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30 lines
1.6 KiB
Markdown
30 lines
1.6 KiB
Markdown
---
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sidebar_position: 2
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title: Agent Overview
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sidebar_label: Agent Overview
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slug: /agent_overview
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sidebar_custom_props: {
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categoryIcon: RagAiAgent
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}
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---
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# Agent Overview
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## Purpose of Agent
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Agent is the business workflow orchestration capability in RAGFlow. Users can add components on a no-code canvas and define execution order via connections. Components can be executed sequentially, or enter different paths according to conditional branches, classification results or loop logic.
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Agents are commonly used in the following scenarios:
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- Answering user questions based on knowledge bases.
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- Identifying user intents and routing to different processing flows.
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- Calling HTTP interfaces, databases, MCP tools or custom code.
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- Splitting and batch processing long texts.
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- Saving session memory or exporting processing results.
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## Relationship Between Agent and Knowledge Base Q&A
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- **Chat**: Suitable for applications mainly based on knowledge base Q&A and multi-turn dialogue.
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- **Agent**: Suitable for business workflows requiring conditional branching, tool calling, data processing or multi-step orchestration.
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The `Retrieval` component can be used inside an Agent to query knowledge bases. Retrieval can also be used as a tool under the Agent component, allowing the LLM to autonomously decide when to perform retrieval.
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For example, an after-sales Agent can first use `Categorize` to judge the type of user questions, then use `Retrieval` to query product materials. If the user requests installation reservation, an HTTP request is used to call the external work order system. Finally, the `Message` component outputs the result.
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