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LangChain 代码节点方法#

¥LangChain Code node methods

n8n 提供了这些方法,以便更轻松地在 LangChain 代码节点 中执行常见任务。

¥n8n provides these methods to make it easier to perform common tasks in the LangChain Code node.

LangChain Code node only

这些变量用于 LangChain Code 节点中的表达式。其他节点中不能使用。

¥These variables are for use in expressions in the LangChain Code node. You can't use them in other nodes.

Method Description
this.addInputData(inputName, data) Populate the data of a specified non-main input. Useful for mocking data.
  • inputName is the input connection type, and must be one of: ai_agent, ai_chain, ai_document, ai_embedding, ai_languageModel, ai_memory, ai_outputParser, ai_retriever, ai_textSplitter, ai_tool, ai_vectorRetriever, ai_vectorStore
  • data contains the data you want to add. Refer to Data structure for information on the data structure expected by n8n.
this.addOutputData(outputName, data) Populate the data of a specified non-main output. Useful for mocking data.
  • outputName is the input connection type, and must be one of: ai_agent, ai_chain, ai_document, ai_embedding, ai_languageModel, ai_memory, ai_outputParser, ai_retriever, ai_textSplitter, ai_tool, ai_vectorRetriever, ai_vectorStore
  • data contains the data you want to add. Refer to Data structure for information on the data structure expected by n8n.
this.getInputConnectionData(inputName, itemIndex, inputIndex?) Get data from a specified non-main input.
  • inputName is the input connection type, and must be one of: ai_agent, ai_chain, ai_document, ai_embedding, ai_languageModel, ai_memory, ai_outputParser, ai_retriever, ai_textSplitter, ai_tool, ai_vectorRetriever, ai_vectorStore
  • itemIndex should always be 0 (this parameter will be used in upcoming functionality)
  • Use inputIndex if there is more than one node connected to the specified input.
this.getInputData(inputIndex?, inputName?) Get data from the main input.
this.getNode() Get the current node.
this.getNodeOutputs() Get the outputs of the current node.
this.getExecutionCancelSignal() Use this to stop the execution of a function when the workflow stops. In most cases n8n handles this, but you may need to use it if building your own chains or agents. It replaces the Cancelling a running LLMChain code that you'd use if building a LangChain application normally.