Research papers search agent

RAG based application to search for research papers and summarise them.

Project description

A simple RAG based application that loads research papers from a csv file and allows users to search for papers based on their queries. The application uses a vector database to store the embeddings of the papers and provides a search interface for users to find relevant papers.

Current State

  • Link to the Research papers search agent - GitHub repository
  • The application is built using Python and uses the langchain library for RAG.
  • It uses FAISS vector database to store the embeddings of the papers.
  • Loads papers from a CSV file and creates embeddings using Sentence Transformers model all-MiniLM-L6-v2.
  • Provides a simple search streamlit interface to find papers based on user queries.
  • Currently, it does not support dynamic loading of papers from external sources like ArXiv or other APIs, uses a static CSV file for demonstration purposes.

How to Run

  1. Clone the repository.
  2. Install the required dependencies using pip install -r requirements.txt.
  3. Run the application using streamlit run app.py.
  4. Open the application in your browser at http://localhost:8501.

Future Improvements

  • Add dynamic loading of papers from ArXiv API or other sources.

References