README

📚 AI Research Agent with Memory

🎓 FREE Step-by-Step Tutorial

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This Streamlit app implements an AI-powered research assistant that helps users search for academic papers on arXiv while maintaining a memory of user interests and past interactions. It utilizes OpenAI's GPT-4o-mini model for processing search results, MultiOn for web browsing, and Mem0 with Qdrant for maintaining user context.

Features

• Search interface for querying arXiv papers
• AI-powered processing of search results for improved readability
• Persistent memory of user interests and past searches
• Utilizes OpenAI's GPT-4o-mini model for intelligent processing
• Implements memory storage and retrieval using Mem0 and Qdrant

How to get Started?

1. Clone the GitHub repository

git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd awesome-llm-apps/llm_apps_with_memory_tutorials/ai_arxiv_agent_memory

2. Install the required dependencies:

pip install -r requirements.txt

3. Ensure Qdrant is running: The app expects Qdrant to be running on localhost:6333. Adjust the configuration in the code if your setup is different.

docker pull qdrant/qdrant

docker run -p 6333:6333 -p 6334:6334 \
    -v $(pwd)/qdrant_storage:/qdrant/storage:z \
    qdrant/qdrant

4. Run the Streamlit App

streamlit run ai_arxiv_agent_memory.py