[WIP] Add comprehensive documentation for RAGbot

[Copilot]

Documentation Enhancement Plan

• 1. Create enhanced README.md with badges, abstract, architecture diagrams, and comprehensive sections
  • Add header with professional badges
  • Add abstract section explaining RAG concept
  • Add key highlights section
  • Add detailed architecture section with ASCII diagram
  • Add enhanced features section
  • Add deployment section with environment variables
  • Add usage examples section
  • Preserve existing Quick Start content
• 2. Create LICENSE file (MIT License)
• 3. Create CODE_OF_CONDUCT.md (Contributor Covenant 2.1)
• 4. Create CONTRIBUTING.md with development guidelines
• 5. Create SECURITY.md with security policy
• 6. Create .github/ folder structure
  • Create .github/ISSUE_TEMPLATE/bug_report.yml
  • Create .github/ISSUE_TEMPLATE/feature_request.yml
  • Create .github/ISSUE_TEMPLATE/config.yml
  • Create .github/pull_request_template.md
• 7. Verify all files are properly formatted and cross-referenced

Original prompt

Create Comprehensive Documentation for RAGbot

Overview

The RAGbot repository currently has only a minimal README.md and is completely missing essential documentation files. This PR will create a comprehensive documentation suite following the professional standards established in your other repositories (BTSC-UNet-ViT style).

Current State

Existing:

• ✅ Basic README.md (3KB, very minimal)
• ✅ Source code structure

Missing (CRITICAL):

• ❌ CODE_OF_CONDUCT.md
• ❌ CONTRIBUTING.md
• ❌ SECURITY.md
• ❌ LICENSE file
• ❌ .github/ folder with issue/PR templates
• ❌ Comprehensive README with badges, architecture, etc.

What This PR Will Create

1. Enhanced README.md ⭐ PRIORITY

Transform the basic README into a comprehensive, professional document.

Current README has:

• Basic project description
• Quick start instructions
• Simple API endpoints
• Basic tech stack

New README will add:

Header Section

# RAGbot

<p align="center">

  <!-- Core Badges -->
  ![GitHub License](https://img.shields.io/github/license/H0NEYP0T-466/RAGbot?style=for-the-badge&color=brightgreen)  
  ![GitHub Stars](https://img.shields.io/github/stars/H0NEYP0T-466/RAGbot?style=for-the-badge&color=yellow)  
  ![GitHub Forks](https://img.shields.io/github/forks/H0NEYP0T-466/RAGbot?style=for-the-badge&color=blue)  
  ![GitHub Issues](https://img.shields.io/github/issues/H0NEYP0T-466/RAGbot?style=for-the-badge&color=red)  
  ![GitHub Pull Requests](https://img.shields.io/github/issues-pr/H0NEYP0T-466/RAGbot?style=for-the-badge&color=orange)  
  ![Contributions Welcome](https://img.shields.io/badge/Contributions-Welcome-brightgreen?style=for-the-badge)  

  <!-- Activity Badges -->
  ![Last Commit](https://img.shields.io/github/last-commit/H0NEYP0T-466/RAGbot?style=for-the-badge&color=purple)  
  ![Commit Activity](https://img.shields.io/github/commit-activity/m/H0NEYP0T-466/RAGbot?style=for-the-badge&color=teal)  
  ![Repo Size](https://img.shields.io/github/repo-size/H0NEYP0T-466/RAGbot?style=for-the-badge&color=blueviolet)  
  ![Code Size](https://img.shields.io/github/languages/code-size/H0NEYP0T-466/RAGbot?style=for-the-badge&color=indigo)  

  <!-- Language Badges -->
  ![Top Language](https://img.shields.io/github/languages/top/H0NEYP0T-466/RAGbot?style=for-the-badge&color=critical)  
  ![Languages Count](https://img.shields.io/github/languages/count/H0NEYP0T-466/RAGbot?style=for-the-badge&color=success)  

  <!-- Community Badges -->
  ![Documentation](https://img.shields.io/badge/Docs-Available-green?style=for-the-badge&logo=readthedocs&logoColor=white)  
  ![Open Source Love](https://img.shields.io/badge/Open%20Source-%E2%9D%A4-red?style=for-the-badge)  

</p>

<p align="center">
  <strong>Production-Ready RAG Chatbot with ChatGPT-like Interface</strong>
</p>

<p align="center">
  <em>Retrieval-Augmented Generation chatbot powered by LangChain, FAISS vector database, and LongCat LLM with a modern React frontend</em>
</p>

Abstract Section

## 📖 Abstract

**RAGbot** is a production-ready **Retrieval-Augmented Generation (RAG) chatbot** that combines the power of large language models with domain-specific knowledge retrieval. Unlike traditional chatbots that rely solely on pre-trained knowledge, RAGbot:

- **Retrieves** relevant information from your custom document collection
- **Augments** LLM prompts with retrieved context
- **Generates** accurate, contextually-aware responses

### How It Works

1. **Document Indexing**: Your PDF/Markdown documents are embedded using HuggingFace Sentence Transformers (all-MiniLM-L6-v2)
2. **Vector Storage**: Embeddings stored in FAISS (Facebook AI Similarity Search) for fast retrieval
3. **Query Processing**: User questions are embedded and matched against the vector database
4. **Context Augmentation**: Top-k relevant documents are retrieved and added to the LLM prompt
5. **Response Generation**: LongCat LLM generates responses with retrieved context, improving accuracy

### Key Benefits

- 🎯 **Accurate Answers**: Responses grounded in your specific documents
- 🔄 **Up-to-Date**: Add new documents without retraining models
- 💬 **ChatGPT-like UX**: Familiar interface with markdown, code highlighting, LaTeX support
- 🚀 **Production-Ready**: FastAPI backend with comprehensive logging and error handling
- 🆓 **Cost-Effective**: Free LongCat LLM tier + open-source stack

Key Highlights

## ✨ Key Highlights

- 🤖 **RAG Architecture** - Retrieval-Augmented Generation for accurate, context-aware responses
- 📚 **Document Knowledge Base** - PDF and Markdown document support with auto-indexing
- 🔍 **FAISS Vector Database** - Fast similarity search for relevant document retrieval
- 🧠 **LongCat LLM Integration** - Powered by advanced language model via OpenAI-compatible API
- 💬 **ChatGPT-like Interface** - Clean, modern chat UI with React 19 + TypeScript
- 📝 **Rich Markdown Rendering** - Syntax-highlighted code blocks, tables,...

</details>



<!-- START COPILOT CODING AGENT SUFFIX -->

*This pull request was created from Copilot chat.*
>

<!-- START COPILOT CODING AGENT TIPS -->
---

💡 You can make Copilot smarter by setting up custom instructions, customizing its development environment and configuring Model Context Protocol (MCP) servers. Learn more [Copilot coding agent tips](https://gh.io/copilot-coding-agent-tips) in the docs.

[vercel]

The latest updates on your projects. Learn more about Vercel for GitHub.

Project	Deployment	Review	Updated (UTC)
ra-gbot	Ready	Preview, Comment	Jan 1, 2026 10:21am