Merge branch 'main' into prompt-api

.github/actions/run-and-record-tests/action.yml

@@ -2,13 +2,6 @@ name: 'Run and Record Tests'
 description: 'Run integration tests and handle recording/artifact upload'
 
 inputs:
-  test-subdirs:
-    description: 'Comma-separated list of test subdirectories to run'
-    required: true
-  test-pattern:
-    description: 'Regex pattern to pass to pytest -k'
-    required: false
-    default: ''
   stack-config:
     description: 'Stack configuration to use'
     required: true
@@ -18,10 +11,18 @@ inputs:
   inference-mode:
     description: 'Inference mode (record or replay)'
     required: true
-  run-vision-tests:
-    description: 'Whether to run vision tests'
+  test-suite:
+    description: 'Test suite to use: base, responses, vision, etc.'
     required: false
-    default: 'false'
+    default: ''
+  test-subdirs:
+    description: 'Comma-separated list of test subdirectories to run; overrides test-suite'
+    required: false
+    default: ''
+  test-pattern:
+    description: 'Regex pattern to pass to pytest -k'
+    required: false
+    default: ''
 
 runs:
   using: 'composite'
@@ -42,7 +43,7 @@ runs:
           --test-subdirs '${{ inputs.test-subdirs }}' \
           --test-pattern '${{ inputs.test-pattern }}' \
           --inference-mode '${{ inputs.inference-mode }}' \
-          ${{ inputs.run-vision-tests == 'true' && '--run-vision-tests' || '' }} \
+          --test-suite '${{ inputs.test-suite }}' \
           | tee pytest-${{ inputs.inference-mode }}.log
 
 
@@ -57,12 +58,7 @@ runs:
           echo "New recordings detected, committing and pushing"
           git add tests/integration/recordings/
 
-          if [ "${{ inputs.run-vision-tests }}" == "true" ]; then
-            git commit -m "Recordings update from CI (vision)"
-          else
-            git commit -m "Recordings update from CI"
-          fi
-
+          git commit -m "Recordings update from CI (test-suite: ${{ inputs.test-suite }})"
           git fetch origin ${{ github.ref_name }}
           git rebase origin/${{ github.ref_name }}
           echo "Rebased successfully"

.github/actions/setup-ollama/action.yml

@@ -1,17 +1,17 @@
 name: Setup Ollama
 description: Start Ollama
 inputs:
-  run-vision-tests:
-    description: 'Run vision tests: "true" or "false"'
+  test-suite:
+    description: 'Test suite to use: base, responses, vision, etc.'
     required: false
-    default: 'false'
+    default: ''
 runs:
   using: "composite"
   steps:
     - name: Start Ollama
       shell: bash
       run: |
-        if [ "${{ inputs.run-vision-tests }}" == "true" ]; then
+        if [ "${{ inputs.test-suite }}" == "vision" ]; then
           image="ollama-with-vision-model"
         else
           image="ollama-with-models"

.github/actions/setup-test-environment/action.yml

@@ -12,10 +12,10 @@ inputs:
     description: 'Provider to setup (ollama or vllm)'
     required: true
     default: 'ollama'
-  run-vision-tests:
-    description: 'Whether to setup provider for vision tests'
+  test-suite:
+    description: 'Test suite to use: base, responses, vision, etc.'
     required: false
-    default: 'false'
+    default: ''
   inference-mode:
     description: 'Inference mode (record or replay)'
     required: true
@@ -33,7 +33,7 @@ runs:
       if: ${{ inputs.provider == 'ollama' && inputs.inference-mode == 'record' }}
       uses: ./.github/actions/setup-ollama
       with:
-        run-vision-tests: ${{ inputs.run-vision-tests }}
+        test-suite: ${{ inputs.test-suite }}
 
     - name: Setup vllm
       if: ${{ inputs.provider == 'vllm' && inputs.inference-mode == 'record' }}

.github/workflows/README.md

@@ -8,7 +8,7 @@ Llama Stack uses GitHub Actions for Continuous Integration (CI). Below is a tabl
 | Installer CI | [install-script-ci.yml](install-script-ci.yml) | Test the installation script |
 | Integration Auth Tests | [integration-auth-tests.yml](integration-auth-tests.yml) | Run the integration test suite with Kubernetes authentication |
 | SqlStore Integration Tests | [integration-sql-store-tests.yml](integration-sql-store-tests.yml) | Run the integration test suite with SqlStore |
-| Integration Tests (Replay) | [integration-tests.yml](integration-tests.yml) | Run the integration test suite from tests/integration in replay mode |
+| Integration Tests (Replay) | [integration-tests.yml](integration-tests.yml) | Run the integration test suites from tests/integration in replay mode |
 | Vector IO Integration Tests | [integration-vector-io-tests.yml](integration-vector-io-tests.yml) | Run the integration test suite with various VectorIO providers |
 | Pre-commit | [pre-commit.yml](pre-commit.yml) | Run pre-commit checks |
 | Test Llama Stack Build | [providers-build.yml](providers-build.yml) | Test llama stack build |

.github/workflows/integration-tests.yml

@@ -1,6 +1,6 @@
 name: Integration Tests (Replay)
 
-run-name: Run the integration test suite from tests/integration in replay mode
+run-name: Run the integration test suites from tests/integration in replay mode
 
 on:
   push:
@@ -32,14 +32,6 @@ on:
         description: 'Test against a specific provider'
         type: string
         default: 'ollama'
-      test-subdirs:
-        description: 'Comma-separated list of test subdirectories to run'
-        type: string
-        default: ''
-      test-pattern:
-        description: 'Regex pattern to pass to pytest -k'
-        type: string
-        default: ''
 
 concurrency:
   # Skip concurrency for pushes to main - each commit should be tested independently
@@ -50,7 +42,7 @@ jobs:
 
   run-replay-mode-tests:
     runs-on: ubuntu-latest
-    name: ${{ format('Integration Tests ({0}, {1}, {2}, client={3}, vision={4})', matrix.client-type, matrix.provider, matrix.python-version, matrix.client-version, matrix.run-vision-tests) }}
+    name: ${{ format('Integration Tests ({0}, {1}, {2}, client={3}, {4})', matrix.client-type, matrix.provider, matrix.python-version, matrix.client-version, matrix.test-suite) }}
 
     strategy:
       fail-fast: false
@@ -61,7 +53,7 @@ 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"]') }}
-        run-vision-tests: [true, false]
+        test-suite: [base, vision]
 
     steps:
       - name: Checkout repository
@@ -73,15 +65,13 @@ jobs:
           python-version: ${{ matrix.python-version }}
           client-version: ${{ matrix.client-version }}
           provider: ${{ matrix.provider }}
-          run-vision-tests: ${{ matrix.run-vision-tests }}
+          test-suite: ${{ matrix.test-suite }}
           inference-mode: 'replay'
 
       - name: Run tests
         uses: ./.github/actions/run-and-record-tests
         with:
-          test-subdirs: ${{ inputs.test-subdirs }}
-          test-pattern: ${{ inputs.test-pattern }}
           stack-config: ${{ matrix.client-type == 'library' && 'ci-tests' || 'server:ci-tests' }}
           provider: ${{ matrix.provider }}
           inference-mode: 'replay'
-          run-vision-tests: ${{ matrix.run-vision-tests }}
+          test-suite: ${{ matrix.test-suite }}

.github/workflows/record-integration-tests.yml

@@ -10,18 +10,18 @@ run-name: Run the integration test suite from tests/integration
 on:
   workflow_dispatch:
     inputs:
-      test-subdirs:
-        description: 'Comma-separated list of test subdirectories to run'
-        type: string
-        default: ''
       test-provider:
         description: 'Test against a specific provider'
         type: string
         default: 'ollama'
-      run-vision-tests:
-        description: 'Whether to run vision tests'
-        type: boolean
-        default: false
+      test-suite:
+        description: 'Test suite to use: base, responses, vision, etc.'
+        type: string
+        default: ''
+      test-subdirs:
+        description: 'Comma-separated list of test subdirectories to run; overrides test-suite'
+        type: string
+        default: ''
       test-pattern:
         description: 'Regex pattern to pass to pytest -k'
         type: string
@@ -38,11 +38,11 @@ jobs:
       - name: Echo workflow inputs
         run: |
           echo "::group::Workflow Inputs"
-          echo "test-subdirs: ${{ inputs.test-subdirs }}"
-          echo "test-provider: ${{ inputs.test-provider }}"
-          echo "run-vision-tests: ${{ inputs.run-vision-tests }}"
-          echo "test-pattern: ${{ inputs.test-pattern }}"
           echo "branch: ${{ github.ref_name }}"
+          echo "test-provider: ${{ inputs.test-provider }}"
+          echo "test-suite: ${{ inputs.test-suite }}"
+          echo "test-subdirs: ${{ inputs.test-subdirs }}"
+          echo "test-pattern: ${{ inputs.test-pattern }}"
           echo "::endgroup::"
 
       - name: Checkout repository
@@ -56,15 +56,15 @@ jobs:
           python-version: "3.12"  # Use single Python version for recording
           client-version: "latest"
           provider: ${{ inputs.test-provider || 'ollama' }}
-          run-vision-tests: ${{ inputs.run-vision-tests }}
+          test-suite: ${{ inputs.test-suite }}
           inference-mode: 'record'
 
       - name: Run and record tests
         uses: ./.github/actions/run-and-record-tests
         with:
-          test-pattern: ${{ inputs.test-pattern }}
-          test-subdirs: ${{ inputs.test-subdirs }}
           stack-config: 'server:ci-tests'  # recording must be done with server since more tests are run
           provider: ${{ inputs.test-provider || 'ollama' }}
           inference-mode: 'record'
-          run-vision-tests: ${{ inputs.run-vision-tests }}
+          test-suite: ${{ inputs.test-suite }}
+          test-subdirs: ${{ inputs.test-subdirs }}
+          test-pattern: ${{ inputs.test-pattern }}

llama_stack/core/routing_tables/vector_dbs.py

@@ -52,7 +52,6 @@ class VectorDBsRoutingTable(CommonRoutingTableImpl, VectorDBs):
         provider_vector_db_id: str | None = None,
         vector_db_name: str | None = None,
     ) -> VectorDB:
-        provider_vector_db_id = provider_vector_db_id or vector_db_id
         if provider_id is None:
             if len(self.impls_by_provider_id) > 0:
                 provider_id = list(self.impls_by_provider_id.keys())[0]
@@ -69,14 +68,33 @@ class VectorDBsRoutingTable(CommonRoutingTableImpl, VectorDBs):
             raise ModelTypeError(embedding_model, model.model_type, ModelType.embedding)
         if "embedding_dimension" not in model.metadata:
             raise ValueError(f"Model {embedding_model} does not have an embedding dimension")
+
+        provider = self.impls_by_provider_id[provider_id]
+        logger.warning(
+            "VectorDB is being deprecated in future releases in favor of VectorStore. Please migrate your usage accordingly."
+        )
+        vector_store = await provider.openai_create_vector_store(
+            name=vector_db_name or vector_db_id,
+            embedding_model=embedding_model,
+            embedding_dimension=model.metadata["embedding_dimension"],
+            provider_id=provider_id,
+            provider_vector_db_id=provider_vector_db_id,
+        )
+
+        vector_store_id = vector_store.id
+        actual_provider_vector_db_id = provider_vector_db_id or vector_store_id
+        logger.warning(
+            f"Ignoring vector_db_id {vector_db_id} and using vector_store_id {vector_store_id} instead. Setting VectorDB {vector_db_id} to VectorDB.vector_db_name"
+        )
+
         vector_db_data = {
-            "identifier": vector_db_id,
+            "identifier": vector_store_id,
             "type": ResourceType.vector_db.value,
             "provider_id": provider_id,
-            "provider_resource_id": provider_vector_db_id,
+            "provider_resource_id": actual_provider_vector_db_id,
             "embedding_model": embedding_model,
             "embedding_dimension": model.metadata["embedding_dimension"],
-            "vector_db_name": vector_db_name,
+            "vector_db_name": vector_store.name,
         }
         vector_db = TypeAdapter(VectorDBWithOwner).validate_python(vector_db_data)
         await self.register_object(vector_db)

llama_stack/providers/inline/batches/reference/batches.py

@@ -178,9 +178,9 @@ class ReferenceBatchesImpl(Batches):
 
         # TODO: set expiration time for garbage collection
 
-        if endpoint not in ["/v1/chat/completions"]:
+        if endpoint not in ["/v1/chat/completions", "/v1/completions"]:
             raise ValueError(
-                f"Invalid endpoint: {endpoint}. Supported values: /v1/chat/completions. Code: invalid_value. Param: endpoint",
+                f"Invalid endpoint: {endpoint}. Supported values: /v1/chat/completions, /v1/completions. Code: invalid_value. Param: endpoint",
             )
 
         if completion_window != "24h":
@@ -424,13 +424,21 @@ class ReferenceBatchesImpl(Batches):
                             )
                             valid = False
 
-                        for param, expected_type, type_string in [
+                        if batch.endpoint == "/v1/chat/completions":
+                            required_params = [
                                 ("model", str, "a string"),
                                 # messages is specific to /v1/chat/completions
                                 # we could skip validating messages here and let inference fail. however,
                                 # that would be a very expensive way to find out messages is wrong.
                                 ("messages", list, "an array"),  # TODO: allow messages to be a string?
-                        ]:
+                            ]
+                        else:  # /v1/completions
+                            required_params = [
+                                ("model", str, "a string"),
+                                ("prompt", str, "a string"),  # TODO: allow prompt to be a list of strings??
+                            ]
+
+                        for param, expected_type, type_string in required_params:
                             if param not in body:
                                 errors.append(
                                     BatchError(
@@ -591,6 +599,7 @@ class ReferenceBatchesImpl(Batches):
 
         try:
             # TODO(SECURITY): review body for security issues
+            if request.url == "/v1/chat/completions":
                 request.body["messages"] = [convert_to_openai_message_param(msg) for msg in request.body["messages"]]
                 chat_response = await self.inference_api.openai_chat_completion(**request.body)
 
@@ -605,6 +614,22 @@ class ReferenceBatchesImpl(Batches):
                         "body": chat_response.model_dump_json(),
                     },
                 }
+            else:  # /v1/completions
+                completion_response = await self.inference_api.openai_completion(**request.body)
+
+                # this is for mypy, we don't allow streaming so we'll get the right type
+                assert hasattr(completion_response, "model_dump_json"), (
+                    "Completion response must have model_dump_json method"
+                )
+                return {
+                    "id": request_id,
+                    "custom_id": request.custom_id,
+                    "response": {
+                        "status_code": 200,
+                        "request_id": request_id,
+                        "body": completion_response.model_dump_json(),
+                    },
+                }
         except Exception as e:
             logger.info(f"Error processing request {request.custom_id} in batch {batch_id}: {e}")
             return {

scripts/github/schedule-record-workflow.sh

@@ -15,7 +15,7 @@ set -euo pipefail
 BRANCH=""
 TEST_SUBDIRS=""
 TEST_PROVIDER="ollama"
-RUN_VISION_TESTS=false
+TEST_SUITE="base"
 TEST_PATTERN=""
 
 # Help function
@@ -27,9 +27,9 @@ Trigger the integration test recording workflow remotely. This way you do not ne
 
 OPTIONS:
     -b, --branch BRANCH         Branch to run the workflow on (defaults to current branch)
-    -s, --test-subdirs DIRS     Comma-separated list of test subdirectories to run (REQUIRED)
     -p, --test-provider PROVIDER Test provider to use: vllm or ollama (default: ollama)
-    -v, --run-vision-tests      Include vision tests in the recording
+    -t, --test-suite SUITE      Test suite to use: base, responses, vision, etc. (default: base)
+    -s, --test-subdirs DIRS     Comma-separated list of test subdirectories to run (overrides suite)
     -k, --test-pattern PATTERN  Regex pattern to pass to pytest -k
     -h, --help                  Show this help message
 
@@ -38,7 +38,7 @@ EXAMPLES:
     $0 --test-subdirs "agents"
 
     # Record tests for specific branch with vision tests
-    $0 -b my-feature-branch --test-subdirs "inference" --run-vision-tests
+    $0 -b my-feature-branch --test-suite vision
 
     # Record multiple test subdirectories with specific provider
     $0 --test-subdirs "agents,inference" --test-provider vllm
@@ -71,9 +71,9 @@ while [[ $# -gt 0 ]]; do
             TEST_PROVIDER="$2"
             shift 2
             ;;
-        -v|--run-vision-tests)
-            RUN_VISION_TESTS=true
-            shift
+        -t|--test-suite)
+            TEST_SUITE="$2"
+            shift 2
             ;;
         -k|--test-pattern)
             TEST_PATTERN="$2"
@@ -92,11 +92,11 @@ while [[ $# -gt 0 ]]; do
 done
 
 # Validate required parameters
-if [[ -z "$TEST_SUBDIRS" ]]; then
-    echo "Error: --test-subdirs is required"
-    echo "Please specify which test subdirectories to run, e.g.:"
+if [[ -z "$TEST_SUBDIRS" && -z "$TEST_SUITE" ]]; then
+    echo "Error: --test-subdirs or --test-suite is required"
+    echo "Please specify which test subdirectories to run or test suite to use, e.g.:"
     echo "  $0 --test-subdirs \"agents,inference\""
-    echo "  $0 --test-subdirs \"inference\" --run-vision-tests"
+    echo "  $0 --test-suite vision"
     echo ""
     exit 1
 fi
@@ -239,17 +239,19 @@ echo "Triggering integration test recording workflow..."
 echo "Branch: $BRANCH"
 echo "Test provider: $TEST_PROVIDER"
 echo "Test subdirs: $TEST_SUBDIRS"
-echo "Run vision tests: $RUN_VISION_TESTS"
+echo "Test suite: $TEST_SUITE"
 echo "Test pattern: ${TEST_PATTERN:-"(none)"}"
 echo ""
 
 # Prepare inputs for gh workflow run
+if [[ -n "$TEST_SUBDIRS" ]]; then
     INPUTS="-f test-subdirs='$TEST_SUBDIRS'"
+fi
 if [[ -n "$TEST_PROVIDER" ]]; then
     INPUTS="$INPUTS -f test-provider='$TEST_PROVIDER'"
 fi
-if [[ "$RUN_VISION_TESTS" == "true" ]]; then
-    INPUTS="$INPUTS -f run-vision-tests=true"
+if [[ -n "$TEST_SUITE" ]]; then
+    INPUTS="$INPUTS -f test-suite='$TEST_SUITE'"
 fi
 if [[ -n "$TEST_PATTERN" ]]; then
     INPUTS="$INPUTS -f test-pattern='$TEST_PATTERN'"

scripts/integration-tests.sh

@@ -16,7 +16,7 @@ STACK_CONFIG=""
 PROVIDER=""
 TEST_SUBDIRS=""
 TEST_PATTERN=""
-RUN_VISION_TESTS="false"
+TEST_SUITE="base"
 INFERENCE_MODE="replay"
 EXTRA_PARAMS=""
 
@@ -28,12 +28,16 @@ Usage: $0 [OPTIONS]
 Options:
     --stack-config STRING    Stack configuration to use (required)
     --provider STRING        Provider to use (ollama, vllm, etc.) (required)
-    --test-subdirs STRING    Comma-separated list of test subdirectories to run (default: 'inference')
-    --run-vision-tests       Run vision tests instead of regular tests
+    --test-suite STRING      Comma-separated list of test suites to run (default: 'base')
     --inference-mode STRING  Inference mode: record or replay (default: replay)
+    --test-subdirs STRING    Comma-separated list of test subdirectories to run (overrides suite)
     --test-pattern STRING    Regex pattern to pass to pytest -k
     --help                   Show this help message
 
+Suites are defined in tests/integration/suites.py. They are used to narrow the collection of tests and provide default model options.
+
+You can also specify subdirectories (of tests/integration) to select tests from, which will override the suite.
+
 Examples:
     # Basic inference tests with ollama
     $0 --stack-config server:ci-tests --provider ollama
@@ -42,7 +46,7 @@ Examples:
     $0 --stack-config server:ci-tests --provider vllm --test-subdirs 'inference,agents'
 
     # Vision tests with ollama
-    $0 --stack-config server:ci-tests --provider ollama --run-vision-tests
+    $0 --stack-config server:ci-tests --provider ollama --test-suite vision
 
     # Record mode for updating test recordings
     $0 --stack-config server:ci-tests --provider ollama --inference-mode record
@@ -64,9 +68,9 @@ while [[ $# -gt 0 ]]; do
             TEST_SUBDIRS="$2"
             shift 2
             ;;
-        --run-vision-tests)
-            RUN_VISION_TESTS="true"
-            shift
+        --test-suite)
+            TEST_SUITE="$2"
+            shift 2
             ;;
         --inference-mode)
             INFERENCE_MODE="$2"
@@ -92,22 +96,25 @@ done
 # Validate required parameters
 if [[ -z "$STACK_CONFIG" ]]; then
     echo "Error: --stack-config is required"
-    usage
     exit 1
 fi
 
 if [[ -z "$PROVIDER" ]]; then
     echo "Error: --provider is required"
-    usage
+    exit 1
+fi
+
+if [[ -z "$TEST_SUITE" && -z "$TEST_SUBDIRS" ]]; then
+    echo "Error: --test-suite or --test-subdirs is required"
     exit 1
 fi
 
 echo "=== Llama Stack Integration Test Runner ==="
 echo "Stack Config: $STACK_CONFIG"
 echo "Provider: $PROVIDER"
-echo "Test Subdirs: $TEST_SUBDIRS"
-echo "Vision Tests: $RUN_VISION_TESTS"
 echo "Inference Mode: $INFERENCE_MODE"
+echo "Test Suite: $TEST_SUITE"
+echo "Test Subdirs: $TEST_SUBDIRS"
 echo "Test Pattern: $TEST_PATTERN"
 echo ""
 
@@ -194,56 +201,12 @@ if [[ -n "$TEST_PATTERN" ]]; then
     PYTEST_PATTERN="${PYTEST_PATTERN} and $TEST_PATTERN"
 fi
 
-# Run vision tests if specified
-if [[ "$RUN_VISION_TESTS" == "true" ]]; then
-    echo "Running vision tests..."
-    set +e
-    pytest -s -v tests/integration/inference/test_vision_inference.py \
-        --stack-config="$STACK_CONFIG" \
-        -k "$PYTEST_PATTERN" \
-        --vision-model=ollama/llama3.2-vision:11b \
-        --embedding-model=sentence-transformers/all-MiniLM-L6-v2 \
-        --color=yes $EXTRA_PARAMS \
-        --capture=tee-sys
-    exit_code=$?
-    set -e
-
-    if [ $exit_code -eq 0 ]; then
-        echo "✅ Vision tests completed successfully"
-    elif [ $exit_code -eq 5 ]; then
-        echo "⚠️ No vision tests collected (pattern matched no tests)"
-    else
-        echo "❌ Vision tests failed"
-        exit 1
-    fi
-    exit 0
-fi
-
-# Run regular tests
-if [[ -z "$TEST_SUBDIRS" ]]; then
-   TEST_SUBDIRS=$(find tests/integration -maxdepth 1 -mindepth 1 -type d |
-            sed 's|tests/integration/||' |
-            grep -Ev "^(__pycache__|fixtures|test_cases|recordings|non_ci|post_training)$" |
-            sort)
-fi
 echo "Test subdirs to run: $TEST_SUBDIRS"
 
+if [[ -n "$TEST_SUBDIRS" ]]; then
     # Collect all test files for the specified test types
     TEST_FILES=""
     for test_subdir in $(echo "$TEST_SUBDIRS" | tr ',' '\n'); do
-    # Skip certain test types for vllm provider
-    if [[ "$PROVIDER" == "vllm" ]]; then
-        if [[ "$test_subdir" == "safety" ]] || [[ "$test_subdir" == "post_training" ]] || [[ "$test_subdir" == "tool_runtime" ]]; then
-            echo "Skipping $test_subdir for vllm provider"
-            continue
-        fi
-    fi
-
-    if [[ "$STACK_CONFIG" != *"server:"* ]] && [[ "$test_subdir" == "batches" ]]; then
-        echo "Skipping $test_subdir for library client until types are supported"
-        continue
-    fi
-
         if [[ -d "tests/integration/$test_subdir" ]]; then
             # Find all Python test files in this directory
             test_files=$(find tests/integration/$test_subdir -name "test_*.py" -o -name "*_test.py")
@@ -265,13 +228,19 @@ echo ""
     echo "=== Running all collected tests in a single pytest command ==="
     echo "Total test files: $(echo $TEST_FILES | wc -w)"
 
+    PYTEST_TARGET="$TEST_FILES"
+    EXTRA_PARAMS="$EXTRA_PARAMS --text-model=$TEXT_MODEL --embedding-model=sentence-transformers/all-MiniLM-L6-v2"
+else
+    PYTEST_TARGET="tests/integration/"
+    EXTRA_PARAMS="$EXTRA_PARAMS --suite=$TEST_SUITE"
+fi
+
 set +e
-pytest -s -v $TEST_FILES \
+pytest -s -v $PYTEST_TARGET \
     --stack-config="$STACK_CONFIG" \
     -k "$PYTEST_PATTERN" \
-    --text-model="$TEXT_MODEL" \
-    --embedding-model=sentence-transformers/all-MiniLM-L6-v2 \
-    --color=yes $EXTRA_PARAMS \
+    $EXTRA_PARAMS \
+    --color=yes \
     --capture=tee-sys
 exit_code=$?
 set -e
@@ -294,7 +263,13 @@ df -h
 # stop server
 if [[ "$STACK_CONFIG" == *"server:"* ]]; then
     echo "Stopping Llama Stack Server..."
-    kill $(lsof -i :8321 | awk 'NR>1 {print $2}')
+    pids=$(lsof -i :8321 | awk 'NR>1 {print $2}')
+    if [[ -n "$pids" ]]; then
+        echo "Killing Llama Stack Server processes: $pids"
+        kill -9 $pids
+    else
+        echo "No Llama Stack Server processes found ?!"
+    fi
     echo "Llama Stack Server stopped"
 fi
 

tests/README.md

@@ -77,7 +77,7 @@ You must be careful when re-recording. CI workflows assume a specific setup for
 ./scripts/github/schedule-record-workflow.sh --test-subdirs "agents,inference"
 
 # Record with vision tests enabled
-./scripts/github/schedule-record-workflow.sh --test-subdirs "inference" --run-vision-tests
+./scripts/github/schedule-record-workflow.sh --test-suite vision
 
 # Record with specific provider
 ./scripts/github/schedule-record-workflow.sh --test-subdirs "agents" --test-provider vllm

tests/integration/README.md

@@ -42,6 +42,27 @@ Model parameters can be influenced by the following options:
 Each of these are comma-separated lists and can be used to generate multiple parameter combinations. Note that tests will be skipped
 if no model is specified.
 
+### Suites (fast selection + sane defaults)
+
+- `--suite`: comma-separated list of named suites that both narrow which tests are collected and prefill common model options (unless you pass them explicitly).
+- Available suites:
+  - `responses`: collects tests under `tests/integration/responses`; this is a separate suite because it needs a strong tool-calling model.
+  - `vision`: collects only `tests/integration/inference/test_vision_inference.py`; defaults `--vision-model=ollama/llama3.2-vision:11b`, `--embedding-model=sentence-transformers/all-MiniLM-L6-v2`.
+- Explicit flags always win. For example, `--suite=responses --text-model=<X>` overrides the suite’s text model.
+
+Examples:
+
+```bash
+# Fast responses run with defaults
+pytest -s -v tests/integration --stack-config=server:starter --suite=responses
+
+# Fast single-file vision run with defaults
+pytest -s -v tests/integration --stack-config=server:starter --suite=vision
+
+# Combine suites and override a default
+pytest -s -v tests/integration --stack-config=server:starter --suite=responses,vision --embedding-model=text-embedding-3-small
+```
+
 ## Examples
 
 ### Testing against a Server

tests/integration/batches/test_batches.py

@@ -268,3 +268,58 @@ class TestBatchesIntegration:
 
         deleted_error_file = openai_client.files.delete(final_batch.error_file_id)
         assert deleted_error_file.deleted, f"Error file {final_batch.error_file_id} was not deleted successfully"
+
+    def test_batch_e2e_completions(self, openai_client, batch_helper, text_model_id):
+        """Run an end-to-end batch with a single successful text completion request."""
+        request_body = {"model": text_model_id, "prompt": "Say completions", "max_tokens": 20}
+
+        batch_requests = [
+            {
+                "custom_id": "success-1",
+                "method": "POST",
+                "url": "/v1/completions",
+                "body": request_body,
+            }
+        ]
+
+        with batch_helper.create_file(batch_requests) as uploaded_file:
+            batch = openai_client.batches.create(
+                input_file_id=uploaded_file.id,
+                endpoint="/v1/completions",
+                completion_window="24h",
+                metadata={"test": "e2e_completions_success"},
+            )
+
+            final_batch = batch_helper.wait_for(
+                batch.id,
+                max_wait_time=3 * 60,
+                expected_statuses={"completed"},
+                timeout_action="skip",
+            )
+
+        assert final_batch.status == "completed"
+        assert final_batch.request_counts is not None
+        assert final_batch.request_counts.total == 1
+        assert final_batch.request_counts.completed == 1
+        assert final_batch.output_file_id is not None
+
+        output_content = openai_client.files.content(final_batch.output_file_id)
+        if isinstance(output_content, str):
+            output_text = output_content
+        else:
+            output_text = output_content.content.decode("utf-8")
+
+        output_lines = output_text.strip().split("\n")
+        assert len(output_lines) == 1
+
+        result = json.loads(output_lines[0])
+        assert result["custom_id"] == "success-1"
+        assert "response" in result
+        assert result["response"]["status_code"] == 200
+
+        deleted_output_file = openai_client.files.delete(final_batch.output_file_id)
+        assert deleted_output_file.deleted
+
+        if final_batch.error_file_id is not None:
+            deleted_error_file = openai_client.files.delete(final_batch.error_file_id)
+            assert deleted_error_file.deleted

tests/integration/conftest.py

@@ -6,15 +6,17 @@
 import inspect
 import itertools
 import os
-import platform
 import textwrap
 import time
+from pathlib import Path
 
 import pytest
 from dotenv import load_dotenv
 
 from llama_stack.log import get_logger
 
+from .suites import SUITE_DEFINITIONS
+
 logger = get_logger(__name__, category="tests")
 
 
@@ -61,9 +63,22 @@ def pytest_configure(config):
         key, value = env_var.split("=", 1)
         os.environ[key] = value
 
-    if platform.system() == "Darwin":  # Darwin is the system name for macOS
-        os.environ["DISABLE_CODE_SANDBOX"] = "1"
-        logger.info("Setting DISABLE_CODE_SANDBOX=1 for macOS")
+    suites_raw = config.getoption("--suite")
+    suites: list[str] = []
+    if suites_raw:
+        suites = [p.strip() for p in str(suites_raw).split(",") if p.strip()]
+        unknown = [p for p in suites if p not in SUITE_DEFINITIONS]
+        if unknown:
+            raise pytest.UsageError(
+                f"Unknown suite(s): {', '.join(unknown)}. Available: {', '.join(sorted(SUITE_DEFINITIONS.keys()))}"
+            )
+    for suite in suites:
+        suite_def = SUITE_DEFINITIONS.get(suite, {})
+        defaults: dict = suite_def.get("defaults", {})
+        for dest, value in defaults.items():
+            current = getattr(config.option, dest, None)
+            if not current:
+                setattr(config.option, dest, value)
 
 
 def pytest_addoption(parser):
@@ -105,16 +120,21 @@ def pytest_addoption(parser):
         default=384,
         help="Output dimensionality of the embedding model to use for testing. Default: 384",
     )
-    parser.addoption(
-        "--record-responses",
-        action="store_true",
-        help="Record new API responses instead of using cached ones.",
-    )
     parser.addoption(
         "--report",
         help="Path where the test report should be written, e.g. --report=/path/to/report.md",
     )
 
+    available_suites = ", ".join(sorted(SUITE_DEFINITIONS.keys()))
+    suite_help = (
+        "Comma-separated integration test suites to narrow collection and prefill defaults. "
+        "Available: "
+        f"{available_suites}. "
+        "Explicit CLI flags (e.g., --text-model) override suite defaults. "
+        "Examples: --suite=responses or --suite=responses,vision."
+    )
+    parser.addoption("--suite", help=suite_help)
+
 
 MODEL_SHORT_IDS = {
     "meta-llama/Llama-3.2-3B-Instruct": "3B",
@@ -197,3 +217,40 @@ def pytest_generate_tests(metafunc):
 
 
 pytest_plugins = ["tests.integration.fixtures.common"]
+
+
+def pytest_ignore_collect(path: str, config: pytest.Config) -> bool:
+    """Skip collecting paths outside the selected suite roots for speed."""
+    suites_raw = config.getoption("--suite")
+    if not suites_raw:
+        return False
+
+    names = [p.strip() for p in str(suites_raw).split(",") if p.strip()]
+    roots: list[str] = []
+    for name in names:
+        suite_def = SUITE_DEFINITIONS.get(name)
+        if suite_def:
+            roots.extend(suite_def.get("roots", []))
+    if not roots:
+        return False
+
+    p = Path(str(path)).resolve()
+
+    # Only constrain within tests/integration to avoid ignoring unrelated tests
+    integration_root = (Path(str(config.rootpath)) / "tests" / "integration").resolve()
+    if not p.is_relative_to(integration_root):
+        return False
+
+    for r in roots:
+        rp = (Path(str(config.rootpath)) / r).resolve()
+        if rp.is_file():
+            # Allow the exact file and any ancestor directories so pytest can walk into it.
+            if p == rp:
+                return False
+            if p.is_dir() and rp.is_relative_to(p):
+                return False
+        else:
+            # Allow anything inside an allowed directory
+            if p.is_relative_to(rp):
+                return False
+    return True

tests/integration/inference/test_openai_completion.py

@@ -58,6 +58,15 @@ def skip_if_model_doesnt_support_suffix(client_with_models, model_id):
         pytest.skip(f"Provider {provider.provider_type} doesn't support suffix.")
 
 
+def skip_if_doesnt_support_n(client_with_models, model_id):
+    provider = provider_from_model(client_with_models, model_id)
+    if provider.provider_type in (
+        "remote::sambanova",
+        "remote::ollama",
+    ):
+        pytest.skip(f"Model {model_id} hosted by {provider.provider_type} doesn't support n param.")
+
+
 def skip_if_model_doesnt_support_openai_chat_completion(client_with_models, model_id):
     provider = provider_from_model(client_with_models, model_id)
     if provider.provider_type in (
@@ -262,10 +271,7 @@ def test_openai_chat_completion_streaming(compat_client, client_with_models, tex
 )
 def test_openai_chat_completion_streaming_with_n(compat_client, client_with_models, text_model_id, test_case):
     skip_if_model_doesnt_support_openai_chat_completion(client_with_models, text_model_id)
-
-    provider = provider_from_model(client_with_models, text_model_id)
-    if provider.provider_type == "remote::ollama":
-        pytest.skip(f"Model {text_model_id} hosted by {provider.provider_type} doesn't support n > 1.")
+    skip_if_doesnt_support_n(client_with_models, text_model_id)
 
     tc = TestCase(test_case)
     question = tc["question"]

tests/integration/recordings/responses/41e27b9b5d09.json

@@ -0,0 +1,42 @@
+{
+  "request": {
+    "method": "POST",
+    "url": "http://0.0.0.0:11434/v1/v1/completions",
+    "headers": {},
+    "body": {
+      "model": "llama3.2:3b-instruct-fp16",
+      "prompt": "Say completions",
+      "max_tokens": 20
+    },
+    "endpoint": "/v1/completions",
+    "model": "llama3.2:3b-instruct-fp16"
+  },
+  "response": {
+    "body": {
+      "__type__": "openai.types.completion.Completion",
+      "__data__": {
+        "id": "cmpl-271",
+        "choices": [
+          {
+            "finish_reason": "length",
+            "index": 0,
+            "logprobs": null,
+            "text": "You want me to respond with a completion, but you didn't specify what I should complete. Could"
+          }
+        ],
+        "created": 1756846620,
+        "model": "llama3.2:3b-instruct-fp16",
+        "object": "text_completion",
+        "system_fingerprint": "fp_ollama",
+        "usage": {
+          "completion_tokens": 20,
+          "prompt_tokens": 28,
+          "total_tokens": 48,
+          "completion_tokens_details": null,
+          "prompt_tokens_details": null
+        }
+      }
+    },
+    "is_streaming": false
+  }
+}

tests/integration/suites.py

@@ -0,0 +1,53 @@
+# 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.
+
+# Central definition of integration test suites. You can use these suites by passing --suite=name to pytest.
+# For example:
+#
+# ```bash
+# pytest tests/integration/ --suite=vision
+# ```
+#
+# Each suite can:
+# - restrict collection to specific roots (dirs or files)
+# - provide default CLI option values (e.g. text_model, embedding_model, etc.)
+
+from pathlib import Path
+
+this_dir = Path(__file__).parent
+default_roots = [
+    str(p)
+    for p in this_dir.glob("*")
+    if p.is_dir()
+    and p.name not in ("__pycache__", "fixtures", "test_cases", "recordings", "responses", "post_training")
+]
+
+SUITE_DEFINITIONS: dict[str, dict] = {
+    "base": {
+        "description": "Base suite that includes most tests but runs them with a text Ollama model",
+        "roots": default_roots,
+        "defaults": {
+            "text_model": "ollama/llama3.2:3b-instruct-fp16",
+            "embedding_model": "sentence-transformers/all-MiniLM-L6-v2",
+        },
+    },
+    "responses": {
+        "description": "Suite that includes only the OpenAI Responses tests; needs a strong tool-calling model",
+        "roots": ["tests/integration/responses"],
+        "defaults": {
+            "text_model": "openai/gpt-4o",
+            "embedding_model": "sentence-transformers/all-MiniLM-L6-v2",
+        },
+    },
+    "vision": {
+        "description": "Suite that includes only the vision tests",
+        "roots": ["tests/integration/inference/test_vision_inference.py"],
+        "defaults": {
+            "vision_model": "ollama/llama3.2-vision:11b",
+            "embedding_model": "sentence-transformers/all-MiniLM-L6-v2",
+        },
+    },
+}

tests/integration/vector_io/test_vector_io.py

@@ -47,34 +47,45 @@ def client_with_empty_registry(client_with_models):
 
 
 def test_vector_db_retrieve(client_with_empty_registry, embedding_model_id, embedding_dimension):
-    # Register a memory bank first
-    vector_db_id = "test_vector_db"
-    client_with_empty_registry.vector_dbs.register(
-        vector_db_id=vector_db_id,
+    vector_db_name = "test_vector_db"
+    register_response = client_with_empty_registry.vector_dbs.register(
+        vector_db_id=vector_db_name,
         embedding_model=embedding_model_id,
         embedding_dimension=embedding_dimension,
     )
 
+    actual_vector_db_id = register_response.identifier
+
     # Retrieve the memory bank and validate its properties
-    response = client_with_empty_registry.vector_dbs.retrieve(vector_db_id=vector_db_id)
+    response = client_with_empty_registry.vector_dbs.retrieve(vector_db_id=actual_vector_db_id)
     assert response is not None
-    assert response.identifier == vector_db_id
+    assert response.identifier == actual_vector_db_id
     assert response.embedding_model == embedding_model_id
-    assert response.provider_resource_id == vector_db_id
+    assert response.identifier.startswith("vs_")
 
 
 def test_vector_db_register(client_with_empty_registry, embedding_model_id, embedding_dimension):
-    vector_db_id = "test_vector_db"
-    client_with_empty_registry.vector_dbs.register(
-        vector_db_id=vector_db_id,
+    vector_db_name = "test_vector_db"
+    response = client_with_empty_registry.vector_dbs.register(
+        vector_db_id=vector_db_name,
         embedding_model=embedding_model_id,
         embedding_dimension=embedding_dimension,
     )
 
-    vector_dbs_after_register = [vector_db.identifier for vector_db in client_with_empty_registry.vector_dbs.list()]
-    assert vector_dbs_after_register == [vector_db_id]
+    actual_vector_db_id = response.identifier
+    assert actual_vector_db_id.startswith("vs_")
+    assert actual_vector_db_id != vector_db_name
 
-    client_with_empty_registry.vector_dbs.unregister(vector_db_id=vector_db_id)
+    vector_dbs_after_register = [vector_db.identifier for vector_db in client_with_empty_registry.vector_dbs.list()]
+    assert vector_dbs_after_register == [actual_vector_db_id]
+
+    vector_stores = client_with_empty_registry.vector_stores.list()
+    assert len(vector_stores.data) == 1
+    vector_store = vector_stores.data[0]
+    assert vector_store.id == actual_vector_db_id
+    assert vector_store.name == vector_db_name
+
+    client_with_empty_registry.vector_dbs.unregister(vector_db_id=actual_vector_db_id)
 
     vector_dbs = [vector_db.identifier for vector_db in client_with_empty_registry.vector_dbs.list()]
     assert len(vector_dbs) == 0
@@ -91,20 +102,22 @@ def test_vector_db_register(client_with_empty_registry, embedding_model_id, embe
     ],
 )
 def test_insert_chunks(client_with_empty_registry, embedding_model_id, embedding_dimension, sample_chunks, test_case):
-    vector_db_id = "test_vector_db"
-    client_with_empty_registry.vector_dbs.register(
-        vector_db_id=vector_db_id,
+    vector_db_name = "test_vector_db"
+    register_response = client_with_empty_registry.vector_dbs.register(
+        vector_db_id=vector_db_name,
         embedding_model=embedding_model_id,
         embedding_dimension=embedding_dimension,
     )
 
+    actual_vector_db_id = register_response.identifier
+
     client_with_empty_registry.vector_io.insert(
-        vector_db_id=vector_db_id,
+        vector_db_id=actual_vector_db_id,
         chunks=sample_chunks,
     )
 
     response = client_with_empty_registry.vector_io.query(
-        vector_db_id=vector_db_id,
+        vector_db_id=actual_vector_db_id,
         query="What is the capital of France?",
     )
     assert response is not None
@@ -113,7 +126,7 @@ def test_insert_chunks(client_with_empty_registry, embedding_model_id, embedding
 
     query, expected_doc_id = test_case
     response = client_with_empty_registry.vector_io.query(
-        vector_db_id=vector_db_id,
+        vector_db_id=actual_vector_db_id,
         query=query,
     )
     assert response is not None
@@ -128,13 +141,15 @@ def test_insert_chunks_with_precomputed_embeddings(client_with_empty_registry, e
         "remote::qdrant": {"score_threshold": -1.0},
         "inline::qdrant": {"score_threshold": -1.0},
     }
-    vector_db_id = "test_precomputed_embeddings_db"
-    client_with_empty_registry.vector_dbs.register(
-        vector_db_id=vector_db_id,
+    vector_db_name = "test_precomputed_embeddings_db"
+    register_response = client_with_empty_registry.vector_dbs.register(
+        vector_db_id=vector_db_name,
         embedding_model=embedding_model_id,
         embedding_dimension=embedding_dimension,
     )
 
+    actual_vector_db_id = register_response.identifier
+
     chunks_with_embeddings = [
         Chunk(
             content="This is a test chunk with precomputed embedding.",
@@ -144,13 +159,13 @@ def test_insert_chunks_with_precomputed_embeddings(client_with_empty_registry, e
     ]
 
     client_with_empty_registry.vector_io.insert(
-        vector_db_id=vector_db_id,
+        vector_db_id=actual_vector_db_id,
         chunks=chunks_with_embeddings,
     )
 
     provider = [p.provider_id for p in client_with_empty_registry.providers.list() if p.api == "vector_io"][0]
     response = client_with_empty_registry.vector_io.query(
-        vector_db_id=vector_db_id,
+        vector_db_id=actual_vector_db_id,
         query="precomputed embedding test",
         params=vector_io_provider_params_dict.get(provider, None),
     )
@@ -173,13 +188,15 @@ def test_query_returns_valid_object_when_identical_to_embedding_in_vdb(
         "remote::qdrant": {"score_threshold": 0.0},
         "inline::qdrant": {"score_threshold": 0.0},
     }
-    vector_db_id = "test_precomputed_embeddings_db"
-    client_with_empty_registry.vector_dbs.register(
-        vector_db_id=vector_db_id,
+    vector_db_name = "test_precomputed_embeddings_db"
+    register_response = client_with_empty_registry.vector_dbs.register(
+        vector_db_id=vector_db_name,
         embedding_model=embedding_model_id,
         embedding_dimension=embedding_dimension,
     )
 
+    actual_vector_db_id = register_response.identifier
+
     chunks_with_embeddings = [
         Chunk(
             content="duplicate",
@@ -189,13 +206,13 @@ def test_query_returns_valid_object_when_identical_to_embedding_in_vdb(
     ]
 
     client_with_empty_registry.vector_io.insert(
-        vector_db_id=vector_db_id,
+        vector_db_id=actual_vector_db_id,
         chunks=chunks_with_embeddings,
     )
 
     provider = [p.provider_id for p in client_with_empty_registry.providers.list() if p.api == "vector_io"][0]
     response = client_with_empty_registry.vector_io.query(
-        vector_db_id=vector_db_id,
+        vector_db_id=actual_vector_db_id,
         query="duplicate",
         params=vector_io_provider_params_dict.get(provider, None),
     )

tests/unit/distribution/routers/test_routing_tables.py

@@ -146,6 +146,20 @@ class VectorDBImpl(Impl):
     async def unregister_vector_db(self, vector_db_id: str):
         return vector_db_id
 
+    async def openai_create_vector_store(self, **kwargs):
+        import time
+        import uuid
+
+        from llama_stack.apis.vector_io.vector_io import VectorStoreFileCounts, VectorStoreObject
+
+        vector_store_id = kwargs.get("provider_vector_db_id") or f"vs_{uuid.uuid4()}"
+        return VectorStoreObject(
+            id=vector_store_id,
+            name=kwargs.get("name", vector_store_id),
+            created_at=int(time.time()),
+            file_counts=VectorStoreFileCounts(completed=0, cancelled=0, failed=0, in_progress=0, total=0),
+        )
+
 
 async def test_models_routing_table(cached_disk_dist_registry):
     table = ModelsRoutingTable({"test_provider": InferenceImpl()}, cached_disk_dist_registry, {})
@@ -247,17 +261,21 @@ async def test_vectordbs_routing_table(cached_disk_dist_registry):
     )
 
     # Register multiple vector databases and verify listing
-    await table.register_vector_db(vector_db_id="test-vectordb", embedding_model="test_provider/test-model")
-    await table.register_vector_db(vector_db_id="test-vectordb-2", embedding_model="test_provider/test-model")
+    vdb1 = await table.register_vector_db(vector_db_id="test-vectordb", embedding_model="test_provider/test-model")
+    vdb2 = await table.register_vector_db(vector_db_id="test-vectordb-2", embedding_model="test_provider/test-model")
     vector_dbs = await table.list_vector_dbs()
 
     assert len(vector_dbs.data) == 2
     vector_db_ids = {v.identifier for v in vector_dbs.data}
-    assert "test-vectordb" in vector_db_ids
-    assert "test-vectordb-2" in vector_db_ids
+    assert vdb1.identifier in vector_db_ids
+    assert vdb2.identifier in vector_db_ids
 
-    await table.unregister_vector_db(vector_db_id="test-vectordb")
-    await table.unregister_vector_db(vector_db_id="test-vectordb-2")
+    # Verify they have UUID-based identifiers
+    assert vdb1.identifier.startswith("vs_")
+    assert vdb2.identifier.startswith("vs_")
+
+    await table.unregister_vector_db(vector_db_id=vdb1.identifier)
+    await table.unregister_vector_db(vector_db_id=vdb2.identifier)
 
     vector_dbs = await table.list_vector_dbs()
     assert len(vector_dbs.data) == 0

tests/unit/distribution/routing_tables/test_vector_dbs.py

@@ -7,6 +7,7 @@
 # Unit tests for the routing tables vector_dbs
 
 import time
+import uuid
 from unittest.mock import AsyncMock
 
 import pytest
@@ -34,6 +35,7 @@ from tests.unit.distribution.routers.test_routing_tables import Impl, InferenceI
 class VectorDBImpl(Impl):
     def __init__(self):
         super().__init__(Api.vector_io)
+        self.vector_stores = {}
 
     async def register_vector_db(self, vector_db: VectorDB):
         return vector_db
@@ -114,8 +116,35 @@ class VectorDBImpl(Impl):
     async def openai_delete_vector_store_file(self, vector_store_id, file_id):
         return VectorStoreFileDeleteResponse(id=file_id, deleted=True)
 
+    async def openai_create_vector_store(
+        self,
+        name=None,
+        embedding_model=None,
+        embedding_dimension=None,
+        provider_id=None,
+        provider_vector_db_id=None,
+        **kwargs,
+    ):
+        vector_store_id = provider_vector_db_id or f"vs_{uuid.uuid4()}"
+        vector_store = VectorStoreObject(
+            id=vector_store_id,
+            name=name or vector_store_id,
+            created_at=int(time.time()),
+            file_counts=VectorStoreFileCounts(completed=0, cancelled=0, failed=0, in_progress=0, total=0),
+        )
+        self.vector_stores[vector_store_id] = vector_store
+        return vector_store
+
+    async def openai_list_vector_stores(self, **kwargs):
+        from llama_stack.apis.vector_io.vector_io import VectorStoreListResponse
+
+        return VectorStoreListResponse(
+            data=list(self.vector_stores.values()), has_more=False, first_id=None, last_id=None
+        )
+
 
 async def test_vectordbs_routing_table(cached_disk_dist_registry):
+    n = 10
     table = VectorDBsRoutingTable({"test_provider": VectorDBImpl()}, cached_disk_dist_registry, {})
     await table.initialize()
 
@@ -129,22 +158,98 @@ async def test_vectordbs_routing_table(cached_disk_dist_registry):
     )
 
     # Register multiple vector databases and verify listing
-    await table.register_vector_db(vector_db_id="test-vectordb", embedding_model="test-model")
-    await table.register_vector_db(vector_db_id="test-vectordb-2", embedding_model="test-model")
+    vdb_dict = {}
+    for i in range(n):
+        vdb_dict[i] = await table.register_vector_db(vector_db_id=f"test-vectordb-{i}", embedding_model="test-model")
+
     vector_dbs = await table.list_vector_dbs()
 
-    assert len(vector_dbs.data) == 2
+    assert len(vector_dbs.data) == len(vdb_dict)
     vector_db_ids = {v.identifier for v in vector_dbs.data}
-    assert "test-vectordb" in vector_db_ids
-    assert "test-vectordb-2" in vector_db_ids
-
-    await table.unregister_vector_db(vector_db_id="test-vectordb")
-    await table.unregister_vector_db(vector_db_id="test-vectordb-2")
+    for k in vdb_dict:
+        assert vdb_dict[k].identifier in vector_db_ids
+    for k in vdb_dict:
+        await table.unregister_vector_db(vector_db_id=vdb_dict[k].identifier)
 
     vector_dbs = await table.list_vector_dbs()
     assert len(vector_dbs.data) == 0
 
 
+async def test_vector_db_and_vector_store_id_mapping(cached_disk_dist_registry):
+    n = 10
+    impl = VectorDBImpl()
+    table = VectorDBsRoutingTable({"test_provider": impl}, cached_disk_dist_registry, {})
+    await table.initialize()
+
+    m_table = ModelsRoutingTable({"test_provider": InferenceImpl()}, cached_disk_dist_registry, {})
+    await m_table.initialize()
+    await m_table.register_model(
+        model_id="test-model",
+        provider_id="test_provider",
+        metadata={"embedding_dimension": 128},
+        model_type=ModelType.embedding,
+    )
+
+    vdb_dict = {}
+    for i in range(n):
+        vdb_dict[i] = await table.register_vector_db(vector_db_id=f"test-vectordb-{i}", embedding_model="test-model")
+
+    vector_dbs = await table.list_vector_dbs()
+    vector_db_ids = {v.identifier for v in vector_dbs.data}
+
+    vector_stores = await impl.openai_list_vector_stores()
+    vector_store_ids = {v.id for v in vector_stores.data}
+
+    assert vector_db_ids == vector_store_ids, (
+        f"Vector DB IDs {vector_db_ids} don't match vector store IDs {vector_store_ids}"
+    )
+
+    for vector_store in vector_stores.data:
+        vector_db = await table.get_vector_db(vector_store.id)
+        assert vector_store.name == vector_db.vector_db_name, (
+            f"Vector store name {vector_store.name} doesn't match vector store ID {vector_store.id}"
+        )
+
+    for vector_db_id in vector_db_ids:
+        await table.unregister_vector_db(vector_db_id)
+
+    assert len((await table.list_vector_dbs()).data) == 0
+
+
+async def test_vector_db_id_becomes_vector_store_name(cached_disk_dist_registry):
+    impl = VectorDBImpl()
+    table = VectorDBsRoutingTable({"test_provider": impl}, cached_disk_dist_registry, {})
+    await table.initialize()
+
+    m_table = ModelsRoutingTable({"test_provider": InferenceImpl()}, cached_disk_dist_registry, {})
+    await m_table.initialize()
+    await m_table.register_model(
+        model_id="test-model",
+        provider_id="test_provider",
+        metadata={"embedding_dimension": 128},
+        model_type=ModelType.embedding,
+    )
+
+    user_provided_id = "my-custom-vector-db"
+    await table.register_vector_db(vector_db_id=user_provided_id, embedding_model="test-model")
+
+    vector_stores = await impl.openai_list_vector_stores()
+    assert len(vector_stores.data) == 1
+
+    vector_store = vector_stores.data[0]
+
+    assert vector_store.name == user_provided_id
+
+    assert vector_store.id.startswith("vs_")
+    assert vector_store.id != user_provided_id
+
+    vector_dbs = await table.list_vector_dbs()
+    assert len(vector_dbs.data) == 1
+    assert vector_dbs.data[0].identifier == vector_store.id
+
+    await table.unregister_vector_db(vector_store.id)
+
+
 async def test_openai_vector_stores_routing_table_roles(cached_disk_dist_registry):
     impl = VectorDBImpl()
     impl.openai_retrieve_vector_store = AsyncMock(return_value="OK")
@@ -164,7 +269,8 @@ async def test_openai_vector_stores_routing_table_roles(cached_disk_dist_registr
 
     authorized_user = User(principal="alice", attributes={"roles": [authorized_team]})
     with request_provider_data_context({}, authorized_user):
-        _ = await table.register_vector_db(vector_db_id="vs1", embedding_model="test-model")
+        registered_vdb = await table.register_vector_db(vector_db_id="vs1", embedding_model="test-model")
+        authorized_table = registered_vdb.identifier  # Use the actual generated ID
 
     # Authorized reader
     with request_provider_data_context({}, authorized_user):
@@ -227,7 +333,8 @@ async def test_openai_vector_stores_routing_table_actions(cached_disk_dist_regis
     )
 
     with request_provider_data_context({}, admin_user):
-        await table.register_vector_db(vector_db_id=vector_db_id, embedding_model="test-model")
+        registered_vdb = await table.register_vector_db(vector_db_id=vector_db_id, embedding_model="test-model")
+        vector_db_id = registered_vdb.identifier  # Use the actual generated ID
 
     read_methods = [
         (table.openai_retrieve_vector_store, (vector_db_id,), {}),

tests/unit/providers/batches/test_reference.py

@@ -46,7 +46,8 @@ The tests are categorized and outlined below, keep this updated:
   * test_validate_input_url_mismatch (negative)
   * test_validate_input_multiple_errors_per_request (negative)
   * test_validate_input_invalid_request_format (negative)
-  * test_validate_input_missing_parameters (parametrized negative - custom_id, method, url, body, model, messages missing validation)
+  * test_validate_input_missing_parameters_chat_completions (parametrized negative - custom_id, method, url, body, model, messages missing validation for chat/completions)
+  * test_validate_input_missing_parameters_completions (parametrized negative - custom_id, method, url, body, model, prompt missing validation for completions)
   * test_validate_input_invalid_parameter_types (parametrized negative - custom_id, url, method, body, model, messages type validation)
 
 The tests use temporary SQLite databases for isolation and mock external
@@ -213,7 +214,6 @@ class TestReferenceBatchesImpl:
         "endpoint",
         [
             "/v1/embeddings",
-            "/v1/completions",
             "/v1/invalid/endpoint",
             "",
         ],
@@ -499,8 +499,10 @@ class TestReferenceBatchesImpl:
             ("messages", "body.messages", "invalid_request", "Messages parameter is required"),
         ],
     )
-    async def test_validate_input_missing_parameters(self, provider, param_name, param_path, error_code, error_message):
-        """Test _validate_input when file contains request with missing required parameters."""
+    async def test_validate_input_missing_parameters_chat_completions(
+        self, provider, param_name, param_path, error_code, error_message
+    ):
+        """Test _validate_input when file contains request with missing required parameters for chat completions."""
         provider.files_api.openai_retrieve_file = AsyncMock()
         mock_response = MagicMock()
 
@@ -541,6 +543,61 @@ class TestReferenceBatchesImpl:
         assert errors[0].message == error_message
         assert errors[0].param == param_path
 
+    @pytest.mark.parametrize(
+        "param_name,param_path,error_code,error_message",
+        [
+            ("custom_id", "custom_id", "missing_required_parameter", "Missing required parameter: custom_id"),
+            ("method", "method", "missing_required_parameter", "Missing required parameter: method"),
+            ("url", "url", "missing_required_parameter", "Missing required parameter: url"),
+            ("body", "body", "missing_required_parameter", "Missing required parameter: body"),
+            ("model", "body.model", "invalid_request", "Model parameter is required"),
+            ("prompt", "body.prompt", "invalid_request", "Prompt parameter is required"),
+        ],
+    )
+    async def test_validate_input_missing_parameters_completions(
+        self, provider, param_name, param_path, error_code, error_message
+    ):
+        """Test _validate_input when file contains request with missing required parameters for text completions."""
+        provider.files_api.openai_retrieve_file = AsyncMock()
+        mock_response = MagicMock()
+
+        base_request = {
+            "custom_id": "req-1",
+            "method": "POST",
+            "url": "/v1/completions",
+            "body": {"model": "test-model", "prompt": "Hello"},
+        }
+
+        # Remove the specific parameter being tested
+        if "." in param_path:
+            top_level, nested_param = param_path.split(".", 1)
+            del base_request[top_level][nested_param]
+        else:
+            del base_request[param_name]
+
+        mock_response.body = json.dumps(base_request).encode()
+        provider.files_api.openai_retrieve_file_content = AsyncMock(return_value=mock_response)
+
+        batch = BatchObject(
+            id="batch_test",
+            object="batch",
+            endpoint="/v1/completions",
+            input_file_id=f"missing_{param_name}_file",
+            completion_window="24h",
+            status="validating",
+            created_at=1234567890,
+        )
+
+        errors, requests = await provider._validate_input(batch)
+
+        assert len(errors) == 1
+        assert len(requests) == 0
+
+        assert errors[0].code == error_code
+        assert errors[0].line == 1
+        assert errors[0].message == error_message
+        assert errors[0].param == param_path
+
     async def test_validate_input_url_mismatch(self, provider):
         """Test _validate_input when file contains request with URL that doesn't match batch endpoint."""
         provider.files_api.openai_retrieve_file = AsyncMock()