https://github.com/kybvwhxw/sequential-thinking-paper
Implementation of Sequential Thinking Paper: A Step-by-Step Approach to AI Content Analysis
https://github.com/kybvwhxw/sequential-thinking-paper
ai content-analysis fastapi nlp python sequential-thinking
Last synced: 2 months ago
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Implementation of Sequential Thinking Paper: A Step-by-Step Approach to AI Content Analysis
- Host: GitHub
- URL: https://github.com/kybvwhxw/sequential-thinking-paper
- Owner: KYBvWHxW
- License: mit
- Created: 2025-02-19T10:24:58.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-20T00:54:30.000Z (over 1 year ago)
- Last Synced: 2025-08-31T20:49:19.616Z (10 months ago)
- Topics: ai, content-analysis, fastapi, nlp, python, sequential-thinking
- Language: Python
- Size: 11.7 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Sequential Thinking Paper
This repository contains the implementation of a Sequential Thinking Server for AI-powered article illustration. The server analyzes article content using a step-by-step approach to extract key information and generate appropriate visual suggestions.
## Features
- Content Analysis: Breaks down articles into meaningful segments
- Keyword Extraction: Identifies key themes and topics
- Emotion Analysis: Determines the emotional tone of content
- Visualization Suggestions: Recommends appropriate visualization types
- Image Prompt Generation: Creates prompts for AI image generation
## Architecture
The system is built using:
- FastAPI for the web server
- OpenAI's GPT-4 for content analysis
- Pydantic for data validation
- pytest for testing
## Installation
1. Clone the repository:
```bash
git clone https://github.com/your-username/sequential-thinking-paper.git
cd sequential-thinking-paper
```
2. Create a virtual environment:
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Set up environment variables:
```bash
cp .env.example .env
# Edit .env with your OpenAI API key
```
## Usage
1. Start the server:
```bash
python run_servers.py
```
2. Send a POST request to analyze content:
```bash
curl -X POST "http://localhost:8000/analyze" \
-H "Content-Type: application/json" \
-d '{"content": "Your article text here", "max_segments": 1, "analysis_type": "article"}'
```
## Testing
Run tests with:
```bash
python -m pytest tests/ -v
```
## Contributing
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add some amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Citation
If you use this work in your research, please cite:
```bibtex
@article{sequential-thinking,
title={Sequential Thinking: A Step-by-Step Approach to AI Content Analysis},
author={Your Name},
year={2025},
journal={Preprint}
}
```