Easy customizable chat RAG Doc DB is a lightweight and flexible framework

chat prototype example

Task (Analyze a YouTube video and transcribe its content from text into any language. TTS )

cost

Test Video V1

Easy customizable chat RAG Doc DB is a lightweight and flexible framework for building AI agents with Retrieval-Augmented Generation (RAG) capabilities. It enables seamless document ingestion, vector-based search, and custom tool integration, allowing developers to create domain-aware AI assistants with minimal setup.

Designed for extensibility, performance, and real-world production use.

🛣️ Roadmap Phase 1 – Core (Current)

✅ Document ingestion & chunking

✅ Vector database integration

✅ Chat-based RAG pipeline

✅ Custom tool support for AI agents

✅ Streaming responses (SSE)

Phase 2 – Agent & Tooling

🔄 Dynamic tool registration

🔄 Multi-agent support

🔄 Tool call streaming & tracing

✅ Agent memory & context control

Phase 3 – Developer Experience

✅ Web UI for chat & document management

⏳ Config-based agent & tool definitions

⏳ Plugin system for external tools

⏳ Improved logging & observability

Phase 4 – Production & Scaling

⏳ Auth & multi-tenant support

⏳ Role-based document access

⏳ Performance optimizations

⏳ Cloud & Docker-first deployment