Merge branch 'main' into chroma

2025-10-04 12:07:34 +00:00 · 2025-08-25 09:59:32 +09:00 · 2025-08-25 09:59:32 +09:00 · d3958fae4f
commit d3958fae4f
parent f23ea0445a cffc4edf47
192 changed files with 7088 additions and 853 deletions
--- a/.github/dependabot.yml
+++ b/.github/dependabot.yml
@ -9,6 +9,7 @@ updates:
      day: "saturday"
    commit-message:
      prefix: chore(github-deps)
+
  - package-ecosystem: "uv"
    directory: "/"
    schedule:
@ -19,3 +20,14 @@ updates:
      - python
    commit-message:
      prefix: chore(python-deps)
+
+  - package-ecosystem: npm
+    directory: "/llama_stack/ui"
+    schedule:
+      interval: "weekly"
+      day: "saturday"
+    labels:
+      - type/dependencies
+      - javascript
+    commit-message:
+      prefix: chore(ui-deps)
--- a/.github/workflows/changelog.yml
+++ b/.github/workflows/changelog.yml
@ -17,7 +17,7 @@ jobs:
      pull-requests: write  # for peter-evans/create-pull-request to create a PR
    runs-on: ubuntu-latest
    steps:
-      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+      - uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
        with:
          ref: main
          fetch-depth: 0
--- a/.github/workflows/install-script-ci.yml
+++ b/.github/workflows/install-script-ci.yml
@ -16,14 +16,14 @@ jobs:
  lint:
    runs-on: ubuntu-latest
    steps:
-      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # 4.2.2
+      - uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # 5.0.0
      - name: Run ShellCheck on install.sh
        run: shellcheck scripts/install.sh
  smoke-test-on-dev:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
--- a/.github/workflows/integration-auth-tests.yml
+++ b/.github/workflows/integration-auth-tests.yml
@ -18,7 +18,7 @@ on:
      - '.github/workflows/integration-auth-tests.yml' # This workflow

 concurrency:
-  group: ${{ github.workflow }}-${{ github.ref }}
+  group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_id || github.ref }}
  cancel-in-progress: true

 jobs:
@ -31,7 +31,7 @@ jobs:

    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
--- a/.github/workflows/integration-sql-store-tests.yml
+++ b/.github/workflows/integration-sql-store-tests.yml
@ -16,7 +16,7 @@ on:
      - '.github/workflows/integration-sql-store-tests.yml' # This workflow

 concurrency:
-  group: ${{ github.workflow }}-${{ github.ref }}
+  group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_id || github.ref }}
  cancel-in-progress: true

 jobs:
@ -44,7 +44,7 @@ jobs:

    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
--- a/.github/workflows/integration-tests.yml
+++ b/.github/workflows/integration-tests.yml
@ -65,7 +65,7 @@ jobs:

    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Setup test environment
        uses: ./.github/actions/setup-test-environment
--- a/.github/workflows/integration-vector-io-tests.yml
+++ b/.github/workflows/integration-vector-io-tests.yml
@ -33,7 +33,7 @@ jobs:

    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
--- a/.github/workflows/pre-commit.yml
+++ b/.github/workflows/pre-commit.yml
@ -8,7 +8,7 @@ on:
    branches: [main]

 concurrency:
-  group: ${{ github.workflow }}-${{ github.ref }}
+  group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_id || github.ref }}
  cancel-in-progress: true

 jobs:
@ -20,7 +20,7 @@ jobs:

    steps:
      - name: Checkout code
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
        with:
          # For dependabot PRs, we need to checkout with a token that can push changes
          token: ${{ github.actor == 'dependabot[bot]' && secrets.GITHUB_TOKEN || github.token }}
--- a/.github/workflows/providers-build.yml
+++ b/.github/workflows/providers-build.yml
@ -26,7 +26,7 @@ on:
      - 'pyproject.toml'

 concurrency:
-  group: ${{ github.workflow }}-${{ github.ref }}
+  group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_id || github.ref }}
  cancel-in-progress: true

 jobs:
@ -36,7 +36,7 @@ jobs:
      distros: ${{ steps.set-matrix.outputs.distros }}
    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Generate Distribution List
        id: set-matrix
@ -55,7 +55,7 @@ jobs:

    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
@ -79,7 +79,7 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
@ -92,7 +92,7 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
@ -106,6 +106,10 @@ jobs:
      - name: Inspect the container image entrypoint
        run: |
          IMAGE_ID=$(docker images --format "{{.Repository}}:{{.Tag}}" | head -n 1)
+          if [ -z "$IMAGE_ID" ]; then
+            echo "No image found"
+            exit 1
+          fi
          entrypoint=$(docker inspect --format '{{ .Config.Entrypoint }}' $IMAGE_ID)
          echo "Entrypoint: $entrypoint"
          if [ "$entrypoint" != "[python -m llama_stack.core.server.server /app/run.yaml]" ]; then
@ -117,7 +121,7 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
@ -140,6 +144,10 @@ jobs:
      - name: Inspect UBI9 image
        run: |
          IMAGE_ID=$(docker images --format "{{.Repository}}:{{.Tag}}" | head -n 1)
+          if [ -z "$IMAGE_ID" ]; then
+            echo "No image found"
+            exit 1
+          fi
          entrypoint=$(docker inspect --format '{{ .Config.Entrypoint }}' $IMAGE_ID)
          echo "Entrypoint: $entrypoint"
          if [ "$entrypoint" != "[python -m llama_stack.core.server.server /app/run.yaml]" ]; then
--- a/.github/workflows/python-build-test.yml
+++ b/.github/workflows/python-build-test.yml
@ -21,10 +21,10 @@ jobs:

    steps:
    - name: Checkout repository
-      uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+      uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

    - name: Install uv
-      uses: astral-sh/setup-uv@e92bafb6253dcd438e0484186d7669ea7a8ca1cc # v6.4.3
+      uses: astral-sh/setup-uv@d9e0f98d3fc6adb07d1e3d37f3043649ddad06a1 # v6.5.0
      with:
        python-version: ${{ matrix.python-version }}
        activate-environment: true
--- a/.github/workflows/record-integration-tests.yml
+++ b/.github/workflows/record-integration-tests.yml
@ -46,7 +46,7 @@ jobs:
          echo "::endgroup::"

      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
        with:
          fetch-depth: 0

--- a/.github/workflows/semantic-pr.yml
+++ b/.github/workflows/semantic-pr.yml
@ -22,6 +22,6 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Check PR Title's semantic conformance
-        uses: amannn/action-semantic-pull-request@0723387faaf9b38adef4775cd42cfd5155ed6017 # v5.5.3
+        uses: amannn/action-semantic-pull-request@7f33ba792281b034f64e96f4c0b5496782dd3b37 # v6.1.0
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
--- a/.github/workflows/test-external-provider-module.yml
+++ b/.github/workflows/test-external-provider-module.yml
@ -27,7 +27,7 @@ jobs:
        # container and point 'uv pip install' to the correct path...
    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
--- a/.github/workflows/test-external.yml
+++ b/.github/workflows/test-external.yml
@ -27,7 +27,7 @@ jobs:
        # container and point 'uv pip install' to the correct path...
    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
--- a/.github/workflows/ui-unit-tests.yml
+++ b/.github/workflows/ui-unit-tests.yml
@ -13,7 +13,7 @@ on:
  workflow_dispatch:

 concurrency:
-  group: ${{ github.workflow }}-${{ github.ref }}
+  group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_id || github.ref }}
  cancel-in-progress: true

 jobs:
@ -26,10 +26,10 @@ jobs:

    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Setup Node.js
-        uses: actions/setup-node@39370e3970a6d050c480ffad4ff0ed4d3fdee5af # v4.1.0
+        uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
        with:
          node-version: ${{ matrix.node-version }}
          cache: 'npm'
--- a/.github/workflows/unit-tests.yml
+++ b/.github/workflows/unit-tests.yml
@ -18,7 +18,7 @@ on:
  workflow_dispatch:

 concurrency:
-  group: ${{ github.workflow }}-${{ github.ref }}
+  group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_id || github.ref }}
  cancel-in-progress: true

 jobs:
@ -32,7 +32,7 @@ jobs:
          - "3.13"
    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
--- a/.github/workflows/update-readthedocs.yml
+++ b/.github/workflows/update-readthedocs.yml
@ -27,7 +27,7 @@ on:
      - '.github/workflows/update-readthedocs.yml'

 concurrency:
-  group: ${{ github.workflow }}-${{ github.ref }}
+  group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_id || github.ref }}
  cancel-in-progress: true

 jobs:
@ -37,7 +37,7 @@ jobs:
      TOKEN: ${{ secrets.READTHEDOCS_TOKEN }}
    steps:
      - name: Checkout repository
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@ -146,20 +146,32 @@ repos:
        pass_filenames: false
        require_serial: true
        files: ^.github/workflows/.*$
-      - id: ui-prettier
-        name: Format UI code with Prettier
-        entry: bash -c 'cd llama_stack/ui && npm ci && npm run format'
+      - id: ui-linter
+        name: Format & Lint UI
+        entry: bash ./scripts/run-ui-linter.sh
        language: system
        files: ^llama_stack/ui/.*\.(ts|tsx)$
        pass_filenames: false
        require_serial: true
-      - id: ui-eslint
-        name: Lint UI code with ESLint
-        entry: bash -c 'cd llama_stack/ui && npm run lint -- --fix --quiet'
+
+      - id: check-log-usage
+        name: Ensure 'llama_stack.log' usage for logging
+        entry: bash
        language: system
-        files: ^llama_stack/ui/.*\.(ts|tsx)$
-        pass_filenames: false
-        require_serial: true
+        types: [python]
+        pass_filenames: true
+        args:
+          - -c
+          - |
+            matches=$(grep -EnH '^[^#]*\b(import\s+logging|from\s+logging\b)' "$@" | grep -v -e '#\s*allow-direct-logging' || true)
+            if [ -n "$matches" ]; then
+              # GitHub Actions annotation format
+              while IFS=: read -r file line_num rest; do
+                echo "::error file=$file,line=$line_num::Do not use 'import logging' or 'from logging import' in $file. Use the custom log instead: from llama_stack.log import get_logger; logger = get_logger(). If direct logging is truly needed, add: # allow-direct-logging"
+              done <<< "$matches"
+              exit 1
+            fi
+            exit 0

 ci:
    autofix_commit_msg: 🎨 [pre-commit.ci] Auto format from pre-commit.com hooks
--- a/docs/_static/llama-stack-spec.html
+++ b/docs/_static/llama-stack-spec.html
@ -4605,6 +4605,49 @@
                }
            }
        },
+        "/v1/inference/rerank": {
+            "post": {
+                "responses": {
+                    "200": {
+                        "description": "RerankResponse with indices sorted by relevance score (descending).",
+                        "content": {
+                            "application/json": {
+                                "schema": {
+                                    "$ref": "#/components/schemas/RerankResponse"
+                                }
+                            }
+                        }
+                    },
+                    "400": {
+                        "$ref": "#/components/responses/BadRequest400"
+                    },
+                    "429": {
+                        "$ref": "#/components/responses/TooManyRequests429"
+                    },
+                    "500": {
+                        "$ref": "#/components/responses/InternalServerError500"
+                    },
+                    "default": {
+                        "$ref": "#/components/responses/DefaultError"
+                    }
+                },
+                "tags": [
+                    "Inference"
+                ],
+                "description": "Rerank a list of documents based on their relevance to a query.",
+                "parameters": [],
+                "requestBody": {
+                    "content": {
+                        "application/json": {
+                            "schema": {
+                                "$ref": "#/components/schemas/RerankRequest"
+                            }
+                        }
+                    },
+                    "required": true
+                }
+            }
+        },
        "/v1/agents/{agent_id}/session/{session_id}/turn/{turn_id}/resume": {
            "post": {
                "responses": {
@ -16024,12 +16067,16 @@
                    "value": {
                        "type": "number",
                        "description": "The numeric value of the metric at this timestamp"
+                    },
+                    "unit": {
+                        "type": "string"
                    }
                },
                "additionalProperties": false,
                "required": [
                    "timestamp",
-                    "value"
+                    "value",
+                    "unit"
                ],
                "title": "MetricDataPoint",
                "description": "A single data point in a metric time series."
@ -16587,6 +16634,95 @@
                ],
                "title": "RegisterVectorDbRequest"
            },
+            "RerankRequest": {
+                "type": "object",
+                "properties": {
+                    "model": {
+                        "type": "string",
+                        "description": "The identifier of the reranking model to use."
+                    },
+                    "query": {
+                        "oneOf": [
+                            {
+                                "type": "string"
+                            },
+                            {
+                                "$ref": "#/components/schemas/OpenAIChatCompletionContentPartTextParam"
+                            },
+                            {
+                                "$ref": "#/components/schemas/OpenAIChatCompletionContentPartImageParam"
+                            }
+                        ],
+                        "description": "The search query to rank items against. Can be a string, text content part, or image content part. The input must not exceed the model's max input token length."
+                    },
+                    "items": {
+                        "type": "array",
+                        "items": {
+                            "oneOf": [
+                                {
+                                    "type": "string"
+                                },
+                                {
+                                    "$ref": "#/components/schemas/OpenAIChatCompletionContentPartTextParam"
+                                },
+                                {
+                                    "$ref": "#/components/schemas/OpenAIChatCompletionContentPartImageParam"
+                                }
+                            ]
+                        },
+                        "description": "List of items to rerank. Each item can be a string, text content part, or image content part. Each input must not exceed the model's max input token length."
+                    },
+                    "max_num_results": {
+                        "type": "integer",
+                        "description": "(Optional) Maximum number of results to return. Default: returns all."
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "model",
+                    "query",
+                    "items"
+                ],
+                "title": "RerankRequest"
+            },
+            "RerankData": {
+                "type": "object",
+                "properties": {
+                    "index": {
+                        "type": "integer",
+                        "description": "The original index of the document in the input list"
+                    },
+                    "relevance_score": {
+                        "type": "number",
+                        "description": "The relevance score from the model output. Values are inverted when applicable so that higher scores indicate greater relevance."
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "index",
+                    "relevance_score"
+                ],
+                "title": "RerankData",
+                "description": "A single rerank result from a reranking response."
+            },
+            "RerankResponse": {
+                "type": "object",
+                "properties": {
+                    "data": {
+                        "type": "array",
+                        "items": {
+                            "$ref": "#/components/schemas/RerankData"
+                        },
+                        "description": "List of rerank result objects, sorted by relevance score (descending)"
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "data"
+                ],
+                "title": "RerankResponse",
+                "description": "Response from a reranking request."
+            },
            "ResumeAgentTurnRequest": {
                "type": "object",
                "properties": {
--- a/docs/_static/llama-stack-spec.yaml
+++ b/docs/_static/llama-stack-spec.yaml
@ -3264,6 +3264,37 @@ paths:
            schema:
              $ref: '#/components/schemas/QueryTracesRequest'
        required: true
+  /v1/inference/rerank:
+    post:
+      responses:
+        '200':
+          description: >-
+            RerankResponse with indices sorted by relevance score (descending).
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/RerankResponse'
+        '400':
+          $ref: '#/components/responses/BadRequest400'
+        '429':
+          $ref: >-
+            #/components/responses/TooManyRequests429
+        '500':
+          $ref: >-
+            #/components/responses/InternalServerError500
+        default:
+          $ref: '#/components/responses/DefaultError'
+      tags:
+        - Inference
+      description: >-
+        Rerank a list of documents based on their relevance to a query.
+      parameters: []
+      requestBody:
+        content:
+          application/json:
+            schema:
+              $ref: '#/components/schemas/RerankRequest'
+        required: true
  /v1/agents/{agent_id}/session/{session_id}/turn/{turn_id}/resume:
    post:
      responses:
@ -11923,10 +11954,13 @@ components:
          type: number
          description: >-
            The numeric value of the metric at this timestamp
+        unit:
+          type: string
      additionalProperties: false
      required:
        - timestamp
        - value
+        - unit
      title: MetricDataPoint
      description: >-
        A single data point in a metric time series.
@ -12337,6 +12371,76 @@ components:
        - vector_db_id
        - embedding_model
      title: RegisterVectorDbRequest
+    RerankRequest:
+      type: object
+      properties:
+        model:
+          type: string
+          description: >-
+            The identifier of the reranking model to use.
+        query:
+          oneOf:
+            - type: string
+            - $ref: '#/components/schemas/OpenAIChatCompletionContentPartTextParam'
+            - $ref: '#/components/schemas/OpenAIChatCompletionContentPartImageParam'
+          description: >-
+            The search query to rank items against. Can be a string, text content
+            part, or image content part. The input must not exceed the model's max
+            input token length.
+        items:
+          type: array
+          items:
+            oneOf:
+              - type: string
+              - $ref: '#/components/schemas/OpenAIChatCompletionContentPartTextParam'
+              - $ref: '#/components/schemas/OpenAIChatCompletionContentPartImageParam'
+          description: >-
+            List of items to rerank. Each item can be a string, text content part,
+            or image content part. Each input must not exceed the model's max input
+            token length.
+        max_num_results:
+          type: integer
+          description: >-
+            (Optional) Maximum number of results to return. Default: returns all.
+      additionalProperties: false
+      required:
+        - model
+        - query
+        - items
+      title: RerankRequest
+    RerankData:
+      type: object
+      properties:
+        index:
+          type: integer
+          description: >-
+            The original index of the document in the input list
+        relevance_score:
+          type: number
+          description: >-
+            The relevance score from the model output. Values are inverted when applicable
+            so that higher scores indicate greater relevance.
+      additionalProperties: false
+      required:
+        - index
+        - relevance_score
+      title: RerankData
+      description: >-
+        A single rerank result from a reranking response.
+    RerankResponse:
+      type: object
+      properties:
+        data:
+          type: array
+          items:
+            $ref: '#/components/schemas/RerankData'
+          description: >-
+            List of rerank result objects, sorted by relevance score (descending)
+      additionalProperties: false
+      required:
+        - data
+      title: RerankResponse
+      description: Response from a reranking request.
    ResumeAgentTurnRequest:
      type: object
      properties:
--- a/docs/source/distributions/configuration.md
+++ b/docs/source/distributions/configuration.md
@ -225,8 +225,32 @@ server:
  port: 8321  # Port to listen on (default: 8321)
  tls_certfile: "/path/to/cert.pem"  # Optional: Path to TLS certificate for HTTPS
  tls_keyfile: "/path/to/key.pem"    # Optional: Path to TLS key for HTTPS
+  cors: true  # Optional: Enable CORS (dev mode) or full config object
 ```

+### CORS Configuration
+
+CORS (Cross-Origin Resource Sharing) can be configured in two ways:
+
+**Local development** (allows localhost origins only):
+```yaml
+server:
+  cors: true
+```
+
+**Explicit configuration** (custom origins and settings):
+```yaml
+server:
+  cors:
+    allow_origins: ["https://myapp.com", "https://app.example.com"]
+    allow_methods: ["GET", "POST", "PUT", "DELETE"]
+    allow_headers: ["Content-Type", "Authorization"]
+    allow_credentials: true
+    max_age: 3600
+```
+
+When `cors: true`, the server enables secure localhost-only access for local development. For production, specify exact origins to maintain security.
+
 ### Authentication Configuration

 > **Breaking Change (v0.2.14)**: The authentication configuration structure has changed. The previous format with `provider_type` and `config` fields has been replaced with a unified `provider_config` field that includes the `type` field. Update your configuration files accordingly.
@ -618,6 +642,54 @@ Content-Type: application/json
 }
 ```

+### CORS Configuration
+
+Configure CORS to allow web browsers to make requests from different domains. Disabled by default.
+
+#### Quick Setup
+
+For development, use the simple boolean flag:
+
+```yaml
+server:
+  cors: true  # Auto-enables localhost with any port
+```
+
+This automatically allows `http://localhost:*` and `https://localhost:*` with secure defaults.
+
+#### Custom Configuration
+
+For specific origins and full control:
+
+```yaml
+server:
+  cors:
+    allow_origins: ["https://myapp.com", "https://staging.myapp.com"]
+    allow_credentials: true
+    allow_methods: ["GET", "POST", "PUT", "DELETE"]
+    allow_headers: ["Content-Type", "Authorization"]
+    allow_origin_regex: "https://.*\\.example\\.com"  # Optional regex pattern
+    expose_headers: ["X-Total-Count"]
+    max_age: 86400
+```
+
+#### Configuration Options
+
+| Field                | Description                                    | Default |
+| -------------------- | ---------------------------------------------- | ------- |
+| `allow_origins`      | List of allowed origins. Use `["*"]` for any. | `["*"]` |
+| `allow_origin_regex` | Regex pattern for allowed origins (optional). | `None`  |
+| `allow_methods`      | Allowed HTTP methods.                          | `["*"]` |
+| `allow_headers`      | Allowed headers.                               | `["*"]` |
+| `allow_credentials`  | Allow credentials (cookies, auth headers).    | `false` |
+| `expose_headers`     | Headers exposed to browser.                   | `[]`    |
+| `max_age`            | Preflight cache time (seconds).               | `600`   |
+
+**Security Notes**:
+- `allow_credentials: true` requires explicit origins (no wildcards)
+- `cors: true` enables localhost access only (secure for development)
+- For public APIs, always specify exact allowed origins
+
 ## Extending to handle Safety

 Configuring Safety can be a little involved so it is instructive to go through an example.
--- a/docs/source/distributions/importing_as_library.md
+++ b/docs/source/distributions/importing_as_library.md
@ -17,7 +17,6 @@ client = LlamaStackAsLibraryClient(
    # provider_data is optional, but if you need to pass in any provider specific data, you can do so here.
    provider_data={"tavily_search_api_key": os.environ["TAVILY_SEARCH_API_KEY"]},
 )
-client.initialize()
 ```

 This will parse your config and set up any inline implementations and remote clients needed for your implementation.
@ -32,5 +31,4 @@ If you've created a [custom distribution](https://llama-stack.readthedocs.io/en/

 ```python
 client = LlamaStackAsLibraryClient(config_path)
-client.initialize()
 ```
--- a/docs/source/providers/batches/index.md
+++ b/docs/source/providers/batches/index.md
@ -2,13 +2,16 @@

 ## Overview

-Protocol for batch processing API operations.
-
 The Batches API enables efficient processing of multiple requests in a single operation,
-particularly useful for processing large datasets, batch evaluation workflows, and
-cost-effective inference at scale.
+    particularly useful for processing large datasets, batch evaluation workflows, and
+    cost-effective inference at scale.

-Note: This API is currently under active development and may undergo changes.
+    The API is designed to allow use of openai client libraries for seamless integration.
+
+    This API provides the following extensions:
+     - idempotent batch creation
+
+    Note: This API is currently under active development and may undergo changes.

 This section contains documentation for all available providers for the **batches** API.

--- a/docs/source/providers/files/index.md
+++ b/docs/source/providers/files/index.md
@ -10,4 +10,5 @@ This section contains documentation for all available providers for the **files*
 :maxdepth: 1

 inline_localfs
+remote_s3
 ```
--- a/docs/source/providers/files/remote_s3.md
+++ b/docs/source/providers/files/remote_s3.md
@ -0,0 +1,33 @@
+# remote::s3
+
+## Description
+
+AWS S3-based file storage provider for scalable cloud file management with metadata persistence.
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `bucket_name` | `<class 'str'>` | No |  | S3 bucket name to store files |
+| `region` | `<class 'str'>` | No | us-east-1 | AWS region where the bucket is located |
+| `aws_access_key_id` | `str \| None` | No |  | AWS access key ID (optional if using IAM roles) |
+| `aws_secret_access_key` | `str \| None` | No |  | AWS secret access key (optional if using IAM roles) |
+| `endpoint_url` | `str \| None` | No |  | Custom S3 endpoint URL (for MinIO, LocalStack, etc.) |
+| `auto_create_bucket` | `<class 'bool'>` | No | False | Automatically create the S3 bucket if it doesn't exist |
+| `metadata_store` | `utils.sqlstore.sqlstore.SqliteSqlStoreConfig \| utils.sqlstore.sqlstore.PostgresSqlStoreConfig` | No | sqlite | SQL store configuration for file metadata |
+
+## Sample Configuration
+
+```yaml
+bucket_name: ${env.S3_BUCKET_NAME}
+region: ${env.AWS_REGION:=us-east-1}
+aws_access_key_id: ${env.AWS_ACCESS_KEY_ID:=}
+aws_secret_access_key: ${env.AWS_SECRET_ACCESS_KEY:=}
+endpoint_url: ${env.S3_ENDPOINT_URL:=}
+auto_create_bucket: ${env.S3_AUTO_CREATE_BUCKET:=false}
+metadata_store:
+  type: sqlite
+  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/dummy}/s3_files_metadata.db
+
+```
+
--- a/docs/source/providers/post_training/index.md
+++ b/docs/source/providers/post_training/index.md
@ -9,7 +9,9 @@ This section contains documentation for all available providers for the **post_t
 ```{toctree}
 :maxdepth: 1

-inline_huggingface
-inline_torchtune
+inline_huggingface-cpu
+inline_huggingface-gpu
+inline_torchtune-cpu
+inline_torchtune-gpu
 remote_nvidia
 ```
--- a/docs/source/providers/post_training/inline_huggingface-cpu.md
+++ b/docs/source/providers/post_training/inline_huggingface-cpu.md
@ -0,0 +1,41 @@
+# inline::huggingface-cpu
+
+## Description
+
+HuggingFace-based post-training provider for fine-tuning models using the HuggingFace ecosystem.
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `device` | `<class 'str'>` | No | cuda |  |
+| `distributed_backend` | `Literal['fsdp', 'deepspeed'` | No |  |  |
+| `checkpoint_format` | `Literal['full_state', 'huggingface'` | No | huggingface |  |
+| `chat_template` | `<class 'str'>` | No | <|user|>
+{input}
+<|assistant|>
+{output} |  |
+| `model_specific_config` | `<class 'dict'>` | No | {'trust_remote_code': True, 'attn_implementation': 'sdpa'} |  |
+| `max_seq_length` | `<class 'int'>` | No | 2048 |  |
+| `gradient_checkpointing` | `<class 'bool'>` | No | False |  |
+| `save_total_limit` | `<class 'int'>` | No | 3 |  |
+| `logging_steps` | `<class 'int'>` | No | 10 |  |
+| `warmup_ratio` | `<class 'float'>` | No | 0.1 |  |
+| `weight_decay` | `<class 'float'>` | No | 0.01 |  |
+| `dataloader_num_workers` | `<class 'int'>` | No | 4 |  |
+| `dataloader_pin_memory` | `<class 'bool'>` | No | True |  |
+| `dpo_beta` | `<class 'float'>` | No | 0.1 |  |
+| `use_reference_model` | `<class 'bool'>` | No | True |  |
+| `dpo_loss_type` | `Literal['sigmoid', 'hinge', 'ipo', 'kto_pair'` | No | sigmoid |  |
+| `dpo_output_dir` | `<class 'str'>` | No |  |  |
+
+## Sample Configuration
+
+```yaml
+checkpoint_format: huggingface
+distributed_backend: null
+device: cpu
+dpo_output_dir: ~/.llama/dummy/dpo_output
+
+```
+
--- a/docs/source/providers/post_training/inline_huggingface-gpu.md
+++ b/docs/source/providers/post_training/inline_huggingface-gpu.md
@ -0,0 +1,41 @@
+# inline::huggingface-gpu
+
+## Description
+
+HuggingFace-based post-training provider for fine-tuning models using the HuggingFace ecosystem.
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `device` | `<class 'str'>` | No | cuda |  |
+| `distributed_backend` | `Literal['fsdp', 'deepspeed'` | No |  |  |
+| `checkpoint_format` | `Literal['full_state', 'huggingface'` | No | huggingface |  |
+| `chat_template` | `<class 'str'>` | No | <|user|>
+{input}
+<|assistant|>
+{output} |  |
+| `model_specific_config` | `<class 'dict'>` | No | {'trust_remote_code': True, 'attn_implementation': 'sdpa'} |  |
+| `max_seq_length` | `<class 'int'>` | No | 2048 |  |
+| `gradient_checkpointing` | `<class 'bool'>` | No | False |  |
+| `save_total_limit` | `<class 'int'>` | No | 3 |  |
+| `logging_steps` | `<class 'int'>` | No | 10 |  |
+| `warmup_ratio` | `<class 'float'>` | No | 0.1 |  |
+| `weight_decay` | `<class 'float'>` | No | 0.01 |  |
+| `dataloader_num_workers` | `<class 'int'>` | No | 4 |  |
+| `dataloader_pin_memory` | `<class 'bool'>` | No | True |  |
+| `dpo_beta` | `<class 'float'>` | No | 0.1 |  |
+| `use_reference_model` | `<class 'bool'>` | No | True |  |
+| `dpo_loss_type` | `Literal['sigmoid', 'hinge', 'ipo', 'kto_pair'` | No | sigmoid |  |
+| `dpo_output_dir` | `<class 'str'>` | No |  |  |
+
+## Sample Configuration
+
+```yaml
+checkpoint_format: huggingface
+distributed_backend: null
+device: cpu
+dpo_output_dir: ~/.llama/dummy/dpo_output
+
+```
+
--- a/docs/source/providers/post_training/inline_torchtune-cpu.md
+++ b/docs/source/providers/post_training/inline_torchtune-cpu.md
@ -0,0 +1,20 @@
+# inline::torchtune-cpu
+
+## Description
+
+TorchTune-based post-training provider for fine-tuning and optimizing models using Meta's TorchTune framework.
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `torch_seed` | `int \| None` | No |  |  |
+| `checkpoint_format` | `Literal['meta', 'huggingface'` | No | meta |  |
+
+## Sample Configuration
+
+```yaml
+checkpoint_format: meta
+
+```
+
--- a/docs/source/providers/post_training/inline_torchtune-gpu.md
+++ b/docs/source/providers/post_training/inline_torchtune-gpu.md
@ -0,0 +1,20 @@
+# inline::torchtune-gpu
+
+## Description
+
+TorchTune-based post-training provider for fine-tuning and optimizing models using Meta's TorchTune framework.
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `torch_seed` | `int \| None` | No |  |  |
+| `checkpoint_format` | `Literal['meta', 'huggingface'` | No | meta |  |
+
+## Sample Configuration
+
+```yaml
+checkpoint_format: meta
+
+```
+
--- a/llama_stack/apis/batches/batches.py
+++ b/llama_stack/apis/batches/batches.py
@ -29,12 +29,16 @@ class ListBatchesResponse(BaseModel):

@runtime_checkable
 class Batches(Protocol):
-    """Protocol for batch processing API operations.
-
+    """
    The Batches API enables efficient processing of multiple requests in a single operation,
    particularly useful for processing large datasets, batch evaluation workflows, and
    cost-effective inference at scale.

+    The API is designed to allow use of openai client libraries for seamless integration.
+
+    This API provides the following extensions:
+     - idempotent batch creation
+
    Note: This API is currently under active development and may undergo changes.
    """

@ -45,6 +49,7 @@ class Batches(Protocol):
        endpoint: str,
        completion_window: Literal["24h"],
        metadata: dict[str, str] | None = None,
+        idempotency_key: str | None = None,
    ) -> BatchObject:
        """Create a new batch for processing multiple API requests.

@ -52,6 +57,7 @@ class Batches(Protocol):
        :param endpoint: The endpoint to be used for all requests in the batch.
        :param completion_window: The time window within which the batch should be processed.
        :param metadata: Optional metadata for the batch.
+        :param idempotency_key: Optional idempotency key. When provided, enables idempotent behavior.
        :returns: The created batch object.
        """
        ...
--- a/llama_stack/apis/inference/inference.py
+++ b/llama_stack/apis/inference/inference.py
@ -473,6 +473,28 @@ class EmbeddingsResponse(BaseModel):
    embeddings: list[list[float]]


+@json_schema_type
+class RerankData(BaseModel):
+    """A single rerank result from a reranking response.
+
+    :param index: The original index of the document in the input list
+    :param relevance_score: The relevance score from the model output. Values are inverted when applicable so that higher scores indicate greater relevance.
+    """
+
+    index: int
+    relevance_score: float
+
+
+@json_schema_type
+class RerankResponse(BaseModel):
+    """Response from a reranking request.
+
+    :param data: List of rerank result objects, sorted by relevance score (descending)
+    """
+
+    data: list[RerankData]
+
+
@json_schema_type
 class OpenAIChatCompletionContentPartTextParam(BaseModel):
    """Text content part for OpenAI-compatible chat completion messages.
@ -1046,6 +1068,7 @@ class InferenceProvider(Protocol):
        :returns: A BatchCompletionResponse with the full completions.
        """
        raise NotImplementedError("Batch completion is not implemented")
+        return  # this is so mypy's safe-super rule will consider the method concrete

    @webmethod(route="/inference/chat-completion", method="POST")
    async def chat_completion(
@ -1110,6 +1133,7 @@ class InferenceProvider(Protocol):
        :returns: A BatchChatCompletionResponse with the full completions.
        """
        raise NotImplementedError("Batch chat completion is not implemented")
+        return  # this is so mypy's safe-super rule will consider the method concrete

    @webmethod(route="/inference/embeddings", method="POST")
    async def embeddings(
@ -1131,6 +1155,25 @@ class InferenceProvider(Protocol):
        """
        ...

+    @webmethod(route="/inference/rerank", method="POST", experimental=True)
+    async def rerank(
+        self,
+        model: str,
+        query: str | OpenAIChatCompletionContentPartTextParam | OpenAIChatCompletionContentPartImageParam,
+        items: list[str | OpenAIChatCompletionContentPartTextParam | OpenAIChatCompletionContentPartImageParam],
+        max_num_results: int | None = None,
+    ) -> RerankResponse:
+        """Rerank a list of documents based on their relevance to a query.
+
+        :param model: The identifier of the reranking model to use.
+        :param query: The search query to rank items against. Can be a string, text content part, or image content part. The input must not exceed the model's max input token length.
+        :param items: List of items to rerank. Each item can be a string, text content part, or image content part. Each input must not exceed the model's max input token length.
+        :param max_num_results: (Optional) Maximum number of results to return. Default: returns all.
+        :returns: RerankResponse with indices sorted by relevance score (descending).
+        """
+        raise NotImplementedError("Reranking is not implemented")
+        return  # this is so mypy's safe-super rule will consider the method concrete
+
    @webmethod(route="/openai/v1/completions", method="POST")
    async def openai_completion(
        self,
--- a/llama_stack/apis/telemetry/telemetry.py
+++ b/llama_stack/apis/telemetry/telemetry.py
@ -386,6 +386,7 @@ class MetricDataPoint(BaseModel):

    timestamp: int
    value: float
+    unit: str


@json_schema_type
@ -518,7 +519,7 @@ class Telemetry(Protocol):
        metric_name: str,
        start_time: int,
        end_time: int | None = None,
-        granularity: str | None = "1d",
+        granularity: str | None = None,
        query_type: MetricQueryType = MetricQueryType.RANGE,
        label_matchers: list[MetricLabelMatcher] | None = None,
    ) -> QueryMetricsResponse:
--- a/llama_stack/cli/stack/run.py
+++ b/llama_stack/cli/stack/run.py
@ -15,7 +15,7 @@ from llama_stack.log import get_logger

 REPO_ROOT = Path(__file__).parent.parent.parent.parent

-logger = get_logger(name=__name__, category="server")
+logger = get_logger(name=__name__, category="cli")


 class StackRun(Subcommand):
--- a/llama_stack/core/build.py
+++ b/llama_stack/core/build.py
@ -5,7 +5,6 @@
 # the root directory of this source tree.

 import importlib.resources
-import logging
 import sys

 from pydantic import BaseModel
@ -17,9 +16,10 @@ from llama_stack.core.external import load_external_apis
 from llama_stack.core.utils.exec import run_command
 from llama_stack.core.utils.image_types import LlamaStackImageType
 from llama_stack.distributions.template import DistributionTemplate
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import Api

-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="core")

 # These are the dependencies needed by the distribution server.
 # `llama-stack` is automatically installed by the installation script.
--- a/llama_stack/core/configure.py
+++ b/llama_stack/core/configure.py
@ -3,7 +3,6 @@
 #
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
-import logging
 import textwrap
 from typing import Any

@ -21,9 +20,10 @@ from llama_stack.core.stack import cast_image_name_to_string, replace_env_vars
 from llama_stack.core.utils.config_dirs import EXTERNAL_PROVIDERS_DIR
 from llama_stack.core.utils.dynamic import instantiate_class_type
 from llama_stack.core.utils.prompt_for_config import prompt_for_config
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import Api, ProviderSpec

-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="core")


 def configure_single_provider(registry: dict[str, ProviderSpec], provider: Provider) -> Provider:
--- a/llama_stack/core/datatypes.py
+++ b/llama_stack/core/datatypes.py
@ -318,6 +318,41 @@ class QuotaConfig(BaseModel):
    period: QuotaPeriod = Field(default=QuotaPeriod.DAY, description="Quota period to set")


+class CORSConfig(BaseModel):
+    allow_origins: list[str] = Field(default_factory=list)
+    allow_origin_regex: str | None = Field(default=None)
+    allow_methods: list[str] = Field(default=["OPTIONS"])
+    allow_headers: list[str] = Field(default_factory=list)
+    allow_credentials: bool = Field(default=False)
+    expose_headers: list[str] = Field(default_factory=list)
+    max_age: int = Field(default=600, ge=0)
+
+    @model_validator(mode="after")
+    def validate_credentials_config(self) -> Self:
+        if self.allow_credentials and (self.allow_origins == ["*"] or "*" in self.allow_origins):
+            raise ValueError("Cannot use wildcard origins with credentials enabled")
+        return self
+
+
+def process_cors_config(cors_config: bool | CORSConfig | None) -> CORSConfig | None:
+    if cors_config is False or cors_config is None:
+        return None
+
+    if cors_config is True:
+        # dev mode: allow localhost on any port
+        return CORSConfig(
+            allow_origins=[],
+            allow_origin_regex=r"https?://localhost:\d+",
+            allow_methods=["GET", "POST", "PUT", "DELETE", "OPTIONS"],
+            allow_headers=["Content-Type", "Authorization", "X-Requested-With"],
+        )
+
+    if isinstance(cors_config, CORSConfig):
+        return cors_config
+
+    raise ValueError(f"Expected bool or CORSConfig, got {type(cors_config).__name__}")
+
+
 class ServerConfig(BaseModel):
    port: int = Field(
        default=8321,
@ -349,6 +384,12 @@ class ServerConfig(BaseModel):
        default=None,
        description="Per client quota request configuration",
    )
+    cors: bool | CORSConfig | None = Field(
+        default=None,
+        description="CORS configuration for cross-origin requests. Can be:\n"
+        "- true: Enable localhost CORS for development\n"
+        "- {allow_origins: [...], allow_methods: [...], ...}: Full configuration",
+    )


 class StackRunConfig(BaseModel):
--- a/llama_stack/core/library_client.py
+++ b/llama_stack/core/library_client.py
@ -7,7 +7,7 @@
 import asyncio
 import inspect
 import json
-import logging
+import logging  # allow-direct-logging
 import os
 import sys
 from concurrent.futures import ThreadPoolExecutor
@ -48,6 +48,7 @@ from llama_stack.core.stack import (
 from llama_stack.core.utils.config import redact_sensitive_fields
 from llama_stack.core.utils.context import preserve_contexts_async_generator
 from llama_stack.core.utils.exec import in_notebook
+from llama_stack.log import get_logger
 from llama_stack.providers.utils.telemetry.tracing import (
    CURRENT_TRACE_CONTEXT,
    end_trace,
@ -55,7 +56,7 @@ from llama_stack.providers.utils.telemetry.tracing import (
    start_trace,
 )

-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="core")

 T = TypeVar("T")

@ -145,39 +146,26 @@ class LlamaStackAsLibraryClient(LlamaStackClient):
    ):
        super().__init__()
        self.async_client = AsyncLlamaStackAsLibraryClient(
-            config_path_or_distro_name, custom_provider_registry, provider_data
+            config_path_or_distro_name, custom_provider_registry, provider_data, skip_logger_removal
        )
        self.pool_executor = ThreadPoolExecutor(max_workers=4)
-        self.skip_logger_removal = skip_logger_removal
        self.provider_data = provider_data

        self.loop = asyncio.new_event_loop()

-    def initialize(self):
-        if in_notebook():
-            import nest_asyncio
-
-            nest_asyncio.apply()
-            if not self.skip_logger_removal:
-                self._remove_root_logger_handlers()
-
        # use a new event loop to avoid interfering with the main event loop
        loop = asyncio.new_event_loop()
        asyncio.set_event_loop(loop)
        try:
-            return loop.run_until_complete(self.async_client.initialize())
+            loop.run_until_complete(self.async_client.initialize())
        finally:
            asyncio.set_event_loop(None)

-    def _remove_root_logger_handlers(self):
+    def initialize(self):
        """
-        Remove all handlers from the root logger. Needed to avoid polluting the console with logs.
+        Deprecated method for backward compatibility.
        """
-        root_logger = logging.getLogger()
-
-        for handler in root_logger.handlers[:]:
-            root_logger.removeHandler(handler)
-            logger.info(f"Removed handler {handler.__class__.__name__} from root logger")
+        pass

    def request(self, *args, **kwargs):
        loop = self.loop
@ -215,6 +203,7 @@ class AsyncLlamaStackAsLibraryClient(AsyncLlamaStackClient):
        config_path_or_distro_name: str,
        custom_provider_registry: ProviderRegistry | None = None,
        provider_data: dict[str, Any] | None = None,
+        skip_logger_removal: bool = False,
    ):
        super().__init__()
        # when using the library client, we should not log to console since many
@ -222,6 +211,13 @@ class AsyncLlamaStackAsLibraryClient(AsyncLlamaStackClient):
        current_sinks = os.environ.get("TELEMETRY_SINKS", "sqlite").split(",")
        os.environ["TELEMETRY_SINKS"] = ",".join(sink for sink in current_sinks if sink != "console")

+        if in_notebook():
+            import nest_asyncio
+
+            nest_asyncio.apply()
+            if not skip_logger_removal:
+                self._remove_root_logger_handlers()
+
        if config_path_or_distro_name.endswith(".yaml"):
            config_path = Path(config_path_or_distro_name)
            if not config_path.exists():
@ -238,7 +234,24 @@ class AsyncLlamaStackAsLibraryClient(AsyncLlamaStackClient):
        self.provider_data = provider_data
        self.route_impls: RouteImpls | None = None  # Initialize to None to prevent AttributeError

+    def _remove_root_logger_handlers(self):
+        """
+        Remove all handlers from the root logger. Needed to avoid polluting the console with logs.
+        """
+        root_logger = logging.getLogger()
+
+        for handler in root_logger.handlers[:]:
+            root_logger.removeHandler(handler)
+            logger.info(f"Removed handler {handler.__class__.__name__} from root logger")
+
    async def initialize(self) -> bool:
+        """
+        Initialize the async client.
+
+        Returns:
+            bool: True if initialization was successful
+        """
+
        try:
            self.route_impls = None
            self.impls = await construct_stack(self.config, self.custom_provider_registry)
--- a/llama_stack/core/request_headers.py
+++ b/llama_stack/core/request_headers.py
@ -6,15 +6,15 @@

 import contextvars
 import json
-import logging
 from contextlib import AbstractContextManager
 from typing import Any

 from llama_stack.core.datatypes import User
+from llama_stack.log import get_logger

 from .utils.dynamic import instantiate_class_type

-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="core")

 # Context variable for request provider data and auth attributes
 PROVIDER_DATA_VAR = contextvars.ContextVar("provider_data", default=None)
--- a/llama_stack/core/routers/datasets.py
+++ b/llama_stack/core/routers/datasets.py
@ -12,7 +12,7 @@ from llama_stack.apis.datasets import DatasetPurpose, DataSource
 from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import RoutingTable

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routers")


 class DatasetIORouter(DatasetIO):
--- a/llama_stack/core/routers/eval_scoring.py
+++ b/llama_stack/core/routers/eval_scoring.py
@ -16,7 +16,7 @@ from llama_stack.apis.scoring import (
 from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import RoutingTable

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routers")


 class ScoringRouter(Scoring):
--- a/llama_stack/core/routers/inference.py
+++ b/llama_stack/core/routers/inference.py
@ -65,7 +65,7 @@ from llama_stack.providers.datatypes import HealthResponse, HealthStatus, Routin
 from llama_stack.providers.utils.inference.inference_store import InferenceStore
 from llama_stack.providers.utils.telemetry.tracing import get_current_span

-logger = get_logger(name=__name__, category="inference")
+logger = get_logger(name=__name__, category="core::routers")


 class InferenceRouter(Inference):
--- a/llama_stack/core/routers/safety.py
+++ b/llama_stack/core/routers/safety.py
@ -13,7 +13,7 @@ from llama_stack.apis.shields import Shield
 from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import RoutingTable

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routers")


 class SafetyRouter(Safety):
--- a/llama_stack/core/routers/tool_runtime.py
+++ b/llama_stack/core/routers/tool_runtime.py
@ -22,7 +22,7 @@ from llama_stack.log import get_logger

 from ..routing_tables.toolgroups import ToolGroupsRoutingTable

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routers")


 class ToolRuntimeRouter(ToolRuntime):
--- a/llama_stack/core/routers/vector_io.py
+++ b/llama_stack/core/routers/vector_io.py
@ -30,7 +30,7 @@ from llama_stack.apis.vector_io import (
 from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import HealthResponse, HealthStatus, RoutingTable

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routers")


 class VectorIORouter(VectorIO):
--- a/llama_stack/core/routing_tables/benchmarks.py
+++ b/llama_stack/core/routing_tables/benchmarks.py
@ -14,7 +14,7 @@ from llama_stack.log import get_logger

 from .common import CommonRoutingTableImpl

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routing_tables")


 class BenchmarksRoutingTable(CommonRoutingTableImpl, Benchmarks):
--- a/llama_stack/core/routing_tables/common.py
+++ b/llama_stack/core/routing_tables/common.py
@ -23,7 +23,7 @@ from llama_stack.core.store import DistributionRegistry
 from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import Api, RoutingTable

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routing_tables")


 def get_impl_api(p: Any) -> Api:
--- a/llama_stack/core/routing_tables/datasets.py
+++ b/llama_stack/core/routing_tables/datasets.py
@ -26,7 +26,7 @@ from llama_stack.log import get_logger

 from .common import CommonRoutingTableImpl

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routing_tables")


 class DatasetsRoutingTable(CommonRoutingTableImpl, Datasets):
--- a/llama_stack/core/routing_tables/models.py
+++ b/llama_stack/core/routing_tables/models.py
@ -17,7 +17,7 @@ from llama_stack.log import get_logger

 from .common import CommonRoutingTableImpl, lookup_model

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routing_tables")


 class ModelsRoutingTable(CommonRoutingTableImpl, Models):
--- a/llama_stack/core/routing_tables/scoring_functions.py
+++ b/llama_stack/core/routing_tables/scoring_functions.py
@ -19,7 +19,7 @@ from llama_stack.log import get_logger

 from .common import CommonRoutingTableImpl

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routing_tables")


 class ScoringFunctionsRoutingTable(CommonRoutingTableImpl, ScoringFunctions):
--- a/llama_stack/core/routing_tables/shields.py
+++ b/llama_stack/core/routing_tables/shields.py
@ -15,7 +15,7 @@ from llama_stack.log import get_logger

 from .common import CommonRoutingTableImpl

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routing_tables")


 class ShieldsRoutingTable(CommonRoutingTableImpl, Shields):
--- a/llama_stack/core/routing_tables/toolgroups.py
+++ b/llama_stack/core/routing_tables/toolgroups.py
@ -14,7 +14,7 @@ from llama_stack.log import get_logger

 from .common import CommonRoutingTableImpl

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routing_tables")


 def parse_toolgroup_from_toolgroup_name_pair(toolgroup_name_with_maybe_tool_name: str) -> str | None:
--- a/llama_stack/core/routing_tables/vector_dbs.py
+++ b/llama_stack/core/routing_tables/vector_dbs.py
@ -30,7 +30,7 @@ from llama_stack.log import get_logger

 from .common import CommonRoutingTableImpl, lookup_model

-logger = get_logger(name=__name__, category="core")
+logger = get_logger(name=__name__, category="core::routing_tables")


 class VectorDBsRoutingTable(CommonRoutingTableImpl, VectorDBs):
--- a/llama_stack/core/server/auth.py
+++ b/llama_stack/core/server/auth.py
@ -15,7 +15,7 @@ from llama_stack.core.server.auth_providers import create_auth_provider
 from llama_stack.core.server.routes import find_matching_route, initialize_route_impls
 from llama_stack.log import get_logger

-logger = get_logger(name=__name__, category="auth")
+logger = get_logger(name=__name__, category="core::auth")


 class AuthenticationMiddleware:
--- a/llama_stack/core/server/auth_providers.py
+++ b/llama_stack/core/server/auth_providers.py
@ -23,7 +23,7 @@ from llama_stack.core.datatypes import (
 )
 from llama_stack.log import get_logger

-logger = get_logger(name=__name__, category="auth")
+logger = get_logger(name=__name__, category="core::auth")


 class AuthResponse(BaseModel):
--- a/llama_stack/core/server/quota.py
+++ b/llama_stack/core/server/quota.py
@ -15,7 +15,7 @@ from llama_stack.providers.utils.kvstore.api import KVStore
 from llama_stack.providers.utils.kvstore.config import KVStoreConfig, SqliteKVStoreConfig
 from llama_stack.providers.utils.kvstore.kvstore import kvstore_impl

-logger = get_logger(name=__name__, category="quota")
+logger = get_logger(name=__name__, category="core::server")


 class QuotaMiddleware:
--- a/llama_stack/core/server/server.py
+++ b/llama_stack/core/server/server.py
@ -9,7 +9,7 @@ import asyncio
 import functools
 import inspect
 import json
-import logging
+import logging  # allow-direct-logging
 import os
 import ssl
 import sys
@ -28,6 +28,7 @@ from aiohttp import hdrs
 from fastapi import Body, FastAPI, HTTPException, Request, Response
 from fastapi import Path as FastapiPath
 from fastapi.exceptions import RequestValidationError
+from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse, StreamingResponse
 from openai import BadRequestError
 from pydantic import BaseModel, ValidationError
@ -40,6 +41,7 @@ from llama_stack.core.datatypes import (
    AuthenticationRequiredError,
    LoggingConfig,
    StackRunConfig,
+    process_cors_config,
 )
 from llama_stack.core.distribution import builtin_automatically_routed_apis
 from llama_stack.core.external import ExternalApiSpec, load_external_apis
@ -82,7 +84,7 @@ from .quota import QuotaMiddleware

 REPO_ROOT = Path(__file__).parent.parent.parent.parent

-logger = get_logger(name=__name__, category="server")
+logger = get_logger(name=__name__, category="core::server")


 def warn_with_traceback(message, category, filename, lineno, file=None, line=None):
@ -413,7 +415,7 @@ def main(args: argparse.Namespace | None = None):
        config_contents = yaml.safe_load(fp)
        if isinstance(config_contents, dict) and (cfg := config_contents.get("logging_config")):
            logger_config = LoggingConfig(**cfg)
-        logger = get_logger(name=__name__, category="server", config=logger_config)
+        logger = get_logger(name=__name__, category="core::server", config=logger_config)
        if args.env:
            for env_pair in args.env:
                try:
@ -483,6 +485,12 @@ def main(args: argparse.Namespace | None = None):
            window_seconds=window_seconds,
        )

+    if config.server.cors:
+        logger.info("Enabling CORS")
+        cors_config = process_cors_config(config.server.cors)
+        if cors_config:
+            app.add_middleware(CORSMiddleware, **cors_config.model_dump())
+
    if Api.telemetry in impls:
        setup_logger(impls[Api.telemetry])
    else:
--- a/llama_stack/core/store/registry.py
+++ b/llama_stack/core/store/registry.py
@ -16,7 +16,7 @@ from llama_stack.log import get_logger
 from llama_stack.providers.utils.kvstore import KVStore, kvstore_impl
 from llama_stack.providers.utils.kvstore.config import KVStoreConfig, SqliteKVStoreConfig

-logger = get_logger(__name__, category="core")
+logger = get_logger(__name__, category="core::registry")


 class DistributionRegistry(Protocol):
--- a/llama_stack/core/utils/config_resolution.py
+++ b/llama_stack/core/utils/config_resolution.py
@ -10,7 +10,7 @@ from pathlib import Path
 from llama_stack.core.utils.config_dirs import DISTRIBS_BASE_DIR
 from llama_stack.log import get_logger

-logger = get_logger(name=__name__, category="config_resolution")
+logger = get_logger(name=__name__, category="core")


 DISTRO_DIR = Path(__file__).parent.parent.parent.parent / "llama_stack" / "distributions"
--- a/llama_stack/core/utils/exec.py
+++ b/llama_stack/core/utils/exec.py
@ -4,7 +4,7 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.

-import logging
+import importlib
 import os
 import signal
 import subprocess
@ -12,9 +12,9 @@ import sys

 from termcolor import cprint

-log = logging.getLogger(__name__)
+from llama_stack.log import get_logger

-import importlib
+log = get_logger(name=__name__, category="core")


 def formulate_run_args(image_type: str, image_name: str) -> list:
--- a/llama_stack/core/utils/prompt_for_config.py
+++ b/llama_stack/core/utils/prompt_for_config.py
@ -6,7 +6,6 @@

 import inspect
 import json
-import logging
 from enum import Enum
 from typing import Annotated, Any, Literal, Union, get_args, get_origin

@ -14,7 +13,9 @@ from pydantic import BaseModel
 from pydantic.fields import FieldInfo
 from pydantic_core import PydanticUndefinedType

-log = logging.getLogger(__name__)
+from llama_stack.log import get_logger
+
+log = get_logger(name=__name__, category="core")


 def is_list_of_primitives(field_type):
--- a/llama_stack/distributions/ci-tests/build.yaml
+++ b/llama_stack/distributions/ci-tests/build.yaml
@ -34,7 +34,7 @@ distribution_spec:
    telemetry:
    - provider_type: inline::meta-reference
    post_training:
-    - provider_type: inline::huggingface
+    - provider_type: inline::huggingface-cpu
    eval:
    - provider_type: inline::meta-reference
    datasetio:
--- a/llama_stack/distributions/ci-tests/run.yaml
+++ b/llama_stack/distributions/ci-tests/run.yaml
@ -156,8 +156,8 @@ providers:
      sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ci-tests}/trace_store.db
      otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
  post_training:
-  - provider_id: huggingface
-    provider_type: inline::huggingface
+  - provider_id: huggingface-cpu
+    provider_type: inline::huggingface-cpu
    config:
      checkpoint_format: huggingface
      distributed_backend: null
--- a/llama_stack/distributions/starter-gpu/init.py
+++ b/llama_stack/distributions/starter-gpu/init.py
@ -0,0 +1,7 @@
+# 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.
+
+from .starter_gpu import get_distribution_template  # noqa: F401
--- a/llama_stack/distributions/starter-gpu/build.yaml
+++ b/llama_stack/distributions/starter-gpu/build.yaml
@ -0,0 +1,59 @@
+version: 2
+distribution_spec:
+  description: Quick start template for running Llama Stack with several popular providers.
+    This distribution is intended for GPU-enabled environments.
+  providers:
+    inference:
+    - provider_type: remote::cerebras
+    - provider_type: remote::ollama
+    - provider_type: remote::vllm
+    - provider_type: remote::tgi
+    - provider_type: remote::fireworks
+    - provider_type: remote::together
+    - provider_type: remote::bedrock
+    - provider_type: remote::nvidia
+    - provider_type: remote::openai
+    - provider_type: remote::anthropic
+    - provider_type: remote::gemini
+    - provider_type: remote::vertexai
+    - provider_type: remote::groq
+    - provider_type: remote::sambanova
+    - provider_type: inline::sentence-transformers
+    vector_io:
+    - provider_type: inline::faiss
+    - provider_type: inline::sqlite-vec
+    - provider_type: inline::milvus
+    - provider_type: remote::chromadb
+    - provider_type: remote::pgvector
+    files:
+    - provider_type: inline::localfs
+    safety:
+    - provider_type: inline::llama-guard
+    - provider_type: inline::code-scanner
+    agents:
+    - provider_type: inline::meta-reference
+    telemetry:
+    - provider_type: inline::meta-reference
+    post_training:
+    - provider_type: inline::torchtune-gpu
+    eval:
+    - provider_type: inline::meta-reference
+    datasetio:
+    - provider_type: remote::huggingface
+    - provider_type: inline::localfs
+    scoring:
+    - provider_type: inline::basic
+    - provider_type: inline::llm-as-judge
+    - provider_type: inline::braintrust
+    tool_runtime:
+    - provider_type: remote::brave-search
+    - provider_type: remote::tavily-search
+    - provider_type: inline::rag-runtime
+    - provider_type: remote::model-context-protocol
+    batches:
+    - provider_type: inline::reference
+image_type: venv
+additional_pip_packages:
+- aiosqlite
+- asyncpg
+- sqlalchemy[asyncio]
--- a/llama_stack/distributions/starter-gpu/run.yaml
+++ b/llama_stack/distributions/starter-gpu/run.yaml
@ -0,0 +1,238 @@
+version: 2
+image_name: starter-gpu
+apis:
+- agents
+- batches
+- datasetio
+- eval
+- files
+- inference
+- post_training
+- safety
+- scoring
+- telemetry
+- tool_runtime
+- vector_io
+providers:
+  inference:
+  - provider_id: ${env.CEREBRAS_API_KEY:+cerebras}
+    provider_type: remote::cerebras
+    config:
+      base_url: https://api.cerebras.ai
+      api_key: ${env.CEREBRAS_API_KEY:=}
+  - provider_id: ${env.OLLAMA_URL:+ollama}
+    provider_type: remote::ollama
+    config:
+      url: ${env.OLLAMA_URL:=http://localhost:11434}
+  - provider_id: ${env.VLLM_URL:+vllm}
+    provider_type: remote::vllm
+    config:
+      url: ${env.VLLM_URL:=}
+      max_tokens: ${env.VLLM_MAX_TOKENS:=4096}
+      api_token: ${env.VLLM_API_TOKEN:=fake}
+      tls_verify: ${env.VLLM_TLS_VERIFY:=true}
+  - provider_id: ${env.TGI_URL:+tgi}
+    provider_type: remote::tgi
+    config:
+      url: ${env.TGI_URL:=}
+  - provider_id: fireworks
+    provider_type: remote::fireworks
+    config:
+      url: https://api.fireworks.ai/inference/v1
+      api_key: ${env.FIREWORKS_API_KEY:=}
+  - provider_id: together
+    provider_type: remote::together
+    config:
+      url: https://api.together.xyz/v1
+      api_key: ${env.TOGETHER_API_KEY:=}
+  - provider_id: bedrock
+    provider_type: remote::bedrock
+  - provider_id: ${env.NVIDIA_API_KEY:+nvidia}
+    provider_type: remote::nvidia
+    config:
+      url: ${env.NVIDIA_BASE_URL:=https://integrate.api.nvidia.com}
+      api_key: ${env.NVIDIA_API_KEY:=}
+      append_api_version: ${env.NVIDIA_APPEND_API_VERSION:=True}
+  - provider_id: openai
+    provider_type: remote::openai
+    config:
+      api_key: ${env.OPENAI_API_KEY:=}
+      base_url: ${env.OPENAI_BASE_URL:=https://api.openai.com/v1}
+  - provider_id: anthropic
+    provider_type: remote::anthropic
+    config:
+      api_key: ${env.ANTHROPIC_API_KEY:=}
+  - provider_id: gemini
+    provider_type: remote::gemini
+    config:
+      api_key: ${env.GEMINI_API_KEY:=}
+  - provider_id: ${env.VERTEX_AI_PROJECT:+vertexai}
+    provider_type: remote::vertexai
+    config:
+      project: ${env.VERTEX_AI_PROJECT:=}
+      location: ${env.VERTEX_AI_LOCATION:=us-central1}
+  - provider_id: groq
+    provider_type: remote::groq
+    config:
+      url: https://api.groq.com
+      api_key: ${env.GROQ_API_KEY:=}
+  - provider_id: sambanova
+    provider_type: remote::sambanova
+    config:
+      url: https://api.sambanova.ai/v1
+      api_key: ${env.SAMBANOVA_API_KEY:=}
+  - provider_id: sentence-transformers
+    provider_type: inline::sentence-transformers
+  vector_io:
+  - provider_id: faiss
+    provider_type: inline::faiss
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/faiss_store.db
+  - provider_id: sqlite-vec
+    provider_type: inline::sqlite-vec
+    config:
+      db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/sqlite_vec.db
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/sqlite_vec_registry.db
+  - provider_id: ${env.MILVUS_URL:+milvus}
+    provider_type: inline::milvus
+    config:
+      db_path: ${env.MILVUS_DB_PATH:=~/.llama/distributions/starter}/milvus.db
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/milvus_registry.db
+  - provider_id: ${env.CHROMADB_URL:+chromadb}
+    provider_type: remote::chromadb
+    config:
+      url: ${env.CHROMADB_URL:=}
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter/}/chroma_remote_registry.db
+  - provider_id: ${env.PGVECTOR_DB:+pgvector}
+    provider_type: remote::pgvector
+    config:
+      host: ${env.PGVECTOR_HOST:=localhost}
+      port: ${env.PGVECTOR_PORT:=5432}
+      db: ${env.PGVECTOR_DB:=}
+      user: ${env.PGVECTOR_USER:=}
+      password: ${env.PGVECTOR_PASSWORD:=}
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/pgvector_registry.db
+  files:
+  - provider_id: meta-reference-files
+    provider_type: inline::localfs
+    config:
+      storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/starter/files}
+      metadata_store:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/files_metadata.db
+  safety:
+  - provider_id: llama-guard
+    provider_type: inline::llama-guard
+    config:
+      excluded_categories: []
+  - provider_id: code-scanner
+    provider_type: inline::code-scanner
+  agents:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      persistence_store:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/agents_store.db
+      responses_store:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/responses_store.db
+  telemetry:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
+      sinks: ${env.TELEMETRY_SINKS:=console,sqlite}
+      sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/trace_store.db
+      otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
+  post_training:
+  - provider_id: torchtune-gpu
+    provider_type: inline::torchtune-gpu
+    config:
+      checkpoint_format: meta
+  eval:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/meta_reference_eval.db
+  datasetio:
+  - provider_id: huggingface
+    provider_type: remote::huggingface
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/huggingface_datasetio.db
+  - provider_id: localfs
+    provider_type: inline::localfs
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/localfs_datasetio.db
+  scoring:
+  - provider_id: basic
+    provider_type: inline::basic
+  - provider_id: llm-as-judge
+    provider_type: inline::llm-as-judge
+  - provider_id: braintrust
+    provider_type: inline::braintrust
+    config:
+      openai_api_key: ${env.OPENAI_API_KEY:=}
+  tool_runtime:
+  - provider_id: brave-search
+    provider_type: remote::brave-search
+    config:
+      api_key: ${env.BRAVE_SEARCH_API_KEY:=}
+      max_results: 3
+  - provider_id: tavily-search
+    provider_type: remote::tavily-search
+    config:
+      api_key: ${env.TAVILY_SEARCH_API_KEY:=}
+      max_results: 3
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
+  batches:
+  - provider_id: reference
+    provider_type: inline::reference
+    config:
+      kvstore:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/batches.db
+metadata_store:
+  type: sqlite
+  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/registry.db
+inference_store:
+  type: sqlite
+  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/inference_store.db
+models: []
+shields:
+- shield_id: llama-guard
+  provider_id: ${env.SAFETY_MODEL:+llama-guard}
+  provider_shield_id: ${env.SAFETY_MODEL:=}
+- shield_id: code-scanner
+  provider_id: ${env.CODE_SCANNER_MODEL:+code-scanner}
+  provider_shield_id: ${env.CODE_SCANNER_MODEL:=}
+vector_dbs: []
+datasets: []
+scoring_fns: []
+benchmarks: []
+tool_groups:
+- toolgroup_id: builtin::websearch
+  provider_id: tavily-search
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
+server:
+  port: 8321
--- a/llama_stack/distributions/starter-gpu/starter_gpu.py
+++ b/llama_stack/distributions/starter-gpu/starter_gpu.py
@ -0,0 +1,22 @@
+# 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.
+
+
+from llama_stack.distributions.template import BuildProvider, DistributionTemplate
+
+from ..starter.starter import get_distribution_template as get_starter_distribution_template
+
+
+def get_distribution_template() -> DistributionTemplate:
+    template = get_starter_distribution_template()
+    name = "starter-gpu"
+    template.name = name
+    template.description = "Quick start template for running Llama Stack with several popular providers. This distribution is intended for GPU-enabled environments."
+
+    template.providers["post_training"] = [
+        BuildProvider(provider_type="inline::torchtune-gpu"),
+    ]
+    return template
--- a/llama_stack/distributions/starter/build.yaml
+++ b/llama_stack/distributions/starter/build.yaml
@ -1,6 +1,7 @@
 version: 2
 distribution_spec:
-  description: Quick start template for running Llama Stack with several popular providers
+  description: Quick start template for running Llama Stack with several popular providers.
+    This distribution is intended for CPU-only environments.
  providers:
    inference:
    - provider_type: remote::cerebras
@ -34,7 +35,7 @@ distribution_spec:
    telemetry:
    - provider_type: inline::meta-reference
    post_training:
-    - provider_type: inline::huggingface
+    - provider_type: inline::huggingface-cpu
    eval:
    - provider_type: inline::meta-reference
    datasetio:
--- a/llama_stack/distributions/starter/run.yaml
+++ b/llama_stack/distributions/starter/run.yaml
@ -156,8 +156,8 @@ providers:
      sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/trace_store.db
      otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
  post_training:
-  - provider_id: huggingface
-    provider_type: inline::huggingface
+  - provider_id: huggingface-cpu
+    provider_type: inline::huggingface-cpu
    config:
      checkpoint_format: huggingface
      distributed_backend: null
--- a/llama_stack/distributions/starter/starter.py
+++ b/llama_stack/distributions/starter/starter.py
@ -120,7 +120,7 @@ def get_distribution_template() -> DistributionTemplate:
        ],
        "agents": [BuildProvider(provider_type="inline::meta-reference")],
        "telemetry": [BuildProvider(provider_type="inline::meta-reference")],
-        "post_training": [BuildProvider(provider_type="inline::huggingface")],
+        "post_training": [BuildProvider(provider_type="inline::huggingface-cpu")],
        "eval": [BuildProvider(provider_type="inline::meta-reference")],
        "datasetio": [
            BuildProvider(provider_type="remote::huggingface"),
@ -178,7 +178,7 @@ def get_distribution_template() -> DistributionTemplate:
    return DistributionTemplate(
        name=name,
        distro_type="self_hosted",
-        description="Quick start template for running Llama Stack with several popular providers",
+        description="Quick start template for running Llama Stack with several popular providers. This distribution is intended for CPU-only environments.",
        container_image=None,
        template_path=None,
        providers=providers,
--- a/llama_stack/log.py
+++ b/llama_stack/log.py
@ -4,10 +4,10 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.

-import logging
+import logging  # allow-direct-logging
 import os
 import re
-from logging.config import dictConfig
+from logging.config import dictConfig  # allow-direct-logging

 from rich.console import Console
 from rich.errors import MarkupError
--- a/llama_stack/models/llama/llama3/multimodal/encoder_utils.py
+++ b/llama_stack/models/llama/llama3/multimodal/encoder_utils.py
@ -13,14 +13,15 @@

 # Copyright (c) Meta Platforms, Inc. and its affiliates.
 import math
-from logging import getLogger

 import torch
 import torch.nn.functional as F

+from llama_stack.log import get_logger
+
 from .utils import get_negative_inf_value, to_2tuple

-logger = getLogger()
+logger = get_logger(name=__name__, category="models::llama")


 def resize_local_position_embedding(orig_pos_embed, grid_size):
--- a/llama_stack/models/llama/llama3/multimodal/image_transform.py
+++ b/llama_stack/models/llama/llama3/multimodal/image_transform.py
@ -13,7 +13,6 @@

 import math
 from collections import defaultdict
-from logging import getLogger
 from typing import Any

 import torch
@ -21,9 +20,11 @@ import torchvision.transforms as tv
 from PIL import Image
 from torchvision.transforms import functional as F

+from llama_stack.log import get_logger
+
 IMAGE_RES = 224

-logger = getLogger()
+logger = get_logger(name=__name__, category="models::llama")


 class VariableSizeImageTransform:
--- a/llama_stack/models/llama/llama3/multimodal/model.py
+++ b/llama_stack/models/llama/llama3/multimodal/model.py
@ -3,8 +3,6 @@
 #
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
-
-import logging
 import math
 from collections.abc import Callable
 from functools import partial
@ -22,6 +20,8 @@ from PIL import Image as PIL_Image
 from torch import Tensor, nn
 from torch.distributed import _functional_collectives as funcol

+from llama_stack.log import get_logger
+
 from ..model import ModelArgs, RMSNorm, apply_rotary_emb, precompute_freqs_cis
 from .encoder_utils import (
    build_encoder_attention_mask,
@ -34,9 +34,10 @@ from .encoder_utils import (
 from .image_transform import VariableSizeImageTransform
 from .utils import get_negative_inf_value, to_2tuple

-logger = logging.getLogger(__name__)
 MP_SCALE = 8

+logger = get_logger(name=__name__, category="models::llama")
+

 def reduce_from_tensor_model_parallel_region(input_):
    """All-reduce the input tensor across model parallel group."""
@ -771,7 +772,7 @@ class TilePositionEmbedding(nn.Module):
        if embed is not None:
            # reshape the weights to the correct shape
            nt_old, nt_old, _, w = embed.shape
-            logging.info(f"Resizing tile embedding from {nt_old}x{nt_old} to {self.num_tiles}x{self.num_tiles}")
+            logger.info(f"Resizing tile embedding from {nt_old}x{nt_old} to {self.num_tiles}x{self.num_tiles}")
            embed_new = TilePositionEmbedding._dynamic_resize(embed, self.num_tiles)
            # assign the weights to the module
            state_dict[prefix + "embedding"] = embed_new
--- a/llama_stack/models/llama/llama3/tokenizer.py
+++ b/llama_stack/models/llama/llama3/tokenizer.py
@ -4,8 +4,8 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.

+
 from collections.abc import Collection, Iterator, Sequence, Set
-from logging import getLogger
 from pathlib import Path
 from typing import (
    Literal,
@ -14,11 +14,9 @@ from typing import (

 import tiktoken

+from llama_stack.log import get_logger
 from llama_stack.models.llama.tokenizer_utils import load_bpe_file

-logger = getLogger(__name__)
-
-
 # The tiktoken tokenizer can handle <=400k chars without
 # pyo3_runtime.PanicException.
 TIKTOKEN_MAX_ENCODE_CHARS = 400_000
@ -31,6 +29,8 @@ MAX_NO_WHITESPACES_CHARS = 25_000

 _INSTANCE = None

+logger = get_logger(name=__name__, category="models::llama")
+

 class Tokenizer:
    """
--- a/llama_stack/models/llama/llama3/tool_utils.py
+++ b/llama_stack/models/llama/llama3/tool_utils.py
@ -11,7 +11,7 @@ from llama_stack.log import get_logger

 from ..datatypes import BuiltinTool, RecursiveType, ToolCall, ToolPromptFormat

-logger = get_logger(name=__name__, category="inference")
+logger = get_logger(name=__name__, category="models::llama")

 BUILTIN_TOOL_PATTERN = r'\b(?P<tool_name>\w+)\.call\(query="(?P<query>[^"]*)"\)'
 CUSTOM_TOOL_CALL_PATTERN = re.compile(r"<function=(?P<function_name>[^}]+)>(?P<args>{.*?})")
--- a/llama_stack/models/llama/llama4/quantization/loader.py
+++ b/llama_stack/models/llama/llama4/quantization/loader.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 logging
 import os
 from collections.abc import Callable

@ -13,11 +12,13 @@ from fairscale.nn.model_parallel.initialize import get_model_parallel_rank
 from torch import Tensor, nn
 from torch.nn import functional as F

+from llama_stack.log import get_logger
+
 from ...datatypes import QuantizationMode
 from ..model import Transformer, TransformerBlock
 from ..moe import MoE

-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="models::llama")


 def swiglu_wrapper_no_reduce(
--- a/llama_stack/models/llama/llama4/tokenizer.py
+++ b/llama_stack/models/llama/llama4/tokenizer.py
@ -5,7 +5,6 @@
 # the root directory of this source tree.

 from collections.abc import Collection, Iterator, Sequence, Set
-from logging import getLogger
 from pathlib import Path
 from typing import (
    Literal,
@ -14,11 +13,9 @@ from typing import (

 import tiktoken

+from llama_stack.log import get_logger
 from llama_stack.models.llama.tokenizer_utils import load_bpe_file

-logger = getLogger(__name__)
-
-
 # The tiktoken tokenizer can handle <=400k chars without
 # pyo3_runtime.PanicException.
 TIKTOKEN_MAX_ENCODE_CHARS = 400_000
@ -101,6 +98,8 @@ BASIC_SPECIAL_TOKENS = [
    "<|fim_suffix|>",
 ]

+logger = get_logger(name=__name__, category="models::llama")
+

 class Tokenizer:
    """
--- a/llama_stack/models/llama/quantize_impls.py
+++ b/llama_stack/models/llama/quantize_impls.py
@ -6,9 +6,10 @@

 # type: ignore
 import collections
-import logging

-log = logging.getLogger(__name__)
+from llama_stack.log import get_logger
+
+log = get_logger(name=__name__, category="models::llama")

 try:
    import fbgemm_gpu.experimental.gen_ai  # noqa: F401
--- a/llama_stack/providers/inline/agents/meta_reference/agent_instance.py
+++ b/llama_stack/providers/inline/agents/meta_reference/agent_instance.py
@ -84,7 +84,7 @@ MEMORY_QUERY_TOOL = "knowledge_search"
 WEB_SEARCH_TOOL = "web_search"
 RAG_TOOL_GROUP = "builtin::rag"

-logger = get_logger(name=__name__, category="agents")
+logger = get_logger(name=__name__, category="agents::meta_reference")


 class ChatAgent(ShieldRunnerMixin):
--- a/llama_stack/providers/inline/agents/meta_reference/agents.py
+++ b/llama_stack/providers/inline/agents/meta_reference/agents.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 logging
 import uuid
 from collections.abc import AsyncGenerator
 from datetime import UTC, datetime
@ -42,6 +41,7 @@ from llama_stack.apis.safety import Safety
 from llama_stack.apis.tools import ToolGroups, ToolRuntime
 from llama_stack.apis.vector_io import VectorIO
 from llama_stack.core.datatypes import AccessRule
+from llama_stack.log import get_logger
 from llama_stack.providers.utils.kvstore import InmemoryKVStoreImpl, kvstore_impl
 from llama_stack.providers.utils.pagination import paginate_records
 from llama_stack.providers.utils.responses.responses_store import ResponsesStore
@ -51,7 +51,7 @@ from .config import MetaReferenceAgentsImplConfig
 from .persistence import AgentInfo
 from .responses.openai_responses import OpenAIResponsesImpl

-logger = logging.getLogger()
+logger = get_logger(name=__name__, category="agents::meta_reference")


 class MetaReferenceAgentsImpl(Agents):
--- a/llama_stack/providers/inline/agents/meta_reference/persistence.py
+++ b/llama_stack/providers/inline/agents/meta_reference/persistence.py
@ -5,7 +5,6 @@
 # the root directory of this source tree.

 import json
-import logging
 import uuid
 from datetime import UTC, datetime

@ -15,9 +14,10 @@ from llama_stack.core.access_control.access_control import AccessDeniedError, is
 from llama_stack.core.access_control.datatypes import AccessRule
 from llama_stack.core.datatypes import User
 from llama_stack.core.request_headers import get_authenticated_user
+from llama_stack.log import get_logger
 from llama_stack.providers.utils.kvstore import KVStore

-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="agents::meta_reference")


 class AgentSessionInfo(Session):
--- a/llama_stack/providers/inline/agents/meta_reference/responses/openai_responses.py
+++ b/llama_stack/providers/inline/agents/meta_reference/responses/openai_responses.py
@ -41,7 +41,7 @@ from .utils import (
    convert_response_text_to_chat_response_format,
 )

-logger = get_logger(name=__name__, category="responses")
+logger = get_logger(name=__name__, category="openai::responses")


 class OpenAIResponsePreviousResponseWithInputItems(BaseModel):
--- a/llama_stack/providers/inline/agents/meta_reference/responses/streaming.py
+++ b/llama_stack/providers/inline/agents/meta_reference/responses/streaming.py
@ -47,7 +47,7 @@ from llama_stack.log import get_logger
 from .types import ChatCompletionContext, ChatCompletionResult
 from .utils import convert_chat_choice_to_response_message, is_function_tool_call

-logger = get_logger(name=__name__, category="responses")
+logger = get_logger(name=__name__, category="agents::meta_reference")


 class StreamingResponseOrchestrator:
--- a/llama_stack/providers/inline/agents/meta_reference/responses/tool_executor.py
+++ b/llama_stack/providers/inline/agents/meta_reference/responses/tool_executor.py
@ -38,7 +38,7 @@ from llama_stack.log import get_logger

 from .types import ChatCompletionContext, ToolExecutionResult

-logger = get_logger(name=__name__, category="responses")
+logger = get_logger(name=__name__, category="agents::meta_reference")


 class ToolExecutor:
--- a/llama_stack/providers/inline/agents/meta_reference/responses/utils.py
+++ b/llama_stack/providers/inline/agents/meta_reference/responses/utils.py
@ -17,6 +17,8 @@ from llama_stack.apis.agents.openai_responses import (
    OpenAIResponseOutputMessageContent,
    OpenAIResponseOutputMessageContentOutputText,
    OpenAIResponseOutputMessageFunctionToolCall,
+    OpenAIResponseOutputMessageMCPCall,
+    OpenAIResponseOutputMessageMCPListTools,
    OpenAIResponseText,
 )
 from llama_stack.apis.inference import (
@ -99,14 +101,22 @@ async def convert_response_input_to_chat_messages(
    """
    messages: list[OpenAIMessageParam] = []
    if isinstance(input, list):
+        # extract all OpenAIResponseInputFunctionToolCallOutput items
+        # so their corresponding OpenAIToolMessageParam instances can
+        # be added immediately following the corresponding
+        # OpenAIAssistantMessageParam
+        tool_call_results = {}
        for input_item in input:
            if isinstance(input_item, OpenAIResponseInputFunctionToolCallOutput):
-                messages.append(
-                    OpenAIToolMessageParam(
+                tool_call_results[input_item.call_id] = OpenAIToolMessageParam(
                    content=input_item.output,
                    tool_call_id=input_item.call_id,
                )
-                )
+
+        for input_item in input:
+            if isinstance(input_item, OpenAIResponseInputFunctionToolCallOutput):
+                # skip as these have been extracted and inserted in order
+                pass
            elif isinstance(input_item, OpenAIResponseOutputMessageFunctionToolCall):
                tool_call = OpenAIChatCompletionToolCall(
                    index=0,
@ -117,6 +127,28 @@ async def convert_response_input_to_chat_messages(
                    ),
                )
                messages.append(OpenAIAssistantMessageParam(tool_calls=[tool_call]))
+                if input_item.call_id in tool_call_results:
+                    messages.append(tool_call_results[input_item.call_id])
+                    del tool_call_results[input_item.call_id]
+            elif isinstance(input_item, OpenAIResponseOutputMessageMCPCall):
+                tool_call = OpenAIChatCompletionToolCall(
+                    index=0,
+                    id=input_item.id,
+                    function=OpenAIChatCompletionToolCallFunction(
+                        name=input_item.name,
+                        arguments=input_item.arguments,
+                    ),
+                )
+                messages.append(OpenAIAssistantMessageParam(tool_calls=[tool_call]))
+                messages.append(
+                    OpenAIToolMessageParam(
+                        content=input_item.output,
+                        tool_call_id=input_item.id,
+                    )
+                )
+            elif isinstance(input_item, OpenAIResponseOutputMessageMCPListTools):
+                # the tool list will be handled separately
+                pass
            else:
                content = await convert_response_content_to_chat_content(input_item.content)
                message_type = await get_message_type_by_role(input_item.role)
@ -125,6 +157,10 @@ async def convert_response_input_to_chat_messages(
                        f"Llama Stack OpenAI Responses does not yet support message role '{input_item.role}' in this context"
                    )
                messages.append(message_type(content=content))
+        if len(tool_call_results):
+            raise ValueError(
+                f"Received function_call_output(s) with call_id(s) {tool_call_results.keys()}, but no corresponding function_call"
+            )
    else:
        messages.append(OpenAIUserMessageParam(content=input))
    return messages
--- a/llama_stack/providers/inline/agents/meta_reference/safety.py
+++ b/llama_stack/providers/inline/agents/meta_reference/safety.py
@ -5,13 +5,13 @@
 # the root directory of this source tree.

 import asyncio
-import logging

 from llama_stack.apis.inference import Message
 from llama_stack.apis.safety import Safety, SafetyViolation, ViolationLevel
+from llama_stack.log import get_logger
 from llama_stack.providers.utils.telemetry import tracing

-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="agents::meta_reference")


 class SafetyException(Exception):  # noqa: N818
--- a/llama_stack/providers/inline/batches/reference/batches.py
+++ b/llama_stack/providers/inline/batches/reference/batches.py
@ -5,6 +5,7 @@
 # the root directory of this source tree.

 import asyncio
+import hashlib
 import itertools
 import json
 import time
@ -136,28 +137,45 @@ class ReferenceBatchesImpl(Batches):
        endpoint: str,
        completion_window: Literal["24h"],
        metadata: dict[str, str] | None = None,
+        idempotency_key: str | None = None,
    ) -> BatchObject:
        """
        Create a new batch for processing multiple API requests.

-        Error handling by levels -
-         0. Input param handling, results in 40x errors before processing, e.g.
-           - Wrong completion_window
-           - Invalid metadata types
-           - Unknown endpoint
-          -> no batch created
-         1. Errors preventing processing, result in BatchErrors aggregated in process_batch, e.g.
-           - input_file_id missing
-           - invalid json in file
-           - missing custom_id, method, url, body
-           - invalid model
-           - streaming
-          -> batch created, validation sends to failed status
-         2. Processing errors, result in error_file_id entries, e.g.
-           - Any error returned from inference endpoint
-          -> batch created, goes to completed status
+        This implementation provides optional idempotency: when an idempotency key
+        (idempotency_key) is provided, a deterministic ID is generated based on the input
+        parameters. If a batch with the same parameters already exists, it will be
+        returned instead of creating a duplicate. Without an idempotency key,
+        each request creates a new batch with a unique ID.
+
+        Args:
+            input_file_id: The ID of an uploaded file containing requests for the batch.
+            endpoint: The endpoint to be used for all requests in the batch.
+            completion_window: The time window within which the batch should be processed.
+            metadata: Optional metadata for the batch.
+            idempotency_key: Optional idempotency key for enabling idempotent behavior.
+
+        Returns:
+            The created or existing batch object.
        """

+        # Error handling by levels -
+        #  0. Input param handling, results in 40x errors before processing, e.g.
+        #    - Wrong completion_window
+        #    - Invalid metadata types
+        #    - Unknown endpoint
+        #   -> no batch created
+        #  1. Errors preventing processing, result in BatchErrors aggregated in process_batch, e.g.
+        #    - input_file_id missing
+        #    - invalid json in file
+        #    - missing custom_id, method, url, body
+        #    - invalid model
+        #    - streaming
+        #   -> batch created, validation sends to failed status
+        #  2. Processing errors, result in error_file_id entries, e.g.
+        #    - Any error returned from inference endpoint
+        #   -> batch created, goes to completed status
+
        # TODO: set expiration time for garbage collection

        if endpoint not in ["/v1/chat/completions"]:
@ -171,6 +189,35 @@ class ReferenceBatchesImpl(Batches):
            )

        batch_id = f"batch_{uuid.uuid4().hex[:16]}"
+
+        # For idempotent requests, use the idempotency key for the batch ID
+        # This ensures the same key always maps to the same batch ID,
+        # allowing us to detect parameter conflicts
+        if idempotency_key is not None:
+            hash_input = idempotency_key.encode("utf-8")
+            hash_digest = hashlib.sha256(hash_input).hexdigest()[:24]
+            batch_id = f"batch_{hash_digest}"
+
+            try:
+                existing_batch = await self.retrieve_batch(batch_id)
+
+                if (
+                    existing_batch.input_file_id != input_file_id
+                    or existing_batch.endpoint != endpoint
+                    or existing_batch.completion_window != completion_window
+                    or existing_batch.metadata != metadata
+                ):
+                    raise ConflictError(
+                        f"Idempotency key '{idempotency_key}' was previously used with different parameters. "
+                        "Either use a new idempotency key or ensure all parameters match the original request."
+                    )
+
+                logger.info(f"Returning existing batch with ID: {batch_id}")
+                return existing_batch
+            except ResourceNotFoundError:
+                # Batch doesn't exist, continue with creation
+                pass
+
        current_time = int(time.time())

        batch = BatchObject(
@ -185,6 +232,7 @@ class ReferenceBatchesImpl(Batches):
        )

        await self.kvstore.set(f"batch:{batch_id}", batch.to_json())
+        logger.info(f"Created new batch with ID: {batch_id}")

        if self.process_batches:
            task = asyncio.create_task(self._process_batch(batch_id))
--- a/llama_stack/providers/inline/files/localfs/files.py
+++ b/llama_stack/providers/inline/files/localfs/files.py
@ -11,6 +11,7 @@ from typing import Annotated

 from fastapi import File, Form, Response, UploadFile

+from llama_stack.apis.common.errors import ResourceNotFoundError
 from llama_stack.apis.common.responses import Order
 from llama_stack.apis.files import (
    Files,
@ -20,12 +21,15 @@ from llama_stack.apis.files import (
    OpenAIFilePurpose,
 )
 from llama_stack.core.datatypes import AccessRule
+from llama_stack.log import get_logger
 from llama_stack.providers.utils.sqlstore.api import ColumnDefinition, ColumnType
 from llama_stack.providers.utils.sqlstore.authorized_sqlstore import AuthorizedSqlStore
 from llama_stack.providers.utils.sqlstore.sqlstore import sqlstore_impl

 from .config import LocalfsFilesImplConfig

+logger = get_logger(name=__name__, category="files")
+

 class LocalfsFilesImpl(Files):
    def __init__(self, config: LocalfsFilesImplConfig, policy: list[AccessRule]) -> None:
@ -65,6 +69,18 @@ class LocalfsFilesImpl(Files):
        """Get the filesystem path for a file ID."""
        return Path(self.config.storage_dir) / file_id

+    async def _lookup_file_id(self, file_id: str) -> tuple[OpenAIFileObject, Path]:
+        """Look up a OpenAIFileObject and filesystem path from its ID."""
+        if not self.sql_store:
+            raise RuntimeError("Files provider not initialized")
+
+        row = await self.sql_store.fetch_one("openai_files", policy=self.policy, where={"id": file_id})
+        if not row:
+            raise ResourceNotFoundError(file_id, "File", "client.files.list()")
+
+        file_path = Path(row.pop("file_path"))
+        return OpenAIFileObject(**row), file_path
+
    # OpenAI Files API Implementation
    async def openai_upload_file(
        self,
@ -157,37 +173,19 @@ class LocalfsFilesImpl(Files):

    async def openai_retrieve_file(self, file_id: str) -> OpenAIFileObject:
        """Returns information about a specific file."""
-        if not self.sql_store:
-            raise RuntimeError("Files provider not initialized")
+        file_obj, _ = await self._lookup_file_id(file_id)

-        row = await self.sql_store.fetch_one("openai_files", policy=self.policy, where={"id": file_id})
-        if not row:
-            raise ValueError(f"File with id {file_id} not found")
-
-        return OpenAIFileObject(
-            id=row["id"],
-            filename=row["filename"],
-            purpose=OpenAIFilePurpose(row["purpose"]),
-            bytes=row["bytes"],
-            created_at=row["created_at"],
-            expires_at=row["expires_at"],
-        )
+        return file_obj

    async def openai_delete_file(self, file_id: str) -> OpenAIFileDeleteResponse:
        """Delete a file."""
-        if not self.sql_store:
-            raise RuntimeError("Files provider not initialized")
-
-        row = await self.sql_store.fetch_one("openai_files", policy=self.policy, where={"id": file_id})
-        if not row:
-            raise ValueError(f"File with id {file_id} not found")
-
        # Delete physical file
-        file_path = Path(row["file_path"])
+        _, file_path = await self._lookup_file_id(file_id)
        if file_path.exists():
            file_path.unlink()

        # Delete metadata from database
+        assert self.sql_store is not None, "Files provider not initialized"
        await self.sql_store.delete("openai_files", where={"id": file_id})

        return OpenAIFileDeleteResponse(
@ -197,25 +195,17 @@ class LocalfsFilesImpl(Files):

    async def openai_retrieve_file_content(self, file_id: str) -> Response:
        """Returns the contents of the specified file."""
-        if not self.sql_store:
-            raise RuntimeError("Files provider not initialized")
-
-        # Get file metadata
-        row = await self.sql_store.fetch_one("openai_files", policy=self.policy, where={"id": file_id})
-        if not row:
-            raise ValueError(f"File with id {file_id} not found")
-
        # Read file content
-        file_path = Path(row["file_path"])
-        if not file_path.exists():
-            raise ValueError(f"File content not found on disk: {file_path}")
+        file_obj, file_path = await self._lookup_file_id(file_id)

-        with open(file_path, "rb") as f:
-            content = f.read()
+        if not file_path.exists():
+            logger.warning(f"File '{file_id}'s underlying '{file_path}' is missing, deleting metadata.")
+            await self.openai_delete_file(file_id)
+            raise ResourceNotFoundError(file_id, "File", "client.files.list()")

        # Return as binary response with appropriate content type
        return Response(
-            content=content,
+            content=file_path.read_bytes(),
            media_type="application/octet-stream",
-            headers={"Content-Disposition": f'attachment; filename="{row["filename"]}"'},
+            headers={"Content-Disposition": f'attachment; filename="{file_obj.filename}"'},
        )
--- a/llama_stack/providers/inline/inference/meta_reference/parallel_utils.py
+++ b/llama_stack/providers/inline/inference/meta_reference/parallel_utils.py
@ -12,7 +12,6 @@

 import copy
 import json
-import logging
 import multiprocessing
 import os
 import tempfile
@ -32,13 +31,14 @@ from fairscale.nn.model_parallel.initialize import (
 from pydantic import BaseModel, Field
 from torch.distributed.launcher.api import LaunchConfig, elastic_launch

+from llama_stack.log import get_logger
 from llama_stack.models.llama.datatypes import GenerationResult
 from llama_stack.providers.utils.inference.prompt_adapter import (
    ChatCompletionRequestWithRawContent,
    CompletionRequestWithRawContent,
 )

-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="inference")


 class ProcessingMessageName(str, Enum):
--- a/llama_stack/providers/inline/inference/sentence_transformers/sentence_transformers.py
+++ b/llama_stack/providers/inline/inference/sentence_transformers/sentence_transformers.py
@ -4,13 +4,11 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.

-import logging
 from collections.abc import AsyncGenerator

 from llama_stack.apis.inference import (
    CompletionResponse,
    InferenceProvider,
-    InterleavedContent,
    LogProbConfig,
    Message,
    ResponseFormat,
@ -21,6 +19,7 @@ from llama_stack.apis.inference import (
    ToolPromptFormat,
 )
 from llama_stack.apis.models import ModelType
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import Model, ModelsProtocolPrivate
 from llama_stack.providers.utils.inference.embedding_mixin import (
    SentenceTransformerEmbeddingMixin,
@ -32,7 +31,7 @@ from llama_stack.providers.utils.inference.openai_compat import (

 from .config import SentenceTransformersInferenceConfig

-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="inference")


 class SentenceTransformersInferenceImpl(
@ -100,25 +99,3 @@ class SentenceTransformersInferenceImpl(
        tool_config: ToolConfig | None = None,
    ) -> AsyncGenerator:
        raise ValueError("Sentence transformers don't support chat completion")
-
-    async def batch_completion(
-        self,
-        model_id: str,
-        content_batch: list[InterleavedContent],
-        sampling_params: SamplingParams | None = None,
-        response_format: ResponseFormat | None = None,
-        logprobs: LogProbConfig | None = None,
-    ):
-        raise NotImplementedError("Batch completion is not supported for Sentence Transformers")
-
-    async def batch_chat_completion(
-        self,
-        model_id: str,
-        messages_batch: list[list[Message]],
-        sampling_params: SamplingParams | None = None,
-        tools: list[ToolDefinition] | None = None,
-        tool_config: ToolConfig | None = None,
-        response_format: ResponseFormat | None = None,
-        logprobs: LogProbConfig | None = None,
-    ):
-        raise NotImplementedError("Batch chat completion is not supported for Sentence Transformers")
--- a/llama_stack/providers/inline/post_training/huggingface/recipes/finetune_single_device.py
+++ b/llama_stack/providers/inline/post_training/huggingface/recipes/finetune_single_device.py
@ -6,7 +6,6 @@

 import gc
 import json
-import logging
 import multiprocessing
 from pathlib import Path
 from typing import Any
@ -28,6 +27,7 @@ from llama_stack.apis.post_training import (
    LoraFinetuningConfig,
    TrainingConfig,
 )
+from llama_stack.log import get_logger
 from llama_stack.providers.inline.post_training.common.utils import evacuate_model_from_device

 from ..config import HuggingFacePostTrainingConfig
@ -44,7 +44,7 @@ from ..utils import (
    split_dataset,
 )

-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="post_training")


 class HFFinetuningSingleDevice:
--- a/llama_stack/providers/inline/post_training/huggingface/recipes/finetune_single_device_dpo.py
+++ b/llama_stack/providers/inline/post_training/huggingface/recipes/finetune_single_device_dpo.py
@ -5,7 +5,6 @@
 # the root directory of this source tree.

 import gc
-import logging
 import multiprocessing
 from pathlib import Path
 from typing import Any
@ -24,6 +23,7 @@ from llama_stack.apis.post_training import (
    DPOAlignmentConfig,
    TrainingConfig,
 )
+from llama_stack.log import get_logger
 from llama_stack.providers.inline.post_training.common.utils import evacuate_model_from_device

 from ..config import HuggingFacePostTrainingConfig
@ -40,7 +40,7 @@ from ..utils import (
    split_dataset,
 )

-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="post_training")


 class HFDPOAlignmentSingleDevice:
--- a/llama_stack/providers/inline/post_training/huggingface/utils.py
+++ b/llama_stack/providers/inline/post_training/huggingface/utils.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 logging
 import os
 import signal
 import sys
@ -19,10 +18,11 @@ from transformers import AutoConfig, AutoModelForCausalLM

 from llama_stack.apis.datasetio import DatasetIO
 from llama_stack.apis.post_training import Checkpoint, TrainingConfig
+from llama_stack.log import get_logger

 from .config import HuggingFacePostTrainingConfig

-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="post_training")


 def setup_environment():
--- a/llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py
+++ b/llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.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 logging
 import os
 import time
 from datetime import UTC, datetime
@ -19,6 +18,7 @@ from torch.utils.data import DataLoader, DistributedSampler
 from torchtune import modules, training
 from torchtune import utils as torchtune_utils
 from torchtune.data import padded_collate_sft
+from torchtune.models.llama3._tokenizer import Llama3Tokenizer
 from torchtune.modules.loss import CEWithChunkedOutputLoss
 from torchtune.modules.peft import (
    get_adapter_params,
@ -45,6 +45,7 @@ from llama_stack.apis.post_training import (
 )
 from llama_stack.core.utils.config_dirs import DEFAULT_CHECKPOINT_DIR
 from llama_stack.core.utils.model_utils import model_local_dir
+from llama_stack.log import get_logger
 from llama_stack.models.llama.sku_list import resolve_model
 from llama_stack.providers.inline.post_training.common.utils import evacuate_model_from_device
 from llama_stack.providers.inline.post_training.torchtune.common import utils
@ -56,9 +57,7 @@ from llama_stack.providers.inline.post_training.torchtune.config import (
 )
 from llama_stack.providers.inline.post_training.torchtune.datasets.sft import SFTDataset

-log = logging.getLogger(__name__)
-
-from torchtune.models.llama3._tokenizer import Llama3Tokenizer
+log = get_logger(name=__name__, category="post_training")


 class LoraFinetuningSingleDevice:
--- a/llama_stack/providers/inline/safety/code_scanner/code_scanner.py
+++ b/llama_stack/providers/inline/safety/code_scanner/code_scanner.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 logging
 import uuid
 from typing import TYPE_CHECKING, Any

@ -20,13 +19,14 @@ from llama_stack.apis.safety import (
 )
 from llama_stack.apis.safety.safety import ModerationObject, ModerationObjectResults
 from llama_stack.apis.shields import Shield
+from llama_stack.log import get_logger
 from llama_stack.providers.utils.inference.prompt_adapter import (
    interleaved_content_as_str,
 )

 from .config import CodeScannerConfig

-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="safety")

 ALLOWED_CODE_SCANNER_MODEL_IDS = [
    "code-scanner",
--- a/llama_stack/providers/inline/safety/llama_guard/llama_guard.py
+++ b/llama_stack/providers/inline/safety/llama_guard/llama_guard.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 logging
 import re
 import uuid
 from string import Template
@ -21,6 +20,7 @@ from llama_stack.apis.safety import (
 from llama_stack.apis.safety.safety import ModerationObject, ModerationObjectResults
 from llama_stack.apis.shields import Shield
 from llama_stack.core.datatypes import Api
+from llama_stack.log import get_logger
 from llama_stack.models.llama.datatypes import Role
 from llama_stack.models.llama.sku_types import CoreModelId
 from llama_stack.providers.datatypes import ShieldsProtocolPrivate
@ -132,6 +132,8 @@ Provide your safety assessment for ONLY THE LAST $agent_type message in the abov

 PROMPT_TEMPLATE = Template(f"{PROMPT_TASK}{SAFETY_CATEGORIES}{PROMPT_CONVERSATION}{PROMPT_INSTRUCTIONS}")

+logger = get_logger(name=__name__, category="safety")
+

 class LlamaGuardSafetyImpl(Safety, ShieldsProtocolPrivate):
    def __init__(self, config: LlamaGuardConfig, deps) -> None:
@ -407,7 +409,7 @@ class LlamaGuardShield:
            unsafe_code_list = [code.strip() for code in unsafe_code.split(",")]
            invalid_codes = [code for code in unsafe_code_list if code not in SAFETY_CODE_TO_CATEGORIES_MAP]
            if invalid_codes:
-                logging.warning(f"Invalid safety codes returned: {invalid_codes}")
+                logger.warning(f"Invalid safety codes returned: {invalid_codes}")
                # just returning safe object, as we don't know what the invalid codes can map to
                return ModerationObject(
                    id=f"modr-{uuid.uuid4()}",
--- a/llama_stack/providers/inline/safety/prompt_guard/prompt_guard.py
+++ b/llama_stack/providers/inline/safety/prompt_guard/prompt_guard.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 logging
 from typing import Any

 import torch
@ -21,6 +20,7 @@ from llama_stack.apis.safety import (
 from llama_stack.apis.safety.safety import ModerationObject
 from llama_stack.apis.shields import Shield
 from llama_stack.core.utils.model_utils import model_local_dir
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import ShieldsProtocolPrivate
 from llama_stack.providers.utils.inference.prompt_adapter import (
    interleaved_content_as_str,
@ -28,7 +28,7 @@ from llama_stack.providers.utils.inference.prompt_adapter import (

 from .config import PromptGuardConfig, PromptGuardType

-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="safety")

 PROMPT_GUARD_MODEL = "Prompt-Guard-86M"

--- a/llama_stack/providers/inline/scoring/basic/utils/ifeval_utils.py
+++ b/llama_stack/providers/inline/scoring/basic/utils/ifeval_utils.py
@ -7,7 +7,6 @@
 import collections
 import functools
 import json
-import logging
 import random
 import re
 import string
@ -20,7 +19,9 @@ import nltk
 from pythainlp.tokenize import sent_tokenize as sent_tokenize_thai
 from pythainlp.tokenize import word_tokenize as word_tokenize_thai

-logger = logging.getLogger()
+from llama_stack.log import get_logger
+
+logger = get_logger(name=__name__, category="scoring")

 WORD_LIST = [
    "western",
--- a/llama_stack/providers/inline/telemetry/meta_reference/telemetry.py
+++ b/llama_stack/providers/inline/telemetry/meta_reference/telemetry.py
@ -4,13 +4,11 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.

-import logging
+import datetime
 import threading
 from typing import Any

 from opentelemetry import metrics, trace
-
-logger = logging.getLogger(__name__)
 from opentelemetry.exporter.otlp.proto.http.metric_exporter import OTLPMetricExporter
 from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
 from opentelemetry.sdk.metrics import MeterProvider
@ -40,6 +38,7 @@ from llama_stack.apis.telemetry import (
    UnstructuredLogEvent,
 )
 from llama_stack.core.datatypes import Api
+from llama_stack.log import get_logger
 from llama_stack.providers.inline.telemetry.meta_reference.console_span_processor import (
    ConsoleSpanProcessor,
 )
@ -61,6 +60,8 @@ _GLOBAL_STORAGE: dict[str, dict[str | int, Any]] = {
 _global_lock = threading.Lock()
 _TRACER_PROVIDER = None

+logger = get_logger(name=__name__, category="telemetry")
+

 def is_tracing_enabled(tracer):
    with tracer.start_as_current_span("check_tracing") as span:
@ -145,11 +146,41 @@ class TelemetryAdapter(TelemetryDatasetMixin, Telemetry):
        metric_name: str,
        start_time: int,
        end_time: int | None = None,
-        granularity: str | None = "1d",
+        granularity: str | None = None,
        query_type: MetricQueryType = MetricQueryType.RANGE,
        label_matchers: list[MetricLabelMatcher] | None = None,
    ) -> QueryMetricsResponse:
-        raise NotImplementedError("Querying metrics is not implemented")
+        """Query metrics from the telemetry store.
+
+        Args:
+            metric_name: The name of the metric to query (e.g., "prompt_tokens")
+            start_time: Start time as Unix timestamp
+            end_time: End time as Unix timestamp (defaults to now if None)
+            granularity: Time granularity for aggregation
+            query_type: Type of query (RANGE or INSTANT)
+            label_matchers: Label filters to apply
+
+        Returns:
+            QueryMetricsResponse with metric time series data
+        """
+        # Convert timestamps to datetime objects
+        start_dt = datetime.datetime.fromtimestamp(start_time, datetime.UTC)
+        end_dt = datetime.datetime.fromtimestamp(end_time, datetime.UTC) if end_time else None
+
+        # Use SQLite trace store if available
+        if hasattr(self, "trace_store") and self.trace_store:
+            return await self.trace_store.query_metrics(
+                metric_name=metric_name,
+                start_time=start_dt,
+                end_time=end_dt,
+                granularity=granularity,
+                query_type=query_type,
+                label_matchers=label_matchers,
+            )
+        else:
+            raise ValueError(
+                f"In order to query_metrics, you must have {TelemetrySink.SQLITE} set in your telemetry sinks"
+            )

    def _log_unstructured(self, event: UnstructuredLogEvent, ttl_seconds: int) -> None:
        with self._lock:
--- a/Show more
+++ b/Show more