feat(testing): remove SQLite dependency from inference recorder (#3254)

Recording files use a predictable naming format, making the SQLite index
redundant. The binary SQLite file was causing frequent git conflicts.
Simplify by calculating file paths directly from request hashes.

Signed-off-by: Derek Higgins <derekh@redhat.com>

llama_stack/testing/inference_recorder.py

@@ -9,7 +9,6 @@ from __future__ import annotations  # for forward references
 import hashlib
 import json
 import os
-import sqlite3
 from collections.abc import Generator
 from contextlib import contextmanager
 from enum import StrEnum
@@ -125,28 +124,13 @@ class ResponseStorage:
     def __init__(self, test_dir: Path):
         self.test_dir = test_dir
         self.responses_dir = self.test_dir / "responses"
-        self.db_path = self.test_dir / "index.sqlite"
 
         self._ensure_directories()
-        self._init_database()
 
     def _ensure_directories(self):
         self.test_dir.mkdir(parents=True, exist_ok=True)
         self.responses_dir.mkdir(exist_ok=True)
 
-    def _init_database(self):
-        with sqlite3.connect(self.db_path) as conn:
-            conn.execute("""
-                CREATE TABLE IF NOT EXISTS recordings (
-                    request_hash TEXT PRIMARY KEY,
-                    response_file TEXT,
-                    endpoint TEXT,
-                    model TEXT,
-                    timestamp TEXT,
-                    is_streaming BOOLEAN
-                )
-            """)
-
     def store_recording(self, request_hash: str, request: dict[str, Any], response: dict[str, Any]):
         """Store a request/response pair."""
         # Generate unique response filename
@@ -169,34 +153,9 @@ class ResponseStorage:
             f.write("\n")
             f.flush()
 
-        # Update SQLite index
-        with sqlite3.connect(self.db_path) as conn:
-            conn.execute(
-                """
-                INSERT OR REPLACE INTO recordings
-                (request_hash, response_file, endpoint, model, timestamp, is_streaming)
-                VALUES (?, ?, ?, ?, datetime('now'), ?)
-            """,
-                (
-                    request_hash,
-                    response_file,
-                    request.get("endpoint", ""),
-                    request.get("model", ""),
-                    response.get("is_streaming", False),
-                ),
-            )
-
     def find_recording(self, request_hash: str) -> dict[str, Any] | None:
         """Find a recorded response by request hash."""
-        with sqlite3.connect(self.db_path) as conn:
-            result = conn.execute(
-                "SELECT response_file FROM recordings WHERE request_hash = ?", (request_hash,)
-            ).fetchone()
-
-        if not result:
-            return None
-
-        response_file = result[0]
+        response_file = f"{request_hash[:12]}.json"
         response_path = self.responses_dir / response_file
 
         if not response_path.exists():

tests/unit/distribution/test_inference_recordings.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import sqlite3
 import tempfile
 from pathlib import Path
 from unittest.mock import patch
@@ -133,7 +132,6 @@ class TestInferenceRecording:
         # Test directory creation
         assert storage.test_dir.exists()
         assert storage.responses_dir.exists()
-        assert storage.db_path.exists()
 
         # Test storing and retrieving a recording
         request_hash = "test_hash_123"
@@ -147,15 +145,6 @@ class TestInferenceRecording:
 
         storage.store_recording(request_hash, request_data, response_data)
 
-        # Verify SQLite record
-        with sqlite3.connect(storage.db_path) as conn:
-            result = conn.execute("SELECT * FROM recordings WHERE request_hash = ?", (request_hash,)).fetchone()
-
-        assert result is not None
-        assert result[0] == request_hash  # request_hash
-        assert result[2] == "/v1/chat/completions"  # endpoint
-        assert result[3] == "llama3.2:3b"  # model
-
         # Verify file storage and retrieval
         retrieved = storage.find_recording(request_hash)
         assert retrieved is not None
@@ -185,10 +174,7 @@ class TestInferenceRecording:
 
         # Verify recording was stored
         storage = ResponseStorage(temp_storage_dir)
-        with sqlite3.connect(storage.db_path) as conn:
-            recordings = conn.execute("SELECT COUNT(*) FROM recordings").fetchone()[0]
-
-        assert recordings == 1
+        assert storage.responses_dir.exists()
 
     async def test_replay_mode(self, temp_storage_dir, real_openai_chat_response):
         """Test that replay mode returns stored responses without making real calls."""