🧠 ScholarLens – AI-Powered Research Assistant with Agentic RAG

ScholarLens is a Streamlit-based AI research assistant that streamlines literature review, research paper summarization, and comparison. It leverages Agentic AI workflows and Agentic RAG (via the Agno library) to let you search, analyze, summarize, and compare academic papers in a deeply interactive way.

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🚀 Features

1. 🔍 ArXiv Smart Search

• Search latest research papers from arXiv by topic.

• Summarizes each paper with:

  • Problem statement
  • Key contributions
  • Summary of findings

• Export results as JSON.

2. 📚 AI Paper Companion

• Upload any PDF research paper.

• Instant Glance Mode:

  • Extracts title, model, dataset, evaluation metrics, and structured summary.

• Guru Mode:

  • Section-wise summarization (Abstract, Methodology, Results, etc.) in bullet-point JSON format.

3. 💬 Agentic RAG Chatbot

• Upload a paper and query it conversationally.

• Uses Agno's Agentic RAG flow:

  • Gemini Embeddings for semantic chunk representation.
  • Pinecone VectorDB for fast similarity search.
  • Gemini LLM as the reasoning engine.

• Supports persistent chat + search history for contextual Q&A.

4. 📊 Compare Research Papers

• Upload two or three research papers (PDF).

• AI-generated Markdown comparison table:

  • Problem statement
  • Methodology
  • Datasets used
  • Model performance and accuracy

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🏗️ Tech Stack

• Frontend: Streamlit
• Agentic Framework: Agno for multi-step RAG orchestration
• LLM Providers: Google Gemini, Groq
• Vector Database: Pinecone
• Embeddings: Gemini Embeddings (models/gemini-embedding-001)
• PDF Processing: PyMuPDF (fitz)
• Agent Framework (ArXiv & Summarization): CrewAI
• APIs: arXiv API, Pinecone API
• Environment Management: python-dotenv

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📂 Project Structure

ScholarLens/
├── main.py                  # Entry point
├── requirements.txt         # Dependencies
├── comparision/             # Paper comparison module
├── rag/                     # Agentic RAG implementation
├── search/                  # Research paper search tools
├── summarization/           # Summarization modules
├── utils/                   # Utilities (memory, DB patches)
└── assets/                  # Images & static assets

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⚙️ Installation

1️⃣ Clone the repository

git clone https://github.com/your-username/scholarlens.git
cd scholarlens

2️⃣ Create a virtual environment

python -m venv venv
source venv/bin/activate    # On Mac/Linux
venv\Scripts\activate       # On Windows

3️⃣ Install dependencies

pip install -r requirements.txt

4️⃣ Set up environment variables Create a .env file in the root directory:

GOOGLE_API_KEY=your_google_gemini_api_key
GROQ_API_KEY=your_groq_api_key
PINECONE_API_KEY=your_pinecone_api_key

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▶️ Usage

Run the app:

streamlit run app.py

In the sidebar, select:

• ArXiv Smart Search → Search papers by topic.
• AI Paper Companion → Upload PDF for summarization.
• Agentic RAG Chatbot → Chat with a paper using Agno's RAG.
• Compare Research Papers → Compare two research PDFs.

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Check out the demo: https://scholarlens.streamlit.app/

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📜 License

MIT License © 2025 ScholarLens AI

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🙌 Acknowledgements

• Agno for the Agentic RAG framework.
• arXiv for open-access research papers.
• Streamlit for the interactive web app framework.
• Google Gemini and Groq for LLM APIs.
• Pinecone for vector database services.
• CrewAI for agentic workflows in research retrieval & summarization.