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**Description** This PR adjusts the external providers documentation to align with the new providers format. Splits up sections into the existing external providers and how to create them as well. <img width="1049" height="478" alt="Screenshot 2025-07-31 at 9 48 26 AM" src="https://github.com/user-attachments/assets/f13599cb-2fd1-4e57-8ca9-27b067264e33" /> Open to feedback and adjusting titles
28 lines
1.3 KiB
Markdown
28 lines
1.3 KiB
Markdown
# API Providers
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The goal of Llama Stack is to build an ecosystem where users can easily swap out different implementations for the same API. Examples for these include:
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- LLM inference providers (e.g., Meta Reference, Ollama, Fireworks, Together, AWS Bedrock, Groq, Cerebras, SambaNova, vLLM, OpenAI, Anthropic, Gemini, WatsonX, etc.),
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- Vector databases (e.g., FAISS, SQLite-Vec, ChromaDB, Weaviate, Qdrant, Milvus, PGVector, etc.),
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- Safety providers (e.g., Meta's Llama Guard, Prompt Guard, Code Scanner, AWS Bedrock Guardrails, etc.),
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- Tool Runtime providers (e.g., RAG Runtime, Brave Search, etc.)
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Providers come in two flavors:
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- **Remote**: the provider runs as a separate service external to the Llama Stack codebase. Llama Stack contains a small amount of adapter code.
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- **Inline**: the provider is fully specified and implemented within the Llama Stack codebase. It may be a simple wrapper around an existing library, or a full fledged implementation within Llama Stack.
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Importantly, Llama Stack always strives to provide at least one fully inline provider for each API so you can iterate on a fully featured environment locally.
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```{toctree}
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:maxdepth: 1
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external/index
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openai
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inference/index
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agents/index
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datasetio/index
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safety/index
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telemetry/index
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vector_io/index
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tool_runtime/index
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files/index
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```
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