LLM-Powered Field Extraction from Files
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This workflow uses OpenAI's LLM to extract specific data fields from various file types, like PDFs, based on defined prompts. It handles different event types for flexible data processing.
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About This Workflow
Overview
This n8n workflow leverages the power of Large Language Models (LLMs), specifically through the Langchain node, to automate the extraction of specific data fields from unstructured or semi-structured files. It begins by routing incoming events based on their type, such as 'row.updated', 'field.created', or 'field.updated', using a switch node. For relevant events, it retrieves file data (presumably from a source like Airtable or another service with file attachments), processes it using an extractFromFile node, and then uses the chainLlm node to extract precise information based on detailed descriptions and desired output formats. This is particularly useful for tasks like digitizing information from documents, analyzing content, or populating structured data from unstructured text.
Why use this?
- Automated Data Extraction: Reduces manual effort in pulling specific data from documents.
- LLM Power: Utilizes advanced AI for nuanced data extraction and interpretation.
- Flexibility: Handles different file types (e.g., PDF) and event triggers.
- Structured Output: Ensures extracted data conforms to predefined formats.
Key Features
- Dynamically routes workflows based on event types.
- Extracts data from files (PDFs supported).
- Utilizes LLM (Langchain node) for intelligent data extraction.
- Extracts specific fields based on descriptions and desired output formats.
- Handles cases where data might not be extractable.
How To Use
- Configure Event Trigger: Set up the initial trigger that sends data to this workflow, ensuring it includes event types and file URLs.
- Define Event Routing: Adjust the
Event Typeswitch node to correctly categorize incoming event types (e.g.,row.updated,field.created). - Input File and Field Data: Ensure the input data includes file objects with
urlproperties and field definitions withname,description, andtype. - Configure HTTP Request and Extract from File: Set up the
Get File DataandExtract from Filenodes to fetch and read the content of the files based on the provided URLs. - Configure LLM Prompting: Carefully craft the
textparameter in theGenerate Field Valuenode. This prompt should include the file content and the specific instructions for the LLM, including the field description and desired output format. - Map Results: Utilize the
Get Resultnode to map the LLM's extracted text to the corresponding fields in your output.
Apps Used
Workflow JSON
{
"id": "342626ec-b46a-43a7-8d8b-6b88be3c7984",
"name": "LLM-Powered Field Extraction from Files",
"nodes": 0,
"category": "AI and LLM Automation",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 342626ec-b46a...
About the Author
AI_Workflow_Bot
LLM Specialist
Building complex chains with OpenAI, Claude, and LangChain.
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