Merge remote-tracking branch 'origin/main' into k8s_demo

2025-07-31 08:00:09 +00:00 · 2025-07-29 09:00:45 -07:00 · 2025-07-29 09:00:45 -07:00 · 95d25ddfe2
commit 95d25ddfe2
parent e614241876 870a37ff4b
101 changed files with 3309 additions and 5108 deletions
--- a/.github/workflows/integration-tests.yml
+++ b/.github/workflows/integration-tests.yml
@ -117,17 +117,13 @@ jobs:

          EXCLUDE_TESTS="builtin_tool or safety_with_image or code_interpreter or test_rag"
          if [ "${{ matrix.provider }}" == "ollama" ]; then
-            export ENABLE_OLLAMA="ollama"
            export OLLAMA_URL="http://0.0.0.0:11434"
-            export OLLAMA_INFERENCE_MODEL="llama3.2:3b-instruct-fp16"
-            export TEXT_MODEL=ollama/$OLLAMA_INFERENCE_MODEL
-            export SAFETY_MODEL="llama-guard3:1b"
-            EXTRA_PARAMS="--safety-shield=$SAFETY_MODEL"
+            export TEXT_MODEL=ollama/llama3.2:3b-instruct-fp16
+            export SAFETY_MODEL="ollama/llama-guard3:1b"
+            EXTRA_PARAMS="--safety-shield=llama-guard"
          else
-            export ENABLE_VLLM="vllm"
            export VLLM_URL="http://localhost:8000/v1"
-            export VLLM_INFERENCE_MODEL="meta-llama/Llama-3.2-1B-Instruct"
-            export TEXT_MODEL=vllm/$VLLM_INFERENCE_MODEL
+            export TEXT_MODEL=vllm/meta-llama/Llama-3.2-1B-Instruct
            # TODO: remove the not(test_inference_store_tool_calls) once we can get the tool called consistently
            EXTRA_PARAMS=
            EXCLUDE_TESTS="${EXCLUDE_TESTS} or test_inference_store_tool_calls"
--- a/.github/workflows/pre-commit.yml
+++ b/.github/workflows/pre-commit.yml
@ -14,10 +14,18 @@ concurrency:
 jobs:
  pre-commit:
    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+      pull-requests: write

    steps:
      - name: Checkout code
        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+        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 }}
+          # Fetch full history for dependabot PRs to allow commits
+          fetch-depth: ${{ github.actor == 'dependabot[bot]' && 0 || 1 }}

      - name: Set up Python
        uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
@ -29,15 +37,45 @@ jobs:
            .pre-commit-config.yaml

      - uses: pre-commit/action@2c7b3805fd2a0fd8c1884dcaebf91fc102a13ecd # v3.0.1
+        continue-on-error: true
        env:
          SKIP: no-commit-to-branch
          RUFF_OUTPUT_FORMAT: github

+      - name: Debug
+        run: |
+          echo "github.ref: ${{ github.ref }}"
+          echo "github.actor: ${{ github.actor }}"
+
+      - name: Commit changes for dependabot PRs
+        if: github.actor == 'dependabot[bot]'
+        run: |
+          if ! git diff --exit-code || [ -n "$(git ls-files --others --exclude-standard)" ]; then
+            git config --local user.email "github-actions[bot]@users.noreply.github.com"
+            git config --local user.name "github-actions[bot]"
+
+            # Ensure we're on the correct branch
+            git checkout -B ${{ github.head_ref }}
+            git add -A
+            git commit -m "Apply pre-commit fixes"
+
+            # Pull latest changes from the PR branch and rebase our commit on top
+            git pull --rebase origin ${{ github.head_ref }}
+
+            # Push to the PR branch
+            git push origin ${{ github.head_ref }}
+            echo "Pre-commit fixes committed and pushed"
+          else
+            echo "No changes to commit"
+          fi
+
      - name: Verify if there are any diff files after pre-commit
+        if: github.actor != 'dependabot[bot]'
        run: |
          git diff --exit-code || (echo "There are uncommitted changes, run pre-commit locally and commit again" && exit 1)

      - name: Verify if there are any new files after pre-commit
+        if: github.actor != 'dependabot[bot]'
        run: |
          unstaged_files=$(git ls-files --others --exclude-standard)
          if [ -n "$unstaged_files" ]; then
--- a/.github/workflows/test-external-provider-module.yml
+++ b/.github/workflows/test-external-provider-module.yml
@ -13,7 +13,8 @@ on:
      - 'uv.lock'
      - 'pyproject.toml'
      - 'requirements.txt'
-      - '.github/workflows/test-external-providers-module.yml' # This workflow
+      - 'tests/external/*'
+      - '.github/workflows/test-external-provider-module.yml' # This workflow

 jobs:
  test-external-providers-from-module:
@ -52,6 +53,7 @@ jobs:
        if: ${{ matrix.image-type }} == 'venv'
        env:
          INFERENCE_MODEL: "llama3.2:3b-instruct-fp16"
+          LLAMA_STACK_LOG_FILE: "server.log"
        run: |
          # Use the virtual environment created by the build step (name comes from build config)
          source ramalama-stack-test/bin/activate
@ -72,3 +74,12 @@ jobs:
          echo "Provider failed to load"
          cat server.log
          exit 1
+
+      - name: Upload all logs to artifacts
+        if: ${{ always() }}
+        uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
+        with:
+          name: logs-${{ github.run_id }}-${{ github.run_attempt }}-external-provider-module-test
+          path: |
+            *.log
+          retention-days: 1
--- a/.github/workflows/test-external.yml
+++ b/.github/workflows/test-external.yml
@ -13,6 +13,7 @@ on:
      - 'uv.lock'
      - 'pyproject.toml'
      - 'requirements.txt'
+      - 'tests/external/*'
      - '.github/workflows/test-external.yml' # This workflow

 jobs:
@ -52,6 +53,7 @@ jobs:
        if: ${{ matrix.image-type }} == 'venv'
        env:
          INFERENCE_MODEL: "meta-llama/Llama-3.2-3B-Instruct"
+          LLAMA_STACK_LOG_FILE: "server.log"
        run: |
          # Use the virtual environment created by the build step (name comes from build config)
          source ci-test/bin/activate
@ -75,3 +77,12 @@ jobs:
      - name: Test external API
        run: |
          curl -sSf http://localhost:8321/v1/weather/locations
+
+      - name: Upload all logs to artifacts
+        if: ${{ always() }}
+        uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
+        with:
+          name: logs-${{ github.run_id }}-${{ github.run_attempt }}-external-test
+          path: |
+            *.log
+          retention-days: 1
--- a/.github/workflows/unit-tests.yml
+++ b/.github/workflows/unit-tests.yml
@ -35,6 +35,8 @@ jobs:

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
+        with:
+          python-version: ${{ matrix.python }}

      - name: Run unit tests
        run: |
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@ -19,7 +19,6 @@ repos:
    -   id: check-yaml
        args: ["--unsafe"]
    -   id: detect-private-key
-    -   id: requirements-txt-fixer
    -   id: mixed-line-ending
        args: [--fix=lf] # Forces to replace line ending by LF (line feed)
    -   id: check-executables-have-shebangs
@ -56,14 +55,6 @@ repos:
    rev: 0.7.20
    hooks:
    -   id: uv-lock
-    -   id: uv-export
-        args: [
-            "--frozen",
-            "--no-hashes",
-            "--no-emit-project",
-            "--no-default-groups",
-            "--output-file=requirements.txt"
-        ]

 -   repo: https://github.com/pre-commit/mirrors-mypy
    rev: v1.16.1
--- a/docs/_static/llama-stack-spec.html
+++ b/docs/_static/llama-stack-spec.html
@ -9770,7 +9770,7 @@
                            {
                                "type": "array",
                                "items": {
-                                    "$ref": "#/components/schemas/OpenAIChatCompletionContentPartParam"
+                                    "$ref": "#/components/schemas/OpenAIChatCompletionContentPartTextParam"
                                }
                            }
                        ],
@ -9821,13 +9821,17 @@
                    },
                    {
                        "$ref": "#/components/schemas/OpenAIChatCompletionContentPartImageParam"
+                    },
+                    {
+                        "$ref": "#/components/schemas/OpenAIFile"
                    }
                ],
                "discriminator": {
                    "propertyName": "type",
                    "mapping": {
                        "text": "#/components/schemas/OpenAIChatCompletionContentPartTextParam",
-                        "image_url": "#/components/schemas/OpenAIChatCompletionContentPartImageParam"
+                        "image_url": "#/components/schemas/OpenAIChatCompletionContentPartImageParam",
+                        "file": "#/components/schemas/OpenAIFile"
                    }
                }
            },
@ -9955,7 +9959,7 @@
                            {
                                "type": "array",
                                "items": {
-                                    "$ref": "#/components/schemas/OpenAIChatCompletionContentPartParam"
+                                    "$ref": "#/components/schemas/OpenAIChatCompletionContentPartTextParam"
                                }
                            }
                        ],
@ -9974,6 +9978,41 @@
                "title": "OpenAIDeveloperMessageParam",
                "description": "A message from the developer in an OpenAI-compatible chat completion request."
            },
+            "OpenAIFile": {
+                "type": "object",
+                "properties": {
+                    "type": {
+                        "type": "string",
+                        "const": "file",
+                        "default": "file"
+                    },
+                    "file": {
+                        "$ref": "#/components/schemas/OpenAIFileFile"
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "type",
+                    "file"
+                ],
+                "title": "OpenAIFile"
+            },
+            "OpenAIFileFile": {
+                "type": "object",
+                "properties": {
+                    "file_data": {
+                        "type": "string"
+                    },
+                    "file_id": {
+                        "type": "string"
+                    },
+                    "filename": {
+                        "type": "string"
+                    }
+                },
+                "additionalProperties": false,
+                "title": "OpenAIFileFile"
+            },
            "OpenAIImageURL": {
                "type": "object",
                "properties": {
@ -10036,7 +10075,7 @@
                            {
                                "type": "array",
                                "items": {
-                                    "$ref": "#/components/schemas/OpenAIChatCompletionContentPartParam"
+                                    "$ref": "#/components/schemas/OpenAIChatCompletionContentPartTextParam"
                                }
                            }
                        ],
@ -10107,7 +10146,7 @@
                            {
                                "type": "array",
                                "items": {
-                                    "$ref": "#/components/schemas/OpenAIChatCompletionContentPartParam"
+                                    "$ref": "#/components/schemas/OpenAIChatCompletionContentPartTextParam"
                                }
                            }
                        ],
--- a/docs/_static/llama-stack-spec.yaml
+++ b/docs/_static/llama-stack-spec.yaml
@ -6895,7 +6895,7 @@ components:
            - type: string
            - type: array
              items:
-                $ref: '#/components/schemas/OpenAIChatCompletionContentPartParam'
+                $ref: '#/components/schemas/OpenAIChatCompletionContentPartTextParam'
          description: The content of the model's response
        name:
          type: string
@ -6934,11 +6934,13 @@ components:
      oneOf:
        - $ref: '#/components/schemas/OpenAIChatCompletionContentPartTextParam'
        - $ref: '#/components/schemas/OpenAIChatCompletionContentPartImageParam'
+        - $ref: '#/components/schemas/OpenAIFile'
      discriminator:
        propertyName: type
        mapping:
          text: '#/components/schemas/OpenAIChatCompletionContentPartTextParam'
          image_url: '#/components/schemas/OpenAIChatCompletionContentPartImageParam'
+          file: '#/components/schemas/OpenAIFile'
    OpenAIChatCompletionContentPartTextParam:
      type: object
      properties:
@ -7037,7 +7039,7 @@ components:
            - type: string
            - type: array
              items:
-                $ref: '#/components/schemas/OpenAIChatCompletionContentPartParam'
+                $ref: '#/components/schemas/OpenAIChatCompletionContentPartTextParam'
          description: The content of the developer message
        name:
          type: string
@ -7050,6 +7052,31 @@ components:
      title: OpenAIDeveloperMessageParam
      description: >-
        A message from the developer in an OpenAI-compatible chat completion request.
+    OpenAIFile:
+      type: object
+      properties:
+        type:
+          type: string
+          const: file
+          default: file
+        file:
+          $ref: '#/components/schemas/OpenAIFileFile'
+      additionalProperties: false
+      required:
+        - type
+        - file
+      title: OpenAIFile
+    OpenAIFileFile:
+      type: object
+      properties:
+        file_data:
+          type: string
+        file_id:
+          type: string
+        filename:
+          type: string
+      additionalProperties: false
+      title: OpenAIFileFile
    OpenAIImageURL:
      type: object
      properties:
@ -7090,7 +7117,7 @@ components:
            - type: string
            - type: array
              items:
-                $ref: '#/components/schemas/OpenAIChatCompletionContentPartParam'
+                $ref: '#/components/schemas/OpenAIChatCompletionContentPartTextParam'
          description: >-
            The content of the "system prompt". If multiple system messages are provided,
            they are concatenated. The underlying Llama Stack code may also add other
@ -7148,7 +7175,7 @@ components:
            - type: string
            - type: array
              items:
-                $ref: '#/components/schemas/OpenAIChatCompletionContentPartParam'
+                $ref: '#/components/schemas/OpenAIChatCompletionContentPartTextParam'
          description: The response content from the tool
      additionalProperties: false
      required:
--- a/docs/quick_start.ipynb
+++ b/docs/quick_start.ipynb
@ -249,12 +249,6 @@
      ],
      "source": [
        "from llama_stack_client import Agent, AgentEventLogger, RAGDocument, LlamaStackClient\n",
-        "import os\n",
-        "\n",
-        "os.environ[\"ENABLE_OLLAMA\"] = \"ollama\"\n",
-        "os.environ[\"OLLAMA_INFERENCE_MODEL\"] = \"llama3.2:3b\"\n",
-        "os.environ[\"OLLAMA_EMBEDDING_MODEL\"] = \"all-minilm:l6-v2\"\n",
-        "os.environ[\"OLLAMA_EMBEDDING_DIMENSION\"] = \"384\"\n",
        "\n",
        "vector_db_id = \"my_demo_vector_db\"\n",
        "client = LlamaStackClient(base_url=\"http://0.0.0.0:8321\")\n",
--- a/docs/source/distributions/importing_as_library.md
+++ b/docs/source/distributions/importing_as_library.md
@ -13,7 +13,7 @@ llama stack build --template starter --image-type venv
 from llama_stack.distribution.library_client import LlamaStackAsLibraryClient

 client = LlamaStackAsLibraryClient(
-    "ollama",
+    "starter",
    # 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"]},
 )
--- a/docs/source/distributions/self_hosted_distro/nvidia.md
+++ b/docs/source/distributions/self_hosted_distro/nvidia.md
@ -40,16 +40,16 @@ The following environment variables can be configured:

 The following models are available by default:

- `meta/llama3-8b-instruct (aliases: meta-llama/Llama-3-8B-Instruct)`
- `meta/llama3-70b-instruct (aliases: meta-llama/Llama-3-70B-Instruct)`
- `meta/llama-3.1-8b-instruct (aliases: meta-llama/Llama-3.1-8B-Instruct)`
- `meta/llama-3.1-70b-instruct (aliases: meta-llama/Llama-3.1-70B-Instruct)`
- `meta/llama-3.1-405b-instruct (aliases: meta-llama/Llama-3.1-405B-Instruct-FP8)`
- `meta/llama-3.2-1b-instruct (aliases: meta-llama/Llama-3.2-1B-Instruct)`
- `meta/llama-3.2-3b-instruct (aliases: meta-llama/Llama-3.2-3B-Instruct)`
- `meta/llama-3.2-11b-vision-instruct (aliases: meta-llama/Llama-3.2-11B-Vision-Instruct)`
- `meta/llama-3.2-90b-vision-instruct (aliases: meta-llama/Llama-3.2-90B-Vision-Instruct)`
- `meta/llama-3.3-70b-instruct (aliases: meta-llama/Llama-3.3-70B-Instruct)`
+- `meta/llama3-8b-instruct `
+- `meta/llama3-70b-instruct `
+- `meta/llama-3.1-8b-instruct `
+- `meta/llama-3.1-70b-instruct `
+- `meta/llama-3.1-405b-instruct `
+- `meta/llama-3.2-1b-instruct `
+- `meta/llama-3.2-3b-instruct `
+- `meta/llama-3.2-11b-vision-instruct `
+- `meta/llama-3.2-90b-vision-instruct `
+- `meta/llama-3.3-70b-instruct `
 - `nvidia/llama-3.2-nv-embedqa-1b-v2 `
 - `nvidia/nv-embedqa-e5-v5 `
 - `nvidia/nv-embedqa-mistral-7b-v2 `
--- a/docs/source/distributions/self_hosted_distro/starter.md
+++ b/docs/source/distributions/self_hosted_distro/starter.md
@ -158,7 +158,7 @@ export ENABLE_PGVECTOR=__disabled__
 The starter distribution uses several patterns for provider IDs:

 1. **Direct provider IDs**: `faiss`, `ollama`, `vllm`
-2. **Environment-based provider IDs**: `${env.ENABLE_SQLITE_VEC+sqlite-vec}`
+2. **Environment-based provider IDs**: `${env.ENABLE_SQLITE_VEC:+sqlite-vec}`
 3. **Model-based provider IDs**: `${env.OLLAMA_INFERENCE_MODEL:__disabled__}`

 When using the `+` pattern (like `${env.ENABLE_SQLITE_VEC+sqlite-vec}`), the provider is enabled by default and can be disabled by setting the environment variable to `__disabled__`.
--- a/docs/source/getting_started/detailed_tutorial.md
+++ b/docs/source/getting_started/detailed_tutorial.md
@ -59,7 +59,7 @@ Now let's build and run the Llama Stack config for Ollama.
 We use `starter` as template. By default all providers are disabled, this requires enable ollama by passing environment variables.

 ```bash
-ENABLE_OLLAMA=ollama OLLAMA_INFERENCE_MODEL="llama3.2:3b" llama stack build --template starter --image-type venv --run
+llama stack build --template starter --image-type venv --run
 ```
 :::
 :::{tab-item} Using `conda`
@ -70,7 +70,7 @@ which defines the providers and their settings.
 Now let's build and run the Llama Stack config for Ollama.

 ```bash
-ENABLE_OLLAMA=ollama INFERENCE_MODEL="llama3.2:3b" llama stack build --template starter --image-type conda --run
+llama stack build --template starter --image-type conda --run
 ```
 :::
 :::{tab-item} Using a Container
@ -80,8 +80,6 @@ component that works with different inference providers out of the box. For this
 configurations, please check out [this guide](../distributions/building_distro.md).
 First lets setup some environment variables and create a local directory to mount into the container’s file system.
 ```bash
-export INFERENCE_MODEL="llama3.2:3b"
-export ENABLE_OLLAMA=ollama
 export LLAMA_STACK_PORT=8321
 mkdir -p ~/.llama
 ```
@ -94,7 +92,6 @@ docker run -it \
  -v ~/.llama:/root/.llama \
  llamastack/distribution-starter \
  --port $LLAMA_STACK_PORT \
-  --env INFERENCE_MODEL=$INFERENCE_MODEL \
  --env OLLAMA_URL=http://host.docker.internal:11434
 ```
 Note to start the container with Podman, you can do the same but replace `docker` at the start of the command with
@ -116,7 +113,6 @@ docker run -it \
  --network=host \
  llamastack/distribution-starter \
  --port $LLAMA_STACK_PORT \
-  --env INFERENCE_MODEL=$INFERENCE_MODEL \
  --env OLLAMA_URL=http://localhost:11434
 ```
 :::
--- a/docs/source/getting_started/quickstart.md
+++ b/docs/source/getting_started/quickstart.md
@ -19,7 +19,7 @@ ollama run llama3.2:3b --keepalive 60m
 #### Step 2: Run the Llama Stack server
 We will use `uv` to run the Llama Stack server.
 ```bash
-ENABLE_OLLAMA=ollama OLLAMA_INFERENCE_MODEL=llama3.2:3b uv run --with llama-stack llama stack build --template starter --image-type venv --run
+uv run --with llama-stack llama stack build --template starter --image-type venv --run
 ```
 #### Step 3: Run the demo
 Now open up a new terminal and copy the following script into a file named `demo_script.py`.
--- a/docs/source/providers/external.md
+++ b/docs/source/providers/external.md
@ -12,8 +12,7 @@ To enable external providers, you need to add `module` into your build yaml, all
 an example entry in your build.yaml should look like:

 ```
- provider_id: ramalama
-  provider_type: remote::ramalama
+- provider_type: remote::ramalama
  module: ramalama_stack
 ```

@ -255,8 +254,7 @@ distribution_spec:
  container_image: null
  providers:
    inference:
-    - provider_id: ramalama
-      provider_type: remote::ramalama
+    - provider_type: remote::ramalama
      module: ramalama_stack==0.3.0a0
 image_type: venv
 image_name: null
--- a/docs/source/providers/inference/remote_anthropic.md
+++ b/docs/source/providers/inference/remote_anthropic.md
@ -13,7 +13,7 @@ Anthropic inference provider for accessing Claude models and Anthropic's AI serv
 ## Sample Configuration

 ```yaml
-api_key: ${env.ANTHROPIC_API_KEY}
+api_key: ${env.ANTHROPIC_API_KEY:=}

 ```

--- a/docs/source/providers/inference/remote_cerebras.md
+++ b/docs/source/providers/inference/remote_cerebras.md
@ -15,7 +15,7 @@ Cerebras inference provider for running models on Cerebras Cloud platform.

 ```yaml
 base_url: https://api.cerebras.ai
-api_key: ${env.CEREBRAS_API_KEY}
+api_key: ${env.CEREBRAS_API_KEY:=}

 ```

--- a/docs/source/providers/inference/remote_databricks.md
+++ b/docs/source/providers/inference/remote_databricks.md
@ -14,8 +14,8 @@ Databricks inference provider for running models on Databricks' unified analytic
 ## Sample Configuration

 ```yaml
-url: ${env.DATABRICKS_URL}
-api_token: ${env.DATABRICKS_API_TOKEN}
+url: ${env.DATABRICKS_URL:=}
+api_token: ${env.DATABRICKS_API_TOKEN:=}

 ```

--- a/docs/source/providers/inference/remote_fireworks.md
+++ b/docs/source/providers/inference/remote_fireworks.md
@ -16,7 +16,7 @@ Fireworks AI inference provider for Llama models and other AI models on the Fire

 ```yaml
 url: https://api.fireworks.ai/inference/v1
-api_key: ${env.FIREWORKS_API_KEY}
+api_key: ${env.FIREWORKS_API_KEY:=}

 ```

--- a/docs/source/providers/inference/remote_gemini.md
+++ b/docs/source/providers/inference/remote_gemini.md
@ -13,7 +13,7 @@ Google Gemini inference provider for accessing Gemini models and Google's AI ser
 ## Sample Configuration

 ```yaml
-api_key: ${env.GEMINI_API_KEY}
+api_key: ${env.GEMINI_API_KEY:=}

 ```

--- a/docs/source/providers/inference/remote_groq.md
+++ b/docs/source/providers/inference/remote_groq.md
@ -15,7 +15,7 @@ Groq inference provider for ultra-fast inference using Groq's LPU technology.

 ```yaml
 url: https://api.groq.com
-api_key: ${env.GROQ_API_KEY}
+api_key: ${env.GROQ_API_KEY:=}

 ```

--- a/docs/source/providers/inference/remote_openai.md
+++ b/docs/source/providers/inference/remote_openai.md
@ -9,11 +9,13 @@ OpenAI inference provider for accessing GPT models and other OpenAI services.
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
 | `api_key` | `str \| None` | No |  | API key for OpenAI models |
+| `base_url` | `<class 'str'>` | No | https://api.openai.com/v1 | Base URL for OpenAI API |

 ## Sample Configuration

 ```yaml
-api_key: ${env.OPENAI_API_KEY}
+api_key: ${env.OPENAI_API_KEY:=}
+base_url: ${env.OPENAI_BASE_URL:=https://api.openai.com/v1}

 ```

--- a/docs/source/providers/inference/remote_sambanova-openai-compat.md
+++ b/docs/source/providers/inference/remote_sambanova-openai-compat.md
@ -15,7 +15,7 @@ SambaNova OpenAI-compatible provider for using SambaNova models with OpenAI API

 ```yaml
 openai_compat_api_base: https://api.sambanova.ai/v1
-api_key: ${env.SAMBANOVA_API_KEY}
+api_key: ${env.SAMBANOVA_API_KEY:=}

 ```

--- a/docs/source/providers/inference/remote_sambanova.md
+++ b/docs/source/providers/inference/remote_sambanova.md
@ -15,7 +15,7 @@ SambaNova inference provider for running models on SambaNova's dataflow architec

 ```yaml
 url: https://api.sambanova.ai/v1
-api_key: ${env.SAMBANOVA_API_KEY}
+api_key: ${env.SAMBANOVA_API_KEY:=}

 ```

--- a/docs/source/providers/inference/remote_tgi.md
+++ b/docs/source/providers/inference/remote_tgi.md
@ -13,7 +13,7 @@ Text Generation Inference (TGI) provider for HuggingFace model serving.
 ## Sample Configuration

 ```yaml
-url: ${env.TGI_URL}
+url: ${env.TGI_URL:=}

 ```

--- a/docs/source/providers/inference/remote_together.md
+++ b/docs/source/providers/inference/remote_together.md
@ -16,7 +16,7 @@ Together AI inference provider for open-source models and collaborative AI devel

 ```yaml
 url: https://api.together.xyz/v1
-api_key: ${env.TOGETHER_API_KEY}
+api_key: ${env.TOGETHER_API_KEY:=}

 ```

--- a/docs/source/providers/safety/remote_sambanova.md
+++ b/docs/source/providers/safety/remote_sambanova.md
@ -15,7 +15,7 @@ SambaNova's safety provider for content moderation and safety filtering.

 ```yaml
 url: https://api.sambanova.ai/v1
-api_key: ${env.SAMBANOVA_API_KEY}
+api_key: ${env.SAMBANOVA_API_KEY:=}

 ```

--- a/llama_stack/apis/inference/inference.py
+++ b/llama_stack/apis/inference/inference.py
@ -455,8 +455,21 @@ class OpenAIChatCompletionContentPartImageParam(BaseModel):
    image_url: OpenAIImageURL


+@json_schema_type
+class OpenAIFileFile(BaseModel):
+    file_data: str | None = None
+    file_id: str | None = None
+    filename: str | None = None
+
+
+@json_schema_type
+class OpenAIFile(BaseModel):
+    type: Literal["file"] = "file"
+    file: OpenAIFileFile
+
+
 OpenAIChatCompletionContentPartParam = Annotated[
-    OpenAIChatCompletionContentPartTextParam | OpenAIChatCompletionContentPartImageParam,
+    OpenAIChatCompletionContentPartTextParam | OpenAIChatCompletionContentPartImageParam | OpenAIFile,
    Field(discriminator="type"),
 ]
 register_schema(OpenAIChatCompletionContentPartParam, name="OpenAIChatCompletionContentPartParam")
@ -464,6 +477,8 @@ register_schema(OpenAIChatCompletionContentPartParam, name="OpenAIChatCompletion

 OpenAIChatCompletionMessageContent = str | list[OpenAIChatCompletionContentPartParam]

+OpenAIChatCompletionTextOnlyMessageContent = str | list[OpenAIChatCompletionContentPartTextParam]
+

@json_schema_type
 class OpenAIUserMessageParam(BaseModel):
@ -489,7 +504,7 @@ class OpenAISystemMessageParam(BaseModel):
    """

    role: Literal["system"] = "system"
-    content: OpenAIChatCompletionMessageContent
+    content: OpenAIChatCompletionTextOnlyMessageContent
    name: str | None = None


@ -518,7 +533,7 @@ class OpenAIAssistantMessageParam(BaseModel):
    """

    role: Literal["assistant"] = "assistant"
-    content: OpenAIChatCompletionMessageContent | None = None
+    content: OpenAIChatCompletionTextOnlyMessageContent | None = None
    name: str | None = None
    tool_calls: list[OpenAIChatCompletionToolCall] | None = None

@ -534,7 +549,7 @@ class OpenAIToolMessageParam(BaseModel):

    role: Literal["tool"] = "tool"
    tool_call_id: str
-    content: OpenAIChatCompletionMessageContent
+    content: OpenAIChatCompletionTextOnlyMessageContent


@json_schema_type
@ -547,7 +562,7 @@ class OpenAIDeveloperMessageParam(BaseModel):
    """

    role: Literal["developer"] = "developer"
-    content: OpenAIChatCompletionMessageContent
+    content: OpenAIChatCompletionTextOnlyMessageContent
    name: str | None = None


--- a/llama_stack/cli/stack/_build.py
+++ b/llama_stack/cli/stack/_build.py
@ -31,6 +31,7 @@ from llama_stack.distribution.build import (
 from llama_stack.distribution.configure import parse_and_maybe_upgrade_config
 from llama_stack.distribution.datatypes import (
    BuildConfig,
+    BuildProvider,
    DistributionSpec,
    Provider,
    StackRunConfig,
@ -94,7 +95,7 @@ def run_stack_build_command(args: argparse.Namespace) -> None:
            )
            sys.exit(1)
    elif args.providers:
-        provider_list: dict[str, list[Provider]] = dict()
+        provider_list: dict[str, list[BuildProvider]] = dict()
        for api_provider in args.providers.split(","):
            if "=" not in api_provider:
                cprint(
@ -113,10 +114,8 @@ def run_stack_build_command(args: argparse.Namespace) -> None:
                )
                sys.exit(1)
            if provider_type in providers_for_api:
-                provider = Provider(
+                provider = BuildProvider(
                    provider_type=provider_type,
-                    provider_id=provider_type.split("::")[1],
-                    config={},
                    module=None,
                )
                provider_list.setdefault(api, []).append(provider)
@ -189,7 +188,7 @@ def run_stack_build_command(args: argparse.Namespace) -> None:

        cprint("Tip: use <TAB> to see options for the providers.\n", color="green", file=sys.stderr)

-        providers: dict[str, list[Provider]] = dict()
+        providers: dict[str, list[BuildProvider]] = dict()
        for api, providers_for_api in get_provider_registry().items():
            available_providers = [x for x in providers_for_api.keys() if x not in ("remote", "remote::sample")]
            if not available_providers:
@ -204,7 +203,10 @@ def run_stack_build_command(args: argparse.Namespace) -> None:
                ),
            )

-            providers[api.value] = api_provider
+            string_providers = api_provider.split(" ")
+
+            for provider in string_providers:
+                providers.setdefault(api.value, []).append(BuildProvider(provider_type=provider))

        description = prompt(
            "\n > (Optional) Enter a short description for your Llama Stack: ",
@ -307,7 +309,7 @@ def _generate_run_config(
        providers = build_config.distribution_spec.providers[api]

        for provider in providers:
-            pid = provider.provider_id
+            pid = provider.provider_type.split("::")[-1]

            p = provider_registry[Api(api)][provider.provider_type]
            if p.deprecation_error:
--- a/llama_stack/distribution/build_container.sh
+++ b/llama_stack/distribution/build_container.sh
@ -18,10 +18,6 @@ UV_HTTP_TIMEOUT=${UV_HTTP_TIMEOUT:-500}

 # mounting is not supported by docker buildx, so we use COPY instead
 USE_COPY_NOT_MOUNT=${USE_COPY_NOT_MOUNT:-}
-
-# Mount command for cache container .cache, can be overridden by the user if needed
-MOUNT_CACHE=${MOUNT_CACHE:-"--mount=type=cache,id=llama-stack-cache,target=/root/.cache"}
-
 # Path to the run.yaml file in the container
 RUN_CONFIG_PATH=/app/run.yaml

@ -176,18 +172,13 @@ RUN pip install uv
 EOF
 fi

-# Set the link mode to copy so that uv doesn't attempt to symlink to the cache directory
-add_to_container << EOF
-ENV UV_LINK_MODE=copy
-EOF
-
 # Add pip dependencies first since llama-stack is what will change most often
 # so we can reuse layers.
 if [ -n "$normal_deps" ]; then
  read -ra pip_args <<<  "$normal_deps"
  quoted_deps=$(printf " %q" "${pip_args[@]}")
  add_to_container << EOF
-RUN $MOUNT_CACHE uv pip install $quoted_deps
+RUN uv pip install --no-cache $quoted_deps
 EOF
 fi

@ -197,7 +188,7 @@ if [ -n "$optional_deps" ]; then
    read -ra pip_args <<< "$part"
    quoted_deps=$(printf " %q" "${pip_args[@]}")
    add_to_container <<EOF
-RUN $MOUNT_CACHE uv pip install $quoted_deps
+RUN uv pip install --no-cache $quoted_deps
 EOF
  done
 fi
@ -208,10 +199,10 @@ if [ -n "$external_provider_deps" ]; then
    read -ra pip_args <<< "$part"
    quoted_deps=$(printf " %q" "${pip_args[@]}")
    add_to_container <<EOF
-RUN $MOUNT_CACHE uv pip install $quoted_deps
+RUN uv pip install --no-cache $quoted_deps
 EOF
    add_to_container <<EOF
-RUN python3 - <<PYTHON | $MOUNT_CACHE uv pip install -r -
+RUN python3 - <<PYTHON | uv pip install --no-cache -r -
 import importlib
 import sys

@ -293,7 +284,7 @@ COPY $dir $mount_point
 EOF
  fi
  add_to_container << EOF
-RUN $MOUNT_CACHE uv pip install -e $mount_point
+RUN uv pip install --no-cache -e $mount_point
 EOF
 }

@ -308,10 +299,10 @@ else
  if [ -n "$TEST_PYPI_VERSION" ]; then
    # these packages are damaged in test-pypi, so install them first
    add_to_container << EOF
-RUN $MOUNT_CACHE uv pip install fastapi libcst
+RUN uv pip install --no-cache fastapi libcst
 EOF
    add_to_container << EOF
-RUN $MOUNT_CACHE uv pip install --extra-index-url https://test.pypi.org/simple/ \
+RUN uv pip install --no-cache --extra-index-url https://test.pypi.org/simple/ \
  --index-strategy unsafe-best-match \
  llama-stack==$TEST_PYPI_VERSION

@ -323,7 +314,7 @@ EOF
      SPEC_VERSION="llama-stack"
    fi
    add_to_container << EOF
-RUN $MOUNT_CACHE uv pip install $SPEC_VERSION
+RUN uv pip install --no-cache $SPEC_VERSION
 EOF
  fi
 fi
--- a/llama_stack/distribution/configure.py
+++ b/llama_stack/distribution/configure.py
@ -100,11 +100,12 @@ def configure_api_providers(config: StackRunConfig, build_spec: DistributionSpec
                    break

                logger.info(f"> Configuring provider `({provider.provider_type})`")
+                pid = provider.provider_type.split("::")[-1]
                updated_providers.append(
                    configure_single_provider(
                        provider_registry[api],
                        Provider(
-                            provider_id=(f"{provider.provider_id}-{i:02d}" if len(plist) > 1 else provider.provider_id),
+                            provider_id=(f"{pid}-{i:02d}" if len(plist) > 1 else pid),
                            provider_type=provider.provider_type,
                            config={},
                        ),
--- a/llama_stack/distribution/datatypes.py
+++ b/llama_stack/distribution/datatypes.py
@ -154,13 +154,27 @@ class Provider(BaseModel):
    )


+class BuildProvider(BaseModel):
+    provider_type: str
+    module: str | None = Field(
+        default=None,
+        description="""
+ Fully-qualified name of the external provider module to import. The module is expected to have:
+
+  - `get_adapter_impl(config, deps)`: returns the adapter implementation
+
+  Example: `module: ramalama_stack`
+ """,
+    )
+
+
 class DistributionSpec(BaseModel):
    description: str | None = Field(
        default="",
        description="Description of the distribution",
    )
    container_image: str | None = None
-    providers: dict[str, list[Provider]] = Field(
+    providers: dict[str, list[BuildProvider]] = Field(
        default_factory=dict,
        description="""
        Provider Types for each of the APIs provided by this distribution. If you
--- a/llama_stack/distribution/library_client.py
+++ b/llama_stack/distribution/library_client.py
@ -33,7 +33,7 @@ from termcolor import cprint

 from llama_stack.distribution.build import print_pip_install_help
 from llama_stack.distribution.configure import parse_and_maybe_upgrade_config
-from llama_stack.distribution.datatypes import Api, BuildConfig, DistributionSpec
+from llama_stack.distribution.datatypes import Api, BuildConfig, BuildProvider, DistributionSpec
 from llama_stack.distribution.request_headers import (
    PROVIDER_DATA_VAR,
    request_provider_data_context,
@ -249,9 +249,16 @@ class AsyncLlamaStackAsLibraryClient(AsyncLlamaStackClient):
                file=sys.stderr,
            )
            if self.config_path_or_template_name.endswith(".yaml"):
+                providers: dict[str, list[BuildProvider]] = {}
+                for api, run_providers in self.config.providers.items():
+                    for provider in run_providers:
+                        providers.setdefault(api, []).append(
+                            BuildProvider(provider_type=provider.provider_type, module=provider.module)
+                        )
+                providers = dict(providers)
                build_config = BuildConfig(
                    distribution_spec=DistributionSpec(
-                        providers=self.config.providers,
+                        providers=providers,
                    ),
                    external_providers_dir=self.config.external_providers_dir,
                )
--- a/llama_stack/distribution/routing_tables/models.py
+++ b/llama_stack/distribution/routing_tables/models.py
@ -25,7 +25,8 @@ class ModelsRoutingTable(CommonRoutingTableImpl, Models):
    async def refresh(self) -> None:
        for provider_id, provider in self.impls_by_provider_id.items():
            refresh = await provider.should_refresh_models()
-            if not (refresh or provider_id in self.listed_providers):
+            refresh = refresh or provider_id not in self.listed_providers
+            if not refresh:
                continue

            try:
@ -138,6 +139,9 @@ class ModelsRoutingTable(CommonRoutingTableImpl, Models):
                # avoid overwriting a non-provider-registered model entry
                continue

+            if model.identifier == model.provider_resource_id:
+                model.identifier = f"{provider_id}/{model.provider_resource_id}"
+
            logger.debug(f"registering model {model.identifier} ({model.provider_resource_id})")
            await self.register_object(
                ModelWithOwner(
--- a/llama_stack/distribution/server/server.py
+++ b/llama_stack/distribution/server/server.py
@ -611,11 +611,8 @@ def extract_path_params(route: str) -> list[str]:

 def remove_disabled_providers(obj):
    if isinstance(obj, dict):
-        if (
-            obj.get("provider_id") == "__disabled__"
-            or obj.get("shield_id") == "__disabled__"
-            or obj.get("provider_model_id") == "__disabled__"
-        ):
+        keys = ["provider_id", "shield_id", "provider_model_id", "model_id"]
+        if any(k in obj and obj[k] in ("__disabled__", "", None) for k in keys):
            return None
        return {k: v for k, v in ((k, remove_disabled_providers(v)) for k, v in obj.items()) if v is not None}
    elif isinstance(obj, list):
--- a/llama_stack/distribution/stack.py
+++ b/llama_stack/distribution/stack.py
@ -105,23 +105,10 @@ async def register_resources(run_config: StackRunConfig, impls: dict[Api, Any]):
        method = getattr(impls[api], register_method)
        for obj in objects:
            logger.debug(f"registering {rsrc.capitalize()} {obj} for provider {obj.provider_id}")
-            # Do not register models on disabled providers
-            if hasattr(obj, "provider_id") and obj.provider_id is not None and obj.provider_id == "__disabled__":
-                logger.debug(f"Skipping {rsrc.capitalize()} registration for disabled provider.")
-                continue
-            # In complex templates, like our starter template, we may have dynamic model ids
-            # given by environment variables. This allows those environment variables to have
-            # a default value of __disabled__ to skip registration of the model if not set.
-            if (
-                hasattr(obj, "provider_model_id")
-                and obj.provider_model_id is not None
-                and "__disabled__" in obj.provider_model_id
-            ):
-                logger.debug(f"Skipping {rsrc.capitalize()} registration for disabled model.")
-                continue

-            if hasattr(obj, "shield_id") and obj.shield_id is not None and obj.shield_id == "__disabled__":
-                logger.debug(f"Skipping {rsrc.capitalize()} registration for disabled shield.")
+            # Do not register models on disabled providers
+            if hasattr(obj, "provider_id") and (not obj.provider_id or obj.provider_id == "__disabled__"):
+                logger.debug(f"Skipping {rsrc.capitalize()} registration for disabled provider.")
                continue

            # we want to maintain the type information in arguments to method.
@ -331,8 +318,10 @@ async def construct_stack(

    await register_resources(run_config, impls)

+    await refresh_registry_once(impls)
+
    global REGISTRY_REFRESH_TASK
-    REGISTRY_REFRESH_TASK = asyncio.create_task(refresh_registry(impls))
+    REGISTRY_REFRESH_TASK = asyncio.create_task(refresh_registry_task(impls))

    def cb(task):
        import traceback
@ -368,11 +357,17 @@ async def shutdown_stack(impls: dict[Api, Any]):
        REGISTRY_REFRESH_TASK.cancel()


-async def refresh_registry(impls: dict[Api, Any]):
+async def refresh_registry_once(impls: dict[Api, Any]):
+    logger.debug("refreshing registry")
    routing_tables = [v for v in impls.values() if isinstance(v, CommonRoutingTableImpl)]
+    for routing_table in routing_tables:
+        await routing_table.refresh()
+
+
+async def refresh_registry_task(impls: dict[Api, Any]):
+    logger.info("starting registry refresh task")
    while True:
-        for routing_table in routing_tables:
-            await routing_table.refresh()
+        await refresh_registry_once(impls)

        await asyncio.sleep(REGISTRY_REFRESH_INTERVAL_SECONDS)

--- a/llama_stack/providers/datatypes.py
+++ b/llama_stack/providers/datatypes.py
@ -43,6 +43,9 @@ class ModelsProtocolPrivate(Protocol):
       -> Provider uses provider-model-id for inference
    """

+    # this should be called `on_model_register` or something like that.
+    # the provider should _not_ be able to change the object in this
+    # callback
    async def register_model(self, model: Model) -> Model: ...

    async def unregister_model(self, model_id: str) -> None: ...
--- a/llama_stack/providers/inline/safety/llama_guard/llama_guard.py
+++ b/llama_stack/providers/inline/safety/llama_guard/llama_guard.py
@ -146,9 +146,9 @@ class LlamaGuardSafetyImpl(Safety, ShieldsProtocolPrivate):
        pass

    async def register_shield(self, shield: Shield) -> None:
-        # Allow any model to be registered as a shield
-        # The model will be validated during runtime when making inference calls
-        pass
+        model_id = shield.provider_resource_id
+        if not model_id:
+            raise ValueError("Llama Guard shield must have a model id")

    async def run_shield(
        self,
--- a/llama_stack/providers/remote/inference/anthropic/anthropic.py
+++ b/llama_stack/providers/remote/inference/anthropic/anthropic.py
@ -15,6 +15,7 @@ class AnthropicInferenceAdapter(LiteLLMOpenAIMixin):
        LiteLLMOpenAIMixin.__init__(
            self,
            MODEL_ENTRIES,
+            litellm_provider_name="anthropic",
            api_key_from_config=config.api_key,
            provider_data_api_key_field="anthropic_api_key",
        )
--- a/llama_stack/providers/remote/inference/anthropic/config.py
+++ b/llama_stack/providers/remote/inference/anthropic/config.py
@ -26,7 +26,7 @@ class AnthropicConfig(BaseModel):
    )

    @classmethod
-    def sample_run_config(cls, api_key: str = "${env.ANTHROPIC_API_KEY}", **kwargs) -> dict[str, Any]:
+    def sample_run_config(cls, api_key: str = "${env.ANTHROPIC_API_KEY:=}", **kwargs) -> dict[str, Any]:
        return {
            "api_key": api_key,
        }
--- a/llama_stack/providers/remote/inference/anthropic/models.py
+++ b/llama_stack/providers/remote/inference/anthropic/models.py
@ -10,9 +10,9 @@ from llama_stack.providers.utils.inference.model_registry import (
 )

 LLM_MODEL_IDS = [
-    "anthropic/claude-3-5-sonnet-latest",
-    "anthropic/claude-3-7-sonnet-latest",
-    "anthropic/claude-3-5-haiku-latest",
+    "claude-3-5-sonnet-latest",
+    "claude-3-7-sonnet-latest",
+    "claude-3-5-haiku-latest",
 ]

 SAFETY_MODELS_ENTRIES = []
@ -21,17 +21,17 @@ MODEL_ENTRIES = (
    [ProviderModelEntry(provider_model_id=m) for m in LLM_MODEL_IDS]
    + [
        ProviderModelEntry(
-            provider_model_id="anthropic/voyage-3",
+            provider_model_id="voyage-3",
            model_type=ModelType.embedding,
            metadata={"embedding_dimension": 1024, "context_length": 32000},
        ),
        ProviderModelEntry(
-            provider_model_id="anthropic/voyage-3-lite",
+            provider_model_id="voyage-3-lite",
            model_type=ModelType.embedding,
            metadata={"embedding_dimension": 512, "context_length": 32000},
        ),
        ProviderModelEntry(
-            provider_model_id="anthropic/voyage-code-3",
+            provider_model_id="voyage-code-3",
            model_type=ModelType.embedding,
            metadata={"embedding_dimension": 1024, "context_length": 32000},
        ),
--- a/llama_stack/providers/remote/inference/bedrock/bedrock.py
+++ b/llama_stack/providers/remote/inference/bedrock/bedrock.py
@ -63,18 +63,20 @@ class BedrockInferenceAdapter(
    def __init__(self, config: BedrockConfig) -> None:
        ModelRegistryHelper.__init__(self, MODEL_ENTRIES)
        self._config = config
-
-        self._client = create_bedrock_client(config)
+        self._client = None

    @property
    def client(self) -> BaseClient:
+        if self._client is None:
+            self._client = create_bedrock_client(self._config)
        return self._client

    async def initialize(self) -> None:
        pass

    async def shutdown(self) -> None:
-        self.client.close()
+        if self._client is not None:
+            self._client.close()

    async def completion(
        self,
--- a/llama_stack/providers/remote/inference/cerebras/cerebras.py
+++ b/llama_stack/providers/remote/inference/cerebras/cerebras.py
@ -65,6 +65,7 @@ class CerebrasInferenceAdapter(
        )
        self.config = config

+        # TODO: make this use provider data, etc. like other providers
        self.client = AsyncCerebras(
            base_url=self.config.base_url,
            api_key=self.config.api_key.get_secret_value(),
--- a/llama_stack/providers/remote/inference/cerebras/config.py
+++ b/llama_stack/providers/remote/inference/cerebras/config.py
@ -26,7 +26,7 @@ class CerebrasImplConfig(BaseModel):
    )

    @classmethod
-    def sample_run_config(cls, api_key: str = "${env.CEREBRAS_API_KEY}", **kwargs) -> dict[str, Any]:
+    def sample_run_config(cls, api_key: str = "${env.CEREBRAS_API_KEY:=}", **kwargs) -> dict[str, Any]:
        return {
            "base_url": DEFAULT_BASE_URL,
            "api_key": api_key,
--- a/llama_stack/providers/remote/inference/databricks/config.py
+++ b/llama_stack/providers/remote/inference/databricks/config.py
@ -25,8 +25,8 @@ class DatabricksImplConfig(BaseModel):
    @classmethod
    def sample_run_config(
        cls,
-        url: str = "${env.DATABRICKS_URL}",
-        api_token: str = "${env.DATABRICKS_API_TOKEN}",
+        url: str = "${env.DATABRICKS_URL:=}",
+        api_token: str = "${env.DATABRICKS_API_TOKEN:=}",
        **kwargs: Any,
    ) -> dict[str, Any]:
        return {
--- a/llama_stack/providers/remote/inference/fireworks/config.py
+++ b/llama_stack/providers/remote/inference/fireworks/config.py
@ -24,7 +24,7 @@ class FireworksImplConfig(RemoteInferenceProviderConfig):
    )

    @classmethod
-    def sample_run_config(cls, api_key: str = "${env.FIREWORKS_API_KEY}", **kwargs) -> dict[str, Any]:
+    def sample_run_config(cls, api_key: str = "${env.FIREWORKS_API_KEY:=}", **kwargs) -> dict[str, Any]:
        return {
            "url": "https://api.fireworks.ai/inference/v1",
            "api_key": api_key,
--- a/llama_stack/providers/remote/inference/gemini/config.py
+++ b/llama_stack/providers/remote/inference/gemini/config.py
@ -26,7 +26,7 @@ class GeminiConfig(BaseModel):
    )

    @classmethod
-    def sample_run_config(cls, api_key: str = "${env.GEMINI_API_KEY}", **kwargs) -> dict[str, Any]:
+    def sample_run_config(cls, api_key: str = "${env.GEMINI_API_KEY:=}", **kwargs) -> dict[str, Any]:
        return {
            "api_key": api_key,
        }
--- a/llama_stack/providers/remote/inference/gemini/gemini.py
+++ b/llama_stack/providers/remote/inference/gemini/gemini.py
@ -15,6 +15,7 @@ class GeminiInferenceAdapter(LiteLLMOpenAIMixin):
        LiteLLMOpenAIMixin.__init__(
            self,
            MODEL_ENTRIES,
+            litellm_provider_name="gemini",
            api_key_from_config=config.api_key,
            provider_data_api_key_field="gemini_api_key",
        )
--- a/llama_stack/providers/remote/inference/gemini/models.py
+++ b/llama_stack/providers/remote/inference/gemini/models.py
@ -10,11 +10,11 @@ from llama_stack.providers.utils.inference.model_registry import (
 )

 LLM_MODEL_IDS = [
-    "gemini/gemini-1.5-flash",
-    "gemini/gemini-1.5-pro",
-    "gemini/gemini-2.0-flash",
-    "gemini/gemini-2.5-flash",
-    "gemini/gemini-2.5-pro",
+    "gemini-1.5-flash",
+    "gemini-1.5-pro",
+    "gemini-2.0-flash",
+    "gemini-2.5-flash",
+    "gemini-2.5-pro",
 ]

 SAFETY_MODELS_ENTRIES = []
@ -23,7 +23,7 @@ MODEL_ENTRIES = (
    [ProviderModelEntry(provider_model_id=m) for m in LLM_MODEL_IDS]
    + [
        ProviderModelEntry(
-            provider_model_id="gemini/text-embedding-004",
+            provider_model_id="text-embedding-004",
            model_type=ModelType.embedding,
            metadata={"embedding_dimension": 768, "context_length": 2048},
        ),
--- a/llama_stack/providers/remote/inference/groq/config.py
+++ b/llama_stack/providers/remote/inference/groq/config.py
@ -32,7 +32,7 @@ class GroqConfig(BaseModel):
    )

    @classmethod
-    def sample_run_config(cls, api_key: str = "${env.GROQ_API_KEY}", **kwargs) -> dict[str, Any]:
+    def sample_run_config(cls, api_key: str = "${env.GROQ_API_KEY:=}", **kwargs) -> dict[str, Any]:
        return {
            "url": "https://api.groq.com",
            "api_key": api_key,
--- a/llama_stack/providers/remote/inference/groq/groq.py
+++ b/llama_stack/providers/remote/inference/groq/groq.py
@ -34,6 +34,7 @@ class GroqInferenceAdapter(LiteLLMOpenAIMixin):
        LiteLLMOpenAIMixin.__init__(
            self,
            model_entries=MODEL_ENTRIES,
+            litellm_provider_name="groq",
            api_key_from_config=config.api_key,
            provider_data_api_key_field="groq_api_key",
        )
@ -96,7 +97,7 @@ class GroqInferenceAdapter(LiteLLMOpenAIMixin):
            tool_choice = "required"

        params = await prepare_openai_completion_params(
-            model=model_obj.provider_resource_id.replace("groq/", ""),
+            model=model_obj.provider_resource_id,
            messages=messages,
            frequency_penalty=frequency_penalty,
            function_call=function_call,
--- a/llama_stack/providers/remote/inference/groq/models.py
+++ b/llama_stack/providers/remote/inference/groq/models.py
@ -14,19 +14,19 @@ SAFETY_MODELS_ENTRIES = []

 MODEL_ENTRIES = [
    build_hf_repo_model_entry(
-        "groq/llama3-8b-8192",
+        "llama3-8b-8192",
        CoreModelId.llama3_1_8b_instruct.value,
    ),
    build_model_entry(
-        "groq/llama-3.1-8b-instant",
+        "llama-3.1-8b-instant",
        CoreModelId.llama3_1_8b_instruct.value,
    ),
    build_hf_repo_model_entry(
-        "groq/llama3-70b-8192",
+        "llama3-70b-8192",
        CoreModelId.llama3_70b_instruct.value,
    ),
    build_hf_repo_model_entry(
-        "groq/llama-3.3-70b-versatile",
+        "llama-3.3-70b-versatile",
        CoreModelId.llama3_3_70b_instruct.value,
    ),
    # Groq only contains a preview version for llama-3.2-3b
@ -34,23 +34,15 @@ MODEL_ENTRIES = [
    # to pass the test fixture
    # TODO(aidand): Replace this with a stable model once Groq supports it
    build_hf_repo_model_entry(
-        "groq/llama-3.2-3b-preview",
+        "llama-3.2-3b-preview",
        CoreModelId.llama3_2_3b_instruct.value,
    ),
    build_hf_repo_model_entry(
-        "groq/llama-4-scout-17b-16e-instruct",
+        "meta-llama/llama-4-scout-17b-16e-instruct",
        CoreModelId.llama4_scout_17b_16e_instruct.value,
    ),
    build_hf_repo_model_entry(
-        "groq/meta-llama/llama-4-scout-17b-16e-instruct",
-        CoreModelId.llama4_scout_17b_16e_instruct.value,
-    ),
-    build_hf_repo_model_entry(
-        "groq/llama-4-maverick-17b-128e-instruct",
-        CoreModelId.llama4_maverick_17b_128e_instruct.value,
-    ),
-    build_hf_repo_model_entry(
-        "groq/meta-llama/llama-4-maverick-17b-128e-instruct",
+        "meta-llama/llama-4-maverick-17b-128e-instruct",
        CoreModelId.llama4_maverick_17b_128e_instruct.value,
    ),
 ] + SAFETY_MODELS_ENTRIES
--- a/llama_stack/providers/remote/inference/llama_openai_compat/llama.py
+++ b/llama_stack/providers/remote/inference/llama_openai_compat/llama.py
@ -32,6 +32,7 @@ class LlamaCompatInferenceAdapter(OpenAIMixin, LiteLLMOpenAIMixin):
        LiteLLMOpenAIMixin.__init__(
            self,
            model_entries=MODEL_ENTRIES,
+            litellm_provider_name="meta_llama",
            api_key_from_config=config.api_key,
            provider_data_api_key_field="llama_api_key",
            openai_compat_api_base=config.openai_compat_api_base,
--- a/llama_stack/providers/remote/inference/ollama/ollama.py
+++ b/llama_stack/providers/remote/inference/ollama/ollama.py
@ -166,7 +166,7 @@ class OllamaInferenceAdapter(
        ]
        for m in response.models:
            # kill embedding models since we don't know dimensions for them
-            if m.details.family in ["bert"]:
+            if "bert" in m.details.family:
                continue
            models.append(
                Model(
@ -420,9 +420,6 @@ class OllamaInferenceAdapter(
        except ValueError:
            pass  # Ignore statically unknown model, will check live listing

-        if model.provider_resource_id is None:
-            raise ValueError("Model provider_resource_id cannot be None")
-
        if model.model_type == ModelType.embedding:
            response = await self.client.list()
            if model.provider_resource_id not in [m.model for m in response.models]:
@ -433,9 +430,9 @@ class OllamaInferenceAdapter(
        #  - models not currently running are run by the ollama server as needed
        response = await self.client.list()
        available_models = [m.model for m in response.models]
-        provider_resource_id = self.register_helper.get_provider_model_id(model.provider_resource_id)
-        if provider_resource_id is None:
-            provider_resource_id = model.provider_resource_id
+
+        provider_resource_id = model.provider_resource_id
+        assert provider_resource_id is not None  # mypy
        if provider_resource_id not in available_models:
            available_models_latest = [m.model.split(":latest")[0] for m in response.models]
            if provider_resource_id in available_models_latest:
@ -443,7 +440,9 @@ class OllamaInferenceAdapter(
                    f"Imprecise provider resource id was used but 'latest' is available in Ollama - using '{model.provider_resource_id}:latest'"
                )
                return model
-            raise UnsupportedModelError(model.provider_resource_id, available_models)
+            raise UnsupportedModelError(provider_resource_id, available_models)
+
+        # mutating this should be considered an anti-pattern
        model.provider_resource_id = provider_resource_id

        return model
--- a/llama_stack/providers/remote/inference/openai/config.py
+++ b/llama_stack/providers/remote/inference/openai/config.py
@ -24,9 +24,19 @@ class OpenAIConfig(BaseModel):
        default=None,
        description="API key for OpenAI models",
    )
+    base_url: str = Field(
+        default="https://api.openai.com/v1",
+        description="Base URL for OpenAI API",
+    )

    @classmethod
-    def sample_run_config(cls, api_key: str = "${env.OPENAI_API_KEY}", **kwargs) -> dict[str, Any]:
+    def sample_run_config(
+        cls,
+        api_key: str = "${env.OPENAI_API_KEY:=}",
+        base_url: str = "${env.OPENAI_BASE_URL:=https://api.openai.com/v1}",
+        **kwargs,
+    ) -> dict[str, Any]:
        return {
            "api_key": api_key,
+            "base_url": base_url,
        }
--- a/llama_stack/providers/remote/inference/openai/openai.py
+++ b/llama_stack/providers/remote/inference/openai/openai.py
@ -45,6 +45,7 @@ class OpenAIInferenceAdapter(OpenAIMixin, LiteLLMOpenAIMixin):
        LiteLLMOpenAIMixin.__init__(
            self,
            MODEL_ENTRIES,
+            litellm_provider_name="openai",
            api_key_from_config=config.api_key,
            provider_data_api_key_field="openai_api_key",
        )
@ -64,9 +65,9 @@ class OpenAIInferenceAdapter(OpenAIMixin, LiteLLMOpenAIMixin):
        """
        Get the OpenAI API base URL.

-        Returns the standard OpenAI API base URL for direct OpenAI API calls.
+        Returns the OpenAI API base URL from the configuration.
        """
-        return "https://api.openai.com/v1"
+        return self.config.base_url

    async def initialize(self) -> None:
        await super().initialize()
--- a/llama_stack/providers/remote/inference/sambanova/config.py
+++ b/llama_stack/providers/remote/inference/sambanova/config.py
@ -30,7 +30,7 @@ class SambaNovaImplConfig(BaseModel):
    )

    @classmethod
-    def sample_run_config(cls, api_key: str = "${env.SAMBANOVA_API_KEY}", **kwargs) -> dict[str, Any]:
+    def sample_run_config(cls, api_key: str = "${env.SAMBANOVA_API_KEY:=}", **kwargs) -> dict[str, Any]:
        return {
            "url": "https://api.sambanova.ai/v1",
            "api_key": api_key,
--- a/llama_stack/providers/remote/inference/sambanova/models.py
+++ b/llama_stack/providers/remote/inference/sambanova/models.py
@ -9,49 +9,20 @@ from llama_stack.providers.utils.inference.model_registry import (
    build_hf_repo_model_entry,
 )

-SAFETY_MODELS_ENTRIES = [
-    build_hf_repo_model_entry(
-        "sambanova/Meta-Llama-Guard-3-8B",
-        CoreModelId.llama_guard_3_8b.value,
-    ),
-]
+SAFETY_MODELS_ENTRIES = []


 MODEL_ENTRIES = [
    build_hf_repo_model_entry(
-        "sambanova/Meta-Llama-3.1-8B-Instruct",
+        "Meta-Llama-3.1-8B-Instruct",
        CoreModelId.llama3_1_8b_instruct.value,
    ),
    build_hf_repo_model_entry(
-        "sambanova/Meta-Llama-3.1-405B-Instruct",
-        CoreModelId.llama3_1_405b_instruct.value,
-    ),
-    build_hf_repo_model_entry(
-        "sambanova/Meta-Llama-3.2-1B-Instruct",
-        CoreModelId.llama3_2_1b_instruct.value,
-    ),
-    build_hf_repo_model_entry(
-        "sambanova/Meta-Llama-3.2-3B-Instruct",
-        CoreModelId.llama3_2_3b_instruct.value,
-    ),
-    build_hf_repo_model_entry(
-        "sambanova/Meta-Llama-3.3-70B-Instruct",
+        "Meta-Llama-3.3-70B-Instruct",
        CoreModelId.llama3_3_70b_instruct.value,
    ),
    build_hf_repo_model_entry(
-        "sambanova/Llama-3.2-11B-Vision-Instruct",
-        CoreModelId.llama3_2_11b_vision_instruct.value,
-    ),
-    build_hf_repo_model_entry(
-        "sambanova/Llama-3.2-90B-Vision-Instruct",
-        CoreModelId.llama3_2_90b_vision_instruct.value,
-    ),
-    build_hf_repo_model_entry(
-        "sambanova/Llama-4-Scout-17B-16E-Instruct",
-        CoreModelId.llama4_scout_17b_16e_instruct.value,
-    ),
-    build_hf_repo_model_entry(
-        "sambanova/Llama-4-Maverick-17B-128E-Instruct",
+        "Llama-4-Maverick-17B-128E-Instruct",
        CoreModelId.llama4_maverick_17b_128e_instruct.value,
    ),
 ] + SAFETY_MODELS_ENTRIES
--- a/llama_stack/providers/remote/inference/sambanova/sambanova.py
+++ b/llama_stack/providers/remote/inference/sambanova/sambanova.py
@ -182,6 +182,7 @@ class SambaNovaInferenceAdapter(LiteLLMOpenAIMixin):
        LiteLLMOpenAIMixin.__init__(
            self,
            model_entries=MODEL_ENTRIES,
+            litellm_provider_name="sambanova",
            api_key_from_config=self.config.api_key.get_secret_value() if self.config.api_key else None,
            provider_data_api_key_field="sambanova_api_key",
        )
--- a/llama_stack/providers/remote/inference/tgi/config.py
+++ b/llama_stack/providers/remote/inference/tgi/config.py
@ -19,7 +19,7 @@ class TGIImplConfig(BaseModel):
    @classmethod
    def sample_run_config(
        cls,
-        url: str = "${env.TGI_URL}",
+        url: str = "${env.TGI_URL:=}",
        **kwargs,
    ):
        return {
--- a/llama_stack/providers/remote/inference/tgi/tgi.py
+++ b/llama_stack/providers/remote/inference/tgi/tgi.py
@ -305,6 +305,8 @@ class _HfAdapter(

 class TGIAdapter(_HfAdapter):
    async def initialize(self, config: TGIImplConfig) -> None:
+        if not config.url:
+            raise ValueError("You must provide a URL in run.yaml (or via the TGI_URL environment variable) to use TGI.")
        log.info(f"Initializing TGI client with url={config.url}")
        self.client = AsyncInferenceClient(
            model=config.url,
--- a/llama_stack/providers/remote/inference/together/config.py
+++ b/llama_stack/providers/remote/inference/together/config.py
@ -27,5 +27,5 @@ class TogetherImplConfig(RemoteInferenceProviderConfig):
    def sample_run_config(cls, **kwargs) -> dict[str, Any]:
        return {
            "url": "https://api.together.xyz/v1",
-            "api_key": "${env.TOGETHER_API_KEY}",
+            "api_key": "${env.TOGETHER_API_KEY:=}",
        }
--- a/llama_stack/providers/remote/inference/together/models.py
+++ b/llama_stack/providers/remote/inference/together/models.py
@ -69,15 +69,9 @@ MODEL_ENTRIES = [
    build_hf_repo_model_entry(
        "meta-llama/Llama-4-Scout-17B-16E-Instruct",
        CoreModelId.llama4_scout_17b_16e_instruct.value,
-        additional_aliases=[
-            "together/meta-llama/Llama-4-Scout-17B-16E-Instruct",
-        ],
    ),
    build_hf_repo_model_entry(
        "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
        CoreModelId.llama4_maverick_17b_128e_instruct.value,
-        additional_aliases=[
-            "together/meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
-        ],
    ),
 ] + SAFETY_MODELS_ENTRIES
--- a/llama_stack/providers/remote/inference/vllm/vllm.py
+++ b/llama_stack/providers/remote/inference/vllm/vllm.py
@ -299,7 +299,10 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
        self.client = None

    async def initialize(self) -> None:
-        pass
+        if not self.config.url:
+            raise ValueError(
+                "You must provide a URL in run.yaml (or via the VLLM_URL environment variable) to use vLLM."
+            )

    async def should_refresh_models(self) -> bool:
        return self.config.refresh_models
@ -337,9 +340,6 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
            HealthResponse: A dictionary containing the health status.
        """
        try:
-            if not self.config.url:
-                return HealthResponse(status=HealthStatus.ERROR, message="vLLM URL is not set")
-
            client = self._create_client() if self.client is None else self.client
            _ = [m async for m in client.models.list()]  # Ensure the client is initialized
            return HealthResponse(status=HealthStatus.OK)
@ -355,11 +355,6 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
        if self.client is not None:
            return

-        if not self.config.url:
-            raise ValueError(
-                "You must provide a vLLM URL in the run.yaml file (or set the VLLM_URL environment variable)"
-            )
-
        log.info(f"Initializing vLLM client with base_url={self.config.url}")
        self.client = self._create_client()

--- a/llama_stack/providers/remote/safety/sambanova/config.py
+++ b/llama_stack/providers/remote/safety/sambanova/config.py
@ -30,7 +30,7 @@ class SambaNovaSafetyConfig(BaseModel):
    )

    @classmethod
-    def sample_run_config(cls, api_key: str = "${env.SAMBANOVA_API_KEY}", **kwargs) -> dict[str, Any]:
+    def sample_run_config(cls, api_key: str = "${env.SAMBANOVA_API_KEY:=}", **kwargs) -> dict[str, Any]:
        return {
            "url": "https://api.sambanova.ai/v1",
            "api_key": api_key,
--- a/llama_stack/providers/utils/inference/litellm_openai_mixin.py
+++ b/llama_stack/providers/utils/inference/litellm_openai_mixin.py
@ -68,11 +68,23 @@ class LiteLLMOpenAIMixin(
    def __init__(
        self,
        model_entries,
+        litellm_provider_name: str,
        api_key_from_config: str | None,
        provider_data_api_key_field: str,
        openai_compat_api_base: str | None = None,
    ):
+        """
+        Initialize the LiteLLMOpenAIMixin.
+
+        :param model_entries: The model entries to register.
+        :param api_key_from_config: The API key to use from the config.
+        :param provider_data_api_key_field: The field in the provider data that contains the API key.
+        :param litellm_provider_name: The name of the provider, used for model lookups.
+        :param openai_compat_api_base: The base URL for OpenAI compatibility, or None if not using OpenAI compatibility.
+        """
        ModelRegistryHelper.__init__(self, model_entries)
+
+        self.litellm_provider_name = litellm_provider_name
        self.api_key_from_config = api_key_from_config
        self.provider_data_api_key_field = provider_data_api_key_field
        self.api_base = openai_compat_api_base
@ -91,7 +103,11 @@ class LiteLLMOpenAIMixin(
    def get_litellm_model_name(self, model_id: str) -> str:
        # users may be using openai/ prefix in their model names. the openai/models.py did this by default.
        # model_id.startswith("openai/") is for backwards compatibility.
-        return "openai/" + model_id if self.is_openai_compat and not model_id.startswith("openai/") else model_id
+        return (
+            f"{self.litellm_provider_name}/{model_id}"
+            if self.is_openai_compat and not model_id.startswith(self.litellm_provider_name)
+            else model_id
+        )

    async def completion(
        self,
@ -421,3 +437,17 @@ class LiteLLMOpenAIMixin(
        logprobs: LogProbConfig | None = None,
    ):
        raise NotImplementedError("Batch chat completion is not supported for OpenAI Compat")
+
+    async def check_model_availability(self, model: str) -> bool:
+        """
+        Check if a specific model is available via LiteLLM for the current
+        provider (self.litellm_provider_name).
+
+        :param model: The model identifier to check.
+        :return: True if the model is available dynamically, False otherwise.
+        """
+        if self.litellm_provider_name not in litellm.models_by_provider:
+            logger.error(f"Provider {self.litellm_provider_name} is not registered in litellm.")
+            return False
+
+        return model in litellm.models_by_provider[self.litellm_provider_name]
--- a/llama_stack/providers/utils/inference/model_registry.py
+++ b/llama_stack/providers/utils/inference/model_registry.py
@ -50,7 +50,8 @@ def build_hf_repo_model_entry(
    additional_aliases: list[str] | None = None,
 ) -> ProviderModelEntry:
    aliases = [
-        get_huggingface_repo(model_descriptor),
+        # NOTE: avoid HF aliases because they _cannot_ be unique across providers
+        # get_huggingface_repo(model_descriptor),
    ]
    if additional_aliases:
        aliases.extend(additional_aliases)
@ -75,7 +76,9 @@ class ModelRegistryHelper(ModelsProtocolPrivate):
    __provider_id__: str

    def __init__(self, model_entries: list[ProviderModelEntry], allowed_models: list[str] | None = None):
+        self.model_entries = model_entries
        self.allowed_models = allowed_models
+
        self.alias_to_provider_id_map = {}
        self.provider_id_to_llama_model_map = {}
        for entry in model_entries:
@ -98,7 +101,7 @@ class ModelRegistryHelper(ModelsProtocolPrivate):
                    continue
                models.append(
                    Model(
-                        model_id=id,
+                        identifier=id,
                        provider_resource_id=entry.provider_model_id,
                        model_type=ModelType.llm,
                        metadata=entry.metadata,
@ -185,8 +188,8 @@ class ModelRegistryHelper(ModelsProtocolPrivate):
        return model

    async def unregister_model(self, model_id: str) -> None:
-        # TODO: should we block unregistering base supported provider model IDs?
-        if model_id not in self.alias_to_provider_id_map:
-            raise ValueError(f"Model id '{model_id}' is not registered.")
-
-        del self.alias_to_provider_id_map[model_id]
+        # model_id is the identifier, not the provider_resource_id
+        # unfortunately, this ID can be of the form provider_id/model_id which
+        # we never registered. TODO: fix this by significantly rewriting
+        # registration and registry helper
+        pass
--- a/llama_stack/templates/ci-tests/build.yaml
+++ b/llama_stack/templates/ci-tests/build.yaml
@ -3,96 +3,50 @@ distribution_spec:
  description: CI tests for Llama Stack
  providers:
    inference:
-    - provider_id: ${env.ENABLE_CEREBRAS:=__disabled__}
-      provider_type: remote::cerebras
-    - provider_id: ${env.ENABLE_OLLAMA:=__disabled__}
-      provider_type: remote::ollama
-    - provider_id: ${env.ENABLE_VLLM:=__disabled__}
-      provider_type: remote::vllm
-    - provider_id: ${env.ENABLE_TGI:=__disabled__}
-      provider_type: remote::tgi
-    - provider_id: ${env.ENABLE_HF_SERVERLESS:=__disabled__}
-      provider_type: remote::hf::serverless
-    - provider_id: ${env.ENABLE_HF_ENDPOINT:=__disabled__}
-      provider_type: remote::hf::endpoint
-    - provider_id: ${env.ENABLE_FIREWORKS:=__disabled__}
-      provider_type: remote::fireworks
-    - provider_id: ${env.ENABLE_TOGETHER:=__disabled__}
-      provider_type: remote::together
-    - provider_id: ${env.ENABLE_BEDROCK:=__disabled__}
-      provider_type: remote::bedrock
-    - provider_id: ${env.ENABLE_DATABRICKS:=__disabled__}
-      provider_type: remote::databricks
-    - provider_id: ${env.ENABLE_NVIDIA:=__disabled__}
-      provider_type: remote::nvidia
-    - provider_id: ${env.ENABLE_RUNPOD:=__disabled__}
-      provider_type: remote::runpod
-    - provider_id: ${env.ENABLE_OPENAI:=__disabled__}
-      provider_type: remote::openai
-    - provider_id: ${env.ENABLE_ANTHROPIC:=__disabled__}
-      provider_type: remote::anthropic
-    - provider_id: ${env.ENABLE_GEMINI:=__disabled__}
-      provider_type: remote::gemini
-    - provider_id: ${env.ENABLE_GROQ:=__disabled__}
-      provider_type: remote::groq
-    - provider_id: ${env.ENABLE_LLAMA_OPENAI_COMPAT:=__disabled__}
-      provider_type: remote::llama-openai-compat
-    - provider_id: ${env.ENABLE_SAMBANOVA:=__disabled__}
-      provider_type: remote::sambanova
-    - provider_id: ${env.ENABLE_PASSTHROUGH:=__disabled__}
-      provider_type: remote::passthrough
-    - provider_id: sentence-transformers
-      provider_type: inline::sentence-transformers
+    - 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::groq
+    - provider_type: remote::sambanova
+    - provider_type: inline::sentence-transformers
    vector_io:
-    - provider_id: ${env.ENABLE_FAISS:=faiss}
-      provider_type: inline::faiss
-    - provider_id: ${env.ENABLE_SQLITE_VEC:=__disabled__}
-      provider_type: inline::sqlite-vec
-    - provider_id: ${env.ENABLE_MILVUS:=__disabled__}
-      provider_type: inline::milvus
-    - provider_id: ${env.ENABLE_CHROMADB:=__disabled__}
-      provider_type: remote::chromadb
-    - provider_id: ${env.ENABLE_PGVECTOR:=__disabled__}
-      provider_type: remote::pgvector
+    - provider_type: inline::faiss
+    - provider_type: inline::sqlite-vec
+    - provider_type: inline::milvus
+    - provider_type: remote::chromadb
+    - provider_type: remote::pgvector
    files:
-    - provider_id: localfs
-      provider_type: inline::localfs
+    - provider_type: inline::localfs
    safety:
-    - provider_id: llama-guard
-      provider_type: inline::llama-guard
+    - provider_type: inline::llama-guard
    agents:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    telemetry:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    post_training:
-    - provider_id: huggingface
-      provider_type: inline::huggingface
+    - provider_type: inline::huggingface
    eval:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    datasetio:
-    - provider_id: huggingface
-      provider_type: remote::huggingface
-    - provider_id: localfs
-      provider_type: inline::localfs
+    - provider_type: remote::huggingface
+    - provider_type: inline::localfs
    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
+    - provider_type: inline::basic
+    - provider_type: inline::llm-as-judge
+    - provider_type: inline::braintrust
    tool_runtime:
-    - provider_id: brave-search
-      provider_type: remote::brave-search
-    - provider_id: tavily-search
-      provider_type: remote::tavily-search
-    - provider_id: rag-runtime
-      provider_type: inline::rag-runtime
-    - provider_id: model-context-protocol
-      provider_type: remote::model-context-protocol
+    - provider_type: remote::brave-search
+    - provider_type: remote::tavily-search
+    - provider_type: inline::rag-runtime
+    - provider_type: remote::model-context-protocol
 image_type: conda
 image_name: ci-tests
 additional_pip_packages:
--- a/llama_stack/templates/ci-tests/run.yaml
+++ b/llama_stack/templates/ci-tests/run.yaml
--- a/llama_stack/templates/dell/build.yaml
+++ b/llama_stack/templates/dell/build.yaml
@ -4,48 +4,31 @@ distribution_spec:
    container
  providers:
    inference:
-    - provider_id: tgi
-      provider_type: remote::tgi
-    - provider_id: sentence-transformers
-      provider_type: inline::sentence-transformers
+    - provider_type: remote::tgi
+    - provider_type: inline::sentence-transformers
    vector_io:
-    - provider_id: faiss
-      provider_type: inline::faiss
-    - provider_id: chromadb
-      provider_type: remote::chromadb
-    - provider_id: pgvector
-      provider_type: remote::pgvector
+    - provider_type: inline::faiss
+    - provider_type: remote::chromadb
+    - provider_type: remote::pgvector
    safety:
-    - provider_id: llama-guard
-      provider_type: inline::llama-guard
+    - provider_type: inline::llama-guard
    agents:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    telemetry:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    eval:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    datasetio:
-    - provider_id: huggingface
-      provider_type: remote::huggingface
-    - provider_id: localfs
-      provider_type: inline::localfs
+    - provider_type: remote::huggingface
+    - provider_type: inline::localfs
    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
+    - provider_type: inline::basic
+    - provider_type: inline::llm-as-judge
+    - provider_type: inline::braintrust
    tool_runtime:
-    - provider_id: brave-search
-      provider_type: remote::brave-search
-    - provider_id: tavily-search
-      provider_type: remote::tavily-search
-    - provider_id: rag-runtime
-      provider_type: inline::rag-runtime
+    - provider_type: remote::brave-search
+    - provider_type: remote::tavily-search
+    - provider_type: inline::rag-runtime
 image_type: conda
 image_name: dell
 additional_pip_packages:
--- a/llama_stack/templates/dell/dell.py
+++ b/llama_stack/templates/dell/dell.py
@ -6,6 +6,7 @@

 from llama_stack.apis.models import ModelType
 from llama_stack.distribution.datatypes import (
+    BuildProvider,
    ModelInput,
    Provider,
    ShieldInput,
@ -20,31 +21,31 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
    providers = {
        "inference": [
-            Provider(provider_id="tgi", provider_type="remote::tgi"),
-            Provider(provider_id="sentence-transformers", provider_type="inline::sentence-transformers"),
+            BuildProvider(provider_type="remote::tgi"),
+            BuildProvider(provider_type="inline::sentence-transformers"),
        ],
        "vector_io": [
-            Provider(provider_id="faiss", provider_type="inline::faiss"),
-            Provider(provider_id="chromadb", provider_type="remote::chromadb"),
-            Provider(provider_id="pgvector", provider_type="remote::pgvector"),
+            BuildProvider(provider_type="inline::faiss"),
+            BuildProvider(provider_type="remote::chromadb"),
+            BuildProvider(provider_type="remote::pgvector"),
        ],
-        "safety": [Provider(provider_id="llama-guard", provider_type="inline::llama-guard")],
-        "agents": [Provider(provider_id="meta-reference", provider_type="inline::meta-reference")],
-        "telemetry": [Provider(provider_id="meta-reference", provider_type="inline::meta-reference")],
-        "eval": [Provider(provider_id="meta-reference", provider_type="inline::meta-reference")],
+        "safety": [BuildProvider(provider_type="inline::llama-guard")],
+        "agents": [BuildProvider(provider_type="inline::meta-reference")],
+        "telemetry": [BuildProvider(provider_type="inline::meta-reference")],
+        "eval": [BuildProvider(provider_type="inline::meta-reference")],
        "datasetio": [
-            Provider(provider_id="huggingface", provider_type="remote::huggingface"),
-            Provider(provider_id="localfs", provider_type="inline::localfs"),
+            BuildProvider(provider_type="remote::huggingface"),
+            BuildProvider(provider_type="inline::localfs"),
        ],
        "scoring": [
-            Provider(provider_id="basic", provider_type="inline::basic"),
-            Provider(provider_id="llm-as-judge", provider_type="inline::llm-as-judge"),
-            Provider(provider_id="braintrust", provider_type="inline::braintrust"),
+            BuildProvider(provider_type="inline::basic"),
+            BuildProvider(provider_type="inline::llm-as-judge"),
+            BuildProvider(provider_type="inline::braintrust"),
        ],
        "tool_runtime": [
-            Provider(provider_id="brave-search", provider_type="remote::brave-search"),
-            Provider(provider_id="tavily-search", provider_type="remote::tavily-search"),
-            Provider(provider_id="rag-runtime", provider_type="inline::rag-runtime"),
+            BuildProvider(provider_type="remote::brave-search"),
+            BuildProvider(provider_type="remote::tavily-search"),
+            BuildProvider(provider_type="inline::rag-runtime"),
        ],
    }
    name = "dell"
--- a/llama_stack/templates/meta-reference-gpu/build.yaml
+++ b/llama_stack/templates/meta-reference-gpu/build.yaml
@ -3,48 +3,31 @@ distribution_spec:
  description: Use Meta Reference for running LLM inference
  providers:
    inference:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    vector_io:
-    - provider_id: faiss
-      provider_type: inline::faiss
-    - provider_id: chromadb
-      provider_type: remote::chromadb
-    - provider_id: pgvector
-      provider_type: remote::pgvector
+    - provider_type: inline::faiss
+    - provider_type: remote::chromadb
+    - provider_type: remote::pgvector
    safety:
-    - provider_id: llama-guard
-      provider_type: inline::llama-guard
+    - provider_type: inline::llama-guard
    agents:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    telemetry:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    eval:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    datasetio:
-    - provider_id: huggingface
-      provider_type: remote::huggingface
-    - provider_id: localfs
-      provider_type: inline::localfs
+    - provider_type: remote::huggingface
+    - provider_type: inline::localfs
    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
+    - provider_type: inline::basic
+    - provider_type: inline::llm-as-judge
+    - provider_type: inline::braintrust
    tool_runtime:
-    - provider_id: brave-search
-      provider_type: remote::brave-search
-    - provider_id: tavily-search
-      provider_type: remote::tavily-search
-    - provider_id: rag-runtime
-      provider_type: inline::rag-runtime
-    - provider_id: model-context-protocol
-      provider_type: remote::model-context-protocol
+    - provider_type: remote::brave-search
+    - provider_type: remote::tavily-search
+    - provider_type: inline::rag-runtime
+    - provider_type: remote::model-context-protocol
 image_type: conda
 image_name: meta-reference-gpu
 additional_pip_packages:
--- a/llama_stack/templates/meta-reference-gpu/meta_reference.py
+++ b/llama_stack/templates/meta-reference-gpu/meta_reference.py
@ -8,6 +8,7 @@ from pathlib import Path

 from llama_stack.apis.models import ModelType
 from llama_stack.distribution.datatypes import (
+    BuildProvider,
    ModelInput,
    Provider,
    ShieldInput,
@ -25,91 +26,30 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin

 def get_distribution_template() -> DistributionTemplate:
    providers = {
-        "inference": [
-            Provider(
-                provider_id="meta-reference",
-                provider_type="inline::meta-reference",
-            )
-        ],
+        "inference": [BuildProvider(provider_type="inline::meta-reference")],
        "vector_io": [
-            Provider(
-                provider_id="faiss",
-                provider_type="inline::faiss",
-            ),
-            Provider(
-                provider_id="chromadb",
-                provider_type="remote::chromadb",
-            ),
-            Provider(
-                provider_id="pgvector",
-                provider_type="remote::pgvector",
-            ),
-        ],
-        "safety": [
-            Provider(
-                provider_id="llama-guard",
-                provider_type="inline::llama-guard",
-            )
-        ],
-        "agents": [
-            Provider(
-                provider_id="meta-reference",
-                provider_type="inline::meta-reference",
-            )
-        ],
-        "telemetry": [
-            Provider(
-                provider_id="meta-reference",
-                provider_type="inline::meta-reference",
-            )
-        ],
-        "eval": [
-            Provider(
-                provider_id="meta-reference",
-                provider_type="inline::meta-reference",
-            )
+            BuildProvider(provider_type="inline::faiss"),
+            BuildProvider(provider_type="remote::chromadb"),
+            BuildProvider(provider_type="remote::pgvector"),
        ],
+        "safety": [BuildProvider(provider_type="inline::llama-guard")],
+        "agents": [BuildProvider(provider_type="inline::meta-reference")],
+        "telemetry": [BuildProvider(provider_type="inline::meta-reference")],
+        "eval": [BuildProvider(provider_type="inline::meta-reference")],
        "datasetio": [
-            Provider(
-                provider_id="huggingface",
-                provider_type="remote::huggingface",
-            ),
-            Provider(
-                provider_id="localfs",
-                provider_type="inline::localfs",
-            ),
+            BuildProvider(provider_type="remote::huggingface"),
+            BuildProvider(provider_type="inline::localfs"),
        ],
        "scoring": [
-            Provider(
-                provider_id="basic",
-                provider_type="inline::basic",
-            ),
-            Provider(
-                provider_id="llm-as-judge",
-                provider_type="inline::llm-as-judge",
-            ),
-            Provider(
-                provider_id="braintrust",
-                provider_type="inline::braintrust",
-            ),
+            BuildProvider(provider_type="inline::basic"),
+            BuildProvider(provider_type="inline::llm-as-judge"),
+            BuildProvider(provider_type="inline::braintrust"),
        ],
        "tool_runtime": [
-            Provider(
-                provider_id="brave-search",
-                provider_type="remote::brave-search",
-            ),
-            Provider(
-                provider_id="tavily-search",
-                provider_type="remote::tavily-search",
-            ),
-            Provider(
-                provider_id="rag-runtime",
-                provider_type="inline::rag-runtime",
-            ),
-            Provider(
-                provider_id="model-context-protocol",
-                provider_type="remote::model-context-protocol",
-            ),
+            BuildProvider(provider_type="remote::brave-search"),
+            BuildProvider(provider_type="remote::tavily-search"),
+            BuildProvider(provider_type="inline::rag-runtime"),
+            BuildProvider(provider_type="remote::model-context-protocol"),
        ],
    }
    name = "meta-reference-gpu"
--- a/llama_stack/templates/nvidia/build.yaml
+++ b/llama_stack/templates/nvidia/build.yaml
@ -3,37 +3,26 @@ distribution_spec:
  description: Use NVIDIA NIM for running LLM inference, evaluation and safety
  providers:
    inference:
-    - provider_id: nvidia
-      provider_type: remote::nvidia
+    - provider_type: remote::nvidia
    vector_io:
-    - provider_id: faiss
-      provider_type: inline::faiss
+    - provider_type: inline::faiss
    safety:
-    - provider_id: nvidia
-      provider_type: remote::nvidia
+    - provider_type: remote::nvidia
    agents:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    telemetry:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    eval:
-    - provider_id: nvidia
-      provider_type: remote::nvidia
+    - provider_type: remote::nvidia
    post_training:
-    - provider_id: nvidia
-      provider_type: remote::nvidia
+    - provider_type: remote::nvidia
    datasetio:
-    - provider_id: localfs
-      provider_type: inline::localfs
-    - provider_id: nvidia
-      provider_type: remote::nvidia
+    - provider_type: inline::localfs
+    - provider_type: remote::nvidia
    scoring:
-    - provider_id: basic
-      provider_type: inline::basic
+    - provider_type: inline::basic
    tool_runtime:
-    - provider_id: rag-runtime
-      provider_type: inline::rag-runtime
+    - provider_type: inline::rag-runtime
 image_type: conda
 image_name: nvidia
 additional_pip_packages:
--- a/llama_stack/templates/nvidia/nvidia.py
+++ b/llama_stack/templates/nvidia/nvidia.py
@ -6,7 +6,7 @@

 from pathlib import Path

-from llama_stack.distribution.datatypes import ModelInput, Provider, ShieldInput, ToolGroupInput
+from llama_stack.distribution.datatypes import BuildProvider, ModelInput, Provider, ShieldInput, ToolGroupInput
 from llama_stack.providers.remote.datasetio.nvidia import NvidiaDatasetIOConfig
 from llama_stack.providers.remote.eval.nvidia import NVIDIAEvalConfig
 from llama_stack.providers.remote.inference.nvidia import NVIDIAConfig
@ -17,65 +17,19 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin

 def get_distribution_template() -> DistributionTemplate:
    providers = {
-        "inference": [
-            Provider(
-                provider_id="nvidia",
-                provider_type="remote::nvidia",
-            )
-        ],
-        "vector_io": [
-            Provider(
-                provider_id="faiss",
-                provider_type="inline::faiss",
-            )
-        ],
-        "safety": [
-            Provider(
-                provider_id="nvidia",
-                provider_type="remote::nvidia",
-            )
-        ],
-        "agents": [
-            Provider(
-                provider_id="meta-reference",
-                provider_type="inline::meta-reference",
-            )
-        ],
-        "telemetry": [
-            Provider(
-                provider_id="meta-reference",
-                provider_type="inline::meta-reference",
-            )
-        ],
-        "eval": [
-            Provider(
-                provider_id="nvidia",
-                provider_type="remote::nvidia",
-            )
-        ],
-        "post_training": [Provider(provider_id="nvidia", provider_type="remote::nvidia", config={})],
+        "inference": [BuildProvider(provider_type="remote::nvidia")],
+        "vector_io": [BuildProvider(provider_type="inline::faiss")],
+        "safety": [BuildProvider(provider_type="remote::nvidia")],
+        "agents": [BuildProvider(provider_type="inline::meta-reference")],
+        "telemetry": [BuildProvider(provider_type="inline::meta-reference")],
+        "eval": [BuildProvider(provider_type="remote::nvidia")],
+        "post_training": [BuildProvider(provider_type="remote::nvidia")],
        "datasetio": [
-            Provider(
-                provider_id="localfs",
-                provider_type="inline::localfs",
-            ),
-            Provider(
-                provider_id="nvidia",
-                provider_type="remote::nvidia",
-            ),
-        ],
-        "scoring": [
-            Provider(
-                provider_id="basic",
-                provider_type="inline::basic",
-            )
-        ],
-        "tool_runtime": [
-            Provider(
-                provider_id="rag-runtime",
-                provider_type="inline::rag-runtime",
-            )
+            BuildProvider(provider_type="inline::localfs"),
+            BuildProvider(provider_type="remote::nvidia"),
        ],
+        "scoring": [BuildProvider(provider_type="inline::basic")],
+        "tool_runtime": [BuildProvider(provider_type="inline::rag-runtime")],
    }

    inference_provider = Provider(
--- a/llama_stack/templates/nvidia/run.yaml
+++ b/llama_stack/templates/nvidia/run.yaml
@ -89,101 +89,51 @@ models:
  provider_id: nvidia
  provider_model_id: meta/llama3-8b-instruct
  model_type: llm
- metadata: {}
-  model_id: meta-llama/Llama-3-8B-Instruct
-  provider_id: nvidia
-  provider_model_id: meta/llama3-8b-instruct
-  model_type: llm
 - metadata: {}
  model_id: meta/llama3-70b-instruct
  provider_id: nvidia
  provider_model_id: meta/llama3-70b-instruct
  model_type: llm
- metadata: {}
-  model_id: meta-llama/Llama-3-70B-Instruct
-  provider_id: nvidia
-  provider_model_id: meta/llama3-70b-instruct
-  model_type: llm
 - metadata: {}
  model_id: meta/llama-3.1-8b-instruct
  provider_id: nvidia
  provider_model_id: meta/llama-3.1-8b-instruct
  model_type: llm
- metadata: {}
-  model_id: meta-llama/Llama-3.1-8B-Instruct
-  provider_id: nvidia
-  provider_model_id: meta/llama-3.1-8b-instruct
-  model_type: llm
 - metadata: {}
  model_id: meta/llama-3.1-70b-instruct
  provider_id: nvidia
  provider_model_id: meta/llama-3.1-70b-instruct
  model_type: llm
- metadata: {}
-  model_id: meta-llama/Llama-3.1-70B-Instruct
-  provider_id: nvidia
-  provider_model_id: meta/llama-3.1-70b-instruct
-  model_type: llm
 - metadata: {}
  model_id: meta/llama-3.1-405b-instruct
  provider_id: nvidia
  provider_model_id: meta/llama-3.1-405b-instruct
  model_type: llm
- metadata: {}
-  model_id: meta-llama/Llama-3.1-405B-Instruct-FP8
-  provider_id: nvidia
-  provider_model_id: meta/llama-3.1-405b-instruct
-  model_type: llm
 - metadata: {}
  model_id: meta/llama-3.2-1b-instruct
  provider_id: nvidia
  provider_model_id: meta/llama-3.2-1b-instruct
  model_type: llm
- metadata: {}
-  model_id: meta-llama/Llama-3.2-1B-Instruct
-  provider_id: nvidia
-  provider_model_id: meta/llama-3.2-1b-instruct
-  model_type: llm
 - metadata: {}
  model_id: meta/llama-3.2-3b-instruct
  provider_id: nvidia
  provider_model_id: meta/llama-3.2-3b-instruct
  model_type: llm
- metadata: {}
-  model_id: meta-llama/Llama-3.2-3B-Instruct
-  provider_id: nvidia
-  provider_model_id: meta/llama-3.2-3b-instruct
-  model_type: llm
 - metadata: {}
  model_id: meta/llama-3.2-11b-vision-instruct
  provider_id: nvidia
  provider_model_id: meta/llama-3.2-11b-vision-instruct
  model_type: llm
- metadata: {}
-  model_id: meta-llama/Llama-3.2-11B-Vision-Instruct
-  provider_id: nvidia
-  provider_model_id: meta/llama-3.2-11b-vision-instruct
-  model_type: llm
 - metadata: {}
  model_id: meta/llama-3.2-90b-vision-instruct
  provider_id: nvidia
  provider_model_id: meta/llama-3.2-90b-vision-instruct
  model_type: llm
- metadata: {}
-  model_id: meta-llama/Llama-3.2-90B-Vision-Instruct
-  provider_id: nvidia
-  provider_model_id: meta/llama-3.2-90b-vision-instruct
-  model_type: llm
 - metadata: {}
  model_id: meta/llama-3.3-70b-instruct
  provider_id: nvidia
  provider_model_id: meta/llama-3.3-70b-instruct
  model_type: llm
- metadata: {}
-  model_id: meta-llama/Llama-3.3-70B-Instruct
-  provider_id: nvidia
-  provider_model_id: meta/llama-3.3-70b-instruct
-  model_type: llm
 - metadata:
    embedding_dimension: 2048
    context_length: 8192
--- a/llama_stack/templates/open-benchmark/build.yaml
+++ b/llama_stack/templates/open-benchmark/build.yaml
@ -3,56 +3,35 @@ distribution_spec:
  description: Distribution for running open benchmarks
  providers:
    inference:
-    - provider_id: openai
-      provider_type: remote::openai
-    - provider_id: anthropic
-      provider_type: remote::anthropic
-    - provider_id: gemini
-      provider_type: remote::gemini
-    - provider_id: groq
-      provider_type: remote::groq
-    - provider_id: together
-      provider_type: remote::together
+    - provider_type: remote::openai
+    - provider_type: remote::anthropic
+    - provider_type: remote::gemini
+    - provider_type: remote::groq
+    - provider_type: remote::together
    vector_io:
-    - provider_id: sqlite-vec
-      provider_type: inline::sqlite-vec
-    - provider_id: chromadb
-      provider_type: remote::chromadb
-    - provider_id: pgvector
-      provider_type: remote::pgvector
+    - provider_type: inline::sqlite-vec
+    - provider_type: remote::chromadb
+    - provider_type: remote::pgvector
    safety:
-    - provider_id: llama-guard
-      provider_type: inline::llama-guard
+    - provider_type: inline::llama-guard
    agents:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    telemetry:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    eval:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    datasetio:
-    - provider_id: huggingface
-      provider_type: remote::huggingface
-    - provider_id: localfs
-      provider_type: inline::localfs
+    - provider_type: remote::huggingface
+    - provider_type: inline::localfs
    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
+    - provider_type: inline::basic
+    - provider_type: inline::llm-as-judge
+    - provider_type: inline::braintrust
    tool_runtime:
-    - provider_id: brave-search
-      provider_type: remote::brave-search
-    - provider_id: tavily-search
-      provider_type: remote::tavily-search
-    - provider_id: rag-runtime
-      provider_type: inline::rag-runtime
-    - provider_id: model-context-protocol
-      provider_type: remote::model-context-protocol
+    - provider_type: remote::brave-search
+    - provider_type: remote::tavily-search
+    - provider_type: inline::rag-runtime
+    - provider_type: remote::model-context-protocol
 image_type: conda
 image_name: open-benchmark
 additional_pip_packages:
--- a/llama_stack/templates/open-benchmark/open_benchmark.py
+++ b/llama_stack/templates/open-benchmark/open_benchmark.py
@ -9,6 +9,7 @@ from llama_stack.apis.datasets import DatasetPurpose, URIDataSource
 from llama_stack.apis.models import ModelType
 from llama_stack.distribution.datatypes import (
    BenchmarkInput,
+    BuildProvider,
    DatasetInput,
    ModelInput,
    Provider,
@ -96,33 +97,30 @@ def get_inference_providers() -> tuple[list[Provider], dict[str, list[ProviderMo
 def get_distribution_template() -> DistributionTemplate:
    inference_providers, available_models = get_inference_providers()
    providers = {
-        "inference": inference_providers,
+        "inference": [BuildProvider(provider_type=p.provider_type, module=p.module) for p in inference_providers],
        "vector_io": [
-            Provider(provider_id="sqlite-vec", provider_type="inline::sqlite-vec"),
-            Provider(provider_id="chromadb", provider_type="remote::chromadb"),
-            Provider(provider_id="pgvector", provider_type="remote::pgvector"),
+            BuildProvider(provider_type="inline::sqlite-vec"),
+            BuildProvider(provider_type="remote::chromadb"),
+            BuildProvider(provider_type="remote::pgvector"),
        ],
-        "safety": [Provider(provider_id="llama-guard", provider_type="inline::llama-guard")],
-        "agents": [Provider(provider_id="meta-reference", provider_type="inline::meta-reference")],
-        "telemetry": [Provider(provider_id="meta-reference", provider_type="inline::meta-reference")],
-        "eval": [Provider(provider_id="meta-reference", provider_type="inline::meta-reference")],
+        "safety": [BuildProvider(provider_type="inline::llama-guard")],
+        "agents": [BuildProvider(provider_type="inline::meta-reference")],
+        "telemetry": [BuildProvider(provider_type="inline::meta-reference")],
+        "eval": [BuildProvider(provider_type="inline::meta-reference")],
        "datasetio": [
-            Provider(provider_id="huggingface", provider_type="remote::huggingface"),
-            Provider(provider_id="localfs", provider_type="inline::localfs"),
+            BuildProvider(provider_type="remote::huggingface"),
+            BuildProvider(provider_type="inline::localfs"),
        ],
        "scoring": [
-            Provider(provider_id="basic", provider_type="inline::basic"),
-            Provider(provider_id="llm-as-judge", provider_type="inline::llm-as-judge"),
-            Provider(provider_id="braintrust", provider_type="inline::braintrust"),
+            BuildProvider(provider_type="inline::basic"),
+            BuildProvider(provider_type="inline::llm-as-judge"),
+            BuildProvider(provider_type="inline::braintrust"),
        ],
        "tool_runtime": [
-            Provider(provider_id="brave-search", provider_type="remote::brave-search"),
-            Provider(provider_id="tavily-search", provider_type="remote::tavily-search"),
-            Provider(provider_id="rag-runtime", provider_type="inline::rag-runtime"),
-            Provider(
-                provider_id="model-context-protocol",
-                provider_type="remote::model-context-protocol",
-            ),
+            BuildProvider(provider_type="remote::brave-search"),
+            BuildProvider(provider_type="remote::tavily-search"),
+            BuildProvider(provider_type="inline::rag-runtime"),
+            BuildProvider(provider_type="remote::model-context-protocol"),
        ],
    }
    name = "open-benchmark"
--- a/llama_stack/templates/open-benchmark/run.yaml
+++ b/llama_stack/templates/open-benchmark/run.yaml
@ -16,6 +16,7 @@ providers:
    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:
@ -33,7 +34,7 @@ providers:
    provider_type: remote::together
    config:
      url: https://api.together.xyz/v1
-      api_key: ${env.TOGETHER_API_KEY}
+      api_key: ${env.TOGETHER_API_KEY:=}
  vector_io:
  - provider_id: sqlite-vec
    provider_type: inline::sqlite-vec
--- a/llama_stack/templates/postgres-demo/build.yaml
+++ b/llama_stack/templates/postgres-demo/build.yaml
@ -3,31 +3,21 @@ distribution_spec:
  description: Quick start template for running Llama Stack with several popular providers
  providers:
    inference:
-    - provider_id: vllm-inference
-      provider_type: remote::vllm
-    - provider_id: sentence-transformers
-      provider_type: inline::sentence-transformers
+    - provider_type: remote::vllm
+    - provider_type: inline::sentence-transformers
    vector_io:
-    - provider_id: chromadb
-      provider_type: remote::chromadb
+    - provider_type: remote::chromadb
    safety:
-    - provider_id: llama-guard
-      provider_type: inline::llama-guard
+    - provider_type: inline::llama-guard
    agents:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    telemetry:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    tool_runtime:
-    - provider_id: brave-search
-      provider_type: remote::brave-search
-    - provider_id: tavily-search
-      provider_type: remote::tavily-search
-    - provider_id: rag-runtime
-      provider_type: inline::rag-runtime
-    - provider_id: model-context-protocol
-      provider_type: remote::model-context-protocol
+    - provider_type: remote::brave-search
+    - provider_type: remote::tavily-search
+    - provider_type: inline::rag-runtime
+    - provider_type: remote::model-context-protocol
 image_type: conda
 image_name: postgres-demo
 additional_pip_packages:
--- a/llama_stack/templates/postgres-demo/postgres_demo.py
+++ b/llama_stack/templates/postgres-demo/postgres_demo.py
@ -7,6 +7,7 @@

 from llama_stack.apis.models import ModelType
 from llama_stack.distribution.datatypes import (
+    BuildProvider,
    ModelInput,
    Provider,
    ShieldInput,
@ -34,24 +35,19 @@ def get_distribution_template() -> DistributionTemplate:
        ),
    ]
    providers = {
-        "inference": inference_providers
-        + [
-            Provider(provider_id="sentence-transformers", provider_type="inline::sentence-transformers"),
+        "inference": [
+            BuildProvider(provider_type="remote::vllm"),
+            BuildProvider(provider_type="inline::sentence-transformers"),
        ],
-        "vector_io": [
-            Provider(provider_id="chromadb", provider_type="remote::chromadb"),
-        ],
-        "safety": [Provider(provider_id="llama-guard", provider_type="inline::llama-guard")],
-        "agents": [Provider(provider_id="meta-reference", provider_type="inline::meta-reference")],
-        "telemetry": [Provider(provider_id="meta-reference", provider_type="inline::meta-reference")],
+        "vector_io": [BuildProvider(provider_type="remote::chromadb")],
+        "safety": [BuildProvider(provider_type="inline::llama-guard")],
+        "agents": [BuildProvider(provider_type="inline::meta-reference")],
+        "telemetry": [BuildProvider(provider_type="inline::meta-reference")],
        "tool_runtime": [
-            Provider(provider_id="brave-search", provider_type="remote::brave-search"),
-            Provider(provider_id="tavily-search", provider_type="remote::tavily-search"),
-            Provider(provider_id="rag-runtime", provider_type="inline::rag-runtime"),
-            Provider(
-                provider_id="model-context-protocol",
-                provider_type="remote::model-context-protocol",
-            ),
+            BuildProvider(provider_type="remote::brave-search"),
+            BuildProvider(provider_type="remote::tavily-search"),
+            BuildProvider(provider_type="inline::rag-runtime"),
+            BuildProvider(provider_type="remote::model-context-protocol"),
        ],
    }
    name = "postgres-demo"
--- a/llama_stack/templates/starter/build.yaml
+++ b/llama_stack/templates/starter/build.yaml
@ -3,96 +3,50 @@ distribution_spec:
  description: Quick start template for running Llama Stack with several popular providers
  providers:
    inference:
-    - provider_id: ${env.ENABLE_CEREBRAS:=__disabled__}
-      provider_type: remote::cerebras
-    - provider_id: ${env.ENABLE_OLLAMA:=__disabled__}
-      provider_type: remote::ollama
-    - provider_id: ${env.ENABLE_VLLM:=__disabled__}
-      provider_type: remote::vllm
-    - provider_id: ${env.ENABLE_TGI:=__disabled__}
-      provider_type: remote::tgi
-    - provider_id: ${env.ENABLE_HF_SERVERLESS:=__disabled__}
-      provider_type: remote::hf::serverless
-    - provider_id: ${env.ENABLE_HF_ENDPOINT:=__disabled__}
-      provider_type: remote::hf::endpoint
-    - provider_id: ${env.ENABLE_FIREWORKS:=__disabled__}
-      provider_type: remote::fireworks
-    - provider_id: ${env.ENABLE_TOGETHER:=__disabled__}
-      provider_type: remote::together
-    - provider_id: ${env.ENABLE_BEDROCK:=__disabled__}
-      provider_type: remote::bedrock
-    - provider_id: ${env.ENABLE_DATABRICKS:=__disabled__}
-      provider_type: remote::databricks
-    - provider_id: ${env.ENABLE_NVIDIA:=__disabled__}
-      provider_type: remote::nvidia
-    - provider_id: ${env.ENABLE_RUNPOD:=__disabled__}
-      provider_type: remote::runpod
-    - provider_id: ${env.ENABLE_OPENAI:=__disabled__}
-      provider_type: remote::openai
-    - provider_id: ${env.ENABLE_ANTHROPIC:=__disabled__}
-      provider_type: remote::anthropic
-    - provider_id: ${env.ENABLE_GEMINI:=__disabled__}
-      provider_type: remote::gemini
-    - provider_id: ${env.ENABLE_GROQ:=__disabled__}
-      provider_type: remote::groq
-    - provider_id: ${env.ENABLE_LLAMA_OPENAI_COMPAT:=__disabled__}
-      provider_type: remote::llama-openai-compat
-    - provider_id: ${env.ENABLE_SAMBANOVA:=__disabled__}
-      provider_type: remote::sambanova
-    - provider_id: ${env.ENABLE_PASSTHROUGH:=__disabled__}
-      provider_type: remote::passthrough
-    - provider_id: sentence-transformers
-      provider_type: inline::sentence-transformers
+    - 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::groq
+    - provider_type: remote::sambanova
+    - provider_type: inline::sentence-transformers
    vector_io:
-    - provider_id: ${env.ENABLE_FAISS:=faiss}
-      provider_type: inline::faiss
-    - provider_id: ${env.ENABLE_SQLITE_VEC:=__disabled__}
-      provider_type: inline::sqlite-vec
-    - provider_id: ${env.ENABLE_MILVUS:=__disabled__}
-      provider_type: inline::milvus
-    - provider_id: ${env.ENABLE_CHROMADB:=__disabled__}
-      provider_type: remote::chromadb
-    - provider_id: ${env.ENABLE_PGVECTOR:=__disabled__}
-      provider_type: remote::pgvector
+    - provider_type: inline::faiss
+    - provider_type: inline::sqlite-vec
+    - provider_type: inline::milvus
+    - provider_type: remote::chromadb
+    - provider_type: remote::pgvector
    files:
-    - provider_id: localfs
-      provider_type: inline::localfs
+    - provider_type: inline::localfs
    safety:
-    - provider_id: llama-guard
-      provider_type: inline::llama-guard
+    - provider_type: inline::llama-guard
    agents:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    telemetry:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    post_training:
-    - provider_id: huggingface
-      provider_type: inline::huggingface
+    - provider_type: inline::huggingface
    eval:
-    - provider_id: meta-reference
-      provider_type: inline::meta-reference
+    - provider_type: inline::meta-reference
    datasetio:
-    - provider_id: huggingface
-      provider_type: remote::huggingface
-    - provider_id: localfs
-      provider_type: inline::localfs
+    - provider_type: remote::huggingface
+    - provider_type: inline::localfs
    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
+    - provider_type: inline::basic
+    - provider_type: inline::llm-as-judge
+    - provider_type: inline::braintrust
    tool_runtime:
-    - provider_id: brave-search
-      provider_type: remote::brave-search
-    - provider_id: tavily-search
-      provider_type: remote::tavily-search
-    - provider_id: rag-runtime
-      provider_type: inline::rag-runtime
-    - provider_id: model-context-protocol
-      provider_type: remote::model-context-protocol
+    - provider_type: remote::brave-search
+    - provider_type: remote::tavily-search
+    - provider_type: inline::rag-runtime
+    - provider_type: remote::model-context-protocol
 image_type: conda
 image_name: starter
 additional_pip_packages:
--- a/llama_stack/templates/starter/run.yaml
+++ b/llama_stack/templates/starter/run.yaml
--- a/llama_stack/templates/starter/starter.py
+++ b/llama_stack/templates/starter/starter.py
@ -7,19 +7,19 @@

 from typing import Any

-from llama_stack.apis.models import ModelType
 from llama_stack.distribution.datatypes import (
-    ModelInput,
+    BuildProvider,
    Provider,
    ProviderSpec,
+    ShieldInput,
    ToolGroupInput,
 )
 from llama_stack.distribution.utils.dynamic import instantiate_class_type
+from llama_stack.providers.datatypes import RemoteProviderSpec
 from llama_stack.providers.inline.files.localfs.config import LocalfsFilesImplConfig
 from llama_stack.providers.inline.inference.sentence_transformers import (
    SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.post_training.huggingface import HuggingFacePostTrainingConfig
 from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
 from llama_stack.providers.inline.vector_io.milvus.config import (
    MilvusVectorIOConfig,
@ -28,117 +28,17 @@ from llama_stack.providers.inline.vector_io.sqlite_vec.config import (
    SQLiteVectorIOConfig,
 )
 from llama_stack.providers.registry.inference import available_providers
-from llama_stack.providers.remote.inference.anthropic.models import (
-    MODEL_ENTRIES as ANTHROPIC_MODEL_ENTRIES,
-)
-from llama_stack.providers.remote.inference.bedrock.models import (
-    MODEL_ENTRIES as BEDROCK_MODEL_ENTRIES,
-)
-from llama_stack.providers.remote.inference.cerebras.models import (
-    MODEL_ENTRIES as CEREBRAS_MODEL_ENTRIES,
-)
-from llama_stack.providers.remote.inference.databricks.databricks import (
-    MODEL_ENTRIES as DATABRICKS_MODEL_ENTRIES,
-)
-from llama_stack.providers.remote.inference.fireworks.models import (
-    MODEL_ENTRIES as FIREWORKS_MODEL_ENTRIES,
-)
-from llama_stack.providers.remote.inference.gemini.models import (
-    MODEL_ENTRIES as GEMINI_MODEL_ENTRIES,
-)
-from llama_stack.providers.remote.inference.groq.models import (
-    MODEL_ENTRIES as GROQ_MODEL_ENTRIES,
-)
-from llama_stack.providers.remote.inference.nvidia.models import (
-    MODEL_ENTRIES as NVIDIA_MODEL_ENTRIES,
-)
-from llama_stack.providers.remote.inference.openai.models import (
-    MODEL_ENTRIES as OPENAI_MODEL_ENTRIES,
-)
-from llama_stack.providers.remote.inference.runpod.runpod import (
-    MODEL_ENTRIES as RUNPOD_MODEL_ENTRIES,
-)
-from llama_stack.providers.remote.inference.sambanova.models import (
-    MODEL_ENTRIES as SAMBANOVA_MODEL_ENTRIES,
-)
-from llama_stack.providers.remote.inference.together.models import (
-    MODEL_ENTRIES as TOGETHER_MODEL_ENTRIES,
-)
 from llama_stack.providers.remote.vector_io.chroma.config import ChromaVectorIOConfig
 from llama_stack.providers.remote.vector_io.pgvector.config import (
    PGVectorVectorIOConfig,
 )
-from llama_stack.providers.utils.inference.model_registry import ProviderModelEntry
 from llama_stack.providers.utils.sqlstore.sqlstore import PostgresSqlStoreConfig
 from llama_stack.templates.template import (
    DistributionTemplate,
    RunConfigSettings,
-    get_model_registry,
-    get_shield_registry,
 )


-def _get_model_entries_for_provider(provider_type: str) -> list[ProviderModelEntry]:
-    """Get model entries for a specific provider type."""
-    model_entries_map = {
-        "openai": OPENAI_MODEL_ENTRIES,
-        "fireworks": FIREWORKS_MODEL_ENTRIES,
-        "together": TOGETHER_MODEL_ENTRIES,
-        "anthropic": ANTHROPIC_MODEL_ENTRIES,
-        "gemini": GEMINI_MODEL_ENTRIES,
-        "groq": GROQ_MODEL_ENTRIES,
-        "sambanova": SAMBANOVA_MODEL_ENTRIES,
-        "cerebras": CEREBRAS_MODEL_ENTRIES,
-        "bedrock": BEDROCK_MODEL_ENTRIES,
-        "databricks": DATABRICKS_MODEL_ENTRIES,
-        "nvidia": NVIDIA_MODEL_ENTRIES,
-        "runpod": RUNPOD_MODEL_ENTRIES,
-    }
-
-    # Special handling for providers with dynamic model entries
-    if provider_type == "ollama":
-        return [
-            ProviderModelEntry(
-                provider_model_id="${env.OLLAMA_INFERENCE_MODEL:=__disabled__}",
-                model_type=ModelType.llm,
-            ),
-            ProviderModelEntry(
-                provider_model_id="${env.SAFETY_MODEL:=__disabled__}",
-                model_type=ModelType.llm,
-            ),
-            ProviderModelEntry(
-                provider_model_id="${env.OLLAMA_EMBEDDING_MODEL:=__disabled__}",
-                model_type=ModelType.embedding,
-                metadata={
-                    "embedding_dimension": "${env.OLLAMA_EMBEDDING_DIMENSION:=384}",
-                },
-            ),
-        ]
-    elif provider_type == "vllm":
-        return [
-            ProviderModelEntry(
-                provider_model_id="${env.VLLM_INFERENCE_MODEL:=__disabled__}",
-                model_type=ModelType.llm,
-            ),
-        ]
-
-    return model_entries_map.get(provider_type, [])
-
-
-def _get_model_safety_entries_for_provider(provider_type: str) -> list[ProviderModelEntry]:
-    """Get model entries for a specific provider type."""
-    safety_model_entries_map = {
-        "ollama": [
-            ProviderModelEntry(
-                provider_model_id="${env.SAFETY_MODEL:=__disabled__}",
-                model_type=ModelType.llm,
-            ),
-        ],
-    }
-
-    return safety_model_entries_map.get(provider_type, [])
-
-
 def _get_config_for_provider(provider_spec: ProviderSpec) -> dict[str, Any]:
    """Get configuration for a provider using its adapter's config class."""
    config_class = instantiate_class_type(provider_spec.config_class)
@ -149,40 +49,48 @@ def _get_config_for_provider(provider_spec: ProviderSpec) -> dict[str, Any]:
    return {}


-def get_remote_inference_providers() -> tuple[list[Provider], dict[str, list[ProviderModelEntry]]]:
-    all_providers = available_providers()
+ENABLED_INFERENCE_PROVIDERS = [
+    "ollama",
+    "vllm",
+    "tgi",
+    "fireworks",
+    "together",
+    "gemini",
+    "groq",
+    "sambanova",
+    "anthropic",
+    "openai",
+    "cerebras",
+    "nvidia",
+    "bedrock",
+]

-    # Filter out inline providers and watsonx - the starter distro only exposes remote providers
+INFERENCE_PROVIDER_IDS = {
+    "vllm": "${env.VLLM_URL:+vllm}",
+    "tgi": "${env.TGI_URL:+tgi}",
+    "cerebras": "${env.CEREBRAS_API_KEY:+cerebras}",
+    "nvidia": "${env.NVIDIA_API_KEY:+nvidia}",
+}
+
+
+def get_remote_inference_providers() -> list[Provider]:
+    # Filter out inline providers and some others - the starter distro only exposes remote providers
    remote_providers = [
        provider
-        for provider in all_providers
-        # TODO: re-add once the Python 3.13 issue is fixed
-        # discussion: https://github.com/meta-llama/llama-stack/pull/2327#discussion_r2156883828
-        if hasattr(provider, "adapter") and provider.adapter.adapter_type != "watsonx"
+        for provider in available_providers()
+        if isinstance(provider, RemoteProviderSpec) and provider.adapter.adapter_type in ENABLED_INFERENCE_PROVIDERS
    ]

-    providers = []
-    available_models = {}
-
+    inference_providers = []
    for provider_spec in remote_providers:
        provider_type = provider_spec.adapter.adapter_type

-        # Build the environment variable name for enabling this provider
-        env_var = f"ENABLE_{provider_type.upper().replace('-', '_').replace('::', '_')}"
-        model_entries = _get_model_entries_for_provider(provider_type)
+        if provider_type in INFERENCE_PROVIDER_IDS:
+            provider_id = INFERENCE_PROVIDER_IDS[provider_type]
+        else:
+            provider_id = provider_type.replace("-", "_").replace("::", "_")
        config = _get_config_for_provider(provider_spec)
-        providers.append(
-            (
-                f"${{env.{env_var}:=__disabled__}}",
-                provider_type,
-                model_entries,
-                config,
-            )
-        )
-        available_models[f"${{env.{env_var}:=__disabled__}}"] = model_entries

-    inference_providers = []
-    for provider_id, provider_type, model_entries, config in providers:
        inference_providers.append(
            Provider(
                provider_id=provider_id,
@ -190,154 +98,43 @@ def get_remote_inference_providers() -> tuple[list[Provider], dict[str, list[Pro
                config=config,
            )
        )
-        available_models[provider_id] = model_entries
-    return inference_providers, available_models
-
-
-# build a list of shields for all possible providers
-def get_safety_models_for_providers(providers: list[Provider]) -> dict[str, list[ProviderModelEntry]]:
-    available_models = {}
-    for provider in providers:
-        provider_type = provider.provider_type.split("::")[1]
-        safety_model_entries = _get_model_safety_entries_for_provider(provider_type)
-        if len(safety_model_entries) == 0:
-            continue
-
-        env_var = f"ENABLE_{provider_type.upper().replace('-', '_').replace('::', '_')}"
-        provider_id = f"${{env.{env_var}:=__disabled__}}"
-
-        available_models[provider_id] = safety_model_entries
-
-    return available_models
+    return inference_providers


 def get_distribution_template() -> DistributionTemplate:
-    remote_inference_providers, available_models = get_remote_inference_providers()
-
+    remote_inference_providers = get_remote_inference_providers()
    name = "starter"

-    vector_io_providers = [
-        Provider(
-            provider_id="${env.ENABLE_FAISS:=faiss}",
-            provider_type="inline::faiss",
-            config=FaissVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
-        ),
-        Provider(
-            provider_id="${env.ENABLE_SQLITE_VEC:=__disabled__}",
-            provider_type="inline::sqlite-vec",
-            config=SQLiteVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
-        ),
-        Provider(
-            provider_id="${env.ENABLE_MILVUS:=__disabled__}",
-            provider_type="inline::milvus",
-            config=MilvusVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
-        ),
-        Provider(
-            provider_id="${env.ENABLE_CHROMADB:=__disabled__}",
-            provider_type="remote::chromadb",
-            config=ChromaVectorIOConfig.sample_run_config(
-                f"~/.llama/distributions/{name}/",
-                url="${env.CHROMADB_URL:=}",
-            ),
-        ),
-        Provider(
-            provider_id="${env.ENABLE_PGVECTOR:=__disabled__}",
-            provider_type="remote::pgvector",
-            config=PGVectorVectorIOConfig.sample_run_config(
-                f"~/.llama/distributions/{name}",
-                db="${env.PGVECTOR_DB:=}",
-                user="${env.PGVECTOR_USER:=}",
-                password="${env.PGVECTOR_PASSWORD:=}",
-            ),
-        ),
-    ]
-
    providers = {
-        "inference": remote_inference_providers
-        + [
-            Provider(
-                provider_id="sentence-transformers",
-                provider_type="inline::sentence-transformers",
-            )
-        ],
-        "vector_io": vector_io_providers,
-        "files": [
-            Provider(
-                provider_id="localfs",
-                provider_type="inline::localfs",
-            )
-        ],
-        "safety": [
-            Provider(
-                provider_id="llama-guard",
-                provider_type="inline::llama-guard",
-            )
-        ],
-        "agents": [
-            Provider(
-                provider_id="meta-reference",
-                provider_type="inline::meta-reference",
-            )
-        ],
-        "telemetry": [
-            Provider(
-                provider_id="meta-reference",
-                provider_type="inline::meta-reference",
-            )
-        ],
-        "post_training": [
-            Provider(
-                provider_id="huggingface",
-                provider_type="inline::huggingface",
-            )
-        ],
-        "eval": [
-            Provider(
-                provider_id="meta-reference",
-                provider_type="inline::meta-reference",
-            )
+        "inference": [BuildProvider(provider_type=p.provider_type, module=p.module) for p in remote_inference_providers]
+        + [BuildProvider(provider_type="inline::sentence-transformers")],
+        "vector_io": [
+            BuildProvider(provider_type="inline::faiss"),
+            BuildProvider(provider_type="inline::sqlite-vec"),
+            BuildProvider(provider_type="inline::milvus"),
+            BuildProvider(provider_type="remote::chromadb"),
+            BuildProvider(provider_type="remote::pgvector"),
        ],
+        "files": [BuildProvider(provider_type="inline::localfs")],
+        "safety": [BuildProvider(provider_type="inline::llama-guard")],
+        "agents": [BuildProvider(provider_type="inline::meta-reference")],
+        "telemetry": [BuildProvider(provider_type="inline::meta-reference")],
+        "post_training": [BuildProvider(provider_type="inline::huggingface")],
+        "eval": [BuildProvider(provider_type="inline::meta-reference")],
        "datasetio": [
-            Provider(
-                provider_id="huggingface",
-                provider_type="remote::huggingface",
-            ),
-            Provider(
-                provider_id="localfs",
-                provider_type="inline::localfs",
-            ),
+            BuildProvider(provider_type="remote::huggingface"),
+            BuildProvider(provider_type="inline::localfs"),
        ],
        "scoring": [
-            Provider(
-                provider_id="basic",
-                provider_type="inline::basic",
-            ),
-            Provider(
-                provider_id="llm-as-judge",
-                provider_type="inline::llm-as-judge",
-            ),
-            Provider(
-                provider_id="braintrust",
-                provider_type="inline::braintrust",
-            ),
+            BuildProvider(provider_type="inline::basic"),
+            BuildProvider(provider_type="inline::llm-as-judge"),
+            BuildProvider(provider_type="inline::braintrust"),
        ],
        "tool_runtime": [
-            Provider(
-                provider_id="brave-search",
-                provider_type="remote::brave-search",
-            ),
-            Provider(
-                provider_id="tavily-search",
-                provider_type="remote::tavily-search",
-            ),
-            Provider(
-                provider_id="rag-runtime",
-                provider_type="inline::rag-runtime",
-            ),
-            Provider(
-                provider_id="model-context-protocol",
-                provider_type="remote::model-context-protocol",
-            ),
+            BuildProvider(provider_type="remote::brave-search"),
+            BuildProvider(provider_type="remote::tavily-search"),
+            BuildProvider(provider_type="inline::rag-runtime"),
+            BuildProvider(provider_type="remote::model-context-protocol"),
        ],
    }
    files_provider = Provider(
@ -346,15 +143,10 @@ def get_distribution_template() -> DistributionTemplate:
        config=LocalfsFilesImplConfig.sample_run_config(f"~/.llama/distributions/{name}"),
    )
    embedding_provider = Provider(
-        provider_id="${env.ENABLE_SENTENCE_TRANSFORMERS:=sentence-transformers}",
+        provider_id="sentence-transformers",
        provider_type="inline::sentence-transformers",
        config=SentenceTransformersInferenceConfig.sample_run_config(),
    )
-    post_training_provider = Provider(
-        provider_id="huggingface",
-        provider_type="inline::huggingface",
-        config=HuggingFacePostTrainingConfig.sample_run_config(f"~/.llama/distributions/{name}"),
-    )
    default_tool_groups = [
        ToolGroupInput(
            toolgroup_id="builtin::websearch",
@ -365,19 +157,14 @@ def get_distribution_template() -> DistributionTemplate:
            provider_id="rag-runtime",
        ),
    ]
-    embedding_model = ModelInput(
-        model_id="all-MiniLM-L6-v2",
-        provider_id=embedding_provider.provider_id,
-        model_type=ModelType.embedding,
-        metadata={
-            "embedding_dimension": 384,
-        },
-    )
-
-    default_models, ids_conflict_in_models = get_model_registry(available_models)
-
-    available_safety_models = get_safety_models_for_providers(remote_inference_providers)
-    shields = get_shield_registry(available_safety_models, ids_conflict_in_models)
+    default_shields = [
+        # if the
+        ShieldInput(
+            shield_id="llama-guard",
+            provider_id="${env.SAFETY_MODEL:+llama-guard}",
+            provider_shield_id="${env.SAFETY_MODEL:=}",
+        ),
+    ]

    return DistributionTemplate(
        name=name,
@ -386,20 +173,51 @@ def get_distribution_template() -> DistributionTemplate:
        container_image=None,
        template_path=None,
        providers=providers,
-        available_models_by_provider=available_models,
        additional_pip_packages=PostgresSqlStoreConfig.pip_packages(),
        run_configs={
            "run.yaml": RunConfigSettings(
                provider_overrides={
                    "inference": remote_inference_providers + [embedding_provider],
-                    "vector_io": vector_io_providers,
+                    "vector_io": [
+                        Provider(
+                            provider_id="faiss",
+                            provider_type="inline::faiss",
+                            config=FaissVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
+                        ),
+                        Provider(
+                            provider_id="sqlite-vec",
+                            provider_type="inline::sqlite-vec",
+                            config=SQLiteVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
+                        ),
+                        Provider(
+                            provider_id="${env.MILVUS_URL:+milvus}",
+                            provider_type="inline::milvus",
+                            config=MilvusVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
+                        ),
+                        Provider(
+                            provider_id="${env.CHROMADB_URL:+chromadb}",
+                            provider_type="remote::chromadb",
+                            config=ChromaVectorIOConfig.sample_run_config(
+                                f"~/.llama/distributions/{name}/",
+                                url="${env.CHROMADB_URL:=}",
+                            ),
+                        ),
+                        Provider(
+                            provider_id="${env.PGVECTOR_DB:+pgvector}",
+                            provider_type="remote::pgvector",
+                            config=PGVectorVectorIOConfig.sample_run_config(
+                                f"~/.llama/distributions/{name}",
+                                db="${env.PGVECTOR_DB:=}",
+                                user="${env.PGVECTOR_USER:=}",
+                                password="${env.PGVECTOR_PASSWORD:=}",
+                            ),
+                        ),
+                    ],
                    "files": [files_provider],
-                    "post_training": [post_training_provider],
                },
-                default_models=[embedding_model] + default_models,
+                default_models=[],
                default_tool_groups=default_tool_groups,
-                # TODO: add a way to enable/disable shields on the fly
-                default_shields=shields,
+                default_shields=default_shields,
            ),
        },
        run_config_env_vars={
@ -443,17 +261,5 @@ def get_distribution_template() -> DistributionTemplate:
                "http://localhost:11434",
                "Ollama URL",
            ),
-            "OLLAMA_INFERENCE_MODEL": (
-                "",
-                "Optional Ollama Inference Model to register on startup",
-            ),
-            "OLLAMA_EMBEDDING_MODEL": (
-                "",
-                "Optional Ollama Embedding Model to register on startup",
-            ),
-            "OLLAMA_EMBEDDING_DIMENSION": (
-                "384",
-                "Ollama Embedding Dimension",
-            ),
        },
    )
--- a/llama_stack/templates/template.py
+++ b/llama_stack/templates/template.py
@ -19,6 +19,7 @@ from llama_stack.distribution.datatypes import (
    Api,
    BenchmarkInput,
    BuildConfig,
+    BuildProvider,
    DatasetInput,
    DistributionSpec,
    ModelInput,
@ -183,7 +184,7 @@ class RunConfigSettings(BaseModel):
    def run_config(
        self,
        name: str,
-        providers: dict[str, list[Provider]],
+        providers: dict[str, list[BuildProvider]],
        container_image: str | None = None,
    ) -> dict:
        provider_registry = get_provider_registry()
@ -199,7 +200,7 @@ class RunConfigSettings(BaseModel):
                api = Api(api_str)
                if provider.provider_type not in provider_registry[api]:
                    raise ValueError(f"Unknown provider type: {provider.provider_type} for API: {api_str}")
-
+                provider_id = provider.provider_type.split("::")[-1]
                config_class = provider_registry[api][provider.provider_type].config_class
                assert config_class is not None, (
                    f"No config class for provider type: {provider.provider_type} for API: {api_str}"
@ -210,10 +211,14 @@ class RunConfigSettings(BaseModel):
                    config = config_class.sample_run_config(__distro_dir__=f"~/.llama/distributions/{name}")
                else:
                    config = {}
-
-                provider.config = config
-                # Convert Provider object to dict for YAML serialization
-                provider_configs[api_str].append(provider.model_dump(exclude_none=True))
+                # BuildProvider does not have a config attribute; skip assignment
+                provider_configs[api_str].append(
+                    Provider(
+                        provider_id=provider_id,
+                        provider_type=provider.provider_type,
+                        config=config,
+                    ).model_dump(exclude_none=True)
+                )
        # Get unique set of APIs from providers
        apis = sorted(providers.keys())

@ -257,7 +262,8 @@ class DistributionTemplate(BaseModel):
    description: str
    distro_type: Literal["self_hosted", "remote_hosted", "ondevice"]

-    providers: dict[str, list[Provider]]
+    # Now uses BuildProvider for build config, not Provider
+    providers: dict[str, list[BuildProvider]]
    run_configs: dict[str, RunConfigSettings]
    template_path: Path | None = None

@ -295,11 +301,9 @@ class DistributionTemplate(BaseModel):
        for api, providers in self.providers.items():
            build_providers[api] = []
            for provider in providers:
-                # Create a minimal provider object with only essential build information
-                build_provider = Provider(
-                    provider_id=provider.provider_id,
+                # Create a minimal build provider object with only essential build information
+                build_provider = BuildProvider(
                    provider_type=provider.provider_type,
-                    config={},  # Empty config for build
                    module=provider.module,
                )
                build_providers[api].append(build_provider)
@ -323,50 +327,52 @@ class DistributionTemplate(BaseModel):
            providers_str = ", ".join(f"`{p.provider_type}`" for p in providers)
            providers_table += f"| {api} | {providers_str} |\n"

-        template = self.template_path.read_text()
-        comment = "<!-- This file was auto-generated by distro_codegen.py, please edit source -->\n"
-        orphantext = "---\norphan: true\n---\n"
+        if self.template_path is not None:
+            template = self.template_path.read_text()
+            comment = "<!-- This file was auto-generated by distro_codegen.py, please edit source -->\n"
+            orphantext = "---\norphan: true\n---\n"

-        if template.startswith(orphantext):
-            template = template.replace(orphantext, orphantext + comment)
-        else:
-            template = comment + template
+            if template.startswith(orphantext):
+                template = template.replace(orphantext, orphantext + comment)
+            else:
+                template = comment + template

-        # Render template with rich-generated table
-        env = jinja2.Environment(
-            trim_blocks=True,
-            lstrip_blocks=True,
-            # NOTE: autoescape is required to prevent XSS attacks
-            autoescape=True,
-        )
-        template = env.from_string(template)
+            # Render template with rich-generated table
+            env = jinja2.Environment(
+                trim_blocks=True,
+                lstrip_blocks=True,
+                # NOTE: autoescape is required to prevent XSS attacks
+                autoescape=True,
+            )
+            template = env.from_string(template)

-        default_models = []
-        if self.available_models_by_provider:
-            has_multiple_providers = len(self.available_models_by_provider.keys()) > 1
-            for provider_id, model_entries in self.available_models_by_provider.items():
-                for model_entry in model_entries:
-                    doc_parts = []
-                    if model_entry.aliases:
-                        doc_parts.append(f"aliases: {', '.join(model_entry.aliases)}")
-                    if has_multiple_providers:
-                        doc_parts.append(f"provider: {provider_id}")
+            default_models = []
+            if self.available_models_by_provider:
+                has_multiple_providers = len(self.available_models_by_provider.keys()) > 1
+                for provider_id, model_entries in self.available_models_by_provider.items():
+                    for model_entry in model_entries:
+                        doc_parts = []
+                        if model_entry.aliases:
+                            doc_parts.append(f"aliases: {', '.join(model_entry.aliases)}")
+                        if has_multiple_providers:
+                            doc_parts.append(f"provider: {provider_id}")

-                    default_models.append(
-                        DefaultModel(
-                            model_id=model_entry.provider_model_id,
-                            doc_string=(f"({' -- '.join(doc_parts)})" if doc_parts else ""),
+                        default_models.append(
+                            DefaultModel(
+                                model_id=model_entry.provider_model_id,
+                                doc_string=(f"({' -- '.join(doc_parts)})" if doc_parts else ""),
+                            )
                        )
-                    )

-        return template.render(
-            name=self.name,
-            description=self.description,
-            providers=self.providers,
-            providers_table=providers_table,
-            run_config_env_vars=self.run_config_env_vars,
-            default_models=default_models,
-        )
+            return template.render(
+                name=self.name,
+                description=self.description,
+                providers=self.providers,
+                providers_table=providers_table,
+                run_config_env_vars=self.run_config_env_vars,
+                default_models=default_models,
+            )
+        return ""

    def save_distribution(self, yaml_output_dir: Path, doc_output_dir: Path) -> None:
        def enum_representer(dumper, data):
--- a/llama_stack/templates/watsonx/watsonx.py
+++ b/llama_stack/templates/watsonx/watsonx.py
@ -7,7 +7,7 @@
 from pathlib import Path

 from llama_stack.apis.models import ModelType
-from llama_stack.distribution.datatypes import ModelInput, Provider, ToolGroupInput
+from llama_stack.distribution.datatypes import BuildProvider, ModelInput, Provider, ToolGroupInput
 from llama_stack.providers.inline.inference.sentence_transformers import (
    SentenceTransformersInferenceConfig,
 )
@ -19,86 +19,28 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
    providers = {
        "inference": [
-            Provider(
-                provider_id="watsonx",
-                provider_type="remote::watsonx",
-            ),
-            Provider(
-                provider_id="sentence-transformers",
-                provider_type="inline::sentence-transformers",
-            ),
-        ],
-        "vector_io": [
-            Provider(
-                provider_id="faiss",
-                provider_type="inline::faiss",
-            )
-        ],
-        "safety": [
-            Provider(
-                provider_id="llama-guard",
-                provider_type="inline::llama-guard",
-            )
-        ],
-        "agents": [
-            Provider(
-                provider_id="meta-reference",
-                provider_type="inline::meta-reference",
-            )
-        ],
-        "telemetry": [
-            Provider(
-                provider_id="meta-reference",
-                provider_type="inline::meta-reference",
-            )
-        ],
-        "eval": [
-            Provider(
-                provider_id="meta-reference",
-                provider_type="inline::meta-reference",
-            )
+            BuildProvider(provider_type="remote::watsonx"),
+            BuildProvider(provider_type="inline::sentence-transformers"),
        ],
+        "vector_io": [BuildProvider(provider_type="inline::faiss")],
+        "safety": [BuildProvider(provider_type="inline::llama-guard")],
+        "agents": [BuildProvider(provider_type="inline::meta-reference")],
+        "telemetry": [BuildProvider(provider_type="inline::meta-reference")],
+        "eval": [BuildProvider(provider_type="inline::meta-reference")],
        "datasetio": [
-            Provider(
-                provider_id="huggingface",
-                provider_type="remote::huggingface",
-            ),
-            Provider(
-                provider_id="localfs",
-                provider_type="inline::localfs",
-            ),
+            BuildProvider(provider_type="remote::huggingface"),
+            BuildProvider(provider_type="inline::localfs"),
        ],
        "scoring": [
-            Provider(
-                provider_id="basic",
-                provider_type="inline::basic",
-            ),
-            Provider(
-                provider_id="llm-as-judge",
-                provider_type="inline::llm-as-judge",
-            ),
-            Provider(
-                provider_id="braintrust",
-                provider_type="inline::braintrust",
-            ),
+            BuildProvider(provider_type="inline::basic"),
+            BuildProvider(provider_type="inline::llm-as-judge"),
+            BuildProvider(provider_type="inline::braintrust"),
        ],
        "tool_runtime": [
-            Provider(
-                provider_id="brave-search",
-                provider_type="remote::brave-search",
-            ),
-            Provider(
-                provider_id="tavily-search",
-                provider_type="remote::tavily-search",
-            ),
-            Provider(
-                provider_id="rag-runtime",
-                provider_type="inline::rag-runtime",
-            ),
-            Provider(
-                provider_id="model-context-protocol",
-                provider_type="remote::model-context-protocol",
-            ),
+            BuildProvider(provider_type="remote::brave-search"),
+            BuildProvider(provider_type="remote::tavily-search"),
+            BuildProvider(provider_type="inline::rag-runtime"),
+            BuildProvider(provider_type="remote::model-context-protocol"),
        ],
    }

--- a/llama_stack/ui/package.json
+++ b/llama_stack/ui/package.json
@ -20,7 +20,7 @@
    "@radix-ui/react-tooltip": "^1.2.6",
    "class-variance-authority": "^0.7.1",
    "clsx": "^2.1.1",
-    "llama-stack-client": "^0.2.15",
+    "llama-stack-client": ""0.2.16",
    "lucide-react": "^0.510.0",
    "next": "15.3.3",
    "next-auth": "^4.24.11",
--- a/pyproject.toml
+++ b/pyproject.toml
@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"

 [project]
 name = "llama_stack"
-version = "0.2.15"
+version = "0.2.16"
 authors = [{ name = "Meta Llama", email = "llama-oss@meta.com" }]
 description = "Llama Stack"
 readme = "README.md"
@ -25,10 +25,10 @@ dependencies = [
    "fastapi>=0.115.0,<1.0",                  # server
    "fire",                                   # for MCP in LLS client
    "httpx",
-    "huggingface-hub>=0.30.0,<1.0",
+    "huggingface-hub>=0.34.0,<1.0",
    "jinja2>=3.1.6",
    "jsonschema",
-    "llama-stack-client>=0.2.15",
+    "llama-stack-client>=0.2.16",
    "llama-api-client>=0.1.2",
    "openai>=1.66",
    "prompt-toolkit",
@ -53,7 +53,7 @@ dependencies = [
 ui = [
    "streamlit",
    "pandas",
-    "llama-stack-client>=0.2.15",
+    "llama-stack-client>=0.2.16",
    "streamlit-option-menu",
 ]

@ -114,6 +114,7 @@ test = [
    "sqlalchemy[asyncio]>=2.0.41",
    "requests",
    "pymilvus>=2.5.12",
+    "reportlab",
 ]
 docs = [
    "setuptools",
--- a/requirements.txt
+++ b/requirements.txt
@ -86,7 +86,7 @@ httpx==0.28.1
    #   llama-stack
    #   llama-stack-client
    #   openai
-huggingface-hub==0.33.0
+huggingface-hub==0.34.1
    # via llama-stack
 idna==3.10
    # via
@ -106,7 +106,7 @@ jsonschema-specifications==2024.10.1
    # via jsonschema
 llama-api-client==0.1.2
    # via llama-stack
-llama-stack-client==0.2.15
+llama-stack-client==0.2.16
    # via llama-stack
 markdown-it-py==3.0.0
    # via rich
@ -167,14 +167,14 @@ pyasn1==0.4.8
    #   rsa
 pycparser==2.22 ; platform_python_implementation != 'PyPy'
    # via cffi
-pydantic==2.10.6
+pydantic==2.11.7
    # via
    #   fastapi
    #   llama-api-client
    #   llama-stack
    #   llama-stack-client
    #   openai
-pydantic-core==2.27.2
+pydantic-core==2.33.2
    # via pydantic
 pygments==2.19.1
    # via rich
@ -253,6 +253,9 @@ typing-extensions==4.12.2
    #   pydantic
    #   pydantic-core
    #   referencing
+    #   typing-inspection
+typing-inspection==0.4.1
+    # via pydantic
 tzdata==2025.1
    # via pandas
 urllib3==2.5.0
--- a/scripts/install.sh
+++ b/scripts/install.sh
@ -222,9 +222,7 @@ cmd=( run -d "${PLATFORM_OPTS[@]}" --name llama-stack \
      --network llama-net \
      -p "${PORT}:${PORT}" \
      "${SERVER_IMAGE}" --port "${PORT}" \
-      --env OLLAMA_INFERENCE_MODEL="${MODEL_ALIAS}" \
-      --env OLLAMA_URL="http://ollama-server:${OLLAMA_PORT}" \
-      --env ENABLE_OLLAMA=ollama)
+      --env OLLAMA_URL="http://ollama-server:${OLLAMA_PORT}")

 log "🦙 Starting Llama Stack..."
 if ! execute_with_log $ENGINE "${cmd[@]}"; then
--- a/scripts/unit-tests.sh
+++ b/scripts/unit-tests.sh
@ -8,6 +8,15 @@

 PYTHON_VERSION=${PYTHON_VERSION:-3.12}

+set -e
+
+# Always run this at the end, even if something fails
+cleanup() {
+    echo "Generating coverage report..."
+    uv run --python "$PYTHON_VERSION" coverage html -d htmlcov-$PYTHON_VERSION
+}
+trap cleanup EXIT
+
 command -v uv >/dev/null 2>&1 || { echo >&2 "uv is required but it's not installed. Exiting."; exit 1; }

 uv python find "$PYTHON_VERSION"
@ -19,6 +28,3 @@ fi
 # Run unit tests with coverage
 uv run --python "$PYTHON_VERSION" --with-editable . --group unit \
    coverage run --source=llama_stack -m pytest -s -v tests/unit/ "$@"
-
-# Generate HTML coverage report
-uv run --python "$PYTHON_VERSION" coverage html -d htmlcov-$PYTHON_VERSION
--- a/tests/external/build.yaml
+++ b/tests/external/build.yaml
@ -3,8 +3,7 @@ distribution_spec:
  description: Custom distro for CI tests
  providers:
    weather:
-    - provider_id: kaze
-      provider_type: remote::kaze
+    - provider_type: remote::kaze
 image_type: venv
 image_name: ci-test
 external_providers_dir: ~/.llama/providers.d
--- a/tests/external/ramalama-stack/build.yaml
+++ b/tests/external/ramalama-stack/build.yaml
@ -4,8 +4,7 @@ distribution_spec:
  container_image: null
  providers:
    inference:
-    - provider_id: ramalama
-      provider_type: remote::ramalama
+    - provider_type: remote::ramalama
      module: ramalama_stack==0.3.0a0
 image_type: venv
 image_name: ramalama-stack-test
--- a/tests/integration/inference/test_openai_completion.py
+++ b/tests/integration/inference/test_openai_completion.py
@ -5,8 +5,14 @@
 # the root directory of this source tree.


+import base64
+import os
+import tempfile
+
 import pytest
 from openai import OpenAI
+from reportlab.lib.pagesizes import letter
+from reportlab.pdfgen import canvas

 from llama_stack.distribution.library_client import LlamaStackAsLibraryClient

@ -82,6 +88,14 @@ def skip_if_provider_isnt_vllm(client_with_models, model_id):
        pytest.skip(f"Model {model_id} hosted by {provider.provider_type} doesn't support vllm extra_body parameters.")


+def skip_if_provider_isnt_openai(client_with_models, model_id):
+    provider = provider_from_model(client_with_models, model_id)
+    if provider.provider_type != "remote::openai":
+        pytest.skip(
+            f"Model {model_id} hosted by {provider.provider_type} doesn't support chat completion calls with base64 encoded files."
+        )
+
+
@pytest.fixture
 def openai_client(client_with_models):
    base_url = f"{client_with_models.base_url}/v1/openai/v1"
@ -418,3 +432,45 @@ def test_inference_store_tool_calls(compat_client, client_with_models, text_mode
        # failed tool call parses show up as a message with content, so ensure
        # that the retrieve response content matches the original request
        assert retrieved_response.choices[0].message.content == content
+
+
+def test_openai_chat_completion_non_streaming_with_file(openai_client, client_with_models, text_model_id):
+    skip_if_provider_isnt_openai(client_with_models, text_model_id)
+
+    # Generate temporary PDF with "Hello World" text
+    with tempfile.NamedTemporaryFile(suffix=".pdf", delete=False) as temp_pdf:
+        c = canvas.Canvas(temp_pdf.name, pagesize=letter)
+        c.drawString(100, 750, "Hello World")
+        c.save()
+
+        # Read the PDF and sencode to base64
+        with open(temp_pdf.name, "rb") as pdf_file:
+            pdf_base64 = base64.b64encode(pdf_file.read()).decode("utf-8")
+
+        # Clean up temporary file
+        os.unlink(temp_pdf.name)
+
+    response = openai_client.chat.completions.create(
+        model=text_model_id,
+        messages=[
+            {
+                "role": "user",
+                "content": "Describe what you see in this PDF file.",
+            },
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "file",
+                        "file": {
+                            "filename": "my-temp-hello-world-pdf",
+                            "file_data": f"data:application/pdf;base64,{pdf_base64}",
+                        },
+                    }
+                ],
+            },
+        ],
+        stream=False,
+    )
+    message_content = response.choices[0].message.content.lower().strip()
+    assert "hello world" in message_content
--- a/tests/unit/distribution/routers/test_routing_tables.py
+++ b/tests/unit/distribution/routers/test_routing_tables.py
@ -502,7 +502,7 @@ async def test_models_source_interaction_preserves_default(cached_disk_dist_regi

    # Find the user model and provider model
    user_model = next((m for m in models.data if m.identifier == "my-custom-alias"), None)
-    provider_model = next((m for m in models.data if m.identifier == "different-model"), None)
+    provider_model = next((m for m in models.data if m.identifier == "test_provider/different-model"), None)

    assert user_model is not None
    assert user_model.source == RegistryEntrySource.via_register_api
@ -558,12 +558,12 @@ async def test_models_source_interaction_cleanup_provider_models(cached_disk_dis

    identifiers = {m.identifier for m in models.data}
    assert "test_provider/user-model" in identifiers  # User model preserved
-    assert "provider-model-new" in identifiers  # New provider model (uses provider's identifier)
-    assert "provider-model-old" not in identifiers  # Old provider model removed
+    assert "test_provider/provider-model-new" in identifiers  # New provider model (uses provider's identifier)
+    assert "test_provider/provider-model-old" not in identifiers  # Old provider model removed

    # Verify sources are correct
    user_model = next((m for m in models.data if m.identifier == "test_provider/user-model"), None)
-    provider_model = next((m for m in models.data if m.identifier == "provider-model-new"), None)
+    provider_model = next((m for m in models.data if m.identifier == "test_provider/provider-model-new"), None)

    assert user_model.source == RegistryEntrySource.via_register_api
    assert provider_model.source == RegistryEntrySource.listed_from_provider
--- a/tests/unit/distribution/test_distribution.py
+++ b/tests/unit/distribution/test_distribution.py
@ -346,7 +346,7 @@ pip_packages:

    def test_external_provider_from_module_building(self, mock_providers):
        """Test loading an external provider from a module during build (building=True, partial spec)."""
-        from llama_stack.distribution.datatypes import BuildConfig, DistributionSpec, Provider
+        from llama_stack.distribution.datatypes import BuildConfig, BuildProvider, DistributionSpec
        from llama_stack.providers.datatypes import Api

        # No importlib patch needed, should not import module when type of `config` is BuildConfig or DistributionSpec
@ -358,10 +358,8 @@ pip_packages:
                description="test",
                providers={
                    "inference": [
-                        Provider(
-                            provider_id="external_test",
+                        BuildProvider(
                            provider_type="external_test",
-                            config={},
                            module="external_test",
                        )
                    ]
--- a/tests/unit/providers/inference/test_openai_base_url_config.py
+++ b/tests/unit/providers/inference/test_openai_base_url_config.py
@ -0,0 +1,125 @@
+# 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.
+
+import os
+from unittest.mock import AsyncMock, MagicMock, patch
+
+from llama_stack.distribution.stack import replace_env_vars
+from llama_stack.providers.remote.inference.openai.config import OpenAIConfig
+from llama_stack.providers.remote.inference.openai.openai import OpenAIInferenceAdapter
+
+
+class TestOpenAIBaseURLConfig:
+    """Test that OPENAI_BASE_URL environment variable properly configures the OpenAI adapter."""
+
+    def test_default_base_url_without_env_var(self):
+        """Test that the adapter uses the default OpenAI base URL when no environment variable is set."""
+        config = OpenAIConfig(api_key="test-key")
+        adapter = OpenAIInferenceAdapter(config)
+
+        assert adapter.get_base_url() == "https://api.openai.com/v1"
+
+    def test_custom_base_url_from_config(self):
+        """Test that the adapter uses a custom base URL when provided in config."""
+        custom_url = "https://custom.openai.com/v1"
+        config = OpenAIConfig(api_key="test-key", base_url=custom_url)
+        adapter = OpenAIInferenceAdapter(config)
+
+        assert adapter.get_base_url() == custom_url
+
+    @patch.dict(os.environ, {"OPENAI_BASE_URL": "https://env.openai.com/v1"})
+    def test_base_url_from_environment_variable(self):
+        """Test that the adapter uses base URL from OPENAI_BASE_URL environment variable."""
+        # Use sample_run_config which has proper environment variable syntax
+        config_data = OpenAIConfig.sample_run_config(api_key="test-key")
+        processed_config = replace_env_vars(config_data)
+        config = OpenAIConfig.model_validate(processed_config)
+        adapter = OpenAIInferenceAdapter(config)
+
+        assert adapter.get_base_url() == "https://env.openai.com/v1"
+
+    @patch.dict(os.environ, {"OPENAI_BASE_URL": "https://env.openai.com/v1"})
+    def test_config_overrides_environment_variable(self):
+        """Test that explicit config value overrides environment variable."""
+        custom_url = "https://config.openai.com/v1"
+        config = OpenAIConfig(api_key="test-key", base_url=custom_url)
+        adapter = OpenAIInferenceAdapter(config)
+
+        # Config should take precedence over environment variable
+        assert adapter.get_base_url() == custom_url
+
+    @patch("llama_stack.providers.utils.inference.openai_mixin.AsyncOpenAI")
+    def test_client_uses_configured_base_url(self, mock_openai_class):
+        """Test that the OpenAI client is initialized with the configured base URL."""
+        custom_url = "https://test.openai.com/v1"
+        config = OpenAIConfig(api_key="test-key", base_url=custom_url)
+        adapter = OpenAIInferenceAdapter(config)
+
+        # Mock the get_api_key method since it's delegated to LiteLLMOpenAIMixin
+        adapter.get_api_key = MagicMock(return_value="test-key")
+
+        # Access the client property to trigger AsyncOpenAI initialization
+        _ = adapter.client
+
+        # Verify AsyncOpenAI was called with the correct base_url
+        mock_openai_class.assert_called_once_with(
+            api_key="test-key",
+            base_url=custom_url,
+        )
+
+    @patch("llama_stack.providers.utils.inference.openai_mixin.AsyncOpenAI")
+    async def test_check_model_availability_uses_configured_url(self, mock_openai_class):
+        """Test that check_model_availability uses the configured base URL."""
+        custom_url = "https://test.openai.com/v1"
+        config = OpenAIConfig(api_key="test-key", base_url=custom_url)
+        adapter = OpenAIInferenceAdapter(config)
+
+        # Mock the get_api_key method
+        adapter.get_api_key = MagicMock(return_value="test-key")
+
+        # Mock the AsyncOpenAI client and its models.retrieve method
+        mock_client = MagicMock()
+        mock_client.models.retrieve = AsyncMock(return_value=MagicMock())
+        mock_openai_class.return_value = mock_client
+
+        # Call check_model_availability and verify it returns True
+        assert await adapter.check_model_availability("gpt-4")
+
+        # Verify the client was created with the custom URL
+        mock_openai_class.assert_called_with(
+            api_key="test-key",
+            base_url=custom_url,
+        )
+
+        # Verify the method was called and returned True
+        mock_client.models.retrieve.assert_called_once_with("gpt-4")
+
+    @patch.dict(os.environ, {"OPENAI_BASE_URL": "https://proxy.openai.com/v1"})
+    @patch("llama_stack.providers.utils.inference.openai_mixin.AsyncOpenAI")
+    async def test_environment_variable_affects_model_availability_check(self, mock_openai_class):
+        """Test that setting OPENAI_BASE_URL environment variable affects where model availability is checked."""
+        # Use sample_run_config which has proper environment variable syntax
+        config_data = OpenAIConfig.sample_run_config(api_key="test-key")
+        processed_config = replace_env_vars(config_data)
+        config = OpenAIConfig.model_validate(processed_config)
+        adapter = OpenAIInferenceAdapter(config)
+
+        # Mock the get_api_key method
+        adapter.get_api_key = MagicMock(return_value="test-key")
+
+        # Mock the AsyncOpenAI client
+        mock_client = MagicMock()
+        mock_client.models.retrieve = AsyncMock(return_value=MagicMock())
+        mock_openai_class.return_value = mock_client
+
+        # Call check_model_availability and verify it returns True
+        assert await adapter.check_model_availability("gpt-4")
+
+        # Verify the client was created with the environment variable URL
+        mock_openai_class.assert_called_with(
+            api_key="test-key",
+            base_url="https://proxy.openai.com/v1",
+        )
--- a/tests/unit/providers/utils/inference/test_openai_compat.py
+++ b/tests/unit/providers/utils/inference/test_openai_compat.py
@ -4,13 +4,19 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.

+import pytest
+from pydantic import ValidationError

 from llama_stack.apis.common.content_types import TextContentItem
 from llama_stack.apis.inference import (
    CompletionMessage,
    OpenAIAssistantMessageParam,
+    OpenAIChatCompletionContentPartImageParam,
    OpenAIChatCompletionContentPartTextParam,
+    OpenAIDeveloperMessageParam,
+    OpenAIImageURL,
    OpenAISystemMessageParam,
+    OpenAIToolMessageParam,
    OpenAIUserMessageParam,
    SystemMessage,
    UserMessage,
@ -108,3 +114,71 @@ async def test_openai_messages_to_messages_with_content_list():
    assert llama_messages[0].content[0].text == "system message"
    assert llama_messages[1].content[0].text == "user message"
    assert llama_messages[2].content[0].text == "assistant message"
+
+
+@pytest.mark.parametrize(
+    "message_class,kwargs",
+    [
+        (OpenAISystemMessageParam, {}),
+        (OpenAIAssistantMessageParam, {}),
+        (OpenAIDeveloperMessageParam, {}),
+        (OpenAIUserMessageParam, {}),
+        (OpenAIToolMessageParam, {"tool_call_id": "call_123"}),
+    ],
+)
+def test_message_accepts_text_string(message_class, kwargs):
+    """Test that messages accept string text content."""
+    msg = message_class(content="Test message", **kwargs)
+    assert msg.content == "Test message"
+
+
+@pytest.mark.parametrize(
+    "message_class,kwargs",
+    [
+        (OpenAISystemMessageParam, {}),
+        (OpenAIAssistantMessageParam, {}),
+        (OpenAIDeveloperMessageParam, {}),
+        (OpenAIUserMessageParam, {}),
+        (OpenAIToolMessageParam, {"tool_call_id": "call_123"}),
+    ],
+)
+def test_message_accepts_text_list(message_class, kwargs):
+    """Test that messages accept list of text content parts."""
+    content_list = [OpenAIChatCompletionContentPartTextParam(text="Test message")]
+    msg = message_class(content=content_list, **kwargs)
+    assert len(msg.content) == 1
+    assert msg.content[0].text == "Test message"
+
+
+@pytest.mark.parametrize(
+    "message_class,kwargs",
+    [
+        (OpenAISystemMessageParam, {}),
+        (OpenAIAssistantMessageParam, {}),
+        (OpenAIDeveloperMessageParam, {}),
+        (OpenAIToolMessageParam, {"tool_call_id": "call_123"}),
+    ],
+)
+def test_message_rejects_images(message_class, kwargs):
+    """Test that system, assistant, developer, and tool messages reject image content."""
+    with pytest.raises(ValidationError):
+        message_class(
+            content=[
+                OpenAIChatCompletionContentPartImageParam(image_url=OpenAIImageURL(url="http://example.com/image.jpg"))
+            ],
+            **kwargs,
+        )
+
+
+def test_user_message_accepts_images():
+    """Test that user messages accept image content (unlike other message types)."""
+    # List with images should work
+    msg = OpenAIUserMessageParam(
+        content=[
+            OpenAIChatCompletionContentPartTextParam(text="Describe this image:"),
+            OpenAIChatCompletionContentPartImageParam(image_url=OpenAIImageURL(url="http://example.com/image.jpg")),
+        ]
+    )
+    assert len(msg.content) == 2
+    assert msg.content[0].text == "Describe this image:"
+    assert msg.content[1].image_url.url == "http://example.com/image.jpg"
--- a/tests/unit/providers/utils/test_model_registry.py
+++ b/tests/unit/providers/utils/test_model_registry.py
@ -162,26 +162,29 @@ async def test_register_model_existing_different(
        await helper.register_model(known_model)


-async def test_unregister_model(helper: ModelRegistryHelper, known_model: Model) -> None:
-    await helper.register_model(known_model)  # duplicate entry
-    assert helper.get_provider_model_id(known_model.model_id) == known_model.provider_model_id
-    await helper.unregister_model(known_model.model_id)
-    assert helper.get_provider_model_id(known_model.model_id) is None
+# TODO: unregister_model functionality was removed/disabled by https://github.com/meta-llama/llama-stack/pull/2916
+# async def test_unregister_model(helper: ModelRegistryHelper, known_model: Model) -> None:
+#     await helper.register_model(known_model)  # duplicate entry
+#     assert helper.get_provider_model_id(known_model.model_id) == known_model.provider_model_id
+#     await helper.unregister_model(known_model.model_id)
+#     assert helper.get_provider_model_id(known_model.model_id) is None


-async def test_unregister_unknown_model(helper: ModelRegistryHelper, unknown_model: Model) -> None:
-    with pytest.raises(ValueError):
-        await helper.unregister_model(unknown_model.model_id)
+# TODO: unregister_model functionality was removed/disabled by https://github.com/meta-llama/llama-stack/pull/2916
+# async def test_unregister_unknown_model(helper: ModelRegistryHelper, unknown_model: Model) -> None:
+#     with pytest.raises(ValueError):
+#         await helper.unregister_model(unknown_model.model_id)


 async def test_register_model_during_init(helper: ModelRegistryHelper, known_model: Model) -> None:
    assert helper.get_provider_model_id(known_model.provider_resource_id) == known_model.provider_model_id


-async def test_unregister_model_during_init(helper: ModelRegistryHelper, known_model: Model) -> None:
-    assert helper.get_provider_model_id(known_model.provider_resource_id) == known_model.provider_model_id
-    await helper.unregister_model(known_model.provider_resource_id)
-    assert helper.get_provider_model_id(known_model.provider_resource_id) is None
+# TODO: unregister_model functionality was removed/disabled by https://github.com/meta-llama/llama-stack/pull/2916
+# async def test_unregister_model_during_init(helper: ModelRegistryHelper, known_model: Model) -> None:
+#     assert helper.get_provider_model_id(known_model.provider_resource_id) == known_model.provider_model_id
+#     await helper.unregister_model(known_model.provider_resource_id)
+#     assert helper.get_provider_model_id(known_model.provider_resource_id) is None


 async def test_register_model_from_check_model_availability(
--- a/tests/unit/server/test_auth_github.py
+++ b/tests/unit/server/test_auth_github.py
@ -49,7 +49,7 @@ def github_token_app():
    )

    # Add auth middleware
-    app.add_middleware(AuthenticationMiddleware, auth_config=auth_config)
+    app.add_middleware(AuthenticationMiddleware, auth_config=auth_config, impls={})

    @app.get("/test")
    def test_endpoint():
@ -149,7 +149,7 @@ def test_github_enterprise_support(mock_client_class):
        access_policy=[],
    )

-    app.add_middleware(AuthenticationMiddleware, auth_config=auth_config)
+    app.add_middleware(AuthenticationMiddleware, auth_config=auth_config, impls={})

    @app.get("/test")
    def test_endpoint():
--- a/Show more
+++ b/Show more