# LangChain

***

By themselves, language models can't take actions - they just output text.

Agents are systems that use an LLM as a reasoning enginer to determine which actions to take and what the inputs to those actions should be. The results of those actions can then be fed back into the agent and it determine whether more actions are needed, or whether it is okay to finish.

### Agent Nodes:

* [Airtable Agent](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/airtable-agent.md)
* [AutoGPT](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/autogpt.md)
* [BabyAGI](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/babyagi.md)
* [CSV Agent](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/csv-agent.md)
* [Conversational Agent](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/conversational-agent.md)
* [Conversational Retrieval Agent](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/broken-reference/README.md)
* [MistralAI Tool Agent](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/broken-reference/README.md)
* [OpenAI Assistant](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/openai-assistant/README.md)
* [OpenAI Function Agent](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/broken-reference/README.md)
* [OpenAI Tool Agent](https://github.com/innovativeSol/tailwinds-docs/blob/main/llamaindex/agents/openai-tool-agent.md)
* [ReAct Agent Chat](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/react-agent-chat.md)
* [ReAct Agent LLM](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/react-agent-llm.md)
* [Tool Agent](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/tool-agent.md)
* [XML Agent](https://github.com/innovativeSol/tailwinds-docs/blob/main/integrations/langchain/xml-agent.md)


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.