RAG Chatbot with Citations
Build a retrieval chatbot that answers from documents and shows source citations.
A practical starter template for learners who want to turn RAG theory into a portfolio-ready app: document ingestion, chunking, embeddings, vector search, citation display, evaluation notes, and a clean deployment path.
Price: $29. Difficulty: Intermediate. Estimated completion time: 6-10 hours.
What is included
- Frontend chat UI scaffold
- Backend API skeleton
- RAG pipeline notes
- Evaluation checklist
- Deployment notes
Tech stack
- Python
- FastAPI
- React
- Vector database
- Embeddings API
- LLM API
- Docker-ready structure
Learning outcomes
- Explain the full RAG pipeline from documents to cited answer
- Build a searchable document assistant with source grounding
- Evaluate hallucination risk and retrieval quality
- Prepare a portfolio demo that connects GenAI with real documents