节点与集成
Think Tool
The Think Tool node is a tool1 that invites an agent2 to do some thinking before answering. Essentially, it allows the agent to reflect on the question by talking to itself before providing an answer. In particular, this is useful for complex queries that require a thoughtful response.
Templates and examples
Browse Think Tool node documentation integration templates or search all templates
Prompting example
As an example, say you ask the agent:
Jack is looking at Anne. Anne is looking at George. Jack is married, George is not, and we don't know if Anne is married. Is a married person looking at an unmarried person?
The agent will do its thinking with the tool:
We have the following information: 1. Jack is looking at Anne. 2. Anne is looking at George. 3. Jack is married. 4. George is not married. 5. We don't know if Anne is married or not.
We need to determine if a married person is looking at an unmarried person. Let's consider both cases for Anne:
Case 1: Anne is married.
- If Anne is married, then she (married) is looking at George (unmarried). In this case, a married person (Anne) is looking at an unmarried person (George).
Case 2: Anne is unmarried.
- If Anne is unmarried, then Jack (married) is looking at Anne (unmarried). In this case, a married person (Jack) is looking at an unmarried person (Anne).
In both scenarios, we find that a married person is looking at an unmarried person. Therefore, the answer to the question is yes.
and then afterward provide the answer:
Yes, a married person is looking at an unmarried person. In both possible scenarios regarding Anne's marital status, we find that a married individual (either Jack or Anne) is looking at an unmarried individual (either George or Anne).
Related resources
Refer to LangChain's documentation on tools for more information about tools in LangChain.
View n8n's Advanced AI documentation.
Footnotes
- Back
In an AI context, a tool is an add-on resource that the AI can refer to for specific information or functionality when responding to a request. The AI model can use a tool to interact with external systems or complete specific, focused tasks.
- Back
AI agents are artificial intelligence systems capable of responding to requests, making decisions, and performing real-world tasks for users. They use large language models (LLMs) to interpret user input and make decisions about how to best process requests using the information and resources they have available.
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