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# Core Concepts
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```{toctree}
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:maxdepth: 1
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:hidden:
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evaluation_concepts
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```
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Given Llama Stack's service-oriented philosophy, a few concepts and workflows arise which may not feel completely natural in the LLM landscape, especially if you are coming with a background in other frameworks.
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@ -26,7 +34,7 @@ We are working on adding a few more APIs to complete the application lifecycle.
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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., Fireworks, Together, AWS Bedrock, Groq, Cerebras, SambaNova, vLLM, etc.),
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- Vector databases (e.g., ChromaDB, Weaviate, Qdrant, FAISS, PGVector, etc.),
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- Vector databases (e.g., ChromaDB, Weaviate, Qdrant, Milvus, FAISS, PGVector, etc.),
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- Safety providers (e.g., Meta's Llama Guard, AWS Bedrock Guardrails, etc.)
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Providers come in two flavors:
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