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Raghotham Murthy 2025-08-26 18:29:17 -07:00
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docs/source/building_applications/responses_vs_agents.md
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Llama Stack (LLS) provides two different APIs for building AI applications with tool calling capabilities: the **Agents API** and the **OpenAI Responses API**. While both enable AI systems to use tools, and maintain full conversation history, they serve different use cases and have distinct characteristics.
```{note}
For simple and basic inferencing, you may want to use the [Chat Completions API](https://llama-stack.readthedocs.io/en/latest/providers/index.html#chat-completions) directly, before progressing to Agents or Responses API.
**Note:** For simple and basic inferencing, you may want to use the [Chat Completions API](../providers/openai.md#chat-completions) directly, before progressing to Agents or Responses API.
```
## Overview
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## For More Information
- **LLS Agents API**: For detailed information on creating and managing agents, see the [Agents documentation](https://llama-stack.readthedocs.io/en/latest/building_applications/agent.html)
- **LLS Agents API**: For detailed information on creating and managing agents, see the [Agents documentation](agent.md)
- **OpenAI Responses API**: For information on using the OpenAI-compatible responses API, see the [OpenAI API documentation](https://platform.openai.com/docs/api-reference/responses)
- **Chat Completions API**: For the default backend API used by Agents, see the [Chat Completions providers documentation](https://llama-stack.readthedocs.io/en/latest/providers/index.html#chat-completions)
- **Agent Execution Loop**: For understanding how agents process turns and steps in their execution, see the [Agent Execution Loop documentation](https://llama-stack.readthedocs.io/en/latest/building_applications/agent_execution_loop.html)
- **Chat Completions API**: For the default backend API used by Agents, see the [Chat Completions providers documentation](../providers/openai.md#chat-completions)
- **Agent Execution Loop**: For understanding how agents process turns and steps in their execution, see the [Agent Execution Loop documentation](agent_execution_loop.md)