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# What does this PR do? This adds some initial content documenting our OpenAI compatible APIs - Responses, Chat Completions, Completions, and Models - along with instructions on how to use them via OpenAI or Llama Stack clients and some simple examples for each. It's not a lot of content, but it's a start so that users have some idea how to get going as we continue to work on these APIs. ## Test Plan I generated the docs site locally and verified things render properly. I also ran each code example to ensure it works as expected. And, I asked my AI code assistant to do a quick spell-check and review of the docs and it didn't flag any obvious errors. --------- Signed-off-by: Ben Browning <bbrownin@redhat.com> Co-authored-by: Francisco Arceo <farceo@redhat.com>
113 lines
5.3 KiB
Markdown
113 lines
5.3 KiB
Markdown
# Llama Stack
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Welcome to Llama Stack, the open-source framework for building generative AI applications.
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```{admonition} Llama 4 is here!
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:class: tip
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Check out [Getting Started with Llama 4](https://colab.research.google.com/github/meta-llama/llama-stack/blob/main/docs/getting_started_llama4.ipynb)
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```
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```{admonition} News
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:class: tip
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Llama Stack {{ llama_stack_version }} is now available! See the {{ llama_stack_version_link }} for more details.
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```
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## What is Llama Stack?
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Llama Stack defines and standardizes the core building blocks needed to bring generative AI applications to market. It provides a unified set of APIs with implementations from leading service providers, enabling seamless transitions between development and production environments. More specifically, it provides
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- **Unified API layer** for Inference, RAG, Agents, Tools, Safety, Evals, and Telemetry.
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- **Plugin architecture** to support the rich ecosystem of implementations of the different APIs in different environments like local development, on-premises, cloud, and mobile.
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- **Prepackaged verified distributions** which offer a one-stop solution for developers to get started quickly and reliably in any environment
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- **Multiple developer interfaces** like CLI and SDKs for Python, Node, iOS, and Android
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- **Standalone applications** as examples for how to build production-grade AI applications with Llama Stack
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```{image} ../_static/llama-stack.png
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:alt: Llama Stack
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:width: 400px
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```
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Our goal is to provide pre-packaged implementations (aka "distributions") which can be run in a variety of deployment environments. LlamaStack can assist you in your entire app development lifecycle - start iterating on local, mobile or desktop and seamlessly transition to on-prem or public cloud deployments. At every point in this transition, the same set of APIs and the same developer experience is available.
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## How does Llama Stack work?
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Llama Stack consists of a [server](./distributions/index.md) (with multiple pluggable API [providers](./providers/index.md)) and Client SDKs (see below) meant to
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be used in your applications. The server can be run in a variety of environments, including local (inline)
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development, on-premises, and cloud. The client SDKs are available for Python, Swift, Node, and
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Kotlin.
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## Quick Links
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- Ready to build? Check out the [Quick Start](getting_started/index) to get started.
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- Want to contribute? See the [Contributing](contributing/index) guide.
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## Client SDKs
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We have a number of client-side SDKs available for different languages.
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| **Language** | **Client SDK** | **Package** |
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| :----: | :----: | :----: |
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| Python | [llama-stack-client-python](https://github.com/meta-llama/llama-stack-client-python) | [](https://pypi.org/project/llama_stack_client/)
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| Swift | [llama-stack-client-swift](https://github.com/meta-llama/llama-stack-client-swift/tree/latest-release) | [](https://swiftpackageindex.com/meta-llama/llama-stack-client-swift)
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| Node | [llama-stack-client-node](https://github.com/meta-llama/llama-stack-client-node) | [](https://npmjs.org/package/llama-stack-client)
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| Kotlin | [llama-stack-client-kotlin](https://github.com/meta-llama/llama-stack-client-kotlin/tree/latest-release) | [](https://central.sonatype.com/artifact/com.llama.llamastack/llama-stack-client-kotlin)
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## Supported Llama Stack Implementations
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A number of "adapters" are available for some popular Inference and Vector Store providers. For other APIs (particularly Safety and Agents), we provide *reference implementations* you can use to get started. We expect this list to grow over time. We are slowly onboarding more providers to the ecosystem as we get more confidence in the APIs.
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**Inference API**
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| **Provider** | **Environments** |
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| :----: | :----: |
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| Meta Reference | Single Node |
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| Ollama | Single Node |
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| Fireworks | Hosted |
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| Together | Hosted |
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| NVIDIA NIM | Hosted and Single Node |
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| vLLM | Hosted and Single Node |
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| TGI | Hosted and Single Node |
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| AWS Bedrock | Hosted |
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| Cerebras | Hosted |
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| Groq | Hosted |
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| SambaNova | Hosted |
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| PyTorch ExecuTorch | On-device iOS, Android |
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| OpenAI | Hosted |
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| Anthropic | Hosted |
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| Gemini | Hosted |
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**Vector IO API**
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| **Provider** | **Environments** |
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| :----: | :----: |
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| FAISS | Single Node |
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| SQLite-Vec| Single Node |
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| Chroma | Hosted and Single Node |
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| Milvus | Hosted and Single Node |
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| Postgres (PGVector) | Hosted and Single Node |
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| Weaviate | Hosted |
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**Safety API**
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| **Provider** | **Environments** |
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| :----: | :----: |
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| Llama Guard | Depends on Inference Provider |
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| Prompt Guard | Single Node |
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| Code Scanner | Single Node |
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| AWS Bedrock | Hosted |
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```{toctree}
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:hidden:
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:maxdepth: 3
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self
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getting_started/index
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getting_started/detailed_tutorial
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introduction/index
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concepts/index
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openai/index
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providers/index
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distributions/index
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building_applications/index
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playground/index
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contributing/index
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references/index
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```
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