| Name | llama-stack JSON |
| Version |
0.2.20
JSON |
| download |
| home_page | None |
| Summary | Llama Stack |
| upload_time | 2025-08-29 21:10:22 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.12 |
| license | MIT |
| keywords |
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| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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| coveralls test coverage |
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# Llama Stack
[](https://pypi.org/project/llama_stack/)
[](https://pypi.org/project/llama-stack/)
[](https://github.com/meta-llama/llama-stack/blob/main/LICENSE)
[](https://discord.gg/llama-stack)
[](https://github.com/meta-llama/llama-stack/actions/workflows/unit-tests.yml?query=branch%3Amain)
[](https://github.com/meta-llama/llama-stack/actions/workflows/integration-tests.yml?query=branch%3Amain)
[**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
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, and Telemetry.
- **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.
<div style="text-align: center;">
<img
src="https://github.com/user-attachments/assets/33d9576d-95ea-468d-95e2-8fa233205a50"
width="480"
title="Llama Stack"
alt="Llama Stack"
/>
</div>
### 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](https://llama-stack.readthedocs.io/en/latest/providers/index.html)
| 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.
### 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](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) | |
### Documentation
Please checkout our [Documentation](https://llama-stack.readthedocs.io/en/latest/index.html) page for more details.
* CLI references
* [llama (server-side) CLI Reference](https://llama-stack.readthedocs.io/en/latest/references/llama_cli_reference/index.html): Guide for using the `llama` CLI to work with Llama models (download, study prompts), and building/starting a Llama Stack distribution.
* [llama (client-side) CLI Reference](https://llama-stack.readthedocs.io/en/latest/references/llama_stack_client_cli_reference.html): Guide for using the `llama-stack-client` CLI, which allows you to query information about the distribution.
* Getting Started
* [Quick guide to start a Llama Stack server](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html).
* [Jupyter notebook](./docs/getting_started.ipynb) to walk-through how to use simple text and vision inference llama_stack_client APIs
* The complete Llama Stack lesson [Colab notebook](https://colab.research.google.com/drive/1dtVmxotBsI4cGZQNsJRYPrLiDeT0Wnwt) of the new [Llama 3.2 course on Deeplearning.ai](https://learn.deeplearning.ai/courses/introducing-multimodal-llama-3-2/lesson/8/llama-stack).
* A [Zero-to-Hero Guide](https://github.com/meta-llama/llama-stack/tree/main/docs/zero_to_hero_guide) that guide you through all the key components of llama stack with code samples.
* [Contributing](CONTRIBUTING.md)
* [Adding a new API Provider](https://llama-stack.readthedocs.io/en/latest/contributing/new_api_provider.html) to walk-through how to add a new API provider.
### Llama Stack Client SDKs
| **Language** | **Client SDK** | **Package** |
| :----: | :----: | :----: |
| Python | [llama-stack-client-python](https://github.com/meta-llama/llama-stack-client-python) | [](https://pypi.org/project/llama_stack_client/)
| Swift | [llama-stack-client-swift](https://github.com/meta-llama/llama-stack-client-swift) | [](https://swiftpackageindex.com/meta-llama/llama-stack-client-swift)
| Typescript | [llama-stack-client-typescript](https://github.com/meta-llama/llama-stack-client-typescript) | [](https://npmjs.org/package/llama-stack-client)
| Kotlin | [llama-stack-client-kotlin](https://github.com/meta-llama/llama-stack-client-kotlin) | [](https://central.sonatype.com/artifact/com.llama.llamastack/llama-stack-client-kotlin)
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
[](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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"description": "# Llama Stack\n\n[](https://pypi.org/project/llama_stack/)\n[](https://pypi.org/project/llama-stack/)\n[](https://github.com/meta-llama/llama-stack/blob/main/LICENSE)\n[](https://discord.gg/llama-stack)\n[](https://github.com/meta-llama/llama-stack/actions/workflows/unit-tests.yml?query=branch%3Amain)\n[](https://github.com/meta-llama/llama-stack/actions/workflows/integration-tests.yml?query=branch%3Amain)\n\n[**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)\n\n\n### \u2728\ud83c\udf89 Llama 4 Support \ud83c\udf89\u2728\nWe 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.\n\n<details>\n\n<summary>\ud83d\udc4b Click here to see how to run Llama 4 models on Llama Stack </summary>\n\n\\\n*Note you need 8xH100 GPU-host to run these models*\n\n```bash\npip install -U llama_stack\n\nMODEL=\"Llama-4-Scout-17B-16E-Instruct\"\n# get meta url from llama.com\nllama model download --source meta --model-id $MODEL --meta-url <META_URL>\n\n# start a llama stack server\nINFERENCE_MODEL=meta-llama/$MODEL llama stack build --run --template meta-reference-gpu\n\n# install client to interact with the server\npip install llama-stack-client\n```\n### CLI\n```bash\n# Run a chat completion\nMODEL=\"Llama-4-Scout-17B-16E-Instruct\"\n\nllama-stack-client --endpoint http://localhost:8321 \\\ninference chat-completion \\\n--model-id meta-llama/$MODEL \\\n--message \"write a haiku for meta's llama 4 models\"\n\nChatCompletionResponse(\n 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=[]),\n logprobs=None,\n 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)]\n)\n```\n### Python SDK\n```python\nfrom llama_stack_client import LlamaStackClient\n\nclient = LlamaStackClient(base_url=f\"http://localhost:8321\")\n\nmodel_id = \"meta-llama/Llama-4-Scout-17B-16E-Instruct\"\nprompt = \"Write a haiku about coding\"\n\nprint(f\"User> {prompt}\")\nresponse = client.inference.chat_completion(\n model_id=model_id,\n messages=[\n {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n {\"role\": \"user\", \"content\": prompt},\n ],\n)\nprint(f\"Assistant> {response.completion_message.content}\")\n```\nAs more providers start supporting Llama 4, you can use them in Llama Stack as well. We are adding to the list. Stay tuned!\n\n\n</details>\n\n### \ud83d\ude80 One-Line Installer \ud83d\ude80\n\nTo try Llama Stack locally, run:\n\n```bash\ncurl -LsSf https://github.com/meta-llama/llama-stack/raw/main/scripts/install.sh | bash\n```\n\n### Overview\n\nLlama Stack standardizes the core building blocks that simplify AI application development. It codifies best practices across the Llama ecosystem. More specifically, it provides\n\n- **Unified API layer** for Inference, RAG, Agents, Tools, Safety, Evals, and Telemetry.\n- **Plugin architecture** to support the rich ecosystem of different API implementations in various environments, including local development, on-premises, cloud, and mobile.\n- **Prepackaged verified distributions** which offer a one-stop solution for developers to get started quickly and reliably in any environment.\n- **Multiple developer interfaces** like CLI and SDKs for Python, Typescript, iOS, and Android.\n- **Standalone applications** as examples for how to build production-grade AI applications with Llama Stack.\n\n<div style=\"text-align: center;\">\n <img\n src=\"https://github.com/user-attachments/assets/33d9576d-95ea-468d-95e2-8fa233205a50\"\n width=\"480\"\n title=\"Llama Stack\"\n alt=\"Llama Stack\"\n />\n</div>\n\n### Llama Stack Benefits\n- **Flexible Options**: Developers can choose their preferred infrastructure without changing APIs and enjoy flexible deployment choices.\n- **Consistent Experience**: With its unified APIs, Llama Stack makes it easier to build, test, and deploy AI applications with consistent application behavior.\n- **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.\n\nBy reducing friction and complexity, Llama Stack empowers developers to focus on what they do best: building transformative generative AI applications.\n\n### API Providers\nHere is a list of the various API providers and available distributions that can help developers get started easily with Llama Stack.\nPlease checkout for [full list](https://llama-stack.readthedocs.io/en/latest/providers/index.html)\n\n| API Provider Builder | Environments | Agents | Inference | VectorIO | Safety | Telemetry | Post Training | Eval | DatasetIO |\n|:--------------------:|:------------:|:------:|:---------:|:--------:|:------:|:---------:|:-------------:|:----:|:--------:|\n| Meta Reference | Single Node | \u2705 | \u2705 | \u2705 | \u2705 | \u2705 | \u2705 | \u2705 | \u2705 |\n| SambaNova | Hosted | | \u2705 | | \u2705 | | | | |\n| Cerebras | Hosted | | \u2705 | | | | | | |\n| Fireworks | Hosted | \u2705 | \u2705 | \u2705 | | | | | |\n| AWS Bedrock | Hosted | | \u2705 | | \u2705 | | | | |\n| Together | Hosted | \u2705 | \u2705 | | \u2705 | | | | |\n| Groq | Hosted | | \u2705 | | | | | | |\n| Ollama | Single Node | | \u2705 | | | | | | |\n| TGI | Hosted/Single Node | | \u2705 | | | | | | |\n| NVIDIA NIM | Hosted/Single Node | | \u2705 | | \u2705 | | | | |\n| ChromaDB | Hosted/Single Node | | | \u2705 | | | | | |\n| Milvus | Hosted/Single Node | | | \u2705 | | | | | |\n| Qdrant | Hosted/Single Node | | | \u2705 | | | | | |\n| Weaviate | Hosted/Single Node | | | \u2705 | | | | | |\n| SQLite-vec | Single Node | | | \u2705 | | | | | |\n| PG Vector | Single Node | | | \u2705 | | | | | |\n| PyTorch ExecuTorch | On-device iOS | \u2705 | \u2705 | | | | | | |\n| vLLM | Single Node | | \u2705 | | | | | | |\n| OpenAI | Hosted | | \u2705 | | | | | | |\n| Anthropic | Hosted | | \u2705 | | | | | | |\n| Gemini | Hosted | | \u2705 | | | | | | |\n| WatsonX | Hosted | | \u2705 | | | | | | |\n| HuggingFace | Single Node | | | | | | \u2705 | | \u2705 |\n| TorchTune | Single Node | | | | | | \u2705 | | |\n| NVIDIA NEMO | Hosted | | \u2705 | \u2705 | | | \u2705 | \u2705 | \u2705 |\n| NVIDIA | Hosted | | | | | | \u2705 | \u2705 | \u2705 |\n\n> **Note**: Additional providers are available through external packages. See [External Providers](https://llama-stack.readthedocs.io/en/latest/providers/external.html) documentation.\n\n### Distributions\n\nA 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.\nHere are some of the distributions we support:\n\n| **Distribution** | **Llama Stack Docker** | Start This Distribution |\n|:---------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------:|\n| 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) |\n| 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) |\n| PostgreSQL | [llamastack/distribution-postgres-demo](https://hub.docker.com/repository/docker/llamastack/distribution-postgres-demo/general) | |\n\n### Documentation\n\nPlease checkout our [Documentation](https://llama-stack.readthedocs.io/en/latest/index.html) page for more details.\n\n* CLI references\n * [llama (server-side) CLI Reference](https://llama-stack.readthedocs.io/en/latest/references/llama_cli_reference/index.html): Guide for using the `llama` CLI to work with Llama models (download, study prompts), and building/starting a Llama Stack distribution.\n * [llama (client-side) CLI Reference](https://llama-stack.readthedocs.io/en/latest/references/llama_stack_client_cli_reference.html): Guide for using the `llama-stack-client` CLI, which allows you to query information about the distribution.\n* Getting Started\n * [Quick guide to start a Llama Stack server](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html).\n * [Jupyter notebook](./docs/getting_started.ipynb) to walk-through how to use simple text and vision inference llama_stack_client APIs\n * The complete Llama Stack lesson [Colab notebook](https://colab.research.google.com/drive/1dtVmxotBsI4cGZQNsJRYPrLiDeT0Wnwt) of the new [Llama 3.2 course on Deeplearning.ai](https://learn.deeplearning.ai/courses/introducing-multimodal-llama-3-2/lesson/8/llama-stack).\n * A [Zero-to-Hero Guide](https://github.com/meta-llama/llama-stack/tree/main/docs/zero_to_hero_guide) that guide you through all the key components of llama stack with code samples.\n* [Contributing](CONTRIBUTING.md)\n * [Adding a new API Provider](https://llama-stack.readthedocs.io/en/latest/contributing/new_api_provider.html) to walk-through how to add a new API provider.\n\n### Llama Stack Client SDKs\n\n| **Language** | **Client SDK** | **Package** |\n| :----: | :----: | :----: |\n| Python | [llama-stack-client-python](https://github.com/meta-llama/llama-stack-client-python) | [](https://pypi.org/project/llama_stack_client/)\n| Swift | [llama-stack-client-swift](https://github.com/meta-llama/llama-stack-client-swift) | [](https://swiftpackageindex.com/meta-llama/llama-stack-client-swift)\n| Typescript | [llama-stack-client-typescript](https://github.com/meta-llama/llama-stack-client-typescript) | [](https://npmjs.org/package/llama-stack-client)\n| Kotlin | [llama-stack-client-kotlin](https://github.com/meta-llama/llama-stack-client-kotlin) | [](https://central.sonatype.com/artifact/com.llama.llamastack/llama-stack-client-kotlin)\n\nCheck 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.\n\nYou 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.\n\n\n## \ud83c\udf1f GitHub Star History\n## Star History\n\n[](https://www.star-history.com/#meta-llama/llama-stack&Date)\n\n## \u2728 Contributors\n\nThanks to all of our amazing contributors!\n\n<a href=\"https://github.com/meta-llama/llama-stack/graphs/contributors\">\n <img src=\"https://contrib.rocks/image?repo=meta-llama/llama-stack\" />\n</a>\n",
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