Open LLMuser opened 3 months ago
Hi @LLMuser, I'm here to help you with any questions or issues you have while waiting for a human maintainer. If you need assistance, feel free to ask!
The workflow for parameter extraction involves several key steps:
Use a Large Language Model (LLM) to infer and extract structured parameters from natural language for subsequent tool invocation or HTTP requests. The parameter extractor converts natural language into tool-recognizable parameters.
Extracting key parameters required by tools from natural language:
2405.10739
Converting text to structured data:
Extracting structured data and using the HTTP Request:
Configuration Steps:
Advanced Settings:
Inference Mode:
Memory:
Output Variables:
__is_success Number
: Extraction success status (1 for success, 0 for failure).__reason String
: Extraction error reason.sections
, and the parameter type is Array[Object]
.Detailed Configuration Steps:
This example demonstrates how parameter extraction can be used to convert text into structured data, which is then processed iteratively to generate content for each chapter of a long story [1][2][3].
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Yes, how can I help you? To explain it in a more intuitive way, the parameter extraction node is used to convert natural language into structured content, such as JSON format content, to facilitate content processing in the next nodes.
Hi all,
there is a manual for parameter extraction: https://github.com/langgenius/dify-docs/blob/main/en/guides/workflow/node/parameter-extractor.md
But I don´t get the workflow. Can someone explain or even can @AllenWriter share the workflow?
Cheers!