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Ollama 聊天模型节点(Ollama Chat Model node)#

Ollama 聊天模型节点允许你使用本地 Llama 2 模型进行对话代理。

🌐 The Ollama Chat Model node allows you use local Llama 2 models with conversational agents.

本页提供 Ollama 聊天模型节点的节点参数以及更多资源的链接。

🌐 On this page, you'll find the node parameters for the Ollama Chat Model node, and links to more resources.

凭证

你可以在此处找到此节点的认证信息。

Parameter resolution in sub-nodes

Sub-nodes behave differently to other nodes when processing multiple items using an expression.

Most nodes, including root nodes, take any number of items as input, process these items, and output the results. You can use expressions to refer to input items, and the node resolves the expression for each item in turn. For example, given an input of five name values, the expression {{ $json.name }} resolves to each name in turn.

In sub-nodes, the expression always resolves to the first item. For example, given an input of five name values, the expression {{ $json.name }} always resolves to the first name.

节点参数(Node parameters)#

  • 模型：选择生成完成内容的模型。可从以下选项中选择：
    • Llama2
    • Llama2 13B
    • Llama2 70B
    • Llama2 未经审查

有关可用模型的更多信息，请参阅 Ollama 模型库文档。

🌐 Refer to the Ollama Models Library documentation for more information about available models.

节点选项(Node options)#

  • 采样温度：使用此选项来控制采样过程的随机性。较高的温度会产生更为多样化的采样，但也会增加出现偏差的风险。
  • Top K：输入模型用于生成下一个标记的标记选择数量。
  • Top P：使用此选项设置完成时应使用的概率。使用较低的值可以忽略不太可能的选项。

模板和示例(Templates and examples)#

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有关该服务的更多信息，请参阅 LangChains 的 Ollama 聊天模型文档。

🌐 Refer to LangChains's Ollama Chat Model documentation for more information about the service.

View n8n's Advanced AI documentation.

常见问题(Common issues)#

有关常见问题或问题及建议的解决方案，请参阅 常见问题。

🌐 For common questions or issues and suggested solutions, refer to Common issues.

Self-hosted AI Starter Kit#

New to working with AI and using self-hosted n8n? Try n8n's self-hosted AI Starter Kit to get started with a proof-of-concept or demo playground using Ollama, Qdrant, and PostgreSQL.