Purpose: A Retrieval-Augmented Generation (RAG) app to ingest technical documents (PDF/TXT), build embeddings, store them in a local vector DB (Chroma), and answer questions via an LLM (Google Gemini) with sources. UI: Streamlit app launched via run_app.py .
TOMMY-CODER28/Personal_RAG
Folders and files
| Name | Name | Last commit date | ||
|---|---|---|---|---|