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GPT-4o Research Assistant

The GPT-4o Research Assistant is a powerful tool designed to leverage GPT-4o in assisting with academic research. It searches for academic papers on ArXiv, identifies the most promising paper based on a given search term, downloads the paper, extracts its contents, and then summarizes it. The tool also suggests a new search term for subsequent research, creating an automated research exploration chain.

Features

  • Organized Research Storage:

    • Creates a structured research_papers directory
    • Organizes papers in subdirectories based on search terms
    • Saves both PDFs and their summaries in respective folders

  • ArXiv Integration:

    • Queries the ArXiv database for academic papers
    • Supports customizable number of results (default: 10)
    • Automatically filters out previously selected papers

  • Intelligent Paper Selection:

    • Uses GPT-4O to analyze and choose the most interesting paper
    • Provides reasoning for paper selection
    • Handles paper deduplication across iterations

  • Automated Processing:

    • Downloads selected papers in PDF format
    • Extracts and processes text content
    • Generates concise summaries using GPT-4O
    • Suggests new research directions

  • User-Friendly Output:

    • Colored terminal output for better readability
    • Clear progress indicators
    • Detailed error messages
    • Structured file organization

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Directory Structure

research_papers/
    └── search_term_sanitized/         # First 30 chars of search term
        ├── paper_title.pdf            # Downloaded paper
        └── paper_title_summary.txt    # GPT-generated summary

Setup

  1. Environment Setup:

    pip install -r requirements.txt

  2. API Key Configuration:

    • Set your OpenAI API key as an environment variable:
    export OPENAI_API_KEY='your-api-key'

Usage

  1. Basic Usage:

    python main.py
    • Default search term: "coding ability of large language models"
    • Default number of iterations: 3

  2. Configuration: Modify the constants in main.py to customize:

    • MODEL: GPT model to use (default: "gpt-4o")
    • MAX_RESULTS: Number of papers to fetch (default: 10)
    • NUMBER_OF_TURNS: Research iterations (default: 3)
    • INITIAL_SEARCH_TERM: Starting search term

Features in Detail

Paper Selection

  • Fetches papers from ArXiv based on search term
  • GPT-4O analyzes paper summaries and selects the most promising one
  • Provides explanation for the selection

Paper Processing

  • Downloads PDF automatically
  • Extracts text content
  • Generates comprehensive summary
  • Saves both PDF and summary in organized folders

Research Chain

  • Analyzes paper content to suggest new research directions
  • Automatically uses suggested terms for next iteration
  • Maintains research continuity while exploring new areas

Error Handling

  • Robust error handling throughout the process
  • Clear error messages with colored output
  • Graceful failure recovery

Limitations

  • Text extraction limited to first 100,000 characters per paper
  • Maximum of 10 papers retrieved per search
  • Requires stable internet connection for ArXiv and API access

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