vidhyadharan-k/ARXIV_assistant

This Streamlit application leverages the power of Langchain and large language models (LLMs) to answer your questions about research papers from arXiv.

arXiv Assistant: A Research Paper Q&A Chatbot

This Streamlit application leverages the power of Langchain and large language models (LLMs) to answer your questions about research papers from arXiv.

Features:

• arXiv Search: Uses the arxiv tool from Langchain to search for relevant papers based on your queries.
• Summarization: Provides concise summaries of the retrieved papers.
• Citations: Includes citations for the papers used in generating the answer, ensuring credibility and transparency.
• Choice of Provider: Select between Google AI or OpenAI as your LLM provider.
• Model Selection: Choose from available models within your selected provider.

Getting Started:

1. Installation:

   pip install streamlit langchain langchain-google-genai openai pyperclip

2. API Keys:

   • Obtain API keys for either Google AI or OpenAI (or both) from their respective platforms.
   • Paste your API keys into the designated fields in the Streamlit sidebar.

3. Run the Application:

   streamlit run arXiv_agent.py

4. Interact:

   • Type your questions about arXiv papers in the text input box.
   • Click the "Ask" button.
   • The chatbot will provide a summarized answer with citations.

Code Structure:

• The code is organized into sections for API key management, model selection, tool loading, agent creation, and Streamlit interface setup.
• Comments explain the purpose of each section and key variables.

Contributing:

• Feel free to contribute by adding new features, improving the code, or fixing bugs.
• Submit pull requests with clear descriptions of your changes.

License:

This project is licensed under the GPL-3.0 license.

Disclaimer:

• The accuracy of the chatbot's responses depends on the quality of the data in arXiv and the capabilities of the chosen LLM.
• Always verify information from multiple sources.