Academic Paper Figure Analyzer

A tool that automatically analyzes academic papers, extracting and explaining figures and their connections to the research. This tool uses LLMs to provide detailed analysis of each figure and its relationship to the paper's content.

Features

• Extracts paper metadata (title, authors, abstract)
• Identifies and counts total figures in the paper
• Provides detailed analysis of each figure
• Generates comprehensive explanations of how figures relate to the research
• Parallel processing for efficient analysis of multiple figures
• Structured output with separate files for metadata, background, and figure analysis

Prerequisites

• Python 3.10+
• OpenAI API key

Installation

1. Clone the repository:

git clone [your-repo-url]
cd [repo-name]

2. Run the setup script:

python setup_project.py

3. Create a .env file in the root directory and add your OpenAI API key:

OPENAI_API_KEY=your_api_key_here

Directory Structure

.
├── papers/             # Place your PDF papers here
├── output/            # Analysis results will be saved here
├── paper_analyzer.py  # Main analysis script
├── utils.py          # Utility functions
├── config.py         # Configuration settings
├── templates.py      # Prompt templates
├── setup.py          # Package setup configuration
└── setup_project.py  # Project setup script

Usage

1. Place your academic paper (PDF format) in the papers/ directory.

2. Run the analyzer:

python paper_analyzer.py papers/your_paper.pdf [--output-dir custom/output/path]

The script will:

• Extract basic paper details (title, authors, abstract)
• Count the total number of figures
• Analyze each figure in detail
• Generate connections between figures and research content
• Analyze background information
• Save the analysis in separate files under the output directory

Output Structure

The analysis will be saved in the output directory with the following files:

• metadata.txt: Paper details (title, authors, abstract, figure count)
• background.txt: Detailed background analysis and prerequisites
• figures_analysis.txt: For each figure:
  • Initial analysis (Information and Connection)
  • Expanded analysis with additional context
  • Detailed relationships to research content

Configuration

You can modify the following settings in config.py:

• PAPER_DIR: Directory for input PDF papers (default: "papers")
• OUTPUT_DIR: Directory for saving analysis results (default: "output")
• DEFAULT_MODEL: GPT model to use for analysis (default: "gpt-4o-mini")

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

TODO

• Enhance paper content extraction:
  • Deep dive analysis of Results and Conclusion sections
  • Extract and analyze Future Work sections
  • Comprehensive analysis of Background/Introduction
  • Generate research context summaries
• Improve figure analysis:
  • Add support for tables and charts
  • Generate figure relationships map
  • Extract figure captions and references
• Advanced features:
  • Citation network analysis
  • Research methodology extraction
  • Key findings summarization

Acknowledgments

• Built with LangChain
• Powered by OpenAI's GPT models