RORONAOzoro456
📄 Rag_document_project - Simple Document Summarization Tool
📦 Overview
Rag_document_project is a local-first document summarization and Q&A tool designed for business users. This app lets you upload multiple documents and creates a single knowledge base for easy access. The software generates a concise summary and answers questions based solely on the uploaded content.
🚀 Getting Started
To get started, follow these simple steps:
1. System Requirements
Ensure your device meets these minimum requirements:
- Operating System: Windows 10 or later, macOS, or a modern Linux distribution.
- RAM: At least 4 GB.
- Storage: Minimum 200 MB available space.
- Network Connection: Required for initial setup.
2. Download & Install
To download the application, visit the Releases page.
On this page, you will find the latest version ready for download. Look for the file named suitable for your operating system.
3. Running the Application
After downloading, locate the file on your computer. If you’re using Windows or macOS, double-click on the downloaded file to start the application. Follow the on-screen instructions to complete the setup.
For Linux users, use the terminal to navigate to the location of the downloaded file and type ./your-downloaded-file to launch the application.
4. Uploading Documents
Once the application is running:
- Click on the “Upload” button.
- Select the documents you want to include. You can upload files in PDF, DOCX, PPTX, TXT, HTML, CSV, XLSX, or JSON formats.
5. Generating Summary and Q&A
After uploading your documents:
- The app will extract text, chunk the content, and build a knowledge base.
- Click the “Generate Summary” button to receive a short combined summary (5–8 bullet points).
- For questions, use the Q&A interface. Type your question and hit “Ask” to get answers strictly from your uploaded documents.
📁 Repository Structure
This repository includes:
app.py: Streamlit UI for document management.rag/loader.py: Tools for loading and chunking documents.rag/vectorstore.py: FAISS vector store interface and helpers.llm.py: Interface for a small local language model.
❓ Frequently Asked Questions
How does the application ensure data privacy?
The application runs locally on your computer. It does not send your documents to external servers. Your data remains private and secure.
What types of documents can I upload?
You can upload various file formats, including but not limited to PDF, DOCX, PPTX, TXT, HTML, CSV, XLSX, and JSON.
Can I run this on my laptop?
Yes, as long as your laptop meets the minimum system requirements listed above, you should be able to install and run the application without issues.
📚 Additional Resources
For more information and updates, check the following:
- Issues Page: Report bugs or request features.
- Wiki: Explore user guides and detailed documentation.
🔄 Contribution
If you would like to contribute, please fork the repository and submit a pull request. Your input is welcome and appreciated.
📥 Download Again
To get the latest version or if you missed the earlier link, click here: Download Rag_document_project