perlathebian/document-chatbot-rag
RAG-based document chatbot — upload PDFs, ask questions, get answers with source citations. Built with LangChain, ChromaDB, sentence-transformers, Groq, FastAPI, and Streamlit.
What's novel
RAG-based document chatbot — upload PDFs, ask questions, get answers with source citations. Built with LangChain, ChromaDB, sentence-transformers, Groq, FastAPI, and Streamlit.
Code Analysis
0 files read · 5 roundsA standard RAG application that allows users to upload PDFs, chunks them, stores embeddings in ChromaDB, and answers questions via a Streamlit UI using the Groq API.
Strengths
The project has a clear separation of concerns between the backend API, the RAG pipeline logic, and the frontend. The README accurately describes the functionality and architecture. It uses standard, well-maintained libraries (LangChain, ChromaDB, FastAPI).
Weaknesses
Error handling is minimal, relying mostly on generic exceptions from libraries without specific catch blocks or user-friendly error messages. Testing is virtually non-existent. The implementation is largely boilerplate for a RAG pipeline with no novel algorithms or optimizations.
Score Breakdown
Signal breakdown
Innovation
Craft
Traction
Scope
Evidence
Commits
21
Contributors
1
Files
19
Active weeks
2
Repository
Language
Python
Stars
1
Forks
0
License
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