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chore: rename run.yaml to config.yaml

Browse source 
since we only have one config, lets call it config.yaml! this should be treated as the source of truth for starting a stack

change all file names, tests, etc.

Signed-off-by: Charlie Doern <cdoern@redhat.com>
This commit is contained in:
Charlie Doern 2025-11-25 12:56:57 -05:00
parent 4a3f9151e3
commit 0cd98c957e
64 changed files with 147 additions and 145 deletions
Download patch file Download diff file Expand all files Collapse all files

2
.github/workflows/README.md vendored
View file

@ -4,7 +4,7 @@ Llama Stack uses GitHub Actions for Continuous Integration (CI). Below is a tabl
| Name | File | Purpose |
| ---- | ---- | ------- |
| Backward Compatibility Check | [backward-compat.yml](backward-compat.yml) | Check backward compatibility for run.yaml configs |
| Backward Compatibility Check | [backward-compat.yml](backward-compat.yml) | Check backward compatibility for config.yaml configs |
| Update Changelog | [changelog.yml](changelog.yml) | Creates PR for updating the CHANGELOG.md |
| API Conformance Tests | [conformance.yml](conformance.yml) | Run the API Conformance test suite on the changes. |
| Installer CI | [install-script-ci.yml](install-script-ci.yml) | Test the installation script |

52
.github/workflows/backward-compat.yml vendored
View file

@ -1,6 +1,6 @@
name: Backward Compatibility Check
run-name: Check backward compatibility for run.yaml configs
run-name: Check backward compatibility for config.yaml configs
on:
pull_request:
@ -12,7 +12,7 @@ on:
paths:
- 'src/llama_stack/core/datatypes.py'
- 'src/llama_stack/providers/datatypes.py'
- 'src/llama_stack/distributions/**/run.yaml'
- 'src/llama_stack/distributions/**/config.yaml'
- 'tests/backward_compat/**'
- '.github/workflows/backward-compat.yml'
@ -45,15 +45,15 @@ jobs:
run: |
uv sync --group dev
- name: Extract run.yaml files from main branch
- name: Extract config.yaml files from main branch
id: extract_configs
run: |
# Get list of run.yaml paths from main
# Get list of config.yaml paths from main
git fetch origin main
CONFIG_PATHS=$(git ls-tree -r --name-only origin/main | grep "src/llama_stack/distributions/.*/run.yaml$" || true)
CONFIG_PATHS=$(git ls-tree -r --name-only origin/main | grep "src/llama_stack/distributions/.*/config.yaml$" || true)
if [ -z "$CONFIG_PATHS" ]; then
echo "No run.yaml files found in main branch"
echo "No config.yaml files found in main branch"
exit 1
fi
@ -125,7 +125,7 @@ jobs:
echo ""
echo "⚠️ WARNING: Breaking changes detected but acknowledged"
echo ""
echo "This PR introduces backward-incompatible changes to run.yaml."
echo "This PR introduces backward-incompatible changes to config.yaml."
echo "The changes have been properly acknowledged."
echo ""
exit 0 # Pass the check
@ -133,7 +133,7 @@ jobs:
echo ""
echo "❌ ERROR: Breaking changes detected without acknowledgment"
echo ""
echo "This PR introduces backward-incompatible changes to run.yaml"
echo "This PR introduces backward-incompatible changes to config.yaml"
echo "that will break existing user configurations."
echo ""
echo "To acknowledge this breaking change, do ONE of:"
@ -155,11 +155,11 @@ jobs:
with:
fetch-depth: 0
- name: Extract ci-tests run.yaml from main
- name: Extract ci-tests config.yaml from main
run: |
git fetch origin main
git show origin/main:src/llama_stack/distributions/ci-tests/run.yaml > /tmp/main-ci-tests-run.yaml
echo "Extracted ci-tests run.yaml from main branch"
git show origin/main:src/llama_stack/distributions/ci-tests/config.yaml > /tmp/main-ci-tests-config.yaml
echo "Extracted ci-tests config.yaml from main branch"
- name: Setup test environment
uses: ./.github/actions/setup-test-environment
@ -175,7 +175,7 @@ jobs:
continue-on-error: true
uses: ./.github/actions/run-and-record-tests
with:
stack-config: /tmp/main-ci-tests-run.yaml
stack-config: /tmp/main-ci-tests-config.yaml
setup: 'ollama'
inference-mode: 'replay'
suite: 'base'
@ -258,21 +258,21 @@ jobs:
env:
GH_TOKEN: ${{ github.token }}
- name: Extract ci-tests run.yaml from release
- name: Extract ci-tests config.yaml from release
if: steps.get_release.outputs.has_release == 'true'
id: extract_config
run: |
RELEASE_TAG="${{ steps.get_release.outputs.tag }}"
# Try with src/ prefix first (newer releases), then without (older releases)
if git show "$RELEASE_TAG:src/llama_stack/distributions/ci-tests/run.yaml" > /tmp/release-ci-tests-run.yaml 2>/dev/null; then
echo "Extracted ci-tests run.yaml from release $RELEASE_TAG (src/ path)"
if git show "$RELEASE_TAG:src/llama_stack/distributions/ci-tests/config.yaml" > /tmp/release-ci-tests-config.yaml 2>/dev/null; then
echo "Extracted ci-tests config.yaml from release $RELEASE_TAG (src/ path)"
echo "has_config=true" >> $GITHUB_OUTPUT
elif git show "$RELEASE_TAG:llama_stack/distributions/ci-tests/run.yaml" > /tmp/release-ci-tests-run.yaml 2>/dev/null; then
echo "Extracted ci-tests run.yaml from release $RELEASE_TAG (old path)"
elif git show "$RELEASE_TAG:llama_stack/distributions/ci-tests/config.yaml" > /tmp/release-ci-tests-config.yaml 2>/dev/null; then
echo "Extracted ci-tests config.yaml from release $RELEASE_TAG (old path)"
echo "has_config=true" >> $GITHUB_OUTPUT
else
echo "::warning::ci-tests/run.yaml not found in release $RELEASE_TAG"
echo "::warning::ci-tests/config.yaml not found in release $RELEASE_TAG"
echo "has_config=false" >> $GITHUB_OUTPUT
fi
@ -292,7 +292,7 @@ jobs:
continue-on-error: true
uses: ./.github/actions/run-and-record-tests
with:
stack-config: /tmp/release-ci-tests-run.yaml
stack-config: /tmp/release-ci-tests-config.yaml
setup: 'ollama'
inference-mode: 'replay'
suite: 'base'
@ -318,7 +318,7 @@ jobs:
continue-on-error: true
uses: ./.github/actions/run-and-record-tests
with:
stack-config: /tmp/release-ci-tests-run.yaml
stack-config: /tmp/release-ci-tests-config.yaml
setup: 'ollama'
inference-mode: 'replay'
suite: 'base'
@ -447,11 +447,11 @@ jobs:
run: |
RELEASE_TAG="${{ steps.get_release.outputs.tag }}"
# Get run.yaml files from the release (try both src/ and old path)
CONFIG_PATHS=$(git ls-tree -r --name-only "$RELEASE_TAG" | grep "llama_stack/distributions/.*/run.yaml$" || true)
# Get config.yaml files from the release (try both src/ and old path)
CONFIG_PATHS=$(git ls-tree -r --name-only "$RELEASE_TAG" | grep "llama_stack/distributions/.*/config.yaml$" || true)
if [ -z "$CONFIG_PATHS" ]; then
echo "::warning::No run.yaml files found in release $RELEASE_TAG"
echo "::warning::No config.yaml files found in release $RELEASE_TAG"
echo "has_configs=false" >> $GITHUB_OUTPUT
exit 0
fi
@ -523,7 +523,7 @@ jobs:
⚠️ This PR introduces a schema breaking change that affects compatibility with the latest release.
- Users on release \`$RELEASE_TAG\` will not be able to upgrade
- Existing run.yaml configurations will fail validation
- Existing config.yaml configurations will fail validation
The tests pass on \`main\` but fail with this PR's changes.
@ -543,7 +543,7 @@ jobs:
- Tests **PASS** on main branch ✅
- Tests **FAIL** on PR branch ❌
- Users on release \`$RELEASE_TAG\` will not be able to upgrade
- Existing run.yaml configurations will fail validation
- Existing config.yaml configurations will fail validation
> **Note:** This is informational only and does not block merge.
> Consider whether this breaking change is acceptable for users.
@ -570,7 +570,7 @@ jobs:
cat >> $GITHUB_STEP_SUMMARY <<EOF
## ✅ Release Schema Compatibility Passed
All run.yaml configs from release \`$RELEASE_TAG\` are compatible.
All config.yaml configs from release \`$RELEASE_TAG\` are compatible.
This PR maintains backward compatibility with the latest release.
EOF
fi

18
.github/workflows/integration-auth-tests.yml vendored
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@ -72,7 +72,7 @@ jobs:
if: ${{ matrix.auth-provider == 'oauth2_token' }}
run: |
run_dir=$(mktemp -d)
cat <<'EOF' > $run_dir/run.yaml
cat <<'EOF' > $run_dir/config.yaml
version: '2'
image_name: kube
apis: []
@ -101,17 +101,17 @@ jobs:
server:
port: 8321
EOF
yq eval '.server.auth.provider_config.type = "${{ matrix.auth-provider }}"' -i $run_dir/run.yaml
yq eval '.server.auth.provider_config.tls_cafile = "${{ env.KUBERNETES_CA_CERT_PATH }}"' -i $run_dir/run.yaml
yq eval '.server.auth.provider_config.issuer = "${{ env.KUBERNETES_ISSUER }}"' -i $run_dir/run.yaml
yq eval '.server.auth.provider_config.audience = "${{ env.KUBERNETES_AUDIENCE }}"' -i $run_dir/run.yaml
yq eval '.server.auth.provider_config.jwks.uri = "${{ env.KUBERNETES_API_SERVER_URL }}"' -i $run_dir/run.yaml
yq eval '.server.auth.provider_config.jwks.token = "${{ env.TOKEN }}"' -i $run_dir/run.yaml
cat $run_dir/run.yaml
yq eval '.server.auth.provider_config.type = "${{ matrix.auth-provider }}"' -i $run_dir/config.yaml
yq eval '.server.auth.provider_config.tls_cafile = "${{ env.KUBERNETES_CA_CERT_PATH }}"' -i $run_dir/config.yaml
yq eval '.server.auth.provider_config.issuer = "${{ env.KUBERNETES_ISSUER }}"' -i $run_dir/config.yaml
yq eval '.server.auth.provider_config.audience = "${{ env.KUBERNETES_AUDIENCE }}"' -i $run_dir/config.yaml
yq eval '.server.auth.provider_config.jwks.uri = "${{ env.KUBERNETES_API_SERVER_URL }}"' -i $run_dir/config.yaml
yq eval '.server.auth.provider_config.jwks.token = "${{ env.TOKEN }}"' -i $run_dir/config.yaml
cat $run_dir/config.yaml
# avoid line breaks in the server log, especially because we grep it below.
export LLAMA_STACK_LOG_WIDTH=200
nohup uv run llama stack run $run_dir/run.yaml > server.log 2>&1 &
nohup uv run llama stack run $run_dir/config.yaml > server.log 2>&1 &
- name: Wait for Llama Stack server to be ready
run: |

4
.github/workflows/providers-build.yml vendored
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@ -116,7 +116,7 @@ jobs:
BASE_IMAGE=$(yq -r '.distribution_spec.container_image // "python:3.12-slim"' src/llama_stack/distributions/ci-tests/build.yaml)
BUILD_ARGS="--build-arg INSTALL_MODE=editable --build-arg DISTRO_NAME=ci-tests"
BUILD_ARGS="$BUILD_ARGS --build-arg BASE_IMAGE=$BASE_IMAGE"
BUILD_ARGS="$BUILD_ARGS --build-arg RUN_CONFIG_PATH=/workspace/src/llama_stack/distributions/ci-tests/run.yaml"
BUILD_ARGS="$BUILD_ARGS --build-arg RUN_CONFIG_PATH=/workspace/src/llama_stack/distributions/ci-tests/config.yaml"
if [ -n "${UV_EXTRA_INDEX_URL:-}" ]; then
BUILD_ARGS="$BUILD_ARGS --build-arg UV_EXTRA_INDEX_URL=$UV_EXTRA_INDEX_URL"
fi
@ -162,7 +162,7 @@ jobs:
BASE_IMAGE=$(yq -r '.distribution_spec.container_image // "registry.access.redhat.com/ubi9:latest"' src/llama_stack/distributions/ci-tests/build.yaml)
BUILD_ARGS="--build-arg INSTALL_MODE=editable --build-arg DISTRO_NAME=ci-tests"
BUILD_ARGS="$BUILD_ARGS --build-arg BASE_IMAGE=$BASE_IMAGE"
BUILD_ARGS="$BUILD_ARGS --build-arg RUN_CONFIG_PATH=/workspace/src/llama_stack/distributions/ci-tests/run.yaml"
BUILD_ARGS="$BUILD_ARGS --build-arg RUN_CONFIG_PATH=/workspace/src/llama_stack/distributions/ci-tests/config.yaml"
if [ -n "${UV_EXTRA_INDEX_URL:-}" ]; then
BUILD_ARGS="$BUILD_ARGS --build-arg UV_EXTRA_INDEX_URL=$UV_EXTRA_INDEX_URL"
fi

2
.github/workflows/providers-list-deps.yml vendored
View file

@ -102,4 +102,4 @@ jobs:
USE_COPY_NOT_MOUNT: "true"
LLAMA_STACK_DIR: "."
run: |
uv run llama stack list-deps src/llama_stack/distributions/ci-tests/run.yaml
uv run llama stack list-deps src/llama_stack/distributions/ci-tests/config.yaml

6
.github/workflows/test-external-provider-module.yml vendored
View file

@ -43,8 +43,8 @@ jobs:
nohup ramalama serve llama3.2:3b-instruct-fp16 > ramalama_server.log 2>&1 &
- name: Apply image type to config file
run: |
yq -i '.image_type = "${{ matrix.image-type }}"' tests/external/ramalama-stack/run.yaml
cat tests/external/ramalama-stack/run.yaml
yq -i '.image_type = "${{ matrix.image-type }}"' tests/external/ramalama-stack/config.yaml
cat tests/external/ramalama-stack/config.yaml
- name: Install distribution dependencies
run: |
@ -59,7 +59,7 @@ jobs:
# Use the virtual environment created by the build step (name comes from build config)
source ramalama-stack-test/bin/activate
uv pip list
nohup llama stack run tests/external/ramalama-stack/run.yaml > server.log 2>&1 &
nohup llama stack run tests/external/ramalama-stack/config.yaml > server.log 2>&1 &
- name: Wait for Llama Stack server to be ready
run: |

2
CHANGELOG.md
View file

@ -85,7 +85,7 @@ Published on: 2025-07-28T23:35:23Z
## Highlights
* Automatic model registration for self-hosted providers (ollama and vllm currently). No need for `INFERENCE_MODEL` environment variables which need to be updated, etc.
* Much simplified starter distribution. Most `ENABLE_` env variables are now gone. When you set `VLLM_URL`, the `vllm` provider is auto-enabled. Similar for `MILVUS_URL`, `PGVECTOR_DB`, etc. Check the [run.yaml](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/templates/starter/run.yaml) for more details.
* Much simplified starter distribution. Most `ENABLE_` env variables are now gone. When you set `VLLM_URL`, the `vllm` provider is auto-enabled. Similar for `MILVUS_URL`, `PGVECTOR_DB`, etc. Check the [config.yaml](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/templates/starter/config.yaml) for more details.
* All tests migrated to pytest now (thanks @Elbehery)
* DPO implementation in the post-training provider (thanks @Nehanth)
* (Huge!) Support for external APIs and providers thereof (thanks @leseb, @cdoern and others). This is a really big deal -- you can now add more APIs completely out of tree and experiment with them before (optionally) wanting to contribute back.

2
docs/docs/advanced_apis/evaluation.mdx
View file

@ -96,7 +96,7 @@ We have built-in functionality to run the supported open-benchmarks using llama-
Spin up llama stack server with 'open-benchmark' template
```
llama stack run llama_stack/distributions/open-benchmark/run.yaml
llama stack run llama_stack/distributions/open-benchmark/config.yaml
```

2
docs/docs/building_applications/rag.mdx
View file

@ -85,7 +85,7 @@ Llama Stack provides OpenAI-compatible RAG capabilities through:
## Configuring Default Embedding Models
To enable automatic vector store creation without specifying embedding models, configure a default embedding model in your run.yaml like so:
To enable automatic vector store creation without specifying embedding models, configure a default embedding model in your config.yaml like so:
```yaml
vector_stores:

2
docs/docs/building_applications/tools.mdx
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@ -85,7 +85,7 @@ Features:
- Context retrieval with token limits
:::note[Default Configuration]
By default, llama stack run.yaml defines toolgroups for web search, wolfram alpha and rag, that are provided by tavily-search, wolfram-alpha and rag providers.
By default, llama stack config.yaml defines toolgroups for web search, wolfram alpha and rag, that are provided by tavily-search, wolfram-alpha and rag providers.
:::
## Model Context Protocol (MCP)

2
docs/docs/concepts/evaluation_concepts.mdx
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@ -47,7 +47,7 @@ We have built-in functionality to run the supported open-benckmarks using llama-
Spin up llama stack server with 'open-benchmark' template
```bash
llama stack run llama_stack/distributions/open-benchmark/run.yaml
llama stack run llama_stack/distributions/open-benchmark/config.yaml
```
#### Run eval CLI

2
docs/docs/contributing/new_api_provider.mdx
View file

@ -14,7 +14,7 @@ This guide will walk you through the process of adding a new API provider to Lla
- Begin by reviewing the [core concepts](../concepts/) of Llama Stack and choose the API your provider belongs to (Inference, Safety, VectorIO, etc.)
- Determine the provider type ([Remote](https://github.com/meta-llama/llama-stack/tree/main/llama_stack/providers/remote) or [Inline](https://github.com/meta-llama/llama-stack/tree/main/llama_stack/providers/inline)). Remote providers make requests to external services, while inline providers execute implementation locally.
- Add your provider to the appropriate [Registry](https://github.com/meta-llama/llama-stack/tree/main/llama_stack/providers/registry/). Specify pip dependencies necessary.
- Update any distribution [Templates](https://github.com/meta-llama/llama-stack/tree/main/llama_stack/distributions/) `build.yaml` and `run.yaml` files if they should include your provider by default. Run [./scripts/distro_codegen.py](https://github.com/meta-llama/llama-stack/blob/main/scripts/distro_codegen.py) if necessary. Note that `distro_codegen.py` will fail if the new provider causes any distribution template to attempt to import provider-specific dependencies. This usually means the distribution's `get_distribution_template()` code path should only import any necessary Config or model alias definitions from each provider and not the provider's actual implementation.
- Update any distribution [Templates](https://github.com/meta-llama/llama-stack/tree/main/llama_stack/distributions/) `build.yaml` and `config.yaml` files if they should include your provider by default. Run [./scripts/distro_codegen.py](https://github.com/meta-llama/llama-stack/blob/main/scripts/distro_codegen.py) if necessary. Note that `distro_codegen.py` will fail if the new provider causes any distribution template to attempt to import provider-specific dependencies. This usually means the distribution's `get_distribution_template()` code path should only import any necessary Config or model alias definitions from each provider and not the provider's actual implementation.
Here are some example PRs to help you get started:

6
docs/docs/deploying/kubernetes_deployment.mdx
View file

@ -133,7 +133,7 @@ For more information about the operator, see the [llama-stack-k8s-operator repos
### Step 4: Deploy Llama Stack Server using Operator
Create a `LlamaStackDistribution` custom resource to deploy the Llama Stack server. The operator will automatically create the necessary Deployment, Service, and other resources.
You can optionally override the default `run.yaml` using `spec.server.userConfig` with a ConfigMap (see [userConfig spec](https://github.com/llamastack/llama-stack-k8s-operator/blob/main/docs/api-overview.md#userconfigspec)).
You can optionally override the default `config.yaml` using `spec.server.userConfig` with a ConfigMap (see [userConfig spec](https://github.com/llamastack/llama-stack-k8s-operator/blob/main/docs/api-overview.md#userconfigspec)).
```yaml
cat <<EOF | kubectl apply -f -
@ -155,7 +155,7 @@ spec:
value: "4096"
- name: VLLM_API_TOKEN
value: "fake"
# Optional: override run.yaml from a ConfigMap using userConfig
# Optional: override config.yaml from a ConfigMap using userConfig
userConfig:
configMap:
name: llama-stack-config
@ -172,7 +172,7 @@ EOF
- `server.distribution.image`: (Optional) Custom container image for non-supported distributions. Use this field when deploying a distribution that is not in the supported list. If specified, this takes precedence over `name`.
- `server.containerSpec.port`: Port on which the Llama Stack server listens (default: 8321)
- `server.containerSpec.env`: Environment variables to configure providers:
- `server.userConfig`: (Optional) Override the default `run.yaml` using a ConfigMap. See [userConfig spec](https://github.com/llamastack/llama-stack-k8s-operator/blob/main/docs/api-overview.md#userconfigspec).
- `server.userConfig`: (Optional) Override the default `config.yaml` using a ConfigMap. See [userConfig spec](https://github.com/llamastack/llama-stack-k8s-operator/blob/main/docs/api-overview.md#userconfigspec).
- `server.storage.size`: Size of the persistent volume for model and data storage
- `server.storage.mountPath`: Where to mount the storage in the container

10
docs/docs/distributions/building_distro.mdx
View file

@ -12,7 +12,7 @@ This guide walks you through inspecting existing distributions, customising thei
All first-party distributions live under `llama_stack/distributions/`. Each directory contains:
- `build.yaml` – the distribution specification (providers, additional dependencies, optional external provider directories).
- `run.yaml` – sample run configuration (when provided).
- `config.yaml` – sample run configuration (when provided).
- Documentation fragments that power this site.
Browse that folder to understand available providers and copy a distribution to use as a starting point. When creating a new stack, duplicate an existing directory, rename it, and adjust the `build.yaml` file to match your requirements.
@ -35,7 +35,7 @@ docker build . \
Handy build arguments:
- `DISTRO_NAME` – distribution directory name (defaults to `starter`).
- `RUN_CONFIG_PATH` – absolute path inside the build context for a run config that should be baked into the image (e.g. `/workspace/run.yaml`).
- `RUN_CONFIG_PATH` – absolute path inside the build context for a run config that should be baked into the image (e.g. `/workspace/config.yaml`).
- `INSTALL_MODE=editable` – install the repository copied into `/workspace` with `uv pip install -e`. Pair it with `--build-arg LLAMA_STACK_DIR=/workspace`.
- `LLAMA_STACK_CLIENT_DIR` – optional editable install of the Python client.
- `PYPI_VERSION` / `TEST_PYPI_VERSION` – pin specific releases when not using editable installs.
@ -50,7 +50,7 @@ External providers live outside the main repository but can be bundled by pointi
1. Copy providers into the build context, for example `cp -R path/to/providers providers.d`.
2. Update `build.yaml` with the directory and provider entries.
3. Adjust run configs to use the in-container path (usually `/.llama/providers.d`). Pass `--build-arg RUN_CONFIG_PATH=/workspace/run.yaml` if you want to bake the config.
3. Adjust run configs to use the in-container path (usually `/.llama/providers.d`). Pass `--build-arg RUN_CONFIG_PATH=/workspace/config.yaml` if you want to bake the config.
Example `build.yaml` excerpt for a custom Ollama provider:
@ -142,7 +142,7 @@ If you prepared a custom run config, mount it into the container and reference i
```bash
docker run \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v $(pwd)/run.yaml:/app/run.yaml \
-v $(pwd)/config.yaml:/app/config.yaml \
llama-stack:starter \
/app/run.yaml
/app/config.yaml
```

4
docs/docs/distributions/configuration.mdx
View file

@ -9,7 +9,7 @@ sidebar_position: 6
The Llama Stack runtime configuration is specified as a YAML file. Here is a simplified version of an example configuration file for the Ollama distribution:
```{note}
The default `run.yaml` files generated by templates are starting points for your configuration. For guidance on customizing these files for your specific needs, see [Customizing Your run.yaml Configuration](customizing_run_yaml.md).
The default `config.yaml` files generated by templates are starting points for your configuration. For guidance on customizing these files for your specific needs, see [Customizing Your config.yaml Configuration](customizing_run_yaml.md).
```
```{dropdown} 👋 Click here for a Sample Configuration File
@ -195,7 +195,7 @@ You can override environment variables at runtime by setting them in your shell
# Set environment variables in your shell
export API_KEY=sk-123
export BASE_URL=https://custom-api.com
llama stack run --config run.yaml
llama stack run --config config.yaml
```
#### Type Safety

18
docs/docs/distributions/customizing_run_yaml.mdx
View file

@ -1,16 +1,16 @@
---
title: Customizing run.yaml
description: Customizing run.yaml files for Llama Stack templates
sidebar_label: Customizing run.yaml
title: Customizing config.yaml
description: Customizing config.yaml files for Llama Stack templates
sidebar_label: Customizing config.yaml
sidebar_position: 4
---
# Customizing run.yaml Files
# Customizing config.yaml Files
The `run.yaml` files generated by Llama Stack templates are **starting points** designed to be customized for your specific needs. They are not meant to be used as-is in production environments.
The `config.yaml` files generated by Llama Stack templates are **starting points** designed to be customized for your specific needs. They are not meant to be used as-is in production environments.
## Key Points
- **Templates are starting points**: Generated `run.yaml` files contain defaults for development/testing
- **Templates are starting points**: Generated `config.yaml` files contain defaults for development/testing
- **Customization expected**: Update URLs, credentials, models, and settings for your environment
- **Version control separately**: Keep customized configs in your own repository
- **Environment-specific**: Create different configurations for dev, staging, production
@ -29,7 +29,7 @@ You can customize:
## Best Practices
- Use environment variables for secrets and environment-specific values
- Create separate `run.yaml` files for different environments (dev, staging, prod)
- Create separate `config.yaml` files for different environments (dev, staging, prod)
- Document your changes with comments
- Test configurations before deployment
- Keep your customized configs in version control
@ -38,8 +38,8 @@ Example structure:
```
your-project/
├── configs/
│ ├── dev-run.yaml
│ ├── prod-run.yaml
│ ├── dev-config.yaml
│ ├── prod-config.yaml
└── README.md
```

2
docs/docs/distributions/importing_as_library.mdx
View file

@ -33,7 +33,7 @@ Then, you can access the APIs like `models` and `inference` on the client and ca
response = client.models.list()
```
If you've created a [custom distribution](./building_distro), you can also use the run.yaml configuration file directly:
If you've created a [custom distribution](./building_distro), you can also use the config.yaml configuration file directly:
```python
client = LlamaStackAsLibraryClient(config_path)

2
docs/docs/distributions/index.mdx
View file

@ -15,7 +15,7 @@ This section provides an overview of the distributions available in Llama Stack.
- **[Available Distributions](./list_of_distributions.mdx)** - Complete list and comparison of all distributions
- **[Building Custom Distributions](./building_distro.mdx)** - Create your own distribution from scratch
- **[Customizing Configuration](./customizing_run_yaml.mdx)** - Customize run.yaml for your needs
- **[Customizing Configuration](./customizing_run_yaml.mdx)** - Customize config.yaml for your needs
- **[Starting Llama Stack Server](./starting_llama_stack_server.mdx)** - How to run distributions
- **[Importing as Library](./importing_as_library.mdx)** - Use distributions in your code
- **[Configuration Reference](./configuration.mdx)** - Configuration file format details

4
docs/docs/distributions/remote_hosted_distro/watsonx.md
View file

@ -67,11 +67,11 @@ LLAMA_STACK_PORT=5001
docker run \
-it \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ./run.yaml:/root/my-run.yaml \
-v ./config.yaml:/root/my-config.yaml \
-e WATSONX_API_KEY=$WATSONX_API_KEY \
-e WATSONX_PROJECT_ID=$WATSONX_PROJECT_ID \
-e WATSONX_BASE_URL=$WATSONX_BASE_URL \
llamastack/distribution-watsonx \
--config /root/my-run.yaml \
--config /root/my-config.yaml \
--port $LLAMA_STACK_PORT
```

6
docs/docs/distributions/self_hosted_distro/dell-tgi.md
View file

@ -29,7 +29,7 @@ The only difference vs. the `tgi` distribution is that it runs the Dell-TGI serv
```
$ cd distributions/dell-tgi/
$ ls
compose.yaml README.md run.yaml
compose.yaml README.md config.yaml
$ docker compose up
```
@ -65,10 +65,10 @@ registry.dell.huggingface.co/enterprise-dell-inference-meta-llama-meta-llama-3.1
#### Start Llama Stack server pointing to TGI server
```
docker run --pull always --network host -it -p 8321:8321 -v ./run.yaml:/root/my-run.yaml --gpus=all llamastack/distribution-tgi --yaml_config /root/my-run.yaml
docker run --pull always --network host -it -p 8321:8321 -v ./config.yaml:/root/my-config.yaml --gpus=all llamastack/distribution-tgi --yaml_config /root/my-config.yaml
```
Make sure in you `run.yaml` file, you inference provider is pointing to the correct TGI server endpoint. E.g.
Make sure in you `config.yaml` file, you inference provider is pointing to the correct TGI server endpoint. E.g.
```
inference:
- provider_id: tgi0

4
docs/docs/distributions/self_hosted_distro/dell.md
View file

@ -152,14 +152,14 @@ docker run \
--pull always \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v $HOME/.llama:/root/.llama \
-v ./llama_stack/distributions/tgi/run-with-safety.yaml:/root/my-run.yaml \
-v ./llama_stack/distributions/tgi/run-with-safety.yaml:/root/my-config.yaml \
-e INFERENCE_MODEL=$INFERENCE_MODEL \
-e DEH_URL=$DEH_URL \
-e SAFETY_MODEL=$SAFETY_MODEL \
-e DEH_SAFETY_URL=$DEH_SAFETY_URL \
-e CHROMA_URL=$CHROMA_URL \
llamastack/distribution-dell \
--config /root/my-run.yaml \
--config /root/my-config.yaml \
--port $LLAMA_STACK_PORT
```

12
docs/docs/distributions/self_hosted_distro/meta-reference-gpu.md
View file

@ -84,8 +84,8 @@ docker run \
You can also run the Docker container with a custom run configuration file by mounting it into the container:
```bash
# Set the path to your custom run.yaml file
CUSTOM_RUN_CONFIG=/path/to/your/custom-run.yaml
# Set the path to your custom config.yaml file
CUSTOM_RUN_CONFIG=/path/to/your/custom-config.yaml
LLAMA_STACK_PORT=8321
docker run \
@ -94,8 +94,8 @@ docker run \
--gpu all \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
-v $CUSTOM_RUN_CONFIG:/app/custom-run.yaml \
-e RUN_CONFIG_PATH=/app/custom-run.yaml \
-v $CUSTOM_RUN_CONFIG:/app/custom-config.yaml \
-e RUN_CONFIG_PATH=/app/custom-config.yaml \
llamastack/distribution-meta-reference-gpu \
--port $LLAMA_STACK_PORT
```
@ -103,7 +103,7 @@ docker run \
**Note**: The run configuration must be mounted into the container before it can be used. The `-v` flag mounts your local file into the container, and the `RUN_CONFIG_PATH` environment variable tells the entrypoint script which configuration to use.
Available run configurations for this distribution:
- `run.yaml`
- `config.yaml`
- `run-with-safety.yaml`
### Via venv
@ -113,7 +113,7 @@ Make sure you have the Llama Stack CLI available.
```bash
llama stack list-deps meta-reference-gpu | xargs -L1 uv pip install
INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
llama stack run distributions/meta-reference-gpu/run.yaml \
llama stack run distributions/meta-reference-gpu/config.yaml \
--port 8321
```

12
docs/docs/distributions/self_hosted_distro/nvidia.md
View file

@ -138,8 +138,8 @@ docker run \
You can also run the Docker container with a custom run configuration file by mounting it into the container:
```bash
# Set the path to your custom run.yaml file
CUSTOM_RUN_CONFIG=/path/to/your/custom-run.yaml
# Set the path to your custom config.yaml file
CUSTOM_RUN_CONFIG=/path/to/your/custom-config.yaml
LLAMA_STACK_PORT=8321
docker run \
@ -147,8 +147,8 @@ docker run \
--pull always \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
-v $CUSTOM_RUN_CONFIG:/app/custom-run.yaml \
-e RUN_CONFIG_PATH=/app/custom-run.yaml \
-v $CUSTOM_RUN_CONFIG:/app/custom-config.yaml \
-e RUN_CONFIG_PATH=/app/custom-config.yaml \
-e NVIDIA_API_KEY=$NVIDIA_API_KEY \
llamastack/distribution-nvidia \
--port $LLAMA_STACK_PORT
@ -157,7 +157,7 @@ docker run \
**Note**: The run configuration must be mounted into the container before it can be used. The `-v` flag mounts your local file into the container, and the `RUN_CONFIG_PATH` environment variable tells the entrypoint script which configuration to use.
Available run configurations for this distribution:
- `run.yaml`
- `config.yaml`
- `run-with-safety.yaml`
### Via venv
@ -169,7 +169,7 @@ INFERENCE_MODEL=meta-llama/Llama-3.1-8B-Instruct
llama stack list-deps nvidia | xargs -L1 uv pip install
NVIDIA_API_KEY=$NVIDIA_API_KEY \
INFERENCE_MODEL=$INFERENCE_MODEL \
llama stack run ./run.yaml \
llama stack run ./config.yaml \
--port 8321
```

2
docs/docs/getting_started/detailed_tutorial.mdx
View file

@ -98,7 +98,7 @@ Note to start the container with Podman, you can do the same but replace `docker
`podman`. If you are using `podman` older than `4.7.0`, please also replace `host.docker.internal` in the `OLLAMA_URL`
with `host.containers.internal`.
The configuration YAML for the Ollama distribution is available at `distributions/ollama/run.yaml`.
The configuration YAML for the Ollama distribution is available at `distributions/ollama/config.yaml`.
:::tip
Docker containers run in their own isolated network namespaces on Linux. To allow the container to communicate with services running on the host via `localhost`, you need `--network=host`. This makes the container use the host's network directly so it can connect to Ollama running on `localhost:11434`.

2
docs/docs/providers/external/external-providers-guide.mdx vendored
View file

@ -222,7 +222,7 @@ def get_provider_spec() -> ProviderSpec:
[ramalama-stack](https://github.com/containers/ramalama-stack) is a recognized external provider that supports installation via module.
To install Llama Stack with this external provider a user can provider the following run.yaml:
To install Llama Stack with this external provider a user can provider the following config.yaml:
```yaml
version: 2

2
docs/docs/providers/files/openai_file_operations_quick_reference.md
View file

@ -51,7 +51,7 @@ results = await client.vector_stores.search(
> **Note**: For detailed configuration examples and options, see [Configuration Examples](../openai_file_operations_support.md#configuration-examples) in the full documentation.
**Basic Setup**: Configure vector_io and files providers in your run.yaml
**Basic Setup**: Configure vector_io and files providers in your config.yaml
## Common Use Cases

4
docs/docs/providers/openai_responses_limitations.mdx
View file

@ -123,7 +123,7 @@ Connectors are MCP servers maintained and managed by the Responses API provider.
**Open Questions:**
- Should Llama Stack include built-in support for some, all, or none of OpenAI's connectors?
- Should there be a mechanism for administrators to add custom connectors via `run.yaml` or an API?
- Should there be a mechanism for administrators to add custom connectors via `config.yaml` or an API?
---
@ -210,7 +210,7 @@ Metadata allows you to attach additional information to a response for your own
**Status:** Feature Request
When calling the OpenAI Responses API, model outputs go through safety models configured by OpenAI administrators. Perhaps Llama Stack should provide a mechanism to configure safety models (or non-model logic) for all Responses requests, either through `run.yaml` or an administrative API.
When calling the OpenAI Responses API, model outputs go through safety models configured by OpenAI administrators. Perhaps Llama Stack should provide a mechanism to configure safety models (or non-model logic) for all Responses requests, either through `config.yaml` or an administrative API.
---

4
docs/docs/references/evals_reference/index.mdx
View file

@ -355,7 +355,7 @@ The purpose of scoring function is to calculate the score for each example based
Firstly, you can see if the existing [llama stack scoring functions](https://github.com/meta-llama/llama-stack/tree/main/llama_stack/providers/inline/scoring) can fulfill your need. If not, you need to write a new scoring function based on what benchmark author / other open source repo describe.
### Add new benchmark into template
Firstly, you need to add the evaluation dataset associated with your benchmark under `datasets` resource in the [open-benchmark](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/distributions/open-benchmark/run.yaml)
Firstly, you need to add the evaluation dataset associated with your benchmark under `datasets` resource in the [open-benchmark](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/distributions/open-benchmark/config.yaml)
Secondly, you need to add the new benchmark you just created under the `benchmarks` resource in the same template. To add the new benchmark, you need to have
- `benchmark_id`: identifier of the benchmark
@ -366,7 +366,7 @@ Secondly, you need to add the new benchmark you just created under the `benchmar
Spin up llama stack server with 'open-benchmark' templates
```bash
llama stack run llama_stack/distributions/open-benchmark/run.yaml
llama stack run llama_stack/distributions/open-benchmark/config.yaml
```
Run eval benchmark CLI with your new benchmark id

8
src/llama_stack/cli/stack/list_stacks.py
View file

@ -64,14 +64,14 @@ class StackListBuilds(Subcommand):
for name, (path, source_type) in sorted(distributions.items()):
row = [name, source_type, str(path)]
# Check for build and run config files
# For built-in distributions, configs are named build.yaml and run.yaml
# For custom distributions, configs are named {name}-build.yaml and {name}-run.yaml
# For built-in distributions, configs are named build.yaml and config.yaml
# For custom distributions, configs are named {name}-build.yaml and {name}-config.yaml
if source_type == "built-in":
build_config = "Yes" if (path / "build.yaml").exists() else "No"
run_config = "Yes" if (path / "run.yaml").exists() else "No"
run_config = "Yes" if (path / "config.yaml").exists() else "No"
else:
build_config = "Yes" if (path / f"{name}-build.yaml").exists() else "No"
run_config = "Yes" if (path / f"{name}-run.yaml").exists() else "No"
run_config = "Yes" if (path / f"{name}-config.yaml").exists() else "No"
row.extend([build_config, run_config])
rows.append(row)
print_table(rows, headers, separate_rows=True)

6
src/llama_stack/cli/stack/utils.py
View file

@ -57,7 +57,7 @@ def generate_run_config(
image_name: str,
) -> Path:
"""
Generate a run.yaml template file for user to edit from a build.yaml file
Generate a config.yaml template file for user to edit from a build.yaml file
"""
apis = list(build_config.distribution_spec.providers.keys())
distro_dir = DISTRIBS_BASE_DIR / image_name
@ -123,7 +123,7 @@ def generate_run_config(
)
run_config.providers[api].append(p_spec)
run_config_file = build_dir / f"{image_name}-run.yaml"
run_config_file = build_dir / f"{image_name}-config.yaml"
with open(run_config_file, "w") as f:
to_write = json.loads(run_config.model_dump_json())
@ -131,7 +131,7 @@ def generate_run_config(
# Only print this message for non-container builds since it will be displayed before the
# container is built
# For non-container builds, the run.yaml is generated at the very end of the build process so it
# For non-container builds, the config.yaml is generated at the very end of the build process so it
# makes sense to display this message
if build_config.image_type != LlamaStackImageType.CONTAINER.value:
cprint(f"You can now run your stack with `llama stack run {run_config_file}`", color="green", file=sys.stderr)

2
src/llama_stack/core/routers/__init__.py
View file

@ -9,8 +9,8 @@ from typing import Any
from llama_stack.core.datatypes import (
AccessRule,
RoutedProtocol,
StackConfig,
)
from llama_stack.core.datatypes import StackConfig
from llama_stack.core.store import DistributionRegistry
from llama_stack.providers.utils.inference.inference_store import InferenceStore
from llama_stack_api import Api, RoutingTable

2
src/llama_stack/core/routing_tables/models.py
View file

@ -224,7 +224,7 @@ class ModelsRoutingTable(CommonRoutingTableImpl, Models):
existing_models = await self.get_all_with_type("model")
# we may have an alias for the model registered by the user (or during initialization
# from run.yaml) that we need to keep track of
# from config.yaml) that we need to keep track of
model_ids = {}
for model in existing_models:
if model.provider_id != provider_id:

2
src/llama_stack/core/stack.py
View file

@ -500,7 +500,7 @@ async def refresh_registry_task(impls: dict[Api, Any]):
def get_stack_run_config_from_distro(distro: str) -> StackConfig:
distro_path = importlib.resources.files("llama_stack") / f"distributions/{distro}/run.yaml"
distro_path = importlib.resources.files("llama_stack") / f"distributions/{distro}/config.yaml"
with importlib.resources.as_file(distro_path) as path:
if not path.exists():

0
src/llama_stack/distributions/ci-tests/run.yaml → src/llama_stack/distributions/ci-tests/config.yaml
View file

0
src/llama_stack/distributions/dell/run.yaml → src/llama_stack/distributions/dell/config.yaml
View file

2
src/llama_stack/distributions/dell/dell.py
View file

@ -111,7 +111,7 @@ def get_distribution_template() -> DistributionTemplate:
container_image=None,
providers=providers,
run_configs={
"run.yaml": RunConfigSettings(
"config.yaml": RunConfigSettings(
provider_overrides={
"inference": [inference_provider, embedding_provider],
"vector_io": [chromadb_provider],

12
src/llama_stack/distributions/dell/doc_template.md
View file

@ -141,14 +141,14 @@ docker run \
--pull always \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v $HOME/.llama:/root/.llama \
-v ./llama_stack/distributions/tgi/run-with-safety.yaml:/root/my-run.yaml \
-v ./llama_stack/distributions/tgi/run-with-safety.yaml:/root/my-config.yaml \
-e INFERENCE_MODEL=$INFERENCE_MODEL \
-e DEH_URL=$DEH_URL \
-e SAFETY_MODEL=$SAFETY_MODEL \
-e DEH_SAFETY_URL=$DEH_SAFETY_URL \
-e CHROMA_URL=$CHROMA_URL \
llamastack/distribution-{{ name }} \
--config /root/my-run.yaml \
--config /root/my-config.yaml \
--port $LLAMA_STACK_PORT
```
@ -157,16 +157,16 @@ docker run \
You can also run the Docker container with a custom run configuration file by mounting it into the container:
```bash
# Set the path to your custom run.yaml file
CUSTOM_RUN_CONFIG=/path/to/your/custom-run.yaml
# Set the path to your custom config.yaml file
CUSTOM_RUN_CONFIG=/path/to/your/custom-config.yaml
docker run -it \
--pull always \
--network host \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v $HOME/.llama:/root/.llama \
-v $CUSTOM_RUN_CONFIG:/app/custom-run.yaml \
-e RUN_CONFIG_PATH=/app/custom-run.yaml \
-v $CUSTOM_RUN_CONFIG:/app/custom-config.yaml \
-e RUN_CONFIG_PATH=/app/custom-config.yaml \
-e INFERENCE_MODEL=$INFERENCE_MODEL \
-e DEH_URL=$DEH_URL \
-e CHROMA_URL=$CHROMA_URL \

0
src/llama_stack/distributions/meta-reference-gpu/run.yaml → src/llama_stack/distributions/meta-reference-gpu/config.yaml
View file

10
src/llama_stack/distributions/meta-reference-gpu/doc_template.md
View file

@ -73,8 +73,8 @@ docker run \
You can also run the Docker container with a custom run configuration file by mounting it into the container:
```bash
# Set the path to your custom run.yaml file
CUSTOM_RUN_CONFIG=/path/to/your/custom-run.yaml
# Set the path to your custom config.yaml file
CUSTOM_RUN_CONFIG=/path/to/your/custom-config.yaml
LLAMA_STACK_PORT=8321
docker run \
@ -83,8 +83,8 @@ docker run \
--gpu all \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
-v $CUSTOM_RUN_CONFIG:/app/custom-run.yaml \
-e RUN_CONFIG_PATH=/app/custom-run.yaml \
-v $CUSTOM_RUN_CONFIG:/app/custom-config.yaml \
-e RUN_CONFIG_PATH=/app/custom-config.yaml \
llamastack/distribution-{{ name }} \
--port $LLAMA_STACK_PORT
```
@ -105,7 +105,7 @@ Make sure you have the Llama Stack CLI available.
```bash
llama stack list-deps meta-reference-gpu | xargs -L1 uv pip install
INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
llama stack run distributions/{{ name }}/run.yaml \
llama stack run distributions/{{ name }}/config.yaml \
--port 8321
```

2
src/llama_stack/distributions/meta-reference-gpu/meta_reference.py
View file

@ -105,7 +105,7 @@ def get_distribution_template() -> DistributionTemplate:
template_path=Path(__file__).parent / "doc_template.md",
providers=providers,
run_configs={
"run.yaml": RunConfigSettings(
"config.yaml": RunConfigSettings(
provider_overrides={
"inference": [inference_provider, embedding_provider],
"vector_io": [vector_io_provider],

0
src/llama_stack/distributions/nvidia/run.yaml → src/llama_stack/distributions/nvidia/config.yaml
View file

10
src/llama_stack/distributions/nvidia/doc_template.md
View file

@ -128,8 +128,8 @@ docker run \
You can also run the Docker container with a custom run configuration file by mounting it into the container:
```bash
# Set the path to your custom run.yaml file
CUSTOM_RUN_CONFIG=/path/to/your/custom-run.yaml
# Set the path to your custom config.yaml file
CUSTOM_RUN_CONFIG=/path/to/your/custom-config.yaml
LLAMA_STACK_PORT=8321
docker run \
@ -137,8 +137,8 @@ docker run \
--pull always \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
-v $CUSTOM_RUN_CONFIG:/app/custom-run.yaml \
-e RUN_CONFIG_PATH=/app/custom-run.yaml \
-v $CUSTOM_RUN_CONFIG:/app/custom-config.yaml \
-e RUN_CONFIG_PATH=/app/custom-config.yaml \
-e NVIDIA_API_KEY=$NVIDIA_API_KEY \
llamastack/distribution-{{ name }} \
--port $LLAMA_STACK_PORT
@ -162,7 +162,7 @@ INFERENCE_MODEL=meta-llama/Llama-3.1-8B-Instruct
llama stack list-deps nvidia | xargs -L1 uv pip install
NVIDIA_API_KEY=$NVIDIA_API_KEY \
INFERENCE_MODEL=$INFERENCE_MODEL \
llama stack run ./run.yaml \
llama stack run ./config.yaml \
--port 8321
```

2
src/llama_stack/distributions/nvidia/nvidia.py
View file

@ -81,7 +81,7 @@ def get_distribution_template(name: str = "nvidia") -> DistributionTemplate:
template_path=Path(__file__).parent / "doc_template.md",
providers=providers,
run_configs={
"run.yaml": RunConfigSettings(
"config.yaml": RunConfigSettings(
provider_overrides={
"inference": [inference_provider],
"datasetio": [datasetio_provider],

0
src/llama_stack/distributions/oci/run.yaml → src/llama_stack/distributions/oci/config.yaml
View file

2
src/llama_stack/distributions/oci/oci.py
View file

@ -74,7 +74,7 @@ def get_distribution_template(name: str = "oci") -> DistributionTemplate:
template_path=Path(__file__).parent / "doc_template.md",
providers=providers,
run_configs={
"run.yaml": RunConfigSettings(
"config.yaml": RunConfigSettings(
provider_overrides={
"inference": [inference_provider],
"vector_io": [vector_io_provider],

0
src/llama_stack/distributions/open-benchmark/run.yaml → src/llama_stack/distributions/open-benchmark/config.yaml
View file

2
src/llama_stack/distributions/open-benchmark/open_benchmark.py
View file

@ -261,7 +261,7 @@ def get_distribution_template() -> DistributionTemplate:
providers=providers,
available_models_by_provider=available_models,
run_configs={
"run.yaml": RunConfigSettings(
"config.yaml": RunConfigSettings(
provider_overrides={
"inference": inference_providers,
"vector_io": vector_io_providers,

0
src/llama_stack/distributions/postgres-demo/run.yaml → src/llama_stack/distributions/postgres-demo/config.yaml
View file

0
src/llama_stack/distributions/starter-gpu/run.yaml → src/llama_stack/distributions/starter-gpu/config.yaml
View file

0
src/llama_stack/distributions/starter/run.yaml → src/llama_stack/distributions/starter/config.yaml
View file

2
src/llama_stack/distributions/starter/starter.py
View file

@ -276,7 +276,7 @@ def get_distribution_template(name: str = "starter") -> DistributionTemplate:
template_path=None,
providers=providers,
run_configs={
"run.yaml": base_run_settings,
"config.yaml": base_run_settings,
"run-with-postgres-store.yaml": postgres_run_settings,
},
run_config_env_vars={

0
src/llama_stack/distributions/watsonx/run.yaml → src/llama_stack/distributions/watsonx/config.yaml
View file

2
src/llama_stack/distributions/watsonx/watsonx.py
View file

@ -69,7 +69,7 @@ def get_distribution_template(name: str = "watsonx") -> DistributionTemplate:
template_path=None,
providers=providers,
run_configs={
"run.yaml": RunConfigSettings(
"config.yaml": RunConfigSettings(
provider_overrides={
"inference": [inference_provider],
"files": [files_provider],

4
src/llama_stack/log.py
View file

@ -92,10 +92,10 @@ def config_to_category_levels(category: str, level: str):
def parse_yaml_config(yaml_config: LoggingConfig) -> dict[str, int]:
"""
Helper function to parse a yaml logging configuration found in the run.yaml
Helper function to parse a yaml logging configuration found in the config.yaml
Parameters:
yaml_config (Logging): the logger config object found in the run.yaml
yaml_config (Logging): the logger config object found in the config.yaml
Returns:
Dict[str, int]: A dictionary mapping categories to their log levels.

2
src/llama_stack/providers/inline/inference/meta_reference/config.py
View file

@ -16,7 +16,7 @@ class MetaReferenceInferenceConfig(BaseModel):
# this is a placeholder to indicate inference model id
# the actual inference model id is dtermined by the moddel id in the request
# Note: you need to register the model before using it for inference
# models in the resouce list in the run.yaml config will be registered automatically
# models in the resouce list in the config.yaml config will be registered automatically
model: str | None = None
torch_seed: int | None = None
max_seq_len: int = 4096

4
src/llama_stack/providers/remote/inference/tgi/tgi.py
View file

@ -51,7 +51,9 @@ class _HfAdapter(OpenAIMixin):
class TGIAdapter(_HfAdapter):
async def initialize(self, config: TGIImplConfig) -> None:
if not config.base_url:
raise ValueError("You must provide a URL in run.yaml (or via the TGI_URL environment variable) to use TGI.")
raise ValueError(
"You must provide a URL in config.yaml (or via the TGI_URL environment variable) to use TGI."
)
log.info(f"Initializing TGI client with url={config.base_url}")
# Extract base URL without /v1 for HF client initialization
base_url_str = str(config.base_url).rstrip("/")

2
src/llama_stack/providers/remote/inference/vllm/vllm.py
View file

@ -46,7 +46,7 @@ class VLLMInferenceAdapter(OpenAIMixin):
async def initialize(self) -> None:
if not self.config.base_url:
raise ValueError(
"You must provide a URL in run.yaml (or via the VLLM_URL environment variable) to use vLLM."
"You must provide a URL in config.yaml (or via the VLLM_URL environment variable) to use vLLM."
)
async def health(self) -> HealthResponse:

2
tests/README.md
View file

@ -35,7 +35,7 @@ For running integration tests, you must provide a few things:
- **`server:<config>`** - automatically start a server with the given config (e.g., `server:starter`). This provides one-step testing by auto-starting the server if the port is available, or reusing an existing server if already running.
- **`server:<config>:<port>`** - same as above but with a custom port (e.g., `server:starter:8322`)
- a URL which points to a Llama Stack distribution server
- a distribution name (e.g., `starter`) or a path to a `run.yaml` file
- a distribution name (e.g., `starter`) or a path to a `config.yaml` file
- a comma-separated list of api=provider pairs, e.g. `inference=fireworks,safety=llama-guard,agents=meta-reference`. This is most useful for testing a single API surface.
- Any API keys you need to use should be set in the environment, or can be passed in with the --env option.

8
tests/backward_compat/test_run_config.py
View file

@ -5,10 +5,10 @@
# the root directory of this source tree.
"""
Backward compatibility test for run.yaml files.
Backward compatibility test for config.yaml files.
This test ensures that changes to StackRunConfig don't break
existing run.yaml files from previous versions.
existing config.yaml files from previous versions.
"""
import os
@ -36,10 +36,10 @@ def get_test_configs():
else:
# Local mode: test current distribution configs
repo_root = Path(__file__).parent.parent.parent
config_files = sorted((repo_root / "src" / "llama_stack" / "distributions").glob("*/run.yaml"))
config_files = sorted((repo_root / "src" / "llama_stack" / "distributions").glob("*/config.yaml"))
if not config_files:
pytest.skip("No run.yaml files found in distributions/")
pytest.skip("No config.yaml files found in distributions/")
return config_files

2
tests/integration/README.md
View file

@ -25,7 +25,7 @@ Here are the most important options:
- **`server:<config>`** - automatically start a server with the given config (e.g., `server:starter`). This provides one-step testing by auto-starting the server if the port is available, or reusing an existing server if already running.
- **`server:<config>:<port>`** - same as above but with a custom port (e.g., `server:starter:8322`)
- a URL which points to a Llama Stack distribution server
- a distribution name (e.g., `starter`) or a path to a `run.yaml` file
- a distribution name (e.g., `starter`) or a path to a `config.yaml` file
- a comma-separated list of api=provider pairs, e.g. `inference=ollama,safety=llama-guard,agents=meta-reference`. This is most useful for testing a single API surface.
- `--env`: set environment variables, e.g. --env KEY=value. this is a utility option to set environment variables required by various providers.

2
tests/integration/conftest.py
View file

@ -151,7 +151,7 @@ def pytest_addoption(parser):
"""
a 'pointer' to the stack. this can be either be:
(a) a template name like `starter`, or
(b) a path to a run.yaml file, or
(b) a path to a config.yaml file, or
(c) an adhoc config spec, e.g. `inference=fireworks,safety=llama-guard,agents=meta-reference`, or
(d) a server config like `server:ci-tests`, or
(e) a docker config like `docker:ci-tests` (builds and runs container)

4
tests/integration/test_persistence_integration.py
View file

@ -17,7 +17,7 @@ from llama_stack.core.storage.datatypes import (
def test_starter_distribution_config_loads_and_resolves():
"""Integration: Actual starter config should parse and have correct storage structure."""
with open("llama_stack/distributions/starter/run.yaml") as f:
with open("llama_stack/distributions/starter/config.yaml") as f:
config_dict = yaml.safe_load(f)
config = StackConfig(**config_dict)
@ -47,7 +47,7 @@ def test_starter_distribution_config_loads_and_resolves():
def test_postgres_demo_distribution_config_loads():
"""Integration: Postgres demo should use Postgres backend for all stores."""
with open("llama_stack/distributions/postgres-demo/run.yaml") as f:
with open("llama_stack/distributions/postgres-demo/config.yaml") as f:
config_dict = yaml.safe_load(f)
config = StackConfig(**config_dict)

2
tests/unit/cli/test_stack_config.py
View file

@ -302,7 +302,7 @@ def test_providers_flag_generates_config_with_api_keys():
# Read the generated config file
from llama_stack.core.utils.config_dirs import DISTRIBS_BASE_DIR
config_file = DISTRIBS_BASE_DIR / "providers-run" / "run.yaml"
config_file = DISTRIBS_BASE_DIR / "providers-run" / "config.yaml"
with open(config_file) as f:
config_dict = yaml.safe_load(f)

4
tests/unit/distribution/test_stack_list.py
View file

@ -32,7 +32,7 @@ def mock_distribs_base_dir(tmp_path):
starter_custom = custom_dir / "starter"
starter_custom.mkdir()
(starter_custom / "starter-build.yaml").write_text("# build config")
(starter_custom / "starter-run.yaml").write_text("# run config")
(starter_custom / "starter-config.yaml").write_text("# run config")
return custom_dir
@ -48,7 +48,7 @@ def mock_distro_dir(tmp_path):
distro_path = distro_dir / distro_name
distro_path.mkdir()
(distro_path / "build.yaml").write_text("# build config")
(distro_path / "run.yaml").write_text("# run config")
(distro_path / "config.yaml").write_text("# run config")
return distro_dir