RAG System from my personal Scientific PDFs
- PDF Parsing: Extract text from scientific PDFs.
- Chunking: Split large documents into meaningful sections.
- Embedding: Convert text into vector representations for efficient retrieval.
- Vector Storage: Store embeddings in a database (FAISS).
- Retrieval & LLM Integration: Retrieve relevant chunks and generate responses.
- API: Deploy RAG as a Flask service.
git clone https://github.com/yourusername/science_papers_rag.git
cd rag_from_pdfs
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt