20a28d6991749ef662ab8a99b.json
+++ /dev/null
@@ -1,424 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/f80da05129ad17acd7d68b9d05f19a6dccf6168b61e08df4d21c78a26706aba9.json b/tests/integration/vector_io/recordings/f80da05129ad17acd7d68b9d05f19a6dccf6168b61e08df4d21c78a26706aba9.json
deleted file mode 100644
index 19303c73a..000000000
--- a/tests/integration/vector_io/recordings/f80da05129ad17acd7d68b9d05f19a6dccf6168b61e08df4d21c78a26706aba9.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
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-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
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diff --git a/tests/integration/vector_io/recordings/f882633c629e0de67bbb6e0e259017bfd4e4f9d1273e5f86e8124e2c7a432e7c.json b/tests/integration/vector_io/recordings/f882633c629e0de67bbb6e0e259017bfd4e4f9d1273e5f86e8124e2c7a432e7c.json
deleted file mode 100644
index ebfec5d9e..000000000
--- a/tests/integration/vector_io/recordings/f882633c629e0de67bbb6e0e259017bfd4e4f9d1273e5f86e8124e2c7a432e7c.json
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diff --git a/tests/integration/vector_io/recordings/f8a5d9de7ebe6814941052c1ad263813662dd1091f3641e953e1cb51c5a1b89d.json b/tests/integration/vector_io/recordings/f8a5d9de7ebe6814941052c1ad263813662dd1091f3641e953e1cb51c5a1b89d.json
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diff --git a/tests/integration/vector_io/recordings/f99165b26b3a5a5a54cd682fc4b8cf047c42af8b3cf00744fe637bf98887a651.json b/tests/integration/vector_io/recordings/f99165b26b3a5a5a54cd682fc4b8cf047c42af8b3cf00744fe637bf98887a651.json
deleted file mode 100644
index 3a79d0113..000000000
--- a/tests/integration/vector_io/recordings/f99165b26b3a5a5a54cd682fc4b8cf047c42af8b3cf00744fe637bf98887a651.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-      "input": [
-        "Why are data structures important?"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
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diff --git a/tests/integration/vector_io/recordings/faea76439cc6264c8698d6600868e3ac8519f91ea44acadfefda9429d237297b.json b/tests/integration/vector_io/recordings/faea76439cc6264c8698d6600868e3ac8519f91ea44acadfefda9429d237297b.json
deleted file mode 100644
index d517c96eb..000000000
--- a/tests/integration/vector_io/recordings/faea76439cc6264c8698d6600868e3ac8519f91ea44acadfefda9429d237297b.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_relevance[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384-test_case3]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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diff --git a/tests/integration/vector_io/recordings/faef0ade19907a4e7a2213a329da8427bda7ce266de8a287bfbac5e479614a36.json b/tests/integration/vector_io/recordings/faef0ade19907a4e7a2213a329da8427bda7ce266de8a287bfbac5e479614a36.json
deleted file mode 100644
index e50e01f6e..000000000
--- a/tests/integration/vector_io/recordings/faef0ade19907a4e7a2213a329da8427bda7ce266de8a287bfbac5e479614a36.json
+++ /dev/null
@@ -1,3132 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_relevance[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384-test_case2]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
-  },
-  "response": {
-    "body": {
-      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
-      "__data__": {
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diff --git a/tests/integration/vector_io/recordings/fc60a0ef012b679d9b7c2b5123de5d0acfcce50d895f8de56e3be427835367df.json b/tests/integration/vector_io/recordings/fc60a0ef012b679d9b7c2b5123de5d0acfcce50d895f8de56e3be427835367df.json
deleted file mode 100644
index d2023a563..000000000
--- a/tests/integration/vector_io/recordings/fc60a0ef012b679d9b7c2b5123de5d0acfcce50d895f8de56e3be427835367df.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-      "input": [
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-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/fc8463ac462290132db1a78f4fecfb78a851d020960650bd978a28a77393c930.json b/tests/integration/vector_io/recordings/fc8463ac462290132db1a78f4fecfb78a851d020960650bd978a28a77393c930.json
deleted file mode 100644
index 16d988768..000000000
--- a/tests/integration/vector_io/recordings/fc8463ac462290132db1a78f4fecfb78a851d020960650bd978a28a77393c930.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/fdc83e55516f8952cf4a1f7941d8fb3281b2b3e0a071188cd1061db60f834d75.json b/tests/integration/vector_io/recordings/fdc83e55516f8952cf4a1f7941d8fb3281b2b3e0a071188cd1061db60f834d75.json
deleted file mode 100644
index d000809df..000000000
--- a/tests/integration/vector_io/recordings/fdc83e55516f8952cf4a1f7941d8fb3281b2b3e0a071188cd1061db60f834d75.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:137m-v1.5-fp16",
-      "input": [
-        "This is a test file 0"
-      ],
-      "encoding_format": "float"
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-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:137m-v1.5-fp16"
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diff --git a/tests/integration/vector_io/recordings/ff718a6f3d9e91eb043c7a47e23b0fc9131466b0fd083a365e8f5ef1532ed1b0.json b/tests/integration/vector_io/recordings/ff718a6f3d9e91eb043c7a47e23b0fc9131466b0fd083a365e8f5ef1532ed1b0.json
deleted file mode 100644
index 81f211091..000000000
--- a/tests/integration/vector_io/recordings/ff718a6f3d9e91eb043c7a47e23b0fc9131466b0fd083a365e8f5ef1532ed1b0.json
+++ /dev/null
@@ -1,1596 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_vector_io.py::test_insert_chunks[emb=ollama/all-minilm:l6-v2:dim=384-test_case4]",
-  "request": {
-    "method": "POST",
-    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "Python is a high-level programming language that emphasizes code readability and allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.",
-        "Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using statistical techniques to give computer systems the ability to progressively improve performance on a specific task.",
-        "Data structures are fundamental to computer science because they provide organized ways to store and access data efficiently, enable faster processing of data through optimized algorithms, and form the building blocks for more complex software systems.",
-        "Neural networks are inspired by biological neural networks found in animal brains, using interconnected nodes called artificial neurons to process information through weighted connections that can be trained to recognize patterns and solve complex problems through iterative learning."
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
-  },
-  "response": {
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diff --git a/tests/integration/vector_io/recordings/ffad66213dc60515c008de1571d5f4a4381b836ad7199e1ad3c1fce2043df1f6.json b/tests/integration/vector_io/recordings/ffad66213dc60515c008de1571d5f4a4381b836ad7199e1ad3c1fce2043df1f6.json
deleted file mode 100644
index cf1db1486..000000000
--- a/tests/integration/vector_io/recordings/ffad66213dc60515c008de1571d5f4a4381b836ad7199e1ad3c1fce2043df1f6.json
+++ /dev/null
@@ -1,807 +0,0 @@
-{
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-  "request": {
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-    "headers": {},
-    "body": {
-      "model": "nomic-embed-text:latest",
-      "input": [
-        "Python is a high-level programming language with code readability and fewer lines than C++ or Java"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "nomic-embed-text:latest"
-  },
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diff --git a/tests/integration/vector_io/recordings/ffc3abdebf6940d1c864b76a7025a61de2a37f349aa6560bb45ac9c96e165aa0.json b/tests/integration/vector_io/recordings/ffc3abdebf6940d1c864b76a7025a61de2a37f349aa6560bb45ac9c96e165aa0.json
deleted file mode 100644
index 348875a88..000000000
--- a/tests/integration/vector_io/recordings/ffc3abdebf6940d1c864b76a7025a61de2a37f349aa6560bb45ac9c96e165aa0.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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-    "headers": {},
-    "body": {
-      "model": "all-minilm:l6-v2",
-      "input": [
-        "This is a test file 0"
-      ],
-      "encoding_format": "float"
-    },
-    "endpoint": "/v1/embeddings",
-    "model": "all-minilm:l6-v2"
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diff --git a/tests/integration/vector_io/recordings/ffcb543b4e9aa0fe18ad6d42b4664264a6273bfff1a2b18261ccccba92dcc655.json b/tests/integration/vector_io/recordings/ffcb543b4e9aa0fe18ad6d42b4664264a6273bfff1a2b18261ccccba92dcc655.json
deleted file mode 100644
index e91f18daa..000000000
--- a/tests/integration/vector_io/recordings/ffcb543b4e9aa0fe18ad6d42b4664264a6273bfff1a2b18261ccccba92dcc655.json
+++ /dev/null
@@ -1,423 +0,0 @@
-{
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diff --git a/tests/integration/vector_io/recordings/ffea5475c2625b87e302ec419cc536f34da3ce7e80eba86bec16d231aa347d00.json b/tests/integration/vector_io/recordings/ffea5475c2625b87e302ec419cc536f34da3ce7e80eba86bec16d231aa347d00.json
deleted file mode 100644
index 8e0f19be1..000000000
--- a/tests/integration/vector_io/recordings/ffea5475c2625b87e302ec419cc536f34da3ce7e80eba86bec16d231aa347d00.json
+++ /dev/null
@@ -1,75 +0,0 @@
-{
-  "test_id": "tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_file_batch_create_and_retrieve[client_with_models-ollama/llama3.2:3b-instruct-fp16-None-ollama/all-minilm:l6-v2-None-384]",
-  "request": {
-    "method": "POST",
-    "url": "http://localhost:11434/api/ps",
-    "headers": {},
-    "body": {},
-    "endpoint": "/api/ps",
-    "model": ""
-  },
-  "response": {
-    "body": {
-      "__type__": "ollama._types.ProcessResponse",
-      "__data__": {
-        "models": [
-          {
-            "model": "llama3.2:3b",
-            "name": "llama3.2:3b",
-            "digest": "a80c4f17acd55265feec403c7aef86be0c25983ab279d83f3bcd3abbcb5b8b72",
-            "expires_at": "2025-10-08T16:14:05.423042-07:00",
-            "size": 3367856128,
-            "size_vram": 3367856128,
-            "details": {
-              "parent_model": "",
-              "format": "gguf",
-              "family": "llama",
-              "families": [
-                "llama"
-              ],
-              "parameter_size": "3.2B",
-              "quantization_level": "Q4_K_M"
-            }
-          },
-          {
-            "model": "nomic-embed-text:latest",
-            "name": "nomic-embed-text:latest",
-            "digest": "0a109f422b47e3a30ba2b10eca18548e944e8a23073ee3f3e947efcf3c45e59f",
-            "expires_at": "2025-10-08T11:32:17.559903-07:00",
-            "size": 848677888,
-            "size_vram": 848677888,
-            "details": {
-              "parent_model": "",
-              "format": "gguf",
-              "family": "nomic-bert",
-              "families": [
-                "nomic-bert"
-              ],
-              "parameter_size": "137M",
-              "quantization_level": "F16"
-            }
-          },
-          {
-            "model": "llama-guard3:1b",
-            "name": "llama-guard3:1b",
-            "digest": "494147e06bf99e10dbe67b63a07ac81c162f18ef3341aa3390007ac828571b3b",
-            "expires_at": "2025-10-08T11:30:00.392919-07:00",
-            "size": 2350966784,
-            "size_vram": 2350966784,
-            "details": {
-              "parent_model": "",
-              "format": "gguf",
-              "family": "llama",
-              "families": [
-                "llama"
-              ],
-              "parameter_size": "1.5B",
-              "quantization_level": "Q8_0"
-            }
-          }
-        ]
-      }
-    },
-    "is_streaming": false
-  }
-}