Composable building blocks to build Llama Apps https://llama-stack.readthedocs.io
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Derek Higgins a29253e9bf fix: access control to fail-closed when owner attributes are missing
Changed UserInOwnersList.matches() to return False instead of True when
a resource's owner attributes are None. This prevents unintended access
when resource when owner attributes arn't present.

For example, checking "user in owners teams" now returns False if the
resource has no teams attribute, rather than defaulting to True.

Changed UserIsOwner.matches() to return True when a resource has no
owner attribute set. This allows access to resources that don't use the
owner attribute.

Updated default_policy to use multiple separate "user in owners"
AccessRules instead of a single rule with multiple when clauses. With
the new fail-closed behavior, only one rule needs to match. Added a
"user is owner" rule to handle resources without attribute-based access.

Closes: #4272

Signed-off-by: Derek Higgins <derekh@redhat.com>
2025-12-02 15:39:02 +00:00
.github feat(api): oasdiff OpenAI openAPI spec against ours (#3529) 2025-12-01 15:27:08 -08:00
benchmarking/k8s-benchmark feat!: Architect Llama Stack Telemetry Around Automatic Open Telemetry Instrumentation (#4127) 2025-12-01 10:33:18 -08:00
client-sdks/stainless feat(api)!: deprecate toolgroup and tool_runtime apis (#4249) 2025-12-01 11:43:58 -08:00
containers fix(ci): use --no-cache instead of --no-cache-dir (#4081) 2025-11-05 12:14:02 -08:00
docs fix(docs): Updated the LS documentation to point users to the correct docker container (#4267) 2025-12-01 21:03:34 -08:00
scripts feat!: Architect Llama Stack Telemetry Around Automatic Open Telemetry Instrumentation (#4127) 2025-12-01 10:33:18 -08:00
src fix: access control to fail-closed when owner attributes are missing 2025-12-02 15:39:02 +00:00
tests fix: access control to fail-closed when owner attributes are missing 2025-12-02 15:39:02 +00:00
.coveragerc chore: move src/llama_stack/ui to src/llama_stack_ui (#4068) 2025-11-04 15:21:49 -08:00
.dockerignore chore: use dockerfile for building containers (#3839) 2025-10-20 10:23:01 -07:00
.gitattributes chore: mark recordings as generated files (#3816) 2025-10-15 11:06:42 -07:00
.gitignore feat(tests): add TypeScript client integration test support (#4185) 2025-11-19 10:07:53 -08:00
.pre-commit-config.yaml feat(api): oasdiff OpenAI openAPI spec against ours (#3529) 2025-12-01 15:27:08 -08:00
CODE_OF_CONDUCT.md Initial commit 2024-07-23 08:32:33 -07:00
CONTRIBUTING.md feat(openapi): switch to fastapi-based generator (#3944) 2025-11-14 15:53:53 -08:00
coverage.svg test: Measure and track code coverage (#2636) 2025-07-18 18:08:36 +02:00
LICENSE Update LICENSE (#47) 2024-08-29 07:39:50 -07:00
MANIFEST.in chore(package): migrate to src/ layout (#3920) 2025-10-27 12:02:21 -07:00
pyproject.toml refactor(storage): make { kvstore, sqlstore } as llama stack "internal" APIs (#4181) 2025-11-18 13:15:16 -08:00
README.md chore(docs): Remove Llama 4 support details from README (#4178) 2025-11-17 15:17:04 -08:00
SECURITY.md Create SECURITY.md 2024-10-08 13:30:40 -04:00
uv.lock chore: remove pyyaml and starlette duplication in pyproject (#4172) 2025-11-17 12:09:02 -08:00

Llama Stack

PyPI version PyPI - Downloads License Discord Unit Tests Integration Tests

Quick Start | Documentation | Colab Notebook | Discord

🚀 One-Line Installer 🚀

To try Llama Stack locally, run:

curl -LsSf https://github.com/llamastack/llama-stack/raw/main/scripts/install.sh | bash

Overview

Llama Stack standardizes the core building blocks that simplify AI application development. It codifies best practices across the Llama ecosystem. More specifically, it provides

  • Unified API layer for Inference, RAG, Agents, Tools, Safety, Evals.
  • Plugin architecture to support the rich ecosystem of different API implementations in various environments, including local development, on-premises, cloud, and mobile.
  • Prepackaged verified distributions which offer a one-stop solution for developers to get started quickly and reliably in any environment.
  • Multiple developer interfaces like CLI and SDKs for Python, Typescript, iOS, and Android.
  • Standalone applications as examples for how to build production-grade AI applications with Llama Stack.
Llama Stack

Llama Stack Benefits

  • Flexible Options: Developers can choose their preferred infrastructure without changing APIs and enjoy flexible deployment choices.
  • Consistent Experience: With its unified APIs, Llama Stack makes it easier to build, test, and deploy AI applications with consistent application behavior.
  • Robust Ecosystem: Llama Stack is already integrated with distribution partners (cloud providers, hardware vendors, and AI-focused companies) that offer tailored infrastructure, software, and services for deploying Llama models.

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

API Provider Builder Environments Agents Inference VectorIO Safety 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 documentation.

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:

Distribution Llama Stack Docker Start This Distribution
Starter Distribution llamastack/distribution-starter Guide
Meta Reference llamastack/distribution-meta-reference-gpu Guide
PostgreSQL llamastack/distribution-postgres-demo

Documentation

Please checkout our Documentation page for more details.

Llama Stack Client SDKs

Language Client SDK Package
Python llama-stack-client-python PyPI version
Swift llama-stack-client-swift Swift Package Index
Typescript llama-stack-client-typescript NPM version
Kotlin llama-stack-client-kotlin Maven version

Check out our client SDKs for connecting to a Llama Stack server in your preferred language, you can choose from python, typescript, swift, and 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 repo.

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Contributors

Thanks to all of our amazing contributors!