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docs/docs/providers/agents/index.mdx
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--- ---
description: "Agents API for creating and interacting with agentic systems. description: "Agents API for creating and interacting with agentic systems.
Main functionalities provided by this API: Main functionalities provided by this API:
- Create agents with specific instructions and ability to use tools. - Create agents with specific instructions and ability to use tools.
- Interactions with agents are grouped into sessions (\"threads\"), and each interaction is called a \"turn\". - Interactions with agents are grouped into sessions (\"threads\"), and each interaction is called a \"turn\".
- Agents can be provided with various tools (see the ToolGroups and ToolRuntime APIs for more details). - Agents can be provided with various tools (see the ToolGroups and ToolRuntime APIs for more details).
- Agents can be provided with various shields (see the Safety API for more details). - Agents can be provided with various shields (see the Safety API for more details).
- Agents can also use Memory to retrieve information from knowledge bases. See the RAG Tool and Vector IO APIs for more details." - Agents can also use Memory to retrieve information from knowledge bases. See the RAG Tool and Vector IO APIs for more details."
sidebar_label: Agents sidebar_label: Agents
title: Agents title: Agents
--- ---
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Agents API for creating and interacting with agentic systems. Agents API for creating and interacting with agentic systems.
Main functionalities provided by this API: Main functionalities provided by this API:
- Create agents with specific instructions and ability to use tools. - Create agents with specific instructions and ability to use tools.
- Interactions with agents are grouped into sessions ("threads"), and each interaction is called a "turn". - Interactions with agents are grouped into sessions ("threads"), and each interaction is called a "turn".
- Agents can be provided with various tools (see the ToolGroups and ToolRuntime APIs for more details). - Agents can be provided with various tools (see the ToolGroups and ToolRuntime APIs for more details).
- Agents can be provided with various shields (see the Safety API for more details). - Agents can be provided with various shields (see the Safety API for more details).
- Agents can also use Memory to retrieve information from knowledge bases. See the RAG Tool and Vector IO APIs for more details. - Agents can also use Memory to retrieve information from knowledge bases. See the RAG Tool and Vector IO APIs for more details.
This section contains documentation for all available providers for the **agents** API. This section contains documentation for all available providers for the **agents** API.

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docs/docs/providers/batches/index.mdx
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--- ---
description: "The Batches API enables efficient processing of multiple requests in a single operation, description: "The Batches API enables efficient processing of multiple requests in a single operation,
particularly useful for processing large datasets, batch evaluation workflows, and particularly useful for processing large datasets, batch evaluation workflows, and
cost-effective inference at scale. cost-effective inference at scale.
The API is designed to allow use of openai client libraries for seamless integration. The API is designed to allow use of openai client libraries for seamless integration.
This API provides the following extensions: This API provides the following extensions:
- idempotent batch creation - idempotent batch creation
Note: This API is currently under active development and may undergo changes." Note: This API is currently under active development and may undergo changes."
sidebar_label: Batches sidebar_label: Batches
title: Batches title: Batches
--- ---
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## Overview ## Overview
The Batches API enables efficient processing of multiple requests in a single operation, The Batches API enables efficient processing of multiple requests in a single operation,
particularly useful for processing large datasets, batch evaluation workflows, and particularly useful for processing large datasets, batch evaluation workflows, and
cost-effective inference at scale. cost-effective inference at scale.
The API is designed to allow use of openai client libraries for seamless integration. The API is designed to allow use of openai client libraries for seamless integration.
This API provides the following extensions: This API provides the following extensions:
- idempotent batch creation - idempotent batch creation
Note: This API is currently under active development and may undergo changes. Note: This API is currently under active development and may undergo changes.
This section contains documentation for all available providers for the **batches** API. This section contains documentation for all available providers for the **batches** API.

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docs/docs/providers/inference/index.mdx
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--- ---
description: "Llama Stack Inference API for generating completions, chat completions, and embeddings. description: "Llama Stack Inference API for generating completions, chat completions, and embeddings.
This API provides the raw interface to the underlying models. Two kinds of models are supported: This API provides the raw interface to the underlying models. Two kinds of models are supported:
- LLM models: these models generate \"raw\" and \"chat\" (conversational) completions. - LLM models: these models generate \"raw\" and \"chat\" (conversational) completions.
- Embedding models: these models generate embeddings to be used for semantic search." - Embedding models: these models generate embeddings to be used for semantic search."
sidebar_label: Inference sidebar_label: Inference
title: Inference title: Inference
--- ---
@ -14,8 +14,8 @@ title: Inference
Llama Stack Inference API for generating completions, chat completions, and embeddings. Llama Stack Inference API for generating completions, chat completions, and embeddings.
This API provides the raw interface to the underlying models. Two kinds of models are supported: This API provides the raw interface to the underlying models. Two kinds of models are supported:
- LLM models: these models generate "raw" and "chat" (conversational) completions. - LLM models: these models generate "raw" and "chat" (conversational) completions.
- Embedding models: these models generate embeddings to be used for semantic search. - Embedding models: these models generate embeddings to be used for semantic search.
This section contains documentation for all available providers for the **inference** API. This section contains documentation for all available providers for the **inference** API.