GenSurv (Generative Survey) is a volunteer initiative aimed at exploring and establishing methods to streamline literature reviews using generative AI. Currently, we are engaged in the following specific endeavors:
- Developing an agent that engages in dialogue to delve deeper into the information users seek, retrieves appropriate literature, and provides summarized responses
- Visualizing areas not approached by prior research by vectorizing literature information
- Developing a system that stores literature information in a vector database and uses it as a basis to answer user questions
For more details about the project, past activities, and how to participate, please check here.
- Python 3.11.4
Environment variables
cp .env.sample .env # Replace with your own API keys, etc.
Python environment
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
Executing the script
python src/main.py --title "Laboratory automation" \
--retrieve_papers --max_papers 5 \
--generate_headings \
--output_path data
To run the evaluation function(evaluate_headings.py) from the src directory, use the following command
python -m gensurv.scripts.evaluate_headings \
--input_data_path ../data/test/manual_by_ono/headings_input_data.json \
--eval_data_path ../data/test/manual_by_ono/headings_evaluation_data.json
Launching the application (locally)
gradio src/app.py
Launching the application (creating a shared link)
gradio src/app.py --share
graph TD
A[Start] --> B[Parse Arguments]
B --> C{Retrieve Papers?}
C -->|Yes| D[Retrieve Papers]
C -->|No| E[Load Papers]
D --> F{Generate Headings?}
E --> F
F -->|Yes| G[Generate Headings]
F -->|No| H[Load Headings]
G --> I[Classify Papers]
H --> I
I --> J[Generate Overview]
J --> K{Generate Draft?}
K -->|Yes| L[Generate Draft]
K -->|No| M[End]
L --> M