🤖 CBase - AI Chatbot Management Platform

Comprehensive AI Chatbot Management Platform with Advanced RAG Features

Features • Quick Start • Documentation • Roadmap • Contributing

📖 Overview

CBase is a production-ready AI chatbot management platform featuring advanced RAG (Retrieval-Augmented Generation) capabilities, inspired by Chatbase's legacy RAG learning chatbots. Build, train, and deploy intelligent AI agents with comprehensive knowledge bases, analytics, and real-time testing capabilities.

🎯 Core Capabilities

🧠 Advanced RAG System - Auto-training with document ingestion, vector embeddings, and semantic search
🤖 Agent Management - Complete lifecycle management for AI chatbots
📊 Analytics Dashboard - Real-time metrics, insights, and performance tracking
💬 Live Playground - Interactive testing environment with RAG-enhanced responses
📝 Chat Logs - Comprehensive conversation history and export capabilities
⚙️ Settings & Integrations - Database integrations (Supabase, Neon), S3 storage, and more

✨ Key Features

🧠 RAG Knowledge Training System

Train your AI agents with custom knowledge sources:

Multiple Source Types: Text, files (PDF, DOCX), URLs, Q&A pairs
Smart Text Processing: Overlapping chunk segmentation with boundary detection
Vector Embeddings: 1536-dimensional vectors via OpenAI-compatible API
Semantic Search: Cosine similarity-based retrieval with relevance scoring
Batch Training: Process multiple sources efficiently
Real-time Status: Monitor training progress and job status

🤖 Agent Management

Complete control over your AI chatbots:

Full CRUD Operations: Create, read, update, delete agents
Configuration: System prompts, models (GPT-4, GPT-3.5), temperature, tokens
Conversation Starters: Pre-defined quick replies for users
Constraints: Rate limiting, visibility controls, max length settings
Status Tracking: Active, training, needs retraining indicators
Templates: Pre-built agent templates for common use cases

📊 Analytics & Insights

Understand your chatbot performance:

Message Analytics: Total counts, user/bot distribution, trends over time
Topic Analysis: Category breakdown and trend identification
Signal Scores: Quality metrics and threshold alerts
Performance Metrics: Response times, success rates, error tracking
Emoji Usage: Sentiment analysis and usage patterns
Custom Reports: Export analytics as CSV, PDF, or JSON

💬 Interactive Playground

Test and refine your agents:

Live Chat Interface: Real-time AI responses with streaming
RAG Toggle: Enable/disable knowledge retrieval on-the-fly
Configuration Panel: Adjust settings without leaving the playground
System Prompt Editor: Inline editing with preview
Export Results: Save test sessions for analysis
Debug Mode: View RAG context and relevance scores

🎨 Modern UI/UX

Beautiful, accessible interface:

Dark Mode: Purple/indigo themed dark interface (default)
Responsive Design: Optimized for desktop, tablet, and mobile
Accessibility: WCAG 2.1 AA compliant
Smooth Animations: Framer Motion powered interactions
Loading States: Skeleton loaders and progress indicators
Toast Notifications: User-friendly feedback system

🚀 Quick Start

Prerequisites

Node.js 18.x or 20.x LTS
pnpm 10.4.1 or higher
MySQL 8.0+
OpenAI API Key or compatible endpoint

Installation

# Clone the repository
git clone https://github.com/o9nn/cbase.git
cd cbase

# Install dependencies
pnpm install

# Configure environment
cp .env.example .env
# Edit .env with your configuration

# Run database migrations
pnpm run db:push

# Start development server
pnpm run dev

The application will be available at http://localhost:3000

Docker Quick Start

# Using Docker Compose
docker-compose up -d

# View logs
docker-compose logs -f

# Stop services
docker-compose down

📚 Documentation

Core Documentation

Development Roadmap - Complete feature roadmap (Phases 1-12)
Features Checklist - Detailed feature status tracking
API Documentation - Complete API reference
Deployment Guide - Production deployment instructions

RAG System

RAG Documentation - Complete RAG system guide
RAG Quick Start - Quick start and overview
RAG Examples - Code examples

Implementation

Implementation Summary - Technical implementation details
Final Report - Project completion report

🏗️ Architecture

Technology Stack

Frontend

React 19 - Modern UI library
TypeScript - Type-safe development
TailwindCSS - Utility-first styling
Radix UI - Accessible component primitives
Framer Motion - Smooth animations
React Query - Data fetching and caching
Wouter - Lightweight routing

Backend

Node.js - Runtime environment
Express - Web framework
tRPC - Type-safe API layer
Drizzle ORM - Type-safe database access
MySQL - Primary database
Zod - Schema validation

Infrastructure

Vite - Fast build tool
pnpm - Efficient package manager
PM2 - Process manager
Docker - Containerization
nginx - Reverse proxy

System Architecture

┌─────────────────────────────────────────────────────────┐
│                     Client (React)                       │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐  ┌─────────┐ │
│  │  Agents  │  │Knowledge │  │Analytics │  │Settings │ │
│  │   Page   │  │   Base   │  │Dashboard │  │  Panel  │ │
│  └──────────┘  └──────────┘  └──────────┘  └─────────┘ │
└────────────────────────┬────────────────────────────────┘
                         │ tRPC API
┌────────────────────────▼────────────────────────────────┐
│                    Server (Node.js)                      │
│  ┌──────────────┐  ┌──────────────┐  ┌───────────────┐ │
│  │    Router    │  │   RAG Core   │  │    Storage    │ │
│  │   (tRPC)     │  │   Service    │  │   (S3/Local)  │ │
│  └──────────────┘  └──────────────┘  └───────────────┘ │
└────────────────────────┬────────────────────────────────┘
                         │ Drizzle ORM
┌────────────────────────▼────────────────────────────────┐
│                    Database (MySQL)                      │
│  ┌─────────┐  ┌─────────────┐  ┌────────────────────┐  │
│  │ Agents  │  │  Knowledge  │  │  Chat Sessions &   │  │
│  │  Table  │  │  Sources &  │  │     Messages       │  │
│  │         │  │  Embeddings │  │                    │  │
│  └─────────┘  └─────────────┘  └────────────────────┘  │
└─────────────────────────────────────────────────────────┘

🗓️ Roadmap

✅ Completed (v2.0.0)

Phase 1-7: Core platform with RAG system (85% complete)
- Agent management system
- RAG knowledge training
- Chat logs and analytics
- Interactive playground
- Settings and integrations
- Dark mode UI with purple/indigo theme
- Comprehensive documentation

✅ Recently Completed (January 2026)

Phase 8: File upload & processing ✅
- PDF, DOCX, DOC, TXT, MD file support
- Automatic text extraction and RAG processing
- File management UI with status tracking
- Secure file handling with authorization
Phase 9: URL scraping & web crawling ✅
- Single URL and multi-page crawling
- Configurable crawl depth (1-3 levels)
- Max pages limit (5-50 pages)
- HTML content extraction with cheerio
- HTML to Markdown conversion
- Robots.txt compliance
- Same-domain restriction
- SSRF protection and URL validation
- Automatic RAG processing of crawled content

🚧 In Progress (Q2 2026)

Enhanced testing infrastructure
Performance optimization

📋 Planned (Q3-Q4 2026)

Phase 10: Advanced training & optimization
Phase 11: Multi-language support
Phase 12: Enterprise features & scaling
Vector database migration
Team collaboration features
Public API & webhooks

See DEVELOPMENT_ROADMAP.md for complete details.

🎯 Use Cases

Customer Support

Train chatbots with FAQs, policies, and documentation for accurate, context-aware support.

Technical Documentation

Index API references, code docs, and guides for developer assistance.

Sales Assistant

Load product information and sales materials for intelligent customer interactions.

Educational Tutor

Train with course materials and textbooks for personalized learning assistance.

🛠️ Development

Project Structure

cbase/
├── client/              # Frontend React application
│   ├── src/
│   │   ├── pages/      # Page components
│   │   ├── components/ # Reusable components
│   │   └── lib/        # Utilities and helpers
│   └── public/         # Static assets
├── server/             # Backend Node.js application
│   ├── _core/          # Core server functionality
│   ├── db.ts           # Database operations
│   ├── rag.ts          # RAG service
│   └── routers.ts      # API routes
├── drizzle/            # Database schema and migrations
├── examples/           # Code examples
└── docs/              # Documentation

Available Scripts

# Development
pnpm run dev           # Start dev server with hot reload

# Building
pnpm run build         # Build for production
pnpm run start         # Start production server

# Quality
pnpm run check         # TypeScript type checking
pnpm run format        # Format code with Prettier
pnpm run test          # Run tests

# Database
pnpm run db:push       # Run database migrations

Environment Variables

Create a .env file with:

# Required
DATABASE_URL=mysql://user:pass@host:3306/db
FORGE_API_KEY=your-api-key-here

# Optional
FORGE_API_URL=https://api.openai.com/v1
AWS_ACCESS_KEY_ID=your-aws-key
AWS_SECRET_ACCESS_KEY=your-aws-secret
S3_BUCKET=your-bucket-name

# ⚠️ WARNING: Never commit actual credentials to version control!
# Use environment variables or secure secrets management in production.

See DEPLOYMENT_GUIDE.md for complete configuration.

🧪 Testing

Running Tests

# Run all tests
pnpm test

# Run tests in watch mode
pnpm test -- --watch

# Run tests with coverage
pnpm test -- --coverage

Test Coverage Goals

Unit Tests: 80% coverage target
Integration Tests: Critical paths covered
E2E Tests: User journey validation

📊 Performance

Benchmarks

Average Response Time: < 2s for RAG queries
Embedding Generation: ~100ms per chunk
Database Queries: < 100ms average
Page Load Time: < 3s initial load
API Uptime: 99.9% target

Optimization

Database indexing on frequently queried fields
React Query caching for API responses
Batch embedding generation
Code splitting and lazy loading
CDN for static assets

🔒 Security

Security Features

JWT-based authentication
Session management with secure cookies
Input validation with Zod schemas
SQL injection prevention via ORM
XSS protection
CSRF protection
Rate limiting
API key management

Reporting Security Issues

Please report security vulnerabilities via GitHub Security Advisories: https://github.com/o9nn/cbase/security/advisories

Do not open public issues for security concerns.

🤝 Contributing

We welcome contributions! Please see our contributing guidelines:

How to Contribute

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

Development Guidelines

Follow TypeScript best practices
Write tests for new features
Update documentation as needed
Follow the existing code style
Use conventional commits

Code of Conduct

Be respectful, inclusive, and professional. See CODE_OF_CONDUCT.md.

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

Inspiration

This project is inspired by Chatbase's legacy RAG learning chatbot system, bringing advanced knowledge training capabilities to modern AI chatbot management.

Technologies

Built with amazing open-source technologies:

React, TypeScript, Node.js
TailwindCSS, Radix UI, Framer Motion
tRPC, Drizzle ORM, MySQL
And many more listed in package.json

📞 Support & Community

Getting Help

Documentation: Complete docs in repository
GitHub Issues: Report bugs
GitHub Discussions: Ask questions

Stay Connected

GitHub: @o9nn
Repository: o9nn/cbase

📈 Project Status

Current Version: 2.2.0
Status: Production Ready ✅
Last Updated: January 31, 2026

Statistics

93% feature complete (Phases 8 & 9 completed)
180+ features implemented
18 API endpoints (4 new URL crawling endpoints added in Phase 9)
8 major pages
5 database tables (added fileUploads, webCrawlJobs)
3,600+ lines of code added for file processing and URL crawling
3 database tables for RAG
1,775 lines of code added in RAG implementation (Phase 7)

🎉 What's New in v2.2.0

Major Features (Phase 9)

✨ URL Scraping & Web Crawling

Crawl single URLs or entire websites
Configurable crawl depth (1-3 levels deep)
Max pages limit (5-50 pages)
Smart content extraction from HTML
HTML to Markdown conversion
Robots.txt compliance
Same-domain restriction for security
SSRF protection with URL validation
Automatic RAG processing of crawled content
Real-time crawl job status tracking

Previous Features (v2.1.0 - Phase 8)

✨ File Upload & Processing

Upload PDF, DOCX, DOC, TXT, MD files
Automatic text extraction
Seamless RAG integration
File management UI with status tracking

Core Features (v2.0.0)

✨ Complete RAG knowledge training system
✨ Advanced vector search with semantic similarity
✨ Batch training capabilities
✨ Real-time training job tracking
✨ Comprehensive analytics dashboard
✨ Export functionality (CSV, PDF)
✨ Dark mode UI with purple/indigo theme

Improvements

🚀 Enhanced web content processing pipeline 🚀 Improved security with SSRF protection 🚀 Better error handling for network operations 🚀 Enhanced file processing pipeline 🚀 Improved security with ownership verification 🚀 Better error handling for file operations 🚀 Enhanced performance with database optimization
🚀 Improved error handling and user feedback
🚀 Better documentation with examples
🚀 Responsive design for all devices
🚀 Accessibility improvements (WCAG 2.1 AA)

🔮 Coming Soon

📅 Scheduled auto-retraining
🌍 Multi-language support
🏢 Team collaboration features
🔌 Public API and webhooks
📱 Mobile app

⬆ Back to Top

Made with ❤️ by the CBase Team

Name		Name	Last commit message	Last commit date
Latest commit History 33 Commits
.manus/db		.manus/db
client		client
drizzle		drizzle
examples		examples
patches		patches
server		server
shared		shared
.gitignore		.gitignore
.gitkeep		.gitkeep
.prettierignore		.prettierignore
.prettierrc		.prettierrc
API_DOCUMENTATION.md		API_DOCUMENTATION.md
DEPLOYMENT_GUIDE.md		DEPLOYMENT_GUIDE.md
DEVELOPMENT_ROADMAP.md		DEVELOPMENT_ROADMAP.md
FEATURES_CHECKLIST.md		FEATURES_CHECKLIST.md
FINAL_REPORT.md		FINAL_REPORT.md
IMPLEMENTATION_COMPLETE.md		IMPLEMENTATION_COMPLETE.md
IMPLEMENTATION_SUMMARY.md		IMPLEMENTATION_SUMMARY.md
IMPLEMENTATION_SUMMARY_PHASE9.md		IMPLEMENTATION_SUMMARY_PHASE9.md
PHASE8_FILE_UPLOAD.md		PHASE8_FILE_UPLOAD.md
PHASE9_URL_SCRAPING.md		PHASE9_URL_SCRAPING.md
RAG_DOCUMENTATION.md		RAG_DOCUMENTATION.md
README.md		README.md
README_RAG.md		README_RAG.md
SECURITY_SUMMARY_PHASE8.md		SECURITY_SUMMARY_PHASE8.md
SECURITY_SUMMARY_PHASE9.md		SECURITY_SUMMARY_PHASE9.md
components.json		components.json
drizzle.config.ts		drizzle.config.ts
package.json		package.json
pnpm-lock.yaml		pnpm-lock.yaml
todo.md		todo.md
tsconfig.json		tsconfig.json
vite.config.ts		vite.config.ts
vitest.config.ts		vitest.config.ts

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