My workflow 3
This workflow implements an intelligent document parsing and analysis system. Users can upload multiple files via a form and provide their email address. The system automatically completes file splitting, parsing, content conversion, and translation, ultimately generating a structured analysis report and sending it to the user's email. Additionally, by integrating a vector database and a Q&A feature, users can interactively ask questions about the documents through a chat interface, significantly enhancing the accessibility and utilization efficiency of document information. This system is suitable for various scenarios, including enterprises, education, and cross-language teams.
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Workflow Name
My workflow 3
Key Features and Highlights
This workflow implements an intelligent document parsing and analysis system based on form file uploads. Users submit multiple files along with their email addresses via a form. The system then automatically performs file splitting, upload parsing, status querying, content conversion, and multilingual translation. Ultimately, it generates a structured analysis report and sends it to the user via email. Additionally, by integrating a vector database and multi-turn Q&A capabilities, it supports interactive querying of document content through a chat interface, enhancing the accessibility and utilization efficiency of document information.
Core Problems Addressed
- Automates multi-file upload and splitting to avoid manual and tedious operations
- Efficiently calls external APIs for deep document parsing, generating content in Markdown format
- Supports automatic recognition and translation of multilingual content, eliminating language barriers
- Structures and analyzes document content to extract key information for quick comprehension
- Stores parsed content in a vector database to enable intelligent retrieval and Q&A
- Sends analysis results promptly via email to improve feedback efficiency
Application Scenarios
- Enterprises or individuals needing to batch upload complex documents and automatically generate readable reports
- Cross-language teams requiring automatic translation and analysis of document content
- Building knowledge bases based on document content to implement intelligent Q&A bots
- Industries such as education, legal, and research that demand document parsing and information extraction
- Customer service scenarios that automatically process user-uploaded files and respond with detailed analysis results
Main Workflow Steps
- Form Trigger: Users submit data through a form containing multiple file upload fields and an email input
- File Splitting: Split the uploaded multiple binary files into individual items
- Document Parsing: Call the LlamaIndex parsing API for each file, upload the file, and poll for parsing status
- Content Retrieval: Upon successful parsing, obtain the document content in Markdown format
- Content Aggregation: Merge multiple document contents, perform language detection, and automatically translate non-English content into English
- In-depth Analysis: Conduct structured analysis, information extraction, and format optimization on the aggregated content
- File Generation: Convert the analysis results into a text file format
- Knowledge Ingestion: Embed the textual content using Mistral Cloud embeddings and store it in the Pinecone vector database
- Email Delivery: Send the analysis report and interactive links to the user’s email via Gmail
- Chat Q&A: Users can interact with the bot through the chat link in the email to ask questions, enabling intelligent Q&A based on the parsed documents
Involved Systems and Services
- n8n: Workflow automation platform
- Form Trigger (formTrigger): Receives user file uploads and email input
- LlamaIndex Cloud API: Document parsing and Markdown content generation
- Google Gemini Chat Model: Used for language model interactions, translation, analysis, and intelligent Q&A
- Mistral Cloud Embeddings: Generates vector representations of text
- Pinecone Vector Store: Vector database for storage and retrieval
- Gmail: Email sending service to deliver analysis results and interaction links
- Webhook and Chat Triggers: Enable real-time interaction between users and the intelligent Q&A bot
Target Users and Value
- Content Analysts and Data Scientists: Automate document processing and information extraction, saving significant manual effort
- Enterprise Customer Service Teams: Quickly respond to user-uploaded files with detailed and professional feedback
- Multinational Teams and Multilingual Users: Automatically translate document content to overcome language barriers
- Educational and Research Institutions: Conveniently generate structured learning materials and research reports
- Software Developers and Automation Enthusiasts: Leverage n8n to integrate multiple AI services for complex document processing automation
This workflow provides users with a comprehensive closed-loop solution from file upload and intelligent parsing to multi-turn Q&A and email notification, significantly enhancing the intelligence and interactivity of document processing.
Docsify Example
This workflow is a dynamic document management system based on Docsify, capable of automatically generating, viewing, editing, and saving workflow documents. It supports the loading and editing of documents in Markdown format, utilizes GPT-4 to generate descriptions and configuration documents, and uses Mermaid.js to create flowcharts, providing real-time preview functionality. Additionally, it receives various requests through Webhooks, streamlining the document management process, making it suitable for teams that require efficient management and maintenance of workflow documents.
Intelligent Document Q&A Query Workflow
This workflow automatically downloads PDF documents from Google Drive and splits the content, converting the text into vectors stored in the Qdrant database. It utilizes OpenAI's GPT-4 model to enable intelligent Q&A. Users can submit queries through a Webhook, and the system provides real-time, accurate answers based on the document content, significantly enhancing document retrieval efficiency and knowledge management capabilities. It is suitable for various scenarios such as corporate knowledge bases, customer support, and research data analysis.
Automated PDF Download and Conversion to PDF/A Format
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React to PDFMonkey Callback
This workflow automates the response to PDF files generated by PDFMonkey. It can automatically receive callback data once the PDF generation is complete, determine the generation status, and automatically download the PDF file upon successful generation. Through a real-time triggering mechanism, it significantly enhances document processing efficiency, addressing the cumbersome issues of traditional manual checks and downloads. This workflow is suitable for scenarios that require quick access to PDF files, such as invoices, contracts, and reports.
Automated Batch Translation Workflow for PDF Files
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PDF Content Extraction Workflow
This workflow can automatically read PDF files from a specified path and extract their content, significantly improving the efficiency and accuracy of document processing. Users only need to manually trigger the process, and the system will sequentially read the binary data and parse it into usable text. It is suitable for the automated processing of documents such as contracts and reports in a digital office environment, helping businesses and developers to collect information and analyze data more conveniently.
Webpage to PDF Automation Workflow
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pdf to text
This workflow enables efficient conversion between PDF and text, supporting the generation of PDF from HTML content and the extraction of text from local or remote PDF files. With a simple configuration and a high degree of automation, users can quickly capture and process document content, addressing the cumbersome issues of content extraction and generation in PDF files. It is suitable for enterprise content management, data analysis, and developers, significantly enhancing the utilization efficiency of textual information and overall work efficiency.