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[run]
omit =
*/tests/*
*/llama_stack/providers/*
*/llama_stack/templates/*
.venv/*
*/llama_stack/cli/scripts/*
*/llama_stack/ui/*
*/llama_stack/distribution/ui/*
*/llama_stack/strong_typing/*
*/llama_stack/env.py
*/__init__.py

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.github/CODEOWNERS vendored
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# These owners will be the default owners for everything in
# the repo. Unless a later match takes precedence,
* @ashwinb @yanxi0830 @hardikjshah @raghotham @ehhuang @terrytangyuan @leseb @bbrowning @reluctantfuturist @mattf @slekkala1
* @ashwinb @yanxi0830 @hardikjshah @dltn @raghotham @dineshyv @vladimirivic @sixianyi0721 @ehhuang @terrytangyuan

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name: 🔧 Tech Debt
description: Something that is functional but should be improved or optimizied
labels: ["tech-debt"]
body:
- type: textarea
id: tech-debt-explanation
attributes:
label: 🤔 What is the technical debt you think should be addressed?
description: >
A clear and concise description of _what_ needs to be addressed - ensure you are describing
constitutes [technical debt](https://en.wikipedia.org/wiki/Technical_debt) and is not a bug
or feature request.
validations:
required: true
- type: textarea
id: tech-debt-motivation
attributes:
label: 💡 What is the benefit of addressing this technical debt?
description: >
A clear and concise description of _why_ this work is needed.
validations:
required: true
- type: textarea
id: other-thoughts
attributes:
label: Other thoughts
description: >
Any thoughts about how this may result in complexity in the codebase, or other trade-offs.

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# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to relevant issues if applicable. -->
[Provide a short summary of what this PR does and why. Link to relevant issues if applicable.]
<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->
[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])
## Test Plan
<!-- Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.* -->
[Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.*]
[//]: # (## Documentation)

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.github/TRIAGERS.md vendored
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# This file documents Triage members in the Llama Stack community
@franciscojavierarceo

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name: 'Run and Record Tests'
description: 'Run integration tests and handle recording/artifact upload'
inputs:
test-subdirs:
description: 'Comma-separated list of test subdirectories to run'
required: true
test-pattern:
description: 'Regex pattern to pass to pytest -k'
required: false
default: ''
stack-config:
description: 'Stack configuration to use'
required: true
provider:
description: 'Provider to use for tests'
required: true
inference-mode:
description: 'Inference mode (record or replay)'
required: true
run-vision-tests:
description: 'Whether to run vision tests'
required: false
default: 'false'
runs:
using: 'composite'
steps:
- name: Check Storage and Memory Available Before Tests
if: ${{ always() }}
shell: bash
run: |
free -h
df -h
- name: Run Integration Tests
shell: bash
run: |
uv run --no-sync ./scripts/integration-tests.sh \
--stack-config '${{ inputs.stack-config }}' \
--provider '${{ inputs.provider }}' \
--test-subdirs '${{ inputs.test-subdirs }}' \
--test-pattern '${{ inputs.test-pattern }}' \
--inference-mode '${{ inputs.inference-mode }}' \
${{ inputs.run-vision-tests == 'true' && '--run-vision-tests' || '' }} \
| tee pytest-${{ inputs.inference-mode }}.log
- name: Commit and push recordings
if: ${{ inputs.inference-mode == 'record' }}
shell: bash
run: |
echo "Checking for recording changes"
git status --porcelain tests/integration/recordings/
if [[ -n $(git status --porcelain tests/integration/recordings/) ]]; then
echo "New recordings detected, committing and pushing"
git add tests/integration/recordings/
if [ "${{ inputs.run-vision-tests }}" == "true" ]; then
git commit -m "Recordings update from CI (vision)"
else
git commit -m "Recordings update from CI"
fi
git fetch origin ${{ github.ref_name }}
git rebase origin/${{ github.ref_name }}
echo "Rebased successfully"
git push origin HEAD:${{ github.ref_name }}
echo "Pushed successfully"
else
echo "No recording changes"
fi
- name: Write inference logs to file
if: ${{ always() }}
shell: bash
run: |
sudo docker logs ollama > ollama-${{ inputs.inference-mode }}.log || true
- name: Upload logs
if: ${{ always() }}
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
with:
name: logs-${{ github.run_id }}-${{ github.run_attempt || '' }}-${{ strategy.job-index }}
path: |
*.log
retention-days: 1

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name: Setup Ollama
description: Start Ollama
inputs:
run-vision-tests:
description: 'Run vision tests: "true" or "false"'
required: false
default: 'false'
runs:
using: "composite"
steps:
- name: Start Ollama
shell: bash
run: |
if [ "${{ inputs.run-vision-tests }}" == "true" ]; then
image="ollama-with-vision-model"
else
image="ollama-with-models"
fi
echo "Starting Ollama with image: $image"
docker run -d --name ollama -p 11434:11434 docker.io/llamastack/$image
echo "Verifying Ollama status..."
timeout 30 bash -c 'while ! curl -s -L http://127.0.0.1:11434; do sleep 1 && echo "."; done'

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name: Setup runner
description: Prepare a runner for the tests (install uv, python, project dependencies, etc.)
inputs:
python-version:
description: The Python version to use
required: false
default: "3.12"
client-version:
description: The llama-stack-client-python version to test against (latest or published)
required: false
default: "latest"
runs:
using: "composite"
steps:
- name: Install uv
uses: astral-sh/setup-uv@6b9c6063abd6010835644d4c2e1bef4cf5cd0fca # v6.0.1
with:
python-version: ${{ inputs.python-version }}
version: 0.7.6
- name: Install dependencies
shell: bash
run: |
echo "Updating project dependencies via uv sync"
uv sync --all-groups
echo "Installing ad-hoc dependencies"
uv pip install faiss-cpu
# Install llama-stack-client-python based on the client-version input
if [ "${{ inputs.client-version }}" = "latest" ]; then
echo "Installing latest llama-stack-client-python from main branch"
uv pip install git+https://github.com/llamastack/llama-stack-client-python.git@main
elif [ "${{ inputs.client-version }}" = "published" ]; then
echo "Installing published llama-stack-client-python from PyPI"
uv pip install llama-stack-client
else
echo "Invalid client-version: ${{ inputs.client-version }}"
exit 1
fi
echo "Installed llama packages"
uv pip list | grep llama

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name: 'Setup Test Environment'
description: 'Common setup steps for integration tests including dependencies, providers, and build'
inputs:
python-version:
description: 'Python version to use'
required: true
client-version:
description: 'Client version (latest or published)'
required: true
provider:
description: 'Provider to setup (ollama or vllm)'
required: true
default: 'ollama'
run-vision-tests:
description: 'Whether to setup provider for vision tests'
required: false
default: 'false'
inference-mode:
description: 'Inference mode (record or replay)'
required: true
runs:
using: 'composite'
steps:
- name: Install dependencies
uses: ./.github/actions/setup-runner
with:
python-version: ${{ inputs.python-version }}
client-version: ${{ inputs.client-version }}
- name: Setup ollama
if: ${{ inputs.provider == 'ollama' && inputs.inference-mode == 'record' }}
uses: ./.github/actions/setup-ollama
with:
run-vision-tests: ${{ inputs.run-vision-tests }}
- name: Setup vllm
if: ${{ inputs.provider == 'vllm' && inputs.inference-mode == 'record' }}
uses: ./.github/actions/setup-vllm
- name: Build Llama Stack
shell: bash
run: |
# Install llama-stack-client-python based on the client-version input
if [ "${{ inputs.client-version }}" = "latest" ]; then
echo "Installing latest llama-stack-client-python from main branch"
export LLAMA_STACK_CLIENT_DIR=git+https://github.com/llamastack/llama-stack-client-python.git@main
elif [ "${{ inputs.client-version }}" = "published" ]; then
echo "Installing published llama-stack-client-python from PyPI"
unset LLAMA_STACK_CLIENT_DIR
else
echo "Invalid client-version: ${{ inputs.client-version }}"
exit 1
fi
echo "Building Llama Stack"
LLAMA_STACK_DIR=. \
uv run --no-sync llama stack build --template ci-tests --image-type venv
- name: Configure git for commits
shell: bash
run: |
git config --local user.email "github-actions[bot]@users.noreply.github.com"
git config --local user.name "github-actions[bot]"

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name: Setup VLLM
description: Start VLLM
runs:
using: "composite"
steps:
- name: Start VLLM
shell: bash
run: |
# Start vllm container
docker run -d \
--name vllm \
-p 8000:8000 \
--privileged=true \
quay.io/higginsd/vllm-cpu:65393ee064 \
--host 0.0.0.0 \
--port 8000 \
--enable-auto-tool-choice \
--tool-call-parser llama3_json \
--model /root/.cache/Llama-3.2-1B-Instruct \
--served-model-name meta-llama/Llama-3.2-1B-Instruct
# Wait for vllm to be ready
echo "Waiting for vllm to be ready..."
timeout 900 bash -c 'until curl -f http://localhost:8000/health; do
echo "Waiting for vllm..."
sleep 5
done'

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# GitHub Dependabot configuration
version: 2
updates:
# Enable version updates for GitHub Actions
- package-ecosystem: "github-actions"
directory: "/" # Will use the default workflow location of `.github/workflows`
schedule:
interval: "weekly"
day: "saturday"
commit-message:
prefix: chore(github-deps)
- package-ecosystem: "uv"
directory: "/"
schedule:
interval: "weekly"
day: "saturday"
labels:
- type/dependencies
- python
commit-message:
prefix: chore(python-deps)
- package-ecosystem: npm
directory: "/llama_stack/ui"
schedule:
interval: "weekly"
day: "saturday"
labels:
- type/dependencies
- javascript
commit-message:
prefix: chore(ui-deps)

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# Llama Stack CI
Llama Stack uses GitHub Actions for Continuous Integration (CI). Below is a table detailing what CI the project includes and the purpose.
| Name | File | Purpose |
| ---- | ---- | ------- |
| Update Changelog | [changelog.yml](changelog.yml) | Creates PR for updating the CHANGELOG.md |
| Installer CI | [install-script-ci.yml](install-script-ci.yml) | Test the installation script |
| Integration Auth Tests | [integration-auth-tests.yml](integration-auth-tests.yml) | Run the integration test suite with Kubernetes authentication |
| SqlStore Integration Tests | [integration-sql-store-tests.yml](integration-sql-store-tests.yml) | Run the integration test suite with SqlStore |
| Integration Tests (Replay) | [integration-tests.yml](integration-tests.yml) | Run the integration test suite from tests/integration in replay mode |
| Vector IO Integration Tests | [integration-vector-io-tests.yml](integration-vector-io-tests.yml) | Run the integration test suite with various VectorIO providers |
| Pre-commit | [pre-commit.yml](pre-commit.yml) | Run pre-commit checks |
| Test Llama Stack Build | [providers-build.yml](providers-build.yml) | Test llama stack build |
| Python Package Build Test | [python-build-test.yml](python-build-test.yml) | Test building the llama-stack PyPI project |
| Integration Tests (Record) | [record-integration-tests.yml](record-integration-tests.yml) | Run the integration test suite from tests/integration |
| Check semantic PR titles | [semantic-pr.yml](semantic-pr.yml) | Ensure that PR titles follow the conventional commit spec |
| Close stale issues and PRs | [stale_bot.yml](stale_bot.yml) | Run the Stale Bot action |
| Test External Providers Installed via Module | [test-external-provider-module.yml](test-external-provider-module.yml) | Test External Provider installation via Python module |
| Test External API and Providers | [test-external.yml](test-external.yml) | Test the External API and Provider mechanisms |
| UI Tests | [ui-unit-tests.yml](ui-unit-tests.yml) | Run the UI test suite |
| Unit Tests | [unit-tests.yml](unit-tests.yml) | Run the unit test suite |
| Update ReadTheDocs | [update-readthedocs.yml](update-readthedocs.yml) | Update the Llama Stack ReadTheDocs site |

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name: Update Changelog
run-name: Creates PR for updating the CHANGELOG.md
on:
release:
types: [published, unpublished, created, edited, deleted, released]
permissions:
contents: read
jobs:
generate_changelog:
name: Generate changelog
permissions:
contents: write # for peter-evans/create-pull-request to create branch
pull-requests: write # for peter-evans/create-pull-request to create a PR
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
with:
ref: main
fetch-depth: 0
- run: |
python ./scripts/gen-changelog.py
- uses: peter-evans/create-pull-request@271a8d0340265f705b14b6d32b9829c1cb33d45e # v7.0.8
with:
title: 'docs: update CHANGELOG.md for ${{ github.ref_name }}'
commit-message: 'docs: update CHANGELOG.md for ${{ github.ref_name }}'
branch: create-pull-request/changelog
signoff: true

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name: "Run Llama-stack Tests"
on:
#### Temporarily disable PR runs until tests run as intended within mainline.
#TODO Add this back.
#pull_request_target:
# types: ["opened"]
# branches:
# - 'main'
# paths:
# - 'llama_stack/**/*.py'
# - 'tests/**/*.py'
workflow_dispatch:
inputs:
runner:
description: 'GHA Runner Scale Set label to run workflow on.'
required: true
default: "llama-stack-gha-runner-gpu"
checkout_reference:
description: "The branch, tag, or SHA to checkout"
required: true
default: "main"
debug:
description: 'Run debugging steps?'
required: false
default: "true"
sleep_time:
description: '[DEBUG] sleep time for debugging'
required: true
default: "0"
provider_id:
description: 'ID of your provider'
required: true
default: "meta_reference"
model_id:
description: 'Shorthand name for target model ID (llama_3b or llama_8b)'
required: true
default: "llama_3b"
model_override_3b:
description: 'Specify shorthand model for <llama_3b> '
required: false
default: "Llama3.2-3B-Instruct"
model_override_8b:
description: 'Specify shorthand model for <llama_8b> '
required: false
default: "Llama3.1-8B-Instruct"
env:
# ID used for each test's provider config
PROVIDER_ID: "${{ inputs.provider_id || 'meta_reference' }}"
# Path to model checkpoints within EFS volume
MODEL_CHECKPOINT_DIR: "/data/llama"
# Path to directory to run tests from
TESTS_PATH: "${{ github.workspace }}/llama_stack/providers/tests"
# Keep track of a list of model IDs that are valid to use within pytest fixture marks
AVAILABLE_MODEL_IDs: "llama_3b llama_8b"
# Shorthand name for model ID, used in pytest fixture marks
MODEL_ID: "${{ inputs.model_id || 'llama_3b' }}"
# Override the `llama_3b` / `llama_8b' models, else use the default.
LLAMA_3B_OVERRIDE: "${{ inputs.model_override_3b || 'Llama3.2-3B-Instruct' }}"
LLAMA_8B_OVERRIDE: "${{ inputs.model_override_8b || 'Llama3.1-8B-Instruct' }}"
# Defines which directories in TESTS_PATH to exclude from the test loop
EXCLUDED_DIRS: "__pycache__"
# Defines the output xml reports generated after a test is run
REPORTS_GEN: ""
jobs:
execute_workflow:
name: Execute workload on Self-Hosted GPU k8s runner
permissions:
pull-requests: write
defaults:
run:
shell: bash
runs-on: ${{ inputs.runner != '' && inputs.runner || 'llama-stack-gha-runner-gpu' }}
if: always()
steps:
##############################
#### INITIAL DEBUG CHECKS ####
##############################
- name: "[DEBUG] Check content of the EFS mount"
id: debug_efs_volume
continue-on-error: true
if: inputs.debug == 'true'
run: |
echo "========= Content of the EFS mount ============="
ls -la ${{ env.MODEL_CHECKPOINT_DIR }}
- name: "[DEBUG] Get runner container OS information"
id: debug_os_info
if: ${{ inputs.debug == 'true' }}
run: |
cat /etc/os-release
- name: "[DEBUG] Print environment variables"
id: debug_env_vars
if: ${{ inputs.debug == 'true' }}
run: |
echo "PROVIDER_ID = ${PROVIDER_ID}"
echo "MODEL_CHECKPOINT_DIR = ${MODEL_CHECKPOINT_DIR}"
echo "AVAILABLE_MODEL_IDs = ${AVAILABLE_MODEL_IDs}"
echo "MODEL_ID = ${MODEL_ID}"
echo "LLAMA_3B_OVERRIDE = ${LLAMA_3B_OVERRIDE}"
echo "LLAMA_8B_OVERRIDE = ${LLAMA_8B_OVERRIDE}"
echo "EXCLUDED_DIRS = ${EXCLUDED_DIRS}"
echo "REPORTS_GEN = ${REPORTS_GEN}"
############################
#### MODEL INPUT CHECKS ####
############################
- name: "Check if env.model_id is valid"
id: check_model_id
run: |
if [[ " ${AVAILABLE_MODEL_IDs[@]} " =~ " ${MODEL_ID} " ]]; then
echo "Model ID '${MODEL_ID}' is valid."
else
echo "Model ID '${MODEL_ID}' is invalid. Terminating workflow."
exit 1
fi
#######################
#### CODE CHECKOUT ####
#######################
- name: "Checkout 'meta-llama/llama-stack' repository"
id: checkout_repo
uses: actions/checkout@v4
with:
ref: ${{ inputs.branch }}
- name: "[DEBUG] Content of the repository after checkout"
id: debug_content_after_checkout
if: ${{ inputs.debug == 'true' }}
run: |
ls -la ${GITHUB_WORKSPACE}
##########################################################
#### OPTIONAL SLEEP DEBUG ####
# #
# Use to "exec" into the test k8s POD and run tests #
# manually to identify what dependencies are being used. #
# #
##########################################################
- name: "[DEBUG] sleep"
id: debug_sleep
if: ${{ inputs.debug == 'true' && inputs.sleep_time != '' }}
run: |
sleep ${{ inputs.sleep_time }}
############################
#### UPDATE SYSTEM PATH ####
############################
- name: "Update path: execute"
id: path_update_exec
run: |
# .local/bin is needed for certain libraries installed below to be recognized
# when calling their executable to install sub-dependencies
mkdir -p ${HOME}/.local/bin
echo "${HOME}/.local/bin" >> "$GITHUB_PATH"
#####################################
#### UPDATE CHECKPOINT DIRECTORY ####
#####################################
- name: "Update checkpoint directory"
id: checkpoint_update
run: |
echo "Checkpoint directory: ${MODEL_CHECKPOINT_DIR}/$LLAMA_3B_OVERRIDE"
if [ "${MODEL_ID}" = "llama_3b" ] && [ -d "${MODEL_CHECKPOINT_DIR}/${LLAMA_3B_OVERRIDE}" ]; then
echo "MODEL_CHECKPOINT_DIR=${MODEL_CHECKPOINT_DIR}/${LLAMA_3B_OVERRIDE}" >> "$GITHUB_ENV"
elif [ "${MODEL_ID}" = "llama_8b" ] && [ -d "${MODEL_CHECKPOINT_DIR}/${LLAMA_8B_OVERRIDE}" ]; then
echo "MODEL_CHECKPOINT_DIR=${MODEL_CHECKPOINT_DIR}/${LLAMA_8B_OVERRIDE}" >> "$GITHUB_ENV"
else
echo "MODEL_ID & LLAMA_*B_OVERRIDE are not a valid pairing. Terminating workflow."
exit 1
fi
- name: "[DEBUG] Checkpoint update check"
id: debug_checkpoint_update
if: ${{ inputs.debug == 'true' }}
run: |
echo "MODEL_CHECKPOINT_DIR (after update) = ${MODEL_CHECKPOINT_DIR}"
##################################
#### DEPENDENCY INSTALLATIONS ####
##################################
- name: "Installing 'apt' required packages"
id: install_apt
run: |
echo "[STEP] Installing 'apt' required packages"
sudo apt update -y
sudo apt install -y python3 python3-pip npm wget
- name: "Installing packages with 'curl'"
id: install_curl
run: |
curl -fsSL https://ollama.com/install.sh | sh
- name: "Installing packages with 'wget'"
id: install_wget
run: |
wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
chmod +x Miniconda3-latest-Linux-x86_64.sh
./Miniconda3-latest-Linux-x86_64.sh -b install -c pytorch -c nvidia faiss-gpu=1.9.0
# Add miniconda3 bin to system path
echo "${HOME}/miniconda3/bin" >> "$GITHUB_PATH"
- name: "Installing packages with 'npm'"
id: install_npm_generic
run: |
sudo npm install -g junit-merge
- name: "Installing pip dependencies"
id: install_pip_generic
run: |
echo "[STEP] Installing 'llama-stack' models"
pip install -U pip setuptools
pip install -r requirements.txt
pip install -e .
pip install -U \
torch torchvision \
pytest pytest_asyncio \
fairscale lm-format-enforcer \
zmq chardet pypdf \
pandas sentence_transformers together \
aiosqlite
- name: "Installing packages with conda"
id: install_conda_generic
run: |
conda install -q -c pytorch -c nvidia faiss-gpu=1.9.0
#############################################################
#### TESTING TO BE DONE FOR BOTH PRS AND MANUAL DISPATCH ####
#############################################################
- name: "Run Tests: Loop"
id: run_tests_loop
working-directory: "${{ github.workspace }}"
run: |
pattern=""
for dir in llama_stack/providers/tests/*; do
if [ -d "$dir" ]; then
dir_name=$(basename "$dir")
if [[ ! " $EXCLUDED_DIRS " =~ " $dir_name " ]]; then
for file in "$dir"/test_*.py; do
test_name=$(basename "$file")
new_file="result-${dir_name}-${test_name}.xml"
if torchrun $(which pytest) -s -v ${TESTS_PATH}/${dir_name}/${test_name} -m "${PROVIDER_ID} and ${MODEL_ID}" \
--junitxml="${{ github.workspace }}/${new_file}"; then
echo "Ran test: ${test_name}"
else
echo "Did NOT run test: ${test_name}"
fi
pattern+="${new_file} "
done
fi
fi
done
echo "REPORTS_GEN=$pattern" >> "$GITHUB_ENV"
- name: "Test Summary: Merge"
id: test_summary_merge
working-directory: "${{ github.workspace }}"
run: |
echo "Merging the following test result files: ${REPORTS_GEN}"
# Defaults to merging them into 'merged-test-results.xml'
junit-merge ${{ env.REPORTS_GEN }}
############################################
#### AUTOMATIC TESTING ON PULL REQUESTS ####
############################################
#### Run tests ####
- name: "PR - Run Tests"
id: pr_run_tests
working-directory: "${{ github.workspace }}"
if: github.event_name == 'pull_request_target'
run: |
echo "[STEP] Running PyTest tests at 'GITHUB_WORKSPACE' path: ${GITHUB_WORKSPACE} | path: ${{ github.workspace }}"
# (Optional) Add more tests here.
# Merge test results with 'merged-test-results.xml' from above.
# junit-merge <new-test-results> merged-test-results.xml
#### Create test summary ####
- name: "PR - Test Summary"
id: pr_test_summary_create
if: github.event_name == 'pull_request_target'
uses: test-summary/action@v2
with:
paths: "${{ github.workspace }}/merged-test-results.xml"
output: test-summary.md
- name: "PR - Upload Test Summary"
id: pr_test_summary_upload
if: github.event_name == 'pull_request_target'
uses: actions/upload-artifact@v3
with:
name: test-summary
path: test-summary.md
#### Update PR request ####
- name: "PR - Update comment"
id: pr_update_comment
if: github.event_name == 'pull_request_target'
uses: thollander/actions-comment-pull-request@v2
with:
filePath: test-summary.md
########################
#### MANUAL TESTING ####
########################
#### Run tests ####
- name: "Manual - Run Tests: Prep"
id: manual_run_tests
working-directory: "${{ github.workspace }}"
if: github.event_name == 'workflow_dispatch'
run: |
echo "[STEP] Running PyTest tests at 'GITHUB_WORKSPACE' path: ${{ github.workspace }}"
#TODO Use this when collection errors are resolved
# pytest -s -v -m "${PROVIDER_ID} and ${MODEL_ID}" --junitxml="${{ github.workspace }}/merged-test-results.xml"
# (Optional) Add more tests here.
# Merge test results with 'merged-test-results.xml' from above.
# junit-merge <new-test-results> merged-test-results.xml
#### Create test summary ####
- name: "Manual - Test Summary"
id: manual_test_summary
if: always() && github.event_name == 'workflow_dispatch'
uses: test-summary/action@v2
with:
paths: "${{ github.workspace }}/merged-test-results.xml"

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@ -1,39 +0,0 @@
name: Installer CI
run-name: Test the installation script
on:
pull_request:
paths:
- 'scripts/install.sh'
push:
paths:
- 'scripts/install.sh'
schedule:
- cron: '0 2 * * *' # every day at 02:00 UTC
jobs:
lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # 5.0.0
- name: Run ShellCheck on install.sh
run: shellcheck scripts/install.sh
smoke-test-on-dev:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Install dependencies
uses: ./.github/actions/setup-runner
- name: Build a single provider
run: |
USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run --no-sync \
llama stack build --template starter --image-type container --image-name test
- name: Run installer end-to-end
run: |
IMAGE_ID=$(docker images --format "{{.Repository}}:{{.Tag}}" | head -n 1)
./scripts/install.sh --image $IMAGE_ID

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@ -1,112 +0,0 @@
name: Integration Auth Tests
run-name: Run the integration test suite with Kubernetes authentication
on:
push:
branches: [ main ]
pull_request:
branches: [ main ]
paths:
- 'distributions/**'
- 'llama_stack/**'
- '!llama_stack/ui/**'
- 'tests/integration/**'
- 'uv.lock'
- 'pyproject.toml'
- 'requirements.txt'
- '.github/workflows/integration-auth-tests.yml' # This workflow
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
test-matrix:
runs-on: ubuntu-latest
strategy:
matrix:
auth-provider: [oauth2_token]
fail-fast: false # we want to run all tests regardless of failure
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Install dependencies
uses: ./.github/actions/setup-runner
- name: Install minikube
if: ${{ matrix.auth-provider == 'kubernetes' }}
uses: medyagh/setup-minikube@e3c7f79eb1e997eabccc536a6cf318a2b0fe19d9 # v0.0.20
- name: Start minikube
if: ${{ matrix.auth-provider == 'oauth2_token' }}
run: |
minikube start
kubectl get pods -A
- name: Configure Kube Auth
if: ${{ matrix.auth-provider == 'oauth2_token' }}
run: |
kubectl create namespace llama-stack
kubectl create serviceaccount llama-stack-auth -n llama-stack
kubectl create token llama-stack-auth -n llama-stack > llama-stack-auth-token
- name: Set Kubernetes Config
if: ${{ matrix.auth-provider == 'oauth2_token' }}
run: |
echo "KUBERNETES_API_SERVER_URL=$(kubectl get --raw /.well-known/openid-configuration| jq -r .jwks_uri)" >> $GITHUB_ENV
echo "KUBERNETES_CA_CERT_PATH=$(kubectl config view --minify -o jsonpath='{.clusters[0].cluster.certificate-authority}')" >> $GITHUB_ENV
echo "KUBERNETES_ISSUER=$(kubectl get --raw /.well-known/openid-configuration| jq -r .issuer)" >> $GITHUB_ENV
echo "KUBERNETES_AUDIENCE=$(kubectl create token llama-stack-auth -n llama-stack --duration=1h | cut -d. -f2 | base64 -d | jq -r '.aud[0]')" >> $GITHUB_ENV
echo "TOKEN=$(cat llama-stack-auth-token)" >> $GITHUB_ENV
- name: Set Kube Auth Config and run server
env:
INFERENCE_MODEL: "meta-llama/Llama-3.2-3B-Instruct"
if: ${{ matrix.auth-provider == 'oauth2_token' }}
run: |
run_dir=$(mktemp -d)
cat <<'EOF' > $run_dir/run.yaml
version: '2'
image_name: kube
apis: []
providers: {}
server:
port: 8321
EOF
yq eval '.server.auth.provider_config.type = "${{ 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
nohup uv run llama stack run $run_dir/run.yaml --image-type venv > server.log 2>&1 &
- name: Wait for Llama Stack server to be ready
run: |
echo "Waiting for Llama Stack server..."
for i in {1..30}; do
if curl -s -L -H "Authorization: Bearer $(cat llama-stack-auth-token)" http://localhost:8321/v1/health | grep -q "OK"; then
echo "Llama Stack server is up!"
if grep -q "Enabling authentication with provider: ${{ matrix.auth-provider }}" server.log; then
echo "Llama Stack server is configured to use ${{ matrix.auth-provider }} auth"
exit 0
else
echo "Llama Stack server is not configured to use ${{ matrix.auth-provider }} auth"
cat server.log
exit 1
fi
fi
sleep 1
done
echo "Llama Stack server failed to start"
cat server.log
exit 1
- name: Test auth
run: |
curl -s -L -H "Authorization: Bearer $(cat llama-stack-auth-token)" http://127.0.0.1:8321/v1/providers|jq

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@ -1,72 +0,0 @@
name: SqlStore Integration Tests
run-name: Run the integration test suite with SqlStore
on:
push:
branches: [ main ]
pull_request:
branches: [ main ]
paths:
- 'llama_stack/providers/utils/sqlstore/**'
- 'tests/integration/sqlstore/**'
- 'uv.lock'
- 'pyproject.toml'
- 'requirements.txt'
- '.github/workflows/integration-sql-store-tests.yml' # This workflow
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
test-postgres:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ["3.12", "3.13"]
fail-fast: false
services:
postgres:
image: postgres:15
env:
POSTGRES_USER: llamastack
POSTGRES_PASSWORD: llamastack
POSTGRES_DB: llamastack
ports:
- 5432:5432
options: >-
--health-cmd pg_isready
--health-interval 10s
--health-timeout 5s
--health-retries 5
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Install dependencies
uses: ./.github/actions/setup-runner
with:
python-version: ${{ matrix.python-version }}
- name: Run SqlStore Integration Tests
env:
ENABLE_POSTGRES_TESTS: "true"
POSTGRES_HOST: localhost
POSTGRES_PORT: 5432
POSTGRES_DB: llamastack
POSTGRES_USER: llamastack
POSTGRES_PASSWORD: llamastack
run: |
uv run pytest -sv tests/integration/providers/utils/sqlstore/
- name: Upload test logs
if: ${{ always() }}
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
with:
name: postgres-test-logs-${{ github.run_id }}-${{ github.run_attempt }}-${{ matrix.python-version }}
path: |
*.log
retention-days: 1

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@ -1,87 +0,0 @@
name: Integration Tests (Replay)
run-name: Run the integration test suite from tests/integration in replay mode
on:
push:
branches: [ main ]
pull_request:
branches: [ main ]
types: [opened, synchronize, reopened]
paths:
- 'llama_stack/**'
- '!llama_stack/ui/**'
- 'tests/**'
- 'uv.lock'
- 'pyproject.toml'
- '.github/workflows/integration-tests.yml' # This workflow
- '.github/actions/setup-ollama/action.yml'
- '.github/actions/setup-test-environment/action.yml'
- '.github/actions/run-and-record-tests/action.yml'
schedule:
# If changing the cron schedule, update the provider in the test-matrix job
- cron: '0 0 * * *' # (test latest client) Daily at 12 AM UTC
- cron: '1 0 * * 0' # (test vllm) Weekly on Sunday at 1 AM UTC
workflow_dispatch:
inputs:
test-all-client-versions:
description: 'Test against both the latest and published versions'
type: boolean
default: false
test-provider:
description: 'Test against a specific provider'
type: string
default: 'ollama'
test-subdirs:
description: 'Comma-separated list of test subdirectories to run'
type: string
default: ''
test-pattern:
description: 'Regex pattern to pass to pytest -k'
type: string
default: ''
concurrency:
# Skip concurrency for pushes to main - each commit should be tested independently
group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_id || github.ref }}
cancel-in-progress: true
jobs:
run-replay-mode-tests:
runs-on: ubuntu-latest
name: ${{ format('Integration Tests ({0}, {1}, {2}, client={3}, vision={4})', matrix.client-type, matrix.provider, matrix.python-version, matrix.client-version, matrix.run-vision-tests) }}
strategy:
fail-fast: false
matrix:
client-type: [library, server]
# Use vllm on weekly schedule, otherwise use test-provider input (defaults to ollama)
provider: ${{ (github.event.schedule == '1 0 * * 0') && fromJSON('["vllm"]') || fromJSON(format('["{0}"]', github.event.inputs.test-provider || 'ollama')) }}
# Use Python 3.13 only on nightly schedule (daily latest client test), otherwise use 3.12
python-version: ${{ github.event.schedule == '0 0 * * *' && fromJSON('["3.12", "3.13"]') || fromJSON('["3.12"]') }}
client-version: ${{ (github.event.schedule == '0 0 * * *' || github.event.inputs.test-all-client-versions == 'true') && fromJSON('["published", "latest"]') || fromJSON('["latest"]') }}
run-vision-tests: [true, false]
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Setup test environment
uses: ./.github/actions/setup-test-environment
with:
python-version: ${{ matrix.python-version }}
client-version: ${{ matrix.client-version }}
provider: ${{ matrix.provider }}
run-vision-tests: ${{ matrix.run-vision-tests }}
inference-mode: 'replay'
- name: Run tests
uses: ./.github/actions/run-and-record-tests
with:
test-subdirs: ${{ inputs.test-subdirs }}
test-pattern: ${{ inputs.test-pattern }}
stack-config: ${{ matrix.client-type == 'library' && 'ci-tests' || 'server:ci-tests' }}
provider: ${{ matrix.provider }}
inference-mode: 'replay'
run-vision-tests: ${{ matrix.run-vision-tests }}

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@ -1,203 +0,0 @@
name: Vector IO Integration Tests
run-name: Run the integration test suite with various VectorIO providers
on:
push:
branches: [ main ]
pull_request:
branches: [ main ]
paths:
- 'llama_stack/**'
- '!llama_stack/ui/**'
- 'tests/integration/vector_io/**'
- 'uv.lock'
- 'pyproject.toml'
- 'requirements.txt'
- '.github/workflows/integration-vector-io-tests.yml' # This workflow
schedule:
- cron: '0 0 * * *' # (test on python 3.13) Daily at 12 AM UTC
concurrency:
group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_id || github.ref }}
cancel-in-progress: true
jobs:
test-matrix:
runs-on: ubuntu-latest
strategy:
matrix:
vector-io-provider: ["inline::faiss", "inline::sqlite-vec", "inline::milvus", "remote::chromadb", "remote::pgvector", "remote::weaviate", "remote::qdrant"]
python-version: ${{ github.event.schedule == '0 0 * * *' && fromJSON('["3.12", "3.13"]') || fromJSON('["3.12"]') }}
fail-fast: false # we want to run all tests regardless of failure
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Install dependencies
uses: ./.github/actions/setup-runner
with:
python-version: ${{ matrix.python-version }}
- name: Setup Chroma
if: matrix.vector-io-provider == 'remote::chromadb'
run: |
docker run --rm -d --pull always \
--name chromadb \
-p 8000:8000 \
-v ~/chroma:/chroma/chroma \
-e IS_PERSISTENT=TRUE \
-e ANONYMIZED_TELEMETRY=FALSE \
chromadb/chroma:latest
- name: Setup Weaviate
if: matrix.vector-io-provider == 'remote::weaviate'
run: |
docker run --rm -d --pull always \
--name weaviate \
-p 8080:8080 -p 50051:50051 \
cr.weaviate.io/semitechnologies/weaviate:1.32.0
- name: Start PGVector DB
if: matrix.vector-io-provider == 'remote::pgvector'
run: |
docker run -d \
--name pgvector \
-e POSTGRES_USER=llamastack \
-e POSTGRES_PASSWORD=llamastack \
-e POSTGRES_DB=llamastack \
-p 5432:5432 \
pgvector/pgvector:pg17
- name: Wait for PGVector to be ready
if: matrix.vector-io-provider == 'remote::pgvector'
run: |
echo "Waiting for Postgres to be ready..."
for i in {1..30}; do
if docker exec pgvector pg_isready -U llamastack > /dev/null 2>&1; then
echo "Postgres is ready!"
break
fi
echo "Not ready yet... ($i)"
sleep 1
done
- name: Enable pgvector extension
if: matrix.vector-io-provider == 'remote::pgvector'
run: |
PGPASSWORD=llamastack psql -h localhost -U llamastack -d llamastack \
-c "CREATE EXTENSION IF NOT EXISTS vector;"
- name: Setup Qdrant
if: matrix.vector-io-provider == 'remote::qdrant'
run: |
docker run --rm -d --pull always \
--name qdrant \
-p 6333:6333 \
qdrant/qdrant
- name: Wait for Qdrant to be ready
if: matrix.vector-io-provider == 'remote::qdrant'
run: |
echo "Waiting for Qdrant to be ready..."
for i in {1..30}; do
if curl -s http://localhost:6333/collections | grep -q '"status":"ok"'; then
echo "Qdrant is ready!"
exit 0
fi
sleep 2
done
echo "Qdrant failed to start"
docker logs qdrant
exit 1
- name: Wait for ChromaDB to be ready
if: matrix.vector-io-provider == 'remote::chromadb'
run: |
echo "Waiting for ChromaDB to be ready..."
for i in {1..30}; do
if curl -s http://localhost:8000/api/v2/heartbeat | grep -q "nanosecond heartbeat"; then
echo "ChromaDB is ready!"
exit 0
fi
sleep 2
done
echo "ChromaDB failed to start"
docker logs chromadb
exit 1
- name: Wait for Weaviate to be ready
if: matrix.vector-io-provider == 'remote::weaviate'
run: |
echo "Waiting for Weaviate to be ready..."
for i in {1..30}; do
if curl -s http://localhost:8080 | grep -q "https://weaviate.io/developers/weaviate/current/"; then
echo "Weaviate is ready!"
exit 0
fi
sleep 2
done
echo "Weaviate failed to start"
docker logs weaviate
exit 1
- name: Build Llama Stack
run: |
uv run --no-sync llama stack build --template ci-tests --image-type venv
- name: Check Storage and Memory Available Before Tests
if: ${{ always() }}
run: |
free -h
df -h
- name: Run Vector IO Integration Tests
env:
ENABLE_CHROMADB: ${{ matrix.vector-io-provider == 'remote::chromadb' && 'true' || '' }}
CHROMADB_URL: ${{ matrix.vector-io-provider == 'remote::chromadb' && 'http://localhost:8000' || '' }}
ENABLE_PGVECTOR: ${{ matrix.vector-io-provider == 'remote::pgvector' && 'true' || '' }}
PGVECTOR_HOST: ${{ matrix.vector-io-provider == 'remote::pgvector' && 'localhost' || '' }}
PGVECTOR_PORT: ${{ matrix.vector-io-provider == 'remote::pgvector' && '5432' || '' }}
PGVECTOR_DB: ${{ matrix.vector-io-provider == 'remote::pgvector' && 'llamastack' || '' }}
PGVECTOR_USER: ${{ matrix.vector-io-provider == 'remote::pgvector' && 'llamastack' || '' }}
PGVECTOR_PASSWORD: ${{ matrix.vector-io-provider == 'remote::pgvector' && 'llamastack' || '' }}
ENABLE_QDRANT: ${{ matrix.vector-io-provider == 'remote::qdrant' && 'true' || '' }}
QDRANT_URL: ${{ matrix.vector-io-provider == 'remote::qdrant' && 'http://localhost:6333' || '' }}
ENABLE_WEAVIATE: ${{ matrix.vector-io-provider == 'remote::weaviate' && 'true' || '' }}
WEAVIATE_CLUSTER_URL: ${{ matrix.vector-io-provider == 'remote::weaviate' && 'localhost:8080' || '' }}
run: |
uv run --no-sync \
pytest -sv --stack-config="files=inline::localfs,inference=inline::sentence-transformers,vector_io=${{ matrix.vector-io-provider }}" \
tests/integration/vector_io \
--embedding-model inline::sentence-transformers/all-MiniLM-L6-v2
- name: Check Storage and Memory Available After Tests
if: ${{ always() }}
run: |
free -h
df -h
- name: Create sanitized provider name
if: ${{ always() }}
run: |
echo "SANITIZED_PROVIDER=$(echo "${{ matrix.vector-io-provider }}" | tr ':' '_')" >> $GITHUB_ENV
- name: Write ChromaDB logs to file
if: ${{ always() && matrix.vector-io-provider == 'remote::chromadb' }}
run: |
docker logs chromadb > chromadb.log
- name: Write Qdrant logs to file
if: ${{ always() && matrix.vector-io-provider == 'remote::qdrant' }}
run: |
docker logs qdrant > qdrant.log
- name: Upload all logs to artifacts
if: ${{ always() }}
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
with:
name: vector-io-logs-${{ github.run_id }}-${{ github.run_attempt }}-${{ env.SANITIZED_PROVIDER }}-${{ matrix.python-version }}
path: |
*.log
retention-days: 1

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@ -1,100 +1,29 @@
name: Pre-commit
run-name: Run pre-commit checks
on:
pull_request:
push:
branches: [main]
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
pre-commit:
runs-on: ubuntu-latest
permissions:
contents: write
pull-requests: write
steps:
- name: Checkout code
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
with:
# For dependabot PRs, we need to checkout with a token that can push changes
token: ${{ github.actor == 'dependabot[bot]' && secrets.GITHUB_TOKEN || github.token }}
# Fetch full history for dependabot PRs to allow commits
fetch-depth: ${{ github.actor == 'dependabot[bot]' && 0 || 1 }}
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
uses: actions/setup-python@v5
with:
python-version: '3.12'
python-version: '3.11'
cache: pip
cache-dependency-path: |
**/requirements*.txt
.pre-commit-config.yaml
# npm ci may fail -
# npm error `npm ci` can only install packages when your package.json and package-lock.json or npm-shrinkwrap.json are in sync. Please update your lock file with `npm install` before continuing.
# npm error Invalid: lock file's llama-stack-client@0.2.17 does not satisfy llama-stack-client@0.2.18
# - name: Set up Node.js
# uses: actions/setup-node@39370e3970a6d050c480ffad4ff0ed4d3fdee5af # v4.1.0
# with:
# node-version: '20'
# cache: 'npm'
# cache-dependency-path: 'llama_stack/ui/'
# - name: Install npm dependencies
# run: npm ci
# working-directory: llama_stack/ui
- 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 ${{ github.head_ref }}
echo "Pre-commit fixes committed and pushed"
else
echo "No changes to commit"
fi
- uses: pre-commit/action@v3.0.1
- name: Verify if there are any diff files after pre-commit
if: github.actor != 'dependabot[bot]'
run: |
git diff --exit-code || (echo "There are uncommitted changes, run pre-commit locally and commit again" && exit 1)
- name: Verify if there are any new files after pre-commit
if: github.actor != 'dependabot[bot]'
run: |
unstaged_files=$(git ls-files --others --exclude-standard)
if [ -n "$unstaged_files" ]; then
echo "There are uncommitted new files, run pre-commit locally and commit again"
echo "$unstaged_files"
exit 1
fi

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@ -1,154 +0,0 @@
name: Test Llama Stack Build
run-name: Test llama stack build
on:
push:
branches:
- main
paths:
- 'llama_stack/cli/stack/build.py'
- 'llama_stack/cli/stack/_build.py'
- 'llama_stack/core/build.*'
- 'llama_stack/core/*.sh'
- '.github/workflows/providers-build.yml'
- 'llama_stack/distributions/**'
- 'pyproject.toml'
pull_request:
paths:
- 'llama_stack/cli/stack/build.py'
- 'llama_stack/cli/stack/_build.py'
- 'llama_stack/core/build.*'
- 'llama_stack/core/*.sh'
- '.github/workflows/providers-build.yml'
- 'llama_stack/distributions/**'
- 'pyproject.toml'
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
generate-matrix:
runs-on: ubuntu-latest
outputs:
distros: ${{ steps.set-matrix.outputs.distros }}
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Generate Distribution List
id: set-matrix
run: |
distros=$(ls llama_stack/distributions/*/*build.yaml | awk -F'/' '{print $(NF-1)}' | jq -R -s -c 'split("\n")[:-1]')
echo "distros=$distros" >> "$GITHUB_OUTPUT"
build:
needs: generate-matrix
runs-on: ubuntu-latest
strategy:
matrix:
distro: ${{ fromJson(needs.generate-matrix.outputs.distros) }}
image-type: [venv, container]
fail-fast: false # We want to run all jobs even if some fail
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Install dependencies
uses: ./.github/actions/setup-runner
- name: Print build dependencies
run: |
uv run llama stack build --distro ${{ matrix.distro }} --image-type ${{ matrix.image-type }} --image-name test --print-deps-only
- name: Run Llama Stack Build
run: |
# USE_COPY_NOT_MOUNT is set to true since mounting is not supported by docker buildx, we use COPY instead
# LLAMA_STACK_DIR is set to the current directory so we are building from the source
USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run llama stack build --distro ${{ matrix.distro }} --image-type ${{ matrix.image-type }} --image-name test
- name: Print dependencies in the image
if: matrix.image-type == 'venv'
run: |
uv pip list
build-single-provider:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Install dependencies
uses: ./.github/actions/setup-runner
- name: Build a single provider
run: |
USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run llama stack build --image-type venv --image-name test --providers inference=remote::ollama
build-custom-container-distribution:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Install dependencies
uses: ./.github/actions/setup-runner
- name: Build a single provider
run: |
yq -i '.image_type = "container"' llama_stack/distributions/ci-tests/build.yaml
yq -i '.image_name = "test"' llama_stack/distributions/ci-tests/build.yaml
USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run llama stack build --config llama_stack/distributions/ci-tests/build.yaml
- name: Inspect the container image entrypoint
run: |
IMAGE_ID=$(docker images --format "{{.Repository}}:{{.Tag}}" | head -n 1)
entrypoint=$(docker inspect --format '{{ .Config.Entrypoint }}' $IMAGE_ID)
echo "Entrypoint: $entrypoint"
if [ "$entrypoint" != "[python -m llama_stack.core.server.server /app/run.yaml]" ]; then
echo "Entrypoint is not correct"
exit 1
fi
build-ubi9-container-distribution:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Install dependencies
uses: ./.github/actions/setup-runner
- name: Pin distribution to UBI9 base
run: |
yq -i '
.image_type = "container" |
.image_name = "ubi9-test" |
.distribution_spec.container_image = "registry.access.redhat.com/ubi9:latest"
' llama_stack/distributions/ci-tests/build.yaml
- name: Build dev container (UBI9)
env:
USE_COPY_NOT_MOUNT: "true"
LLAMA_STACK_DIR: "."
run: |
uv run llama stack build --config llama_stack/distributions/ci-tests/build.yaml
- name: Inspect UBI9 image
run: |
IMAGE_ID=$(docker images --format "{{.Repository}}:{{.Tag}}" | head -n 1)
entrypoint=$(docker inspect --format '{{ .Config.Entrypoint }}' $IMAGE_ID)
echo "Entrypoint: $entrypoint"
if [ "$entrypoint" != "[python -m llama_stack.core.server.server /app/run.yaml]" ]; then
echo "Entrypoint is not correct"
exit 1
fi
echo "Checking /etc/os-release in $IMAGE_ID"
docker run --rm --entrypoint sh "$IMAGE_ID" -c \
'source /etc/os-release && echo "$ID"' \
| grep -qE '^(rhel|ubi)$' \
|| { echo "Base image is not UBI 9!"; exit 1; }

View file

@ -1,49 +0,0 @@
name: Python Package Build Test
run-name: Test building the llama-stack PyPI project
on:
push:
branches:
- main
pull_request:
branches:
- main
paths-ignore:
- 'llama_stack/ui/**'
jobs:
build:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.12', '3.13']
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Install uv
uses: astral-sh/setup-uv@d9e0f98d3fc6adb07d1e3d37f3043649ddad06a1 # v6.5.0
with:
python-version: ${{ matrix.python-version }}
activate-environment: true
version: 0.7.6
- name: Build Llama Stack package
run: |
uv build
- name: Install Llama Stack package
run: |
uv pip install dist/*.whl
- name: Verify Llama Stack package
run: |
uv pip list
uv pip show llama-stack
command -v llama
llama model prompt-format -m Llama3.2-90B-Vision-Instruct
llama model list
llama stack list-apis
llama stack list-providers inference

View file

@ -1,70 +0,0 @@
# This workflow should be run manually when needing to re-record tests. This happens when you have
# - added a new test
# - or changed an existing test such that a new inference call is made
# You should make a PR and then run this workflow on that PR branch. The workflow will re-record the
# tests and commit the recordings to the PR branch.
name: Integration Tests (Record)
run-name: Run the integration test suite from tests/integration
on:
workflow_dispatch:
inputs:
test-subdirs:
description: 'Comma-separated list of test subdirectories to run'
type: string
default: ''
test-provider:
description: 'Test against a specific provider'
type: string
default: 'ollama'
run-vision-tests:
description: 'Whether to run vision tests'
type: boolean
default: false
test-pattern:
description: 'Regex pattern to pass to pytest -k'
type: string
default: ''
jobs:
record-tests:
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- name: Echo workflow inputs
run: |
echo "::group::Workflow Inputs"
echo "test-subdirs: ${{ inputs.test-subdirs }}"
echo "test-provider: ${{ inputs.test-provider }}"
echo "run-vision-tests: ${{ inputs.run-vision-tests }}"
echo "test-pattern: ${{ inputs.test-pattern }}"
echo "branch: ${{ github.ref_name }}"
echo "::endgroup::"
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
with:
fetch-depth: 0
- name: Setup test environment
uses: ./.github/actions/setup-test-environment
with:
python-version: "3.12" # Use single Python version for recording
client-version: "latest"
provider: ${{ inputs.test-provider || 'ollama' }}
run-vision-tests: ${{ inputs.run-vision-tests }}
inference-mode: 'record'
- name: Run and record tests
uses: ./.github/actions/run-and-record-tests
with:
test-pattern: ${{ inputs.test-pattern }}
test-subdirs: ${{ inputs.test-subdirs }}
stack-config: 'server:ci-tests' # recording must be done with server since more tests are run
provider: ${{ inputs.test-provider || 'ollama' }}
inference-mode: 'record'
run-vision-tests: ${{ inputs.run-vision-tests }}

View file

@ -1,7 +1,5 @@
name: Check semantic PR titles
run-name: Ensure that PR titles follow the conventional commit spec
on:
pull_request_target:
types:
@ -10,10 +8,6 @@ on:
- reopened
- synchronize
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number }}
cancel-in-progress: true
permissions:
contents: read
@ -22,6 +16,6 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Check PR Title's semantic conformance
uses: amannn/action-semantic-pull-request@7f33ba792281b034f64e96f4c0b5496782dd3b37 # v6.1.0
uses: amannn/action-semantic-pull-request@v5
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

View file

@ -1,47 +0,0 @@
name: Close stale issues and PRs
run-name: Run the Stale Bot action
on:
schedule:
- cron: '0 0 * * *' # every day at midnight
env:
LC_ALL: en_US.UTF-8
defaults:
run:
shell: bash
permissions:
contents: read
jobs:
stale:
permissions:
issues: write
pull-requests: write
runs-on: ubuntu-latest
steps:
- name: Stale Action
uses: actions/stale@5bef64f19d7facfb25b37b414482c7164d639639 # v9.1.0
with:
stale-issue-label: 'stale'
stale-issue-message: >
This issue has been automatically marked as stale because it has not had activity within 60 days.
It will be automatically closed if no further activity occurs within 30 days.
close-issue-message: >
This issue has been automatically closed due to inactivity.
Please feel free to reopen if you feel it is still relevant!
days-before-issue-stale: 60
days-before-issue-close: 30
stale-pr-label: 'stale'
stale-pr-message: >
This pull request has been automatically marked as stale because it has not had activity within 60 days.
It will be automatically closed if no further activity occurs within 30 days.
close-pr-message: >
This pull request has been automatically closed due to inactivity.
Please feel free to reopen if you intend to continue working on it!
days-before-pr-stale: 60
days-before-pr-close: 30
operations-per-run: 300

View file

@ -1,86 +0,0 @@
name: Test External Providers Installed via Module
run-name: Test External Provider installation via Python module
on:
push:
branches: [ main ]
pull_request:
branches: [ main ]
paths:
- 'llama_stack/**'
- 'tests/integration/**'
- 'uv.lock'
- 'pyproject.toml'
- 'tests/external/*'
- '.github/workflows/test-external-provider-module.yml' # This workflow
jobs:
test-external-providers-from-module:
# This workflow is disabled. See https://github.com/meta-llama/llama-stack/pull/2975#issuecomment-3138702984 for details
if: false
runs-on: ubuntu-latest
strategy:
matrix:
image-type: [venv]
# We don't do container yet, it's tricky to install a package from the host into the
# container and point 'uv pip install' to the correct path...
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Install dependencies
uses: ./.github/actions/setup-runner
- name: Install Ramalama
shell: bash
run: |
uv pip install ramalama
- name: Run Ramalama
shell: bash
run: |
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
- name: Build distro from config file
run: |
USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run llama stack build --config tests/external/ramalama-stack/build.yaml
- name: Start Llama Stack server in background
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
uv pip list
nohup llama stack run tests/external/ramalama-stack/run.yaml --image-type ${{ matrix.image-type }} > server.log 2>&1 &
- name: Wait for Llama Stack server to be ready
run: |
for i in {1..30}; do
if ! grep -q "successfully connected to Ramalama" server.log; then
echo "Waiting for Llama Stack server to load the provider..."
sleep 1
else
echo "Provider loaded"
exit 0
fi
done
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

View file

@ -1,89 +0,0 @@
name: Test External API and Providers
run-name: Test the External API and Provider mechanisms
on:
push:
branches: [ main ]
pull_request:
branches: [ main ]
paths:
- 'llama_stack/**'
- '!llama_stack/ui/**'
- 'tests/integration/**'
- 'uv.lock'
- 'pyproject.toml'
- 'requirements.txt'
- 'tests/external/*'
- '.github/workflows/test-external.yml' # This workflow
jobs:
test-external:
runs-on: ubuntu-latest
strategy:
matrix:
image-type: [venv]
# We don't do container yet, it's tricky to install a package from the host into the
# container and point 'uv pip install' to the correct path...
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Install dependencies
uses: ./.github/actions/setup-runner
- name: Create API configuration
run: |
mkdir -p /home/runner/.llama/apis.d
cp tests/external/weather.yaml /home/runner/.llama/apis.d/weather.yaml
- name: Create provider configuration
run: |
mkdir -p /home/runner/.llama/providers.d/remote/weather
cp tests/external/kaze.yaml /home/runner/.llama/providers.d/remote/weather/kaze.yaml
- name: Print distro dependencies
run: |
USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run --no-sync llama stack build --config tests/external/build.yaml --print-deps-only
- name: Build distro from config file
run: |
USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run --no-sync llama stack build --config tests/external/build.yaml
- name: Start Llama Stack server in background
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
uv pip list
nohup llama stack run tests/external/run-byoa.yaml --image-type ${{ matrix.image-type }} > server.log 2>&1 &
- name: Wait for Llama Stack server to be ready
run: |
echo "Waiting for Llama Stack server..."
for i in {1..30}; do
if curl -sSf http://localhost:8321/v1/health | grep -q "OK"; then
echo "Llama Stack server is up!"
exit 0
fi
sleep 1
done
echo "Llama Stack server failed to start"
cat server.log
exit 1
- 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

69
.github/workflows/tests.yml vendored Normal file
View file

@ -0,0 +1,69 @@
name: auto-tests
on:
# pull_request:
workflow_dispatch:
inputs:
commit_sha:
description: 'Specific Commit SHA to trigger on'
required: false
default: $GITHUB_SHA # default to the last commit of $GITHUB_REF branch
jobs:
test-llama-stack-as-library:
runs-on: ubuntu-latest
env:
TOGETHER_API_KEY: ${{ secrets.TOGETHER_API_KEY }}
FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
TAVILY_SEARCH_API_KEY: ${{ secrets.TAVILY_SEARCH_API_KEY }}
strategy:
matrix:
provider: [fireworks, together]
steps:
- uses: actions/checkout@v4
with:
ref: ${{ github.event.inputs.commit_sha }}
- name: Echo commit SHA
run: |
echo "Triggered on commit SHA: ${{ github.event.inputs.commit_sha }}"
git rev-parse HEAD
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt pytest
pip install -e .
- name: Build providers
run: |
llama stack build --template ${{ matrix.provider }} --image-type venv
- name: Install the latest llama-stack-client & llama-models packages
run: |
pip install -e git+https://github.com/meta-llama/llama-stack-client-python.git#egg=llama-stack-client
pip install -e git+https://github.com/meta-llama/llama-models.git#egg=llama-models
- name: Run client-sdk test
working-directory: "${{ github.workspace }}"
env:
REPORT_OUTPUT: md_report.md
shell: bash
run: |
pip install --upgrade pytest-md-report
echo "REPORT_FILE=${REPORT_OUTPUT}" >> "$GITHUB_ENV"
export INFERENCE_MODEL=meta-llama/Llama-3.1-8B-Instruct
LLAMA_STACK_CONFIG=./llama_stack/templates/${{ matrix.provider }}/run.yaml pytest --md-report --md-report-verbose=1 ./tests/client-sdk/inference/ --md-report-output "$REPORT_OUTPUT"
- name: Output reports to the job summary
if: always()
shell: bash
run: |
if [ -f "$REPORT_FILE" ]; then
echo "<details><summary> Test Report for ${{ matrix.provider }} </summary>" >> $GITHUB_STEP_SUMMARY
echo "" >> $GITHUB_STEP_SUMMARY
cat "$REPORT_FILE" >> $GITHUB_STEP_SUMMARY
echo "" >> $GITHUB_STEP_SUMMARY
echo "</details>" >> $GITHUB_STEP_SUMMARY
fi

View file

@ -1,55 +0,0 @@
name: UI Tests
run-name: Run the UI test suite
on:
push:
branches: [ main ]
pull_request:
branches: [ main ]
paths:
- 'llama_stack/ui/**'
- '.github/workflows/ui-unit-tests.yml' # This workflow
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
ui-tests:
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
node-version: [22]
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Setup Node.js
uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
with:
node-version: ${{ matrix.node-version }}
cache: 'npm'
cache-dependency-path: 'llama_stack/ui/package-lock.json'
- name: Install dependencies
working-directory: llama_stack/ui
run: npm ci
- name: Run linting
working-directory: llama_stack/ui
run: npm run lint
- name: Run format check
working-directory: llama_stack/ui
run: npm run format:check
- name: Run unit tests
working-directory: llama_stack/ui
env:
CI: true
run: npm test -- --coverage --watchAll=false --passWithNoTests

View file

@ -1,55 +0,0 @@
name: Unit Tests
run-name: Run the unit test suite
on:
push:
branches: [ main ]
pull_request:
branches: [ main ]
paths:
- 'llama_stack/**'
- '!llama_stack/ui/**'
- 'tests/unit/**'
- 'uv.lock'
- 'pyproject.toml'
- 'requirements.txt'
- '.github/workflows/unit-tests.yml' # This workflow
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
unit-tests:
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python:
- "3.12"
- "3.13"
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
- name: Install dependencies
uses: ./.github/actions/setup-runner
with:
python-version: ${{ matrix.python }}
- name: Run unit tests
run: |
PYTHON_VERSION=${{ matrix.python }} ./scripts/unit-tests.sh --junitxml=pytest-report-${{ matrix.python }}.xml
- name: Upload test results
if: always()
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
with:
name: test-results-${{ matrix.python }}
path: |
.pytest_cache/
pytest-report-${{ matrix.python }}.xml
htmlcov-${{ matrix.python }}/
retention-days: 7

View file

@ -1,7 +1,5 @@
name: Update ReadTheDocs
run-name: Update the Llama Stack ReadTheDocs site
on:
workflow_dispatch:
inputs:
@ -14,22 +12,14 @@ on:
- main
paths:
- 'docs/**'
- 'pyproject.toml'
- '.github/workflows/update-readthedocs.yml'
tags:
- '*'
pull_request:
branches:
- main
paths:
- 'docs/**'
- 'pyproject.toml'
- '.github/workflows/update-readthedocs.yml'
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
update-readthedocs:
runs-on: ubuntu-latest
@ -37,10 +27,18 @@ jobs:
TOKEN: ${{ secrets.READTHEDOCS_TOKEN }}
steps:
- name: Checkout repository
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
uses: actions/checkout@v4
- name: Install dependencies
uses: ./.github/actions/setup-runner
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install the latest version of uv
uses: astral-sh/setup-uv@v5
- name: Sync with uv
run: uv sync --extra docs
- name: Build HTML
run: |
@ -57,10 +55,7 @@ jobs:
response=$(curl -X POST \
-H "Content-Type: application/json" \
-d "{
\"token\": \"$TOKEN\",
\"version\": \"$GITHUB_REF_NAME\"
}" \
-d "{\"token\": \"$TOKEN\"}" \
https://readthedocs.org/api/v2/webhook/llama-stack/289768/)
echo "Response: $response"

8
.gitignore vendored
View file

@ -6,7 +6,6 @@ dev_requirements.txt
build
.DS_Store
llama_stack/configs/*
.cursor/
xcuserdata/
*.hmap
.DS_Store
@ -19,12 +18,5 @@ Package.resolved
.vscode
_build
docs/src
# Sample tool-calling datasets generated by NVIDIA notebooks
docs/notebooks/nvidia/tool_calling/sample_data/
pyrightconfig.json
venv/
pytest-report.xml
.coverage
.python-version
CLAUDE.md
.claude/

3
.gitmodules vendored Normal file
View file

@ -0,0 +1,3 @@
[submodule "llama_stack/providers/impls/ios/inference/executorch"]
path = llama_stack/providers/inline/ios/inference/executorch
url = https://github.com/pytorch/executorch

View file

@ -1,35 +1,24 @@
exclude: 'build/'
default_language_version:
python: python3.12
node: "22"
python: python3
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v5.0.0 # Latest stable version
hooks:
- id: check-merge-conflict
args: ['--assume-in-merge']
- id: trailing-whitespace
exclude: '\.py$' # Exclude Python files as Ruff already handles them
- id: check-added-large-files
args: ['--maxkb=1000']
- id: end-of-file-fixer
exclude: '^(.*\.svg|.*\.md)$'
- id: no-commit-to-branch
- id: check-yaml
args: ["--unsafe"]
- id: detect-private-key
- id: mixed-line-ending
args: [--fix=lf] # Forces to replace line ending by LF (line feed)
- id: check-executables-have-shebangs
- id: check-json
- id: check-shebang-scripts-are-executable
- id: check-symlinks
- id: check-toml
exclude: '^(.*\.svg)$'
# Temporarily disabling this
# - id: no-commit-to-branch
# args: ['--branch=main']
- repo: https://github.com/Lucas-C/pre-commit-hooks
rev: v1.5.5
rev: v1.5.4
hooks:
- id: insert-license
files: \.py$|\.sh$
@ -38,27 +27,34 @@ repos:
- docs/license_header.txt
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.12.2
rev: v0.9.4
hooks:
- id: ruff
args: [ --fix ]
exclude: ^llama_stack/strong_typing/.*$
- id: ruff-format
- repo: https://github.com/adamchainz/blacken-docs
rev: 1.19.1
rev: 1.19.0
hooks:
- id: blacken-docs
additional_dependencies:
- black==24.3.0
- repo: https://github.com/astral-sh/uv-pre-commit
rev: 0.7.20
rev: 0.5.26
hooks:
- id: uv-lock
- id: uv-export
args: [
"--frozen",
"--no-hashes",
"--no-emit-project",
"--output-file=requirements.txt"
]
files: ^pyproject\.toml$
- id: uv-sync
- repo: https://github.com/pre-commit/mirrors-mypy
rev: v1.16.1
rev: v1.15.0
hooks:
- id: mypy
additional_dependencies:
@ -70,6 +66,12 @@ repos:
- pydantic
pass_filenames: false
# - repo: https://github.com/jsh9/pydoclint
# rev: d88180a8632bb1602a4d81344085cf320f288c5a
# hooks:
# - id: pydoclint
# args: [--config=pyproject.toml]
# - repo: https://github.com/tcort/markdown-link-check
# rev: v3.11.2
# hooks:
@ -81,121 +83,16 @@ repos:
- id: distro-codegen
name: Distribution Template Codegen
additional_dependencies:
- uv==0.7.8
entry: uv run --group codegen ./scripts/distro_codegen.py
- rich
- pydantic
- uv==0.6.0
entry: uv run python -m llama_stack.scripts.distro_codegen
language: python
pass_filenames: false
require_serial: true
files: ^llama_stack/templates/.*$|^llama_stack/providers/.*/inference/.*/models\.py$
- id: provider-codegen
name: Provider Codegen
additional_dependencies:
- uv==0.7.8
entry: uv run --group codegen ./scripts/provider_codegen.py
language: python
pass_filenames: false
require_serial: true
files: ^llama_stack/providers/.*$
- id: openapi-codegen
name: API Spec Codegen
additional_dependencies:
- uv==0.7.8
entry: sh -c 'uv run ./docs/openapi_generator/run_openapi_generator.sh > /dev/null'
language: python
pass_filenames: false
require_serial: true
files: ^llama_stack/apis/|^docs/openapi_generator/
- id: check-workflows-use-hashes
name: Check GitHub Actions use SHA-pinned actions
entry: ./scripts/check-workflows-use-hashes.sh
language: system
pass_filenames: false
require_serial: true
always_run: true
files: ^\.github/workflows/.*\.ya?ml$
- id: check-init-py
name: Check for missing __init__.py files
entry: ./scripts/check-init-py.sh
language: system
pass_filenames: false
require_serial: true
always_run: true
files: ^llama_stack/.*$
- id: forbid-pytest-asyncio
name: Block @pytest.mark.asyncio and @pytest_asyncio.fixture
entry: bash
language: system
types: [python]
pass_filenames: true
args:
- -c
- |
grep -EnH '^[^#]*@pytest\.mark\.asyncio|@pytest_asyncio\.fixture' "$@" && {
echo;
echo "❌ Do not use @pytest.mark.asyncio or @pytest_asyncio.fixture."
echo " pytest is already configured with async-mode=auto."
echo;
exit 1;
} || true
- id: generate-ci-docs
name: Generate CI documentation
additional_dependencies:
- uv==0.7.8
entry: uv run ./scripts/gen-ci-docs.py
language: python
pass_filenames: false
require_serial: true
files: ^.github/workflows/.*$
# ui-prettier and ui-eslint are disabled until we can avoid `npm ci`, which is slow and may fail -
# npm error `npm ci` can only install packages when your package.json and package-lock.json or npm-shrinkwrap.json are in sync. Please update your lock file with `npm install` before continuing.
# npm error Invalid: lock file's llama-stack-client@0.2.17 does not satisfy llama-stack-client@0.2.18
# and until we have infra for installing prettier and next via npm -
# Lint UI code with ESLint.....................................................Failed
# - hook id: ui-eslint
# - exit code: 127
# > ui@0.1.0 lint
# > next lint --fix --quiet
# sh: line 1: next: command not found
#
# - id: ui-prettier
# name: Format UI code with Prettier
# entry: bash -c 'cd llama_stack/ui && npm ci && npm run format'
# language: system
# files: ^llama_stack/ui/.*\.(ts|tsx)$
# pass_filenames: false
# require_serial: true
# - id: ui-eslint
# name: Lint UI code with ESLint
# entry: bash -c 'cd llama_stack/ui && npm run lint -- --fix --quiet'
# language: system
# files: ^llama_stack/ui/.*\.(ts|tsx)$
# pass_filenames: false
# require_serial: true
- id: check-log-usage
name: Ensure 'llama_stack.log' usage for logging
entry: bash
language: system
types: [python]
pass_filenames: true
args:
- -c
- |
matches=$(grep -EnH '^[^#]*\b(import\s+logging|from\s+logging\b)' "$@" | grep -v -e '#\s*allow-direct-logging' || true)
if [ -n "$matches" ]; then
# GitHub Actions annotation format
while IFS=: read -r file line_num rest; do
echo "::error file=$file,line=$line_num::Do not use 'import logging' or 'from logging import' in $file. Use the custom log instead: from llama_stack.log import get_logger; logger = get_logger(). If direct logging is truly needed, add: # allow-direct-logging"
done <<< "$matches"
exit 1
fi
exit 0
files: ^llama_stack/templates/.*$
files: ^llama_stack/providers/.*/inference/.*/models\.py$
ci:
autofix_commit_msg: 🎨 [pre-commit.ci] Auto format from pre-commit.com hooks
autoupdate_commit_msg: ⬆ [pre-commit.ci] pre-commit autoupdate
autofix_prs: true
autoupdate_branch: ''
autoupdate_schedule: weekly
skip: []
submodules: false

View file

@ -5,21 +5,28 @@
# Required
version: 2
# Build documentation in the "docs/" directory with Sphinx
sphinx:
configuration: docs/source/conf.py
# Set the OS, Python version and other tools you might need
build:
os: ubuntu-22.04
tools:
python: "3.12"
jobs:
pre_create_environment:
- asdf plugin add uv
- asdf install uv latest
- asdf global uv latest
create_environment:
- uv venv "${READTHEDOCS_VIRTUALENV_PATH}"
install:
- UV_PROJECT_ENVIRONMENT="${READTHEDOCS_VIRTUALENV_PATH}" uv sync --frozen --group docs
# You can also specify other tool versions:
# nodejs: "19"
# rust: "1.64"
# golang: "1.19"
# Build documentation in the "docs/" directory with Sphinx
sphinx:
configuration: docs/source/conf.py
# Optionally build your docs in additional formats such as PDF and ePub
# formats:
# - pdf
# - epub
# Optional but recommended, declare the Python requirements required
# to build your documentation
# See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html
python:
install:
- requirements: docs/requirements.txt

View file

@ -1,516 +0,0 @@
# Changelog
# v0.2.15
Published on: 2025-07-16T03:30:01Z
---
# v0.2.14
Published on: 2025-07-04T16:06:48Z
## Highlights
* Support for Llama Guard 4
* Added Milvus support to vector-stores API
* Documentation and zero-to-hero updates for latest APIs
---
# v0.2.13
Published on: 2025-06-28T04:28:11Z
## Highlights
* search_mode support in OpenAI vector store API
* Security fixes
---
# v0.2.12
Published on: 2025-06-20T22:52:12Z
## Highlights
* Filter support in file search
* Support auth attributes in inference and response stores
---
# v0.2.11
Published on: 2025-06-17T20:26:26Z
## Highlights
* OpenAI-compatible vector store APIs
* Hybrid Search in Sqlite-vec
* File search tool in Responses API
* Pagination in inference and response stores
* Added `suffix` to completions API for fill-in-the-middle tasks
---
# v0.2.10.1
Published on: 2025-06-06T20:11:02Z
## Highlights
* ChromaDB provider fix
---
# v0.2.10
Published on: 2025-06-05T23:21:45Z
## Highlights
* OpenAI-compatible embeddings API
* OpenAI-compatible Files API
* Postgres support in starter distro
* Enable ingestion of precomputed embeddings
* Full multi-turn support in Responses API
* Fine-grained access control policy
---
# v0.2.9
Published on: 2025-05-30T20:01:56Z
## Highlights
* Added initial streaming support in Responses API
* UI view for Responses
* Postgres inference store support
---
# v0.2.8
Published on: 2025-05-27T21:03:47Z
# Release v0.2.8
## Highlights
* Server-side MCP with auth firewalls now works in the Stack - both for Agents and Responses
* Get chat completions APIs and UI to show chat completions
* Enable keyword search for sqlite-vec
---
# v0.2.7
Published on: 2025-05-16T20:38:10Z
## Highlights
This is a small update. But a couple highlights:
* feat: function tools in OpenAI Responses by @bbrowning in https://github.com/meta-llama/llama-stack/pull/2094, getting closer to ready. Streaming is the next missing piece.
* feat: Adding support for customizing chunk context in RAG insertion and querying by @franciscojavierarceo in https://github.com/meta-llama/llama-stack/pull/2134
* feat: scaffolding for Llama Stack UI by @ehhuang in https://github.com/meta-llama/llama-stack/pull/2149, more to come in the coming releases.
---
# v0.2.6
Published on: 2025-05-12T18:06:52Z
---
# v0.2.5
Published on: 2025-05-04T20:16:49Z
---
# v0.2.4
Published on: 2025-04-29T17:26:01Z
## Highlights
* One-liner to install and run Llama Stack yay! by @reluctantfuturist in https://github.com/meta-llama/llama-stack/pull/1383
* support for NVIDIA NeMo datastore by @raspawar in https://github.com/meta-llama/llama-stack/pull/1852
* (yuge!) Kubernetes authentication by @leseb in https://github.com/meta-llama/llama-stack/pull/1778
* (yuge!) OpenAI Responses API by @bbrowning in https://github.com/meta-llama/llama-stack/pull/1989
* add api.llama provider, llama-guard-4 model by @ashwinb in https://github.com/meta-llama/llama-stack/pull/2058
---
# v0.2.3
Published on: 2025-04-25T22:46:21Z
## Highlights
* OpenAI compatible inference endpoints and client-SDK support. `client.chat.completions.create()` now works.
* significant improvements and functionality added to the nVIDIA distribution
* many improvements to the test verification suite.
* new inference providers: Ramalama, IBM WatsonX
* many improvements to the Playground UI
---
# v0.2.2
Published on: 2025-04-13T01:19:49Z
## Main changes
- Bring Your Own Provider (@leseb) - use out-of-tree provider code to execute the distribution server
- OpenAI compatible inference API in progress (@bbrowning)
- Provider verifications (@ehhuang)
- Many updates and fixes to playground
- Several llama4 related fixes
---
# v0.2.1
Published on: 2025-04-05T23:13:00Z
---
# v0.2.0
Published on: 2025-04-05T19:04:29Z
## Llama 4 Support
Checkout more at https://www.llama.com
---
# v0.1.9
Published on: 2025-03-29T00:52:23Z
### Build and Test Agents
* Agents: Entire document context with attachments
* RAG: Documentation with sqlite-vec faiss comparison
* Getting started: Fixes to getting started notebook.
### Agent Evals and Model Customization
* (**New**) Post-training: Add nemo customizer
### Better Engineering
* Moved sqlite-vec to non-blocking calls
* Don't return a payload on file delete
---
# v0.1.8
Published on: 2025-03-24T01:28:50Z
# v0.1.8 Release Notes
### Build and Test Agents
* Safety: Integrated NVIDIA as a safety provider.
* VectorDB: Added Qdrant as an inline provider.
* Agents: Added support for multiple tool groups in agents.
* Agents: Simplified imports for Agents in client package
### Agent Evals and Model Customization
* Introduced DocVQA and IfEval benchmarks.
### Deploying and Monitoring Agents
* Introduced a Containerfile and image workflow for the Playground.
* Implemented support for Bearer (API Key) authentication.
* Added attribute-based access control for resources.
* Fixes on docker deployments: use --pull always and standardized the default port to 8321
* Deprecated: /v1/inspect/providers use /v1/providers/ instead
### Better Engineering
* Consolidated scripts under the ./scripts directory.
* Addressed mypy violations in various modules.
* Added Dependabot scans for Python dependencies.
* Implemented a scheduled workflow to update the changelog automatically.
* Enforced concurrency to reduce CI loads.
### New Contributors
* @cmodi-meta made their first contribution in https://github.com/meta-llama/llama-stack/pull/1650
* @jeffmaury made their first contribution in https://github.com/meta-llama/llama-stack/pull/1671
* @derekhiggins made their first contribution in https://github.com/meta-llama/llama-stack/pull/1698
* @Bobbins228 made their first contribution in https://github.com/meta-llama/llama-stack/pull/1745
**Full Changelog**: https://github.com/meta-llama/llama-stack/compare/v0.1.7...v0.1.8
---
# v0.1.7
Published on: 2025-03-14T22:30:51Z
## 0.1.7 Release Notes
### Build and Test Agents
* Inference: ImageType is now refactored to LlamaStackImageType
* Inference: Added tests to measure TTFT
* Inference: Bring back usage metrics
* Agents: Added endpoint for get agent, list agents and list sessions
* Agents: Automated conversion of type hints in client tool for lite llm format
* Agents: Deprecated ToolResponseMessage in agent.resume API
* Added Provider API for listing and inspecting provider info
### Agent Evals and Model Customization
* Eval: Added new eval benchmarks Math 500 and BFCL v3
* Deploy and Monitoring of Agents
* Telemetry: Fix tracing to work across coroutines
### Better Engineering
* Display code coverage for unit tests
* Updated call sites (inference, tool calls, agents) to move to async non blocking calls
* Unit tests also run on Python 3.11, 3.12, and 3.13
* Added ollama inference to Integration tests CI
* Improved documentation across examples, testing, CLI, updated providers table )
---
# v0.1.6
Published on: 2025-03-08T04:35:08Z
## 0.1.6 Release Notes
### Build and Test Agents
* Inference: Fixed support for inline vllm provider
* (**New**) Agent: Build & Monitor Agent Workflows with Llama Stack + Anthropic's Best Practice [Notebook](https://github.com/meta-llama/llama-stack/blob/main/docs/notebooks/Llama_Stack_Agent_Workflows.ipynb)
* (**New**) Agent: Revamped agent [documentation](https://llama-stack.readthedocs.io/en/latest/building_applications/agent.html) with more details and examples
* Agent: Unify tools and Python SDK Agents API
* Agent: AsyncAgent Python SDK wrapper supporting async client tool calls
* Agent: Support python functions without @client_tool decorator as client tools
* Agent: deprecation for allow_resume_turn flag, and remove need to specify tool_prompt_format
* VectorIO: MilvusDB support added
### Agent Evals and Model Customization
* (**New**) Agent: Llama Stack RAG Lifecycle [Notebook](https://github.com/meta-llama/llama-stack/blob/main/docs/notebooks/Llama_Stack_RAG_Lifecycle.ipynb)
* Eval: Documentation for eval, scoring, adding new benchmarks
* Eval: Distribution template to run benchmarks on llama & non-llama models
* Eval: Ability to register new custom LLM-as-judge scoring functions
* (**New**) Looking for contributors for open benchmarks. See [documentation](https://llama-stack.readthedocs.io/en/latest/references/evals_reference/index.html#open-benchmark-contributing-guide) for details.
### Deploy and Monitoring of Agents
* Better support for different log levels across all components for better monitoring
### Better Engineering
* Enhance OpenAPI spec to include Error types across all APIs
* Moved all tests to /tests and created unit tests to run on each PR
* Removed all dependencies on llama-models repo
---
# v0.1.5.1
Published on: 2025-02-28T22:37:44Z
## 0.1.5.1 Release Notes
* Fixes for security risk in https://github.com/meta-llama/llama-stack/pull/1327 and https://github.com/meta-llama/llama-stack/pull/1328
**Full Changelog**: https://github.com/meta-llama/llama-stack/compare/v0.1.5...v0.1.5.1
---
# v0.1.5
Published on: 2025-02-28T18:14:01Z
## 0.1.5 Release Notes
### Build Agents
* Inference: Support more non-llama models (openai, anthropic, gemini)
* Inference: Can use the provider's model name in addition to the HF alias
* Inference: Fixed issues with calling tools that weren't specified in the prompt
* RAG: Improved system prompt for RAG and no more need for hard-coded rag-tool calling
* Embeddings: Added support for Nemo retriever embedding models
* Tools: Added support for MCP tools in Ollama Distribution
* Distributions: Added new Groq distribution
### Customize Models
* Save post-trained checkpoint in SafeTensor format to allow Ollama inference provider to use the post-trained model
### Monitor agents
* More comprehensive logging of agent steps including client tools
* Telemetry inputs/outputs are now structured and queryable
* Ability to retrieve agents session, turn, step by ids
### Better Engineering
* Moved executorch Swift code out of this repo into the llama-stack-client-swift repo, similar to kotlin
* Move most logging to use logger instead of prints
* Completed text /chat-completion and /completion tests
---
# v0.1.4
Published on: 2025-02-25T00:02:43Z
## v0.1.4 Release Notes
Here are the key changes coming as part of this release:
### Build and Test Agents
* Inference: Added support for non-llama models
* Inference: Added option to list all downloaded models and remove models
* Agent: Introduce new api agents.resume_turn to include client side tool execution in the same turn
* Agent: AgentConfig introduces new variable “tool_config” that allows for better tool configuration and system prompt overrides
* Agent: Added logging for agent step start and completion times
* Agent: Added support for logging for tool execution metadata
* Embedding: Updated /inference/embeddings to support asymmetric models, truncation and variable sized outputs
* Embedding: Updated embedding models for Ollama, Together, and Fireworks with available defaults
* VectorIO: Improved performance of sqlite-vec using chunked writes
### Agent Evals and Model Customization
* Deprecated api /eval-tasks. Use /eval/benchmark instead
* Added CPU training support for TorchTune
### Deploy and Monitoring of Agents
* Consistent view of client and server tool calls in telemetry
### Better Engineering
* Made tests more data-driven for consistent evaluation
* Fixed documentation links and improved API reference generation
* Various small fixes for build scripts and system reliability
---
# v0.1.3
Published on: 2025-02-14T20:24:32Z
## v0.1.3 Release
Here are some key changes that are coming as part of this release.
### Build and Test Agents
Streamlined the initial development experience
- Added support for llama stack run --image-type venv
- Enhanced vector store options with new sqlite-vec provider and improved Qdrant integration
- vLLM improvements for tool calling and logprobs
- Better handling of sporadic code_interpreter tool calls
### Agent Evals
Better benchmarking and Agent performance assessment
- Renamed eval API /eval-task to /benchmarks
- Improved documentation and notebooks for RAG and evals
### Deploy and Monitoring of Agents
Improved production readiness
- Added usage metrics collection for chat completions
- CLI improvements for provider information
- Improved error handling and system reliability
- Better model endpoint handling and accessibility
- Improved signal handling on distro server
### Better Engineering
Infrastructure and code quality improvements
- Faster text-based chat completion tests
- Improved testing for non-streaming agent apis
- Standardized import formatting with ruff linter
- Added conventional commits standard
- Fixed documentation parsing issues
---
# v0.1.2
Published on: 2025-02-07T22:06:49Z
# TL;DR
- Several stabilizations to development flows after the switch to `uv`
- Migrated CI workflows to new OSS repo - [llama-stack-ops](https://github.com/meta-llama/llama-stack-ops)
- Added automated rebuilds for ReadTheDocs
- Llama Stack server supports HTTPS
- Added system prompt overrides support
- Several bug fixes and improvements to documentation (check out Kubernetes deployment guide by @terrytangyuan )
---
# v0.1.1
Published on: 2025-02-02T02:29:24Z
A bunch of small / big improvements everywhere including support for Windows, switching to `uv` and many provider improvements.
---
# v0.1.0
Published on: 2025-01-24T17:47:47Z
We are excited to announce a stable API release of Llama Stack, which enables developers to build RAG applications and Agents using tools and safety shields, monitor and those agents with telemetry, and evaluate the agent with scoring functions.
## Context
GenAI application developers need more than just an LLM - they need to integrate tools, connect with their data sources, establish guardrails, and ground the LLM responses effectively. Currently, developers must piece together various tools and APIs, complicating the development lifecycle and increasing costs. The result is that developers are spending more time on these integrations rather than focusing on the application logic itself. The bespoke coupling of components also makes it challenging to adopt state-of-the-art solutions in the rapidly evolving GenAI space. This is particularly difficult for open models like Llama, as best practices are not widely established in the open.
Llama Stack was created to provide developers with a comprehensive and coherent interface that simplifies AI application development and codifies best practices across the Llama ecosystem. Since our launch in September 2024, we have seen a huge uptick in interest in Llama Stack APIs by both AI developers and from partners building AI services with Llama models. Partners like Nvidia, Fireworks, and Ollama have collaborated with us to develop implementations across various APIs, including inference, memory, and safety.
With Llama Stack, you can easily build a RAG agent which can also search the web, do complex math, and custom tool calling. You can use telemetry to inspect those traces, and convert telemetry into evals datasets. And with Llama Stacks plugin architecture and prepackage distributions, you choose to run your agent anywhere - in the cloud with our partners, deploy your own environment using virtualenv or Docker, operate locally with Ollama, or even run on mobile devices with our SDKs. Llama Stack offers unprecedented flexibility while also simplifying the developer experience.
## Release
After iterating on the APIs for the last 3 months, today were launching a stable release (V1) of the Llama Stack APIs and the corresponding llama-stack server and client packages(v0.1.0). We now have automated tests for providers. These tests make sure that all provider implementations are verified. Developers can now easily and reliably select distributions or providers based on their specific requirements.
There are example standalone apps in llama-stack-apps.
## Key Features of this release
- **Unified API Layer**
- Inference: Run LLM models
- RAG: Store and retrieve knowledge for RAG
- Agents: Build multi-step agentic workflows
- Tools: Register tools that can be called by the agent
- Safety: Apply content filtering and safety policies
- Evaluation: Test model and agent quality
- Telemetry: Collect and analyze usage data and complex agentic traces
- Post Training ( Coming Soon ): Fine tune models for specific use cases
- **Rich Provider Ecosystem**
- Local Development: Meta's Reference, Ollama
- Cloud: Fireworks, Together, Nvidia, AWS Bedrock, Groq, Cerebras
- On-premises: Nvidia NIM, vLLM, TGI, Dell-TGI
- On-device: iOS and Android support
- **Built for Production**
- Pre-packaged distributions for common deployment scenarios
- Backwards compatibility across model versions
- Comprehensive evaluation capabilities
- Full observability and monitoring
- **Multiple developer interfaces**
- CLI: Command line interface
- Python SDK
- Swift iOS SDK
- Kotlin Android SDK
- **Sample llama stack applications**
- Python
- iOS
- Android
---
# v0.1.0rc12
Published on: 2025-01-22T22:24:01Z
---
# v0.0.63
Published on: 2024-12-18T07:17:43Z
A small but important bug-fix release to update the URL datatype for the client-SDKs. The issue affected multimodal agentic turns especially.
**Full Changelog**: https://github.com/meta-llama/llama-stack/compare/v0.0.62...v0.0.63
---

View file

@ -1,91 +1,17 @@
# Contributing to Llama Stack
# Contributing to Llama-Stack
We want to make contributing to this project as easy and transparent as
possible.
## Set up your development environment
We use [uv](https://github.com/astral-sh/uv) to manage python dependencies and virtual environments.
You can install `uv` by following this [guide](https://docs.astral.sh/uv/getting-started/installation/).
You can install the dependencies by running:
```bash
cd llama-stack
uv sync --group dev
uv pip install -e .
source .venv/bin/activate
```
```{note}
You can use a specific version of Python with `uv` by adding the `--python <version>` flag (e.g. `--python 3.12`).
Otherwise, `uv` will automatically select a Python version according to the `requires-python` section of the `pyproject.toml`.
For more info, see the [uv docs around Python versions](https://docs.astral.sh/uv/concepts/python-versions/).
```
Note that you can create a dotenv file `.env` that includes necessary environment variables:
```
LLAMA_STACK_BASE_URL=http://localhost:8321
LLAMA_STACK_CLIENT_LOG=debug
LLAMA_STACK_PORT=8321
LLAMA_STACK_CONFIG=<provider-name>
TAVILY_SEARCH_API_KEY=
BRAVE_SEARCH_API_KEY=
```
And then use this dotenv file when running client SDK tests via the following:
```bash
uv run --env-file .env -- pytest -v tests/integration/inference/test_text_inference.py --text-model=meta-llama/Llama-3.1-8B-Instruct
```
### Pre-commit Hooks
We use [pre-commit](https://pre-commit.com/) to run linting and formatting checks on your code. You can install the pre-commit hooks by running:
```bash
uv run pre-commit install
```
After that, pre-commit hooks will run automatically before each commit.
Alternatively, if you don't want to install the pre-commit hooks, you can run the checks manually by running:
```bash
uv run pre-commit run --all-files
```
```{caution}
Before pushing your changes, make sure that the pre-commit hooks have passed successfully.
```
## Discussions -> Issues -> Pull Requests
We actively welcome your pull requests. However, please read the following. This is heavily inspired by [Ghostty](https://github.com/ghostty-org/ghostty/blob/main/CONTRIBUTING.md).
If in doubt, please open a [discussion](https://github.com/meta-llama/llama-stack/discussions); we can always convert that to an issue later.
### Issues
We use GitHub issues to track public bugs. Please ensure your description is
clear and has sufficient instructions to be able to reproduce the issue.
Meta has a [bounty program](http://facebook.com/whitehat/info) for the safe
disclosure of security bugs. In those cases, please go through the process
outlined on that page and do not file a public issue.
### Contributor License Agreement ("CLA")
In order to accept your pull request, we need you to submit a CLA. You only need
to do this once to work on any of Meta's open source projects.
Complete your CLA here: <https://code.facebook.com/cla>
**I'd like to contribute!**
If you are new to the project, start by looking at the issues tagged with "good first issue". If you're interested
leave a comment on the issue and a triager will assign it to you.
Please avoid picking up too many issues at once. This helps you stay focused and ensures that others in the community also have opportunities to contribute.
- Try to work on only 12 issues at a time, especially if youre still getting familiar with the codebase.
- Before taking an issue, check if its already assigned or being actively discussed.
- If youre blocked or cant continue with an issue, feel free to unassign yourself or leave a comment so others can step in.
All issues are actionable (please report if they are not.) Pick one and start working on it. Thank you.
If you need help or guidance, comment on the issue. Issues that are extra friendly to new contributors are tagged with "contributor friendly".
**I have a bug!**
@ -115,44 +41,68 @@ Please avoid picking up too many issues at once. This helps you stay focused and
4. Make sure your code lints using `pre-commit`.
5. If you haven't already, complete the Contributor License Agreement ("CLA").
6. Ensure your pull request follows the [conventional commits format](https://www.conventionalcommits.org/en/v1.0.0/).
7. Ensure your pull request follows the [coding style](#coding-style).
## Contributor License Agreement ("CLA")
In order to accept your pull request, we need you to submit a CLA. You only need
to do this once to work on any of Meta's open source projects.
Complete your CLA here: <https://code.facebook.com/cla>
## Issues
We use GitHub issues to track public bugs. Please ensure your description is
clear and has sufficient instructions to be able to reproduce the issue.
Meta has a [bounty program](http://facebook.com/whitehat/info) for the safe
disclosure of security bugs. In those cases, please go through the process
outlined on that page and do not file a public issue.
Please keep pull requests (PRs) small and focused. If you have a large set of changes, consider splitting them into logically grouped, smaller PRs to facilitate review and testing.
## Set up your development environment
```{tip}
As a general guideline:
- Experienced contributors should try to keep no more than 5 open PRs at a time.
- New contributors are encouraged to have only one open PR at a time until theyre familiar with the codebase and process.
We use [uv](https://github.com/astral-sh/uv) to manage python dependencies and virtual environments.
You can install `uv` by following this [guide](https://docs.astral.sh/uv/getting-started/installation/).
You can install the dependencies by running:
```bash
$ cd llama-stack
$ uv sync --extra dev
$ uv pip install -e .
$ source .venv/bin/activate
```
## Repository guidelines
## Pre-commit Hooks
### Coding Style
We use [pre-commit](https://pre-commit.com/) to run linting and formatting checks on your code. You can install the pre-commit hooks by running:
* Comments should provide meaningful insights into the code. Avoid filler comments that simply
describe the next step, as they create unnecessary clutter, same goes for docstrings.
* Prefer comments to clarify surprising behavior and/or relationships between parts of the code
rather than explain what the next line of code does.
* Catching exceptions, prefer using a specific exception type rather than a broad catch-all like
`Exception`.
* Error messages should be prefixed with "Failed to ..."
* 4 spaces for indentation rather than tab
* When using `# noqa` to suppress a style or linter warning, include a comment explaining the
justification for bypassing the check.
* When using `# type: ignore` to suppress a mypy warning, include a comment explaining the
justification for bypassing the check.
* Don't use unicode characters in the codebase. ASCII-only is preferred for compatibility or
readability reasons.
* Providers configuration class should be Pydantic Field class. It should have a `description` field
that describes the configuration. These descriptions will be used to generate the provider
documentation.
* When possible, use keyword arguments only when calling functions.
* Llama Stack utilizes [custom Exception classes](llama_stack/apis/common/errors.py) for certain Resources that should be used where applicable.
```bash
$ uv run pre-commit install
```
### License
By contributing to Llama, you agree that your contributions will be licensed
under the LICENSE file in the root directory of this source tree.
After that, pre-commit hooks will run automatically before each commit.
Alternatively, if you don't want to install the pre-commit hooks, you can run the checks manually by running:
```bash
$ uv run pre-commit run --all-files
```
> [!CAUTION]
> Before pushing your changes, make sure that the pre-commit hooks have passed successfully.
## Adding a new dependency to the project
To add a new dependency to the project, you can use the `uv` command. For example, to add `foo` to the project, you can run:
```bash
$ uv add foo
$ uv sync
```
## Coding Style
* 4 spaces for indentation rather than tabs
* 80 character line length
* ...
## Common Tasks
@ -160,41 +110,35 @@ Some tips about common tasks you work on while contributing to Llama Stack:
### Using `llama stack build`
Building a stack image will use the production version of the `llama-stack` and `llama-stack-client` packages. If you are developing with a llama-stack repository checked out and need your code to be reflected in the stack image, set `LLAMA_STACK_DIR` and `LLAMA_STACK_CLIENT_DIR` to the appropriate checked out directories when running any of the `llama` CLI commands.
Building a stack image (conda / docker) will use the production version of the `llama-stack`, `llama-models` and `llama-stack-client` packages. If you are developing with a llama-stack repository checked out and need your code to be reflected in the stack image, set `LLAMA_STACK_DIR` and `LLAMA_MODELS_DIR` to the appropriate checked out directories when running any of the `llama` CLI commands.
Example:
```bash
cd work/
git clone https://github.com/meta-llama/llama-stack.git
git clone https://github.com/meta-llama/llama-stack-client-python.git
cd llama-stack
LLAMA_STACK_DIR=$(pwd) LLAMA_STACK_CLIENT_DIR=../llama-stack-client-python llama stack build --distro <...>
$ cd work/
$ git clone https://github.com/meta-llama/llama-stack.git
$ git clone https://github.com/meta-llama/llama-models.git
$ cd llama-stack
$ LLAMA_STACK_DIR=$(pwd) LLAMA_MODELS_DIR=../llama-models llama stack build --template <...>
```
### Updating distribution configurations
If you have made changes to a provider's configuration in any form (introducing a new config key, or
changing models, etc.), you should run `./scripts/distro_codegen.py` to re-generate various YAML
files as well as the documentation. You should not change `docs/source/.../distributions/` files
manually as they are auto-generated.
### Updating Provider Configurations
### Updating the provider documentation
If you have made changes to a provider's configuration, you should run `./scripts/provider_codegen.py`
to re-generate the documentation. You should not change `docs/source/.../providers/` files manually
as they are auto-generated.
Note that the provider "description" field will be used to generate the provider documentation.
If you have made changes to a provider's configuration in any form (introducing a new config key, or changing models, etc.), you should run `python llama_stack/scripts/distro_codegen.py` to re-generate various YAML files as well as the documentation. You should not change `docs/source/.../distributions/` files manually as they are auto-generated.
### Building the Documentation
If you are making changes to the documentation at [https://llama-stack.readthedocs.io/en/latest/](https://llama-stack.readthedocs.io/en/latest/), you can use the following command to build the documentation and preview your changes. You will need [Sphinx](https://www.sphinx-doc.org/en/master/) and the readthedocs theme.
```bash
$ cd llama-stack/docs
$ uv sync --extra docs
# This rebuilds the documentation pages.
uv run --group docs make -C docs/ html
$ uv run make html
# This will start a local server (usually at http://127.0.0.1:8000) that automatically rebuilds and refreshes when you make changes to the documentation.
uv run --group docs sphinx-autobuild docs/source docs/build/html --write-all
$ uv run sphinx-autobuild source build/html --write-all
```
### Update API Documentation
@ -202,7 +146,12 @@ uv run --group docs sphinx-autobuild docs/source docs/build/html --write-all
If you modify or add new API endpoints, update the API documentation accordingly. You can do this by running the following command:
```bash
uv run ./docs/openapi_generator/run_openapi_generator.sh
$ uv sync --extra dev
$ uv run ./docs/openapi_generator/run_openapi_generator.sh
```
The generated API documentation will be available in `docs/_static/`. Make sure to review the changes before committing.
The generated API documentation will be available in `docs/_static/`. Make sure to review the changes before committing.
## License
By contributing to Llama, you agree that your contributions will be licensed
under the LICENSE file in the root directory of this source tree.

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@ -1,9 +1,6 @@
include pyproject.toml
include llama_stack/models/llama/llama3/tokenizer.model
include llama_stack/models/llama/llama4/tokenizer.model
include llama_stack/core/*.sh
include distributions/dependencies.json
include llama_stack/distribution/*.sh
include llama_stack/cli/scripts/*.sh
include llama_stack/distributions/*/*.yaml
include llama_stack/providers/tests/test_cases/inference/*.json
include llama_stack/models/llama/*/*.md
include llama_stack/tests/integration/*.jpg
include llama_stack/templates/*/*.yaml
include llama_stack/providers/tests/test_cases/*.json

177
README.md
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@ -3,85 +3,9 @@
[![PyPI version](https://img.shields.io/pypi/v/llama_stack.svg)](https://pypi.org/project/llama_stack/)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/llama-stack)](https://pypi.org/project/llama-stack/)
[![License](https://img.shields.io/pypi/l/llama_stack.svg)](https://github.com/meta-llama/llama-stack/blob/main/LICENSE)
[![Discord](https://img.shields.io/discord/1257833999603335178?color=6A7EC2&logo=discord&logoColor=ffffff)](https://discord.gg/llama-stack)
[![Unit Tests](https://github.com/meta-llama/llama-stack/actions/workflows/unit-tests.yml/badge.svg?branch=main)](https://github.com/meta-llama/llama-stack/actions/workflows/unit-tests.yml?query=branch%3Amain)
[![Integration Tests](https://github.com/meta-llama/llama-stack/actions/workflows/integration-tests.yml/badge.svg?branch=main)](https://github.com/meta-llama/llama-stack/actions/workflows/integration-tests.yml?query=branch%3Amain)
[![Discord](https://img.shields.io/discord/1257833999603335178)](https://discord.gg/llama-stack)
[**Quick Start**](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html) | [**Documentation**](https://llama-stack.readthedocs.io/en/latest/index.html) | [**Colab Notebook**](./docs/getting_started.ipynb) | [**Discord**](https://discord.gg/llama-stack)
### ✨🎉 Llama 4 Support 🎉✨
We released [Version 0.2.0](https://github.com/meta-llama/llama-stack/releases/tag/v0.2.0) with support for the Llama 4 herd of models released by Meta.
<details>
<summary>👋 Click here to see how to run Llama 4 models on Llama Stack </summary>
\
*Note you need 8xH100 GPU-host to run these models*
```bash
pip install -U llama_stack
MODEL="Llama-4-Scout-17B-16E-Instruct"
# get meta url from llama.com
llama model download --source meta --model-id $MODEL --meta-url <META_URL>
# start a llama stack server
INFERENCE_MODEL=meta-llama/$MODEL llama stack build --run --template meta-reference-gpu
# install client to interact with the server
pip install llama-stack-client
```
### CLI
```bash
# Run a chat completion
MODEL="Llama-4-Scout-17B-16E-Instruct"
llama-stack-client --endpoint http://localhost:8321 \
inference chat-completion \
--model-id meta-llama/$MODEL \
--message "write a haiku for meta's llama 4 models"
ChatCompletionResponse(
completion_message=CompletionMessage(content="Whispers in code born\nLlama's gentle, wise heartbeat\nFuture's soft unfold", role='assistant', stop_reason='end_of_turn', tool_calls=[]),
logprobs=None,
metrics=[Metric(metric='prompt_tokens', value=21.0, unit=None), Metric(metric='completion_tokens', value=28.0, unit=None), Metric(metric='total_tokens', value=49.0, unit=None)]
)
```
### Python SDK
```python
from llama_stack_client import LlamaStackClient
client = LlamaStackClient(base_url=f"http://localhost:8321")
model_id = "meta-llama/Llama-4-Scout-17B-16E-Instruct"
prompt = "Write a haiku about coding"
print(f"User> {prompt}")
response = client.inference.chat_completion(
model_id=model_id,
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": prompt},
],
)
print(f"Assistant> {response.completion_message.content}")
```
As more providers start supporting Llama 4, you can use them in Llama Stack as well. We are adding to the list. Stay tuned!
</details>
### 🚀 One-Line Installer 🚀
To try Llama Stack locally, run:
```bash
curl -LsSf https://github.com/meta-llama/llama-stack/raw/main/scripts/install.sh | bash
```
### Overview
[**Quick Start**](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html) | [**Documentation**](https://llama-stack.readthedocs.io/en/latest/index.html) | [**Colab Notebook**](./docs/getting_started.ipynb)
Llama Stack standardizes the core building blocks that simplify AI application development. It codifies best practices across the Llama ecosystem. More specifically, it provides
@ -108,50 +32,61 @@ Llama Stack standardizes the core building blocks that simplify AI application d
By reducing friction and complexity, Llama Stack empowers developers to focus on what they do best: building transformative generative AI applications.
### API Providers
Here is a list of the various API providers and available distributions that can help developers get started easily with Llama Stack.
Please checkout for [full list](https://llama-stack.readthedocs.io/en/latest/providers/index.html)
Here is a list of the various API providers and available distributions that can help developers get started easily with Llama Stack.
| API Provider Builder | Environments | Agents | Inference | VectorIO | Safety | Telemetry | Post Training | Eval | DatasetIO |
|:--------------------:|:------------:|:------:|:---------:|:--------:|:------:|:---------:|:-------------:|:----:|:--------:|
| Meta Reference | Single Node | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| SambaNova | Hosted | | ✅ | | ✅ | | | | |
| Cerebras | Hosted | | ✅ | | | | | | |
| Fireworks | Hosted | ✅ | ✅ | ✅ | | | | | |
| AWS Bedrock | Hosted | | ✅ | | ✅ | | | | |
| Together | Hosted | ✅ | ✅ | | ✅ | | | | |
| Groq | Hosted | | ✅ | | | | | | |
| Ollama | Single Node | | ✅ | | | | | | |
| TGI | Hosted/Single Node | | ✅ | | | | | | |
| NVIDIA NIM | Hosted/Single Node | | ✅ | | ✅ | | | | |
| ChromaDB | Hosted/Single Node | | | ✅ | | | | | |
| Milvus | Hosted/Single Node | | | ✅ | | | | | |
| Qdrant | Hosted/Single Node | | | ✅ | | | | | |
| Weaviate | Hosted/Single Node | | | ✅ | | | | | |
| SQLite-vec | Single Node | | | ✅ | | | | | |
| PG Vector | Single Node | | | ✅ | | | | | |
| PyTorch ExecuTorch | On-device iOS | ✅ | ✅ | | | | | | |
| vLLM | Single Node | | ✅ | | | | | | |
| OpenAI | Hosted | | ✅ | | | | | | |
| Anthropic | Hosted | | ✅ | | | | | | |
| Gemini | Hosted | | ✅ | | | | | | |
| WatsonX | Hosted | | ✅ | | | | | | |
| HuggingFace | Single Node | | | | | | ✅ | | ✅ |
| TorchTune | Single Node | | | | | | ✅ | | |
| NVIDIA NEMO | Hosted | | ✅ | ✅ | | | ✅ | ✅ | ✅ |
| NVIDIA | Hosted | | | | | | ✅ | ✅ | ✅ |
> **Note**: Additional providers are available through external packages. See [External Providers](https://llama-stack.readthedocs.io/en/latest/providers/external.html) documentation.
| **API Provider Builder** | **Environments** | **Agents** | **Inference** | **Memory** | **Safety** | **Telemetry** |
|:------------------------:|:----------------------:|:----------:|:-------------:|:----------:|:----------:|:-------------:|
| Meta Reference | Single Node | ✅ | ✅ | ✅ | ✅ | ✅ |
| SambaNova | Hosted | | ✅ | | | |
| Cerebras | Hosted | | ✅ | | | |
| Fireworks | Hosted | ✅ | ✅ | ✅ | | |
| AWS Bedrock | Hosted | | ✅ | | ✅ | |
| Together | Hosted | ✅ | ✅ | | ✅ | |
| Groq | Hosted | | ✅ | | | |
| Ollama | Single Node | | ✅ | | | |
| TGI | Hosted and Single Node | | ✅ | | | |
| NVIDIA NIM | Hosted and Single Node | | ✅ | | | |
| Chroma | Single Node | | | ✅ | | |
| PG Vector | Single Node | | | ✅ | | |
| PyTorch ExecuTorch | On-device iOS | ✅ | ✅ | | | |
| vLLM | Hosted and Single Node | | ✅ | | | |
### Distributions
A Llama Stack Distribution (or "distro") is a pre-configured bundle of provider implementations for each API component. Distributions make it easy to get started with a specific deployment scenario - you can begin with a local development setup (eg. ollama) and seamlessly transition to production (eg. Fireworks) without changing your application code.
Here are some of the distributions we support:
A Llama Stack Distribution (or "distro") is a pre-configured bundle of provider implementations for each API component. Distributions make it easy to get started with a specific deployment scenario - you can begin with a local development setup (eg. ollama) and seamlessly transition to production (eg. Fireworks) without changing your application code. Here are some of the distributions we support:
| **Distribution** | **Llama Stack Docker** | Start This Distribution |
|:---------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------:|
| Starter Distribution | [llamastack/distribution-starter](https://hub.docker.com/repository/docker/llamastack/distribution-starter/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/starter.html) |
| Meta Reference | [llamastack/distribution-meta-reference-gpu](https://hub.docker.com/repository/docker/llamastack/distribution-meta-reference-gpu/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/meta-reference-gpu.html) |
| PostgreSQL | [llamastack/distribution-postgres-demo](https://hub.docker.com/repository/docker/llamastack/distribution-postgres-demo/general) | |
| Meta Reference Quantized | [llamastack/distribution-meta-reference-quantized-gpu](https://hub.docker.com/repository/docker/llamastack/distribution-meta-reference-quantized-gpu/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/meta-reference-quantized-gpu.html) |
| SambaNova | [llamastack/distribution-sambanova](https://hub.docker.com/repository/docker/llamastack/distribution-sambanova/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/sambanova.html) |
| Cerebras | [llamastack/distribution-cerebras](https://hub.docker.com/repository/docker/llamastack/distribution-cerebras/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/cerebras.html) |
| Ollama | [llamastack/distribution-ollama](https://hub.docker.com/repository/docker/llamastack/distribution-ollama/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/ollama.html) |
| TGI | [llamastack/distribution-tgi](https://hub.docker.com/repository/docker/llamastack/distribution-tgi/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/tgi.html) |
| Together | [llamastack/distribution-together](https://hub.docker.com/repository/docker/llamastack/distribution-together/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/together.html) |
| Fireworks | [llamastack/distribution-fireworks](https://hub.docker.com/repository/docker/llamastack/distribution-fireworks/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/fireworks.html) |
| vLLM | [llamastack/distribution-remote-vllm](https://hub.docker.com/repository/docker/llamastack/distribution-remote-vllm/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/remote-vllm.html) |
### Installation
You have two ways to install this repository:
* **Install as a package**:
You can install the repository directly from [PyPI](https://pypi.org/project/llama-stack/) by running the following command:
```bash
pip install llama-stack
```
* **Install from source**:
If you prefer to install from the source code, we recommend using [uv](https://github.com/astral-sh/uv).
Then, run the following commands:
```bash
git clone git@github.com:meta-llama/llama-stack.git
cd llama-stack
uv sync
uv pip install -e .
```
### Documentation
@ -180,17 +115,3 @@ Please checkout our [Documentation](https://llama-stack.readthedocs.io/en/latest
Check out our client SDKs for connecting to a Llama Stack server in your preferred language, you can choose from [python](https://github.com/meta-llama/llama-stack-client-python), [typescript](https://github.com/meta-llama/llama-stack-client-typescript), [swift](https://github.com/meta-llama/llama-stack-client-swift), and [kotlin](https://github.com/meta-llama/llama-stack-client-kotlin) programming languages to quickly build your applications.
You can find more example scripts with client SDKs to talk with the Llama Stack server in our [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main/examples) repo.
## 🌟 GitHub Star History
## Star History
[![Star History Chart](https://api.star-history.com/svg?repos=meta-llama/llama-stack&type=Date)](https://www.star-history.com/#meta-llama/llama-stack&Date)
## ✨ Contributors
Thanks to all of our amazing contributors!
<a href="https://github.com/meta-llama/llama-stack/graphs/contributors">
<img src="https://contrib.rocks/image?repo=meta-llama/llama-stack" />
</a>

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<text x="31.5" y="15" fill="#010101" fill-opacity=".3">coverage</text>
<text x="31.5" y="14">coverage</text>
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services:
llamastack:
image: distribution-bedrock
volumes:
- ~/.llama:/root/.llama
- ./run.yaml:/root/llamastack-run-bedrock.yaml
ports:
- "8321:8321"
entrypoint: bash -c "python -m llama_stack.distribution.server.server --yaml_config /root/llamastack-run-bedrock.yaml"
deploy:
restart_policy:
condition: on-failure
delay: 3s
max_attempts: 5
window: 60s

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../../llama_stack/templates/bedrock/run.yaml

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services:
llamastack:
image: llamastack/distribution-cerebras
network_mode: "host"
volumes:
- ~/.llama:/root/.llama
- ./run.yaml:/root/llamastack-run-cerebras.yaml
ports:
- "8321:8321"
entrypoint: bash -c "python -m llama_stack.distribution.server.server --yaml_config /root/llamastack-run-cerebras.yaml"
deploy:
restart_policy:
condition: on-failure
delay: 3s
max_attempts: 5
window: 60s

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services:
text-generation-inference:
image: registry.dell.huggingface.co/enterprise-dell-inference-meta-llama-meta-llama-3.1-8b-instruct
network_mode: "host"
volumes:
- $HOME/.cache/huggingface:/data
ports:
- "5009:5009"
devices:
- nvidia.com/gpu=all
environment:
- CUDA_VISIBLE_DEVICES=0,1,2,3,4
- NUM_SHARD=4
- MAX_BATCH_PREFILL_TOKENS=32768
- MAX_INPUT_TOKENS=8000
- MAX_TOTAL_TOKENS=8192
command: []
deploy:
resources:
reservations:
devices:
- driver: nvidia
# that's the closest analogue to --gpus; provide
# an integer amount of devices or 'all'
count: all
# Devices are reserved using a list of capabilities, making
# capabilities the only required field. A device MUST
# satisfy all the requested capabilities for a successful
# reservation.
capabilities: [gpu]
runtime: nvidia
llamastack:
depends_on:
text-generation-inference:
condition: service_healthy
image: llamastack/distribution-tgi
network_mode: "host"
volumes:
- ~/.llama:/root/.llama
# Link to TGI run.yaml file
- ./run.yaml:/root/my-run.yaml
ports:
- "8321:8321"
# Hack: wait for TGI server to start before starting docker
entrypoint: bash -c "sleep 60; python -m llama_stack.distribution.server.server --yaml_config /root/my-run.yaml"
restart_policy:
condition: on-failure
delay: 3s
max_attempts: 5
window: 60s

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version: '2'
image_name: local
container_image: null
conda_env: local
apis:
- shields
- agents
- models
- memory
- memory_banks
- inference
- safety
providers:
inference:
- provider_id: tgi0
provider_type: remote::tgi
config:
url: http://127.0.0.1:80
safety:
- provider_id: meta0
provider_type: inline::llama-guard
config:
model: Llama-Guard-3-1B
excluded_categories: []
- provider_id: meta1
provider_type: inline::prompt-guard
config:
model: Prompt-Guard-86M
memory:
- provider_id: meta0
provider_type: inline::faiss
config: {}
agents:
- provider_id: meta0
provider_type: inline::meta-reference
config:
persistence_store:
namespace: null
type: sqlite
db_path: ~/.llama/runtime/kvstore.db
telemetry:
- provider_id: meta0
provider_type: inline::meta-reference
config: {}

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{
"bedrock": [
"aiosqlite",
"autoevals",
"blobfile",
"boto3",
"chardet",
"chromadb-client",
"datasets",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"matplotlib",
"mcp",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"tqdm",
"transformers",
"uvicorn"
],
"cerebras": [
"aiosqlite",
"autoevals",
"blobfile",
"cerebras_cloud_sdk",
"chardet",
"chromadb-client",
"datasets",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"matplotlib",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"tqdm",
"transformers",
"uvicorn",
"sentence-transformers --no-deps",
"torch torchvision --index-url https://download.pytorch.org/whl/cpu"
],
"dell": [
"aiohttp",
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"chromadb-client",
"datasets",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"huggingface_hub",
"matplotlib",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"tqdm",
"transformers",
"uvicorn",
"sentence-transformers --no-deps",
"torch torchvision --index-url https://download.pytorch.org/whl/cpu"
],
"fireworks": [
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"chromadb-client",
"datasets",
"faiss-cpu",
"fastapi",
"fire",
"fireworks-ai",
"httpx",
"matplotlib",
"mcp",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"tqdm",
"transformers",
"uvicorn",
"sentence-transformers --no-deps",
"torch torchvision --index-url https://download.pytorch.org/whl/cpu"
],
"hf-endpoint": [
"aiohttp",
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"chromadb-client",
"datasets",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"huggingface_hub",
"matplotlib",
"mcp",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"tqdm",
"transformers",
"uvicorn"
],
"hf-serverless": [
"aiohttp",
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"chromadb-client",
"datasets",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"huggingface_hub",
"matplotlib",
"mcp",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"tqdm",
"transformers",
"uvicorn",
"sentence-transformers --no-deps",
"torch torchvision --index-url https://download.pytorch.org/whl/cpu"
],
"meta-reference-gpu": [
"accelerate",
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"chromadb-client",
"datasets",
"fairscale",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"lm-format-enforcer",
"matplotlib",
"mcp",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentence-transformers",
"sentencepiece",
"torch",
"torchvision",
"tqdm",
"transformers",
"uvicorn",
"zmq"
],
"meta-reference-quantized-gpu": [
"accelerate",
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"chromadb-client",
"datasets",
"fairscale",
"faiss-cpu",
"fastapi",
"fbgemm-gpu",
"fire",
"httpx",
"lm-format-enforcer",
"matplotlib",
"mcp",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentence-transformers",
"sentencepiece",
"torch",
"torchao==0.5.0",
"torchvision",
"tqdm",
"transformers",
"uvicorn",
"zmq"
],
"nvidia": [
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"datasets",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"matplotlib",
"mcp",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"tqdm",
"transformers",
"uvicorn"
],
"ollama": [
"aiohttp",
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"chromadb-client",
"datasets",
"fastapi",
"fire",
"httpx",
"matplotlib",
"nltk",
"numpy",
"ollama",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"sqlite-vec",
"tqdm",
"transformers",
"uvicorn"
],
"remote-vllm": [
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"chromadb-client",
"datasets",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"matplotlib",
"mcp",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"tqdm",
"transformers",
"uvicorn",
"sentence-transformers --no-deps",
"torch torchvision --index-url https://download.pytorch.org/whl/cpu"
],
"sambanova": [
"aiosqlite",
"blobfile",
"chardet",
"chromadb-client",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"matplotlib",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"tqdm",
"transformers",
"uvicorn"
],
"tgi": [
"aiohttp",
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"chromadb-client",
"datasets",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"huggingface_hub",
"matplotlib",
"mcp",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"tqdm",
"transformers",
"uvicorn",
"sentence-transformers --no-deps",
"torch torchvision --index-url https://download.pytorch.org/whl/cpu"
],
"together": [
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"chromadb-client",
"datasets",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"matplotlib",
"mcp",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"together",
"tqdm",
"transformers",
"uvicorn",
"sentence-transformers --no-deps",
"torch torchvision --index-url https://download.pytorch.org/whl/cpu"
],
"vllm-gpu": [
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"chromadb-client",
"datasets",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"matplotlib",
"mcp",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentencepiece",
"tqdm",
"transformers",
"uvicorn",
"vllm",
"sentence-transformers --no-deps",
"torch torchvision --index-url https://download.pytorch.org/whl/cpu"
]
}

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../../llama_stack/templates/fireworks/build.yaml

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services:
llamastack:
image: llamastack/distribution-fireworks
ports:
- "8321:8321"
environment:
- FIREWORKS_API_KEY=${FIREWORKS_API_KEY}
entrypoint: bash -c "python -m llama_stack.distribution.server.server --template fireworks"
deploy:
restart_policy:
condition: on-failure
delay: 3s
max_attempts: 5
window: 60s

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../../llama_stack/templates/fireworks/run.yaml

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../../llama_stack/templates/meta-reference-gpu/build.yaml

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services:
llamastack:
image: llamastack/distribution-meta-reference-gpu
network_mode: "host"
volumes:
- ~/.llama:/root/.llama
- ./run.yaml:/root/my-run.yaml
ports:
- "8321:8321"
devices:
- nvidia.com/gpu=all
environment:
- CUDA_VISIBLE_DEVICES=0
command: []
deploy:
resources:
reservations:
devices:
- driver: nvidia
# that's the closest analogue to --gpus; provide
# an integer amount of devices or 'all'
count: 1
# Devices are reserved using a list of capabilities, making
# capabilities the only required field. A device MUST
# satisfy all the requested capabilities for a successful
# reservation.
capabilities: [gpu]
restart_policy:
condition: on-failure
delay: 3s
max_attempts: 5
window: 60s
runtime: nvidia
entrypoint: bash -c "python -m llama_stack.distribution.server.server --yaml_config /root/my-run.yaml"

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../../llama_stack/templates/meta-reference-gpu/run-with-safety.yaml

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../../llama_stack/templates/meta-reference-gpu/run.yaml

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../../llama_stack/templates/meta-reference-quantized-gpu/build.yaml

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services:
llamastack:
image: llamastack/distribution-meta-reference-quantized-gpu
network_mode: "host"
volumes:
- ~/.llama:/root/.llama
- ./run.yaml:/root/my-run.yaml
ports:
- "8321:8321"
devices:
- nvidia.com/gpu=all
environment:
- CUDA_VISIBLE_DEVICES=0
command: []
deploy:
resources:
reservations:
devices:
- driver: nvidia
# that's the closest analogue to --gpus; provide
# an integer amount of devices or 'all'
count: 1
# Devices are reserved using a list of capabilities, making
# capabilities the only required field. A device MUST
# satisfy all the requested capabilities for a successful
# reservation.
capabilities: [gpu]
runtime: nvidia
entrypoint: bash -c "python -m llama_stack.distribution.server.server --yaml_config /root/my-run.yaml"
deploy:
restart_policy:
condition: on-failure
delay: 3s
max_attempts: 5
window: 60s

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version: '2'
image_name: local
container_image: null
conda_env: local
apis:
- shields
- agents
- models
- memory
- memory_banks
- inference
- safety
providers:
inference:
- provider_id: meta0
provider_type: inline::meta-reference-quantized
config:
model: Llama3.2-3B-Instruct:int4-qlora-eo8
quantization:
type: int4
torch_seed: null
max_seq_len: 2048
max_batch_size: 1
- provider_id: meta1
provider_type: inline::meta-reference-quantized
config:
# not a quantized model !
model: Llama-Guard-3-1B
quantization: null
torch_seed: null
max_seq_len: 2048
max_batch_size: 1
safety:
- provider_id: meta0
provider_type: inline::llama-guard
config:
model: Llama-Guard-3-1B
excluded_categories: []
- provider_id: meta1
provider_type: inline::prompt-guard
config:
model: Prompt-Guard-86M
memory:
- provider_id: meta0
provider_type: inline::meta-reference
config: {}
agents:
- provider_id: meta0
provider_type: inline::meta-reference
config:
persistence_store:
namespace: null
type: sqlite
db_path: ~/.llama/runtime/kvstore.db
telemetry:
- provider_id: meta0
provider_type: inline::meta-reference
config: {}

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../../llama_stack/templates/ollama/build.yaml

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services:
ollama:
image: ollama/ollama:latest
network_mode: ${NETWORK_MODE:-bridge}
volumes:
- ~/.ollama:/root/.ollama
ports:
- "11434:11434"
environment:
OLLAMA_DEBUG: 1
command: []
deploy:
resources:
limits:
memory: 8G # Set maximum memory
reservations:
memory: 8G # Set minimum memory reservation
# healthcheck:
# # ugh, no CURL in ollama image
# test: ["CMD", "curl", "-f", "http://ollama:11434"]
# interval: 10s
# timeout: 5s
# retries: 5
ollama-init:
image: ollama/ollama:latest
depends_on:
- ollama
# condition: service_healthy
network_mode: ${NETWORK_MODE:-bridge}
environment:
- OLLAMA_HOST=ollama
- INFERENCE_MODEL=${INFERENCE_MODEL}
- SAFETY_MODEL=${SAFETY_MODEL:-}
volumes:
- ~/.ollama:/root/.ollama
- ./pull-models.sh:/pull-models.sh
entrypoint: ["/pull-models.sh"]
llamastack:
depends_on:
ollama:
condition: service_started
ollama-init:
condition: service_started
image: ${LLAMA_STACK_IMAGE:-llamastack/distribution-ollama}
network_mode: ${NETWORK_MODE:-bridge}
volumes:
- ~/.llama:/root/.llama
# Link to ollama run.yaml file
- ~/local/llama-stack/:/app/llama-stack-source
- ./run${SAFETY_MODEL:+-with-safety}.yaml:/root/my-run.yaml
ports:
- "${LLAMA_STACK_PORT:-5001}:${LLAMA_STACK_PORT:-5001}"
environment:
- INFERENCE_MODEL=${INFERENCE_MODEL}
- SAFETY_MODEL=${SAFETY_MODEL:-}
- OLLAMA_URL=http://ollama:11434
entrypoint: >
python -m llama_stack.distribution.server.server /root/my-run.yaml \
--port ${LLAMA_STACK_PORT:-5001}
deploy:
restart_policy:
condition: on-failure
delay: 10s
max_attempts: 3
window: 60s
volumes:
ollama:
ollama-init:
llamastack:

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#!/bin/sh
# 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.
echo "Preloading (${INFERENCE_MODEL}, ${SAFETY_MODEL})..."
for model in ${INFERENCE_MODEL} ${SAFETY_MODEL}; do
echo "Preloading $model..."
if ! ollama run "$model"; then
echo "Failed to pull and run $model"
exit 1
fi
done
echo "All models pulled successfully"

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../../llama_stack/templates/ollama/run-with-safety.yaml

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../../llama_stack/templates/ollama/run.yaml

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../../llama_stack/templates/nvidia/build.yaml

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services:
llamastack:
image: distribution-nvidia:dev
network_mode: "host"
volumes:
- ~/.llama:/root/.llama
- ./run.yaml:/root/llamastack-run-nvidia.yaml
ports:
- "8321:8321"
environment:
- INFERENCE_MODEL=${INFERENCE_MODEL:-Llama3.1-8B-Instruct}
- NVIDIA_API_KEY=${NVIDIA_API_KEY:-}
entrypoint: bash -c "python -m llama_stack.distribution.server.server --yaml-config /root/llamastack-run-nvidia.yaml"
deploy:
restart_policy:
condition: on-failure
delay: 3s
max_attempts: 5
window: 60s

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../../llama_stack/templates/nvidia/run.yaml

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../../llama_stack/templates/remote-vllm/build.yaml

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services:
vllm-inference:
image: vllm/vllm-openai:latest
volumes:
- $HOME/.cache/huggingface:/root/.cache/huggingface
network_mode: ${NETWORK_MODE:-bridged}
ports:
- "${VLLM_INFERENCE_PORT:-5100}:${VLLM_INFERENCE_PORT:-5100}"
devices:
- nvidia.com/gpu=all
environment:
- CUDA_VISIBLE_DEVICES=${VLLM_INFERENCE_GPU:-0}
- HUGGING_FACE_HUB_TOKEN=$HF_TOKEN
command: >
--gpu-memory-utilization 0.75
--model ${VLLM_INFERENCE_MODEL:-meta-llama/Llama-3.2-3B-Instruct}
--enforce-eager
--max-model-len 8192
--max-num-seqs 16
--port ${VLLM_INFERENCE_PORT:-5100}
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:${VLLM_INFERENCE_PORT:-5100}/v1/health"]
interval: 30s
timeout: 10s
retries: 5
deploy:
resources:
reservations:
devices:
- driver: nvidia
capabilities: [gpu]
runtime: nvidia
# A little trick:
# if VLLM_SAFETY_MODEL is set, we will create a service for the safety model
# otherwise, the entry will end in a hyphen which gets ignored by docker compose
vllm-${VLLM_SAFETY_MODEL:+safety}:
image: vllm/vllm-openai:latest
volumes:
- $HOME/.cache/huggingface:/root/.cache/huggingface
network_mode: ${NETWORK_MODE:-bridged}
ports:
- "${VLLM_SAFETY_PORT:-5101}:${VLLM_SAFETY_PORT:-5101}"
devices:
- nvidia.com/gpu=all
environment:
- CUDA_VISIBLE_DEVICES=${VLLM_SAFETY_GPU:-1}
- HUGGING_FACE_HUB_TOKEN=$HF_TOKEN
command: >
--gpu-memory-utilization 0.75
--model ${VLLM_SAFETY_MODEL}
--enforce-eager
--max-model-len 8192
--max-num-seqs 16
--port ${VLLM_SAFETY_PORT:-5101}
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:${VLLM_SAFETY_PORT:-5101}/v1/health"]
interval: 30s
timeout: 10s
retries: 5
deploy:
resources:
reservations:
devices:
- driver: nvidia
capabilities: [gpu]
runtime: nvidia
llamastack:
depends_on:
- vllm-inference:
condition: service_healthy
- vllm-${VLLM_SAFETY_MODEL:+safety}:
condition: service_healthy
# image: llamastack/distribution-remote-vllm
image: llamastack/distribution-remote-vllm:test-0.0.52rc3
volumes:
- ~/.llama:/root/.llama
- ./run${VLLM_SAFETY_MODEL:+-with-safety}.yaml:/root/llamastack-run-remote-vllm.yaml
network_mode: ${NETWORK_MODE:-bridged}
environment:
- VLLM_URL=http://vllm-inference:${VLLM_INFERENCE_PORT:-5100}/v1
- VLLM_SAFETY_URL=http://vllm-safety:${VLLM_SAFETY_PORT:-5101}/v1
- INFERENCE_MODEL=${INFERENCE_MODEL:-meta-llama/Llama-3.2-3B-Instruct}
- MAX_TOKENS=${MAX_TOKENS:-4096}
- SQLITE_STORE_DIR=${SQLITE_STORE_DIR:-$HOME/.llama/distributions/remote-vllm}
- SAFETY_MODEL=${SAFETY_MODEL:-meta-llama/Llama-Guard-3-1B}
ports:
- "${LLAMA_STACK_PORT:-5001}:${LLAMA_STACK_PORT:-5001}"
# Hack: wait for vLLM server to start before starting docker
entrypoint: bash -c "sleep 60; python -m llama_stack.distribution.server.server --yaml_config /root/llamastack-run-remote-vllm.yaml --port 5001"
deploy:
restart_policy:
condition: on-failure
delay: 3s
max_attempts: 5
window: 60s
volumes:
vllm-inference:
vllm-safety:
llamastack:

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../../llama_stack/templates/remote-vllm/run-with-safety.yaml

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@ -0,0 +1 @@
../../llama_stack/templates/remote-vllm/run.yaml

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@ -0,0 +1,9 @@
name: runpod
distribution_spec:
description: Use Runpod for running LLM inference
providers:
inference: remote::runpod
memory: meta-reference
safety: meta-reference
agents: meta-reference
telemetry: meta-reference

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@ -0,0 +1 @@
../../llama_stack/templates/sambanova/build.yaml

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@ -0,0 +1,16 @@
services:
llamastack:
image: llamastack/distribution-sambanova
network_mode: "host"
volumes:
- ~/.llama:/root/.llama
- ./run.yaml:/root/llamastack-run-sambanova.yaml
ports:
- "5000:5000"
entrypoint: bash -c "python -m llama_stack.distribution.server.server --yaml_config /root/llamastack-run-sambanova.yaml"
deploy:
restart_policy:
condition: on-failure
delay: 3s
max_attempts: 5
window: 60s

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@ -0,0 +1 @@
../../llama_stack/templates/sambanova/run.yaml

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@ -0,0 +1 @@
../../llama_stack/templates/tgi/build.yaml

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services:
tgi-inference:
image: ghcr.io/huggingface/text-generation-inference:latest
volumes:
- $HOME/.cache/huggingface:/data
network_mode: ${NETWORK_MODE:-bridged}
ports:
- "${TGI_INFERENCE_PORT:-8080}:${TGI_INFERENCE_PORT:-8080}"
devices:
- nvidia.com/gpu=all
environment:
- CUDA_VISIBLE_DEVICES=${TGI_INFERENCE_GPU:-0}
- HF_TOKEN=$HF_TOKEN
- HF_HOME=/data
- HF_DATASETS_CACHE=/data
- HF_MODULES_CACHE=/data
- HF_HUB_CACHE=/data
command: >
--dtype bfloat16
--usage-stats off
--sharded false
--model-id ${TGI_INFERENCE_MODEL:-meta-llama/Llama-3.2-3B-Instruct}
--port ${TGI_INFERENCE_PORT:-8080}
--cuda-memory-fraction 0.75
healthcheck:
test: ["CMD", "curl", "-f", "http://tgi-inference:${TGI_INFERENCE_PORT:-8080}/health"]
interval: 5s
timeout: 5s
retries: 30
deploy:
resources:
reservations:
devices:
- driver: nvidia
capabilities: [gpu]
runtime: nvidia
tgi-${TGI_SAFETY_MODEL:+safety}:
image: ghcr.io/huggingface/text-generation-inference:latest
volumes:
- $HOME/.cache/huggingface:/data
network_mode: ${NETWORK_MODE:-bridged}
ports:
- "${TGI_SAFETY_PORT:-8081}:${TGI_SAFETY_PORT:-8081}"
devices:
- nvidia.com/gpu=all
environment:
- CUDA_VISIBLE_DEVICES=${TGI_SAFETY_GPU:-1}
- HF_TOKEN=$HF_TOKEN
- HF_HOME=/data
- HF_DATASETS_CACHE=/data
- HF_MODULES_CACHE=/data
- HF_HUB_CACHE=/data
command: >
--dtype bfloat16
--usage-stats off
--sharded false
--model-id ${TGI_SAFETY_MODEL:-meta-llama/Llama-Guard-3-1B}
--port ${TGI_SAFETY_PORT:-8081}
--cuda-memory-fraction 0.75
healthcheck:
test: ["CMD", "curl", "-f", "http://tgi-safety:${TGI_SAFETY_PORT:-8081}/health"]
interval: 5s
timeout: 5s
retries: 30
deploy:
resources:
reservations:
devices:
- driver: nvidia
capabilities: [gpu]
runtime: nvidia
llamastack:
depends_on:
tgi-inference:
condition: service_healthy
tgi-${TGI_SAFETY_MODEL:+safety}:
condition: service_healthy
image: llamastack/distribution-tgi:test-0.0.52rc3
network_mode: ${NETWORK_MODE:-bridged}
volumes:
- ~/.llama:/root/.llama
- ./run${TGI_SAFETY_MODEL:+-with-safety}.yaml:/root/my-run.yaml
ports:
- "${LLAMA_STACK_PORT:-5001}:${LLAMA_STACK_PORT:-5001}"
# Hack: wait for TGI server to start before starting docker
entrypoint: bash -c "sleep 60; python -m llama_stack.distribution.server.server --yaml_config /root/my-run.yaml"
restart_policy:
condition: on-failure
delay: 3s
max_attempts: 5
window: 60s
environment:
- TGI_URL=http://tgi-inference:${TGI_INFERENCE_PORT:-8080}
- SAFETY_TGI_URL=http://tgi-safety:${TGI_SAFETY_PORT:-8081}
- INFERENCE_MODEL=${INFERENCE_MODEL:-meta-llama/Llama-3.2-3B-Instruct}
- SAFETY_MODEL=${SAFETY_MODEL:-meta-llama/Llama-Guard-3-1B}
volumes:
tgi-inference:
tgi-safety:
llamastack:

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@ -0,0 +1 @@
../../llama_stack/templates/tgi/run-with-safety.yaml

1
distributions/tgi/run.yaml Symbolic link
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@ -0,0 +1 @@
../../llama_stack/templates/tgi/run.yaml

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@ -0,0 +1 @@
../../llama_stack/templates/together/build.yaml

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@ -0,0 +1,14 @@
services:
llamastack:
image: llamastack/distribution-together
ports:
- "8321:8321"
environment:
- TOGETHER_API_KEY=${TOGETHER_API_KEY}
entrypoint: bash -c "python -m llama_stack.distribution.server.server --template together"
deploy:
restart_policy:
condition: on-failure
delay: 3s
max_attempts: 5
window: 60s

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@ -0,0 +1 @@
../../llama_stack/templates/together/run.yaml

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@ -0,0 +1 @@
../../llama_stack/templates/inline-vllm/build.yaml

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@ -0,0 +1,35 @@
services:
llamastack:
image: llamastack/distribution-inline-vllm
network_mode: "host"
volumes:
- ~/.llama:/root/.llama
- ./run.yaml:/root/my-run.yaml
ports:
- "8321:8321"
devices:
- nvidia.com/gpu=all
environment:
- CUDA_VISIBLE_DEVICES=0
command: []
deploy:
resources:
reservations:
devices:
- driver: nvidia
# that's the closest analogue to --gpus; provide
# an integer amount of devices or 'all'
count: 1
# Devices are reserved using a list of capabilities, making
# capabilities the only required field. A device MUST
# satisfy all the requested capabilities for a successful
# reservation.
capabilities: [gpu]
runtime: nvidia
entrypoint: bash -c "python -m llama_stack.distribution.server.server --yaml_config /root/my-run.yaml"
deploy:
restart_policy:
condition: on-failure
delay: 3s
max_attempts: 5
window: 60s

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@ -0,0 +1,66 @@
version: '2'
image_name: local
container_image: null
conda_env: local
apis:
- shields
- agents
- models
- memory
- memory_banks
- inference
- safety
providers:
inference:
- provider_id: vllm-inference
provider_type: inline::vllm
config:
model: Llama3.2-3B-Instruct
tensor_parallel_size: 1
gpu_memory_utilization: 0.4
enforce_eager: true
max_tokens: 4096
- provider_id: vllm-inference-safety
provider_type: inline::vllm
config:
model: Llama-Guard-3-1B
tensor_parallel_size: 1
gpu_memory_utilization: 0.2
enforce_eager: true
max_tokens: 4096
safety:
- provider_id: meta0
provider_type: inline::llama-guard
config:
model: Llama-Guard-3-1B
excluded_categories: []
# Uncomment to use prompt guard
# - provider_id: meta1
# provider_type: inline::prompt-guard
# config:
# model: Prompt-Guard-86M
memory:
- provider_id: meta0
provider_type: inline::meta-reference
config: {}
# Uncomment to use pgvector
# - provider_id: pgvector
# provider_type: remote::pgvector
# config:
# host: 127.0.0.1
# port: 5432
# db: postgres
# user: postgres
# password: mysecretpassword
agents:
- provider_id: meta0
provider_type: inline::meta-reference
config:
persistence_store:
namespace: null
type: sqlite
db_path: ~/.llama/runtime/agents_store.db
telemetry:
- provider_id: meta0
provider_type: inline::meta-reference
config: {}

View file

@ -16,20 +16,3 @@
.hide-title h1 {
display: none;
}
h2, h3, h4 {
font-weight: normal;
}
html[data-theme="dark"] .rst-content div[class^="highlight"] {
background-color: #0b0b0b;
}
pre {
white-space: pre-wrap !important;
word-break: break-all;
}
[data-theme="dark"] .mermaid {
background-color: #f4f4f6 !important;
border-radius: 6px;
padding: 0.5em;
}

View file

@ -1,32 +0,0 @@
document.addEventListener("DOMContentLoaded", function () {
const prefersDark = window.matchMedia("(prefers-color-scheme: dark)").matches;
const htmlElement = document.documentElement;
// Check if theme is saved in localStorage
const savedTheme = localStorage.getItem("sphinx-rtd-theme");
if (savedTheme) {
// Use the saved theme preference
htmlElement.setAttribute("data-theme", savedTheme);
document.body.classList.toggle("dark", savedTheme === "dark");
} else {
// Fall back to system preference
const theme = prefersDark ? "dark" : "light";
htmlElement.setAttribute("data-theme", theme);
document.body.classList.toggle("dark", theme === "dark");
// Save initial preference
localStorage.setItem("sphinx-rtd-theme", theme);
}
// Listen for theme changes from the existing toggle
const observer = new MutationObserver(function(mutations) {
mutations.forEach(function(mutation) {
if (mutation.attributeName === "data-theme") {
const currentTheme = htmlElement.getAttribute("data-theme");
localStorage.setItem("sphinx-rtd-theme", currentTheme);
}
});
});
observer.observe(htmlElement, { attributes: true });
});

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@ -1,14 +0,0 @@
document.addEventListener('keydown', function(event) {
// command+K or ctrl+K
if ((event.metaKey || event.ctrlKey) && event.key === 'k') {
event.preventDefault();
document.querySelector('.search-input, .search-field, input[name="q"]').focus();
}
// forward slash
if (event.key === '/' &&
!event.target.matches('input, textarea, select')) {
event.preventDefault();
document.querySelector('.search-input, .search-field, input[name="q"]').focus();
}
});

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@ -4,21 +4,6 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import os
import time
def pytest_collection_modifyitems(items):
for item in items:
item.name = item.name.replace(' ', '_')
def pytest_runtest_teardown(item):
interval_seconds = os.getenv("LLAMA_STACK_TEST_INTERVAL_SECONDS")
if interval_seconds:
time.sleep(float(interval_seconds))
def pytest_configure(config):
config.option.tbstyle = "short"
config.option.disable_warnings = True

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@ -1,35 +1,35 @@
@ECHO OFF
pushd %~dp0
REM Command file for Sphinx documentation
if "%SPHINXBUILD%" == "" (
set SPHINXBUILD=sphinx-build
)
set SOURCEDIR=.
set BUILDDIR=_build
%SPHINXBUILD% >NUL 2>NUL
if errorlevel 9009 (
echo.
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
echo.installed, then set the SPHINXBUILD environment variable to point
echo.to the full path of the 'sphinx-build' executable. Alternatively you
echo.may add the Sphinx directory to PATH.
echo.
echo.If you don't have Sphinx installed, grab it from
echo.https://www.sphinx-doc.org/
exit /b 1
)
if "%1" == "" goto help
%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
goto end
:help
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
:end
popd
@ECHO OFF
pushd %~dp0
REM Command file for Sphinx documentation
if "%SPHINXBUILD%" == "" (
set SPHINXBUILD=sphinx-build
)
set SOURCEDIR=.
set BUILDDIR=_build
%SPHINXBUILD% >NUL 2>NUL
if errorlevel 9009 (
echo.
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
echo.installed, then set the SPHINXBUILD environment variable to point
echo.to the full path of the 'sphinx-build' executable. Alternatively you
echo.may add the Sphinx directory to PATH.
echo.
echo.If you don't have Sphinx installed, grab it from
echo.https://www.sphinx-doc.org/
exit /b 1
)
if "%1" == "" goto help
%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
goto end
:help
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
:end
popd

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