LangChain 代码节点方法(LangChain Code node methods)#

n8n 提供了这些方法，以便在 LangChain 代码节点中更轻松地执行常见任务。

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

仅限 LangChain 代码节点

这些变量用于在 LangChain 代码节点中的表达式中使用。你不能在其他节点中使用它们。

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.