metadata

title: 'CoT-Lab: Human-AI Co-Thinking Laboratory'
emoji: 🤖
colorFrom: blue
colorTo: gray
sdk: gradio
python_version: '3.13'
sdk_version: 5.13.1
app_file: app.py
models:
  - deepseek-ai/DeepSeek-R1
tags:
  - writing-assistant
  - multilingual
license: mit

CoT-Lab: Human-AI Co-Thinking Laboratory

Huggingface Spaces 🤗 | GitHub Repository 🌐 中文README

Sync your thinking with AI reasoning models to achieve deeper cognitive alignment Follow, learn, and iterate the thought within one turn

🌟 Introduction

CoT-Lab is an experimental interface exploring new paradigms in human-AI collaboration. Based on Cognitive Load Theory and Active Learning principles, it creates a "Thought Partner" relationship by enabling:

🧠 Cognitive Synchronization
Slow-paced AI output aligned with human information processing speed
✍️ Collaborative Thought Weaving
Human active participation in AI's Chain of Thought

** This project is part of ongoing exploration. Under active development, discussion and feedback are welcome! **

🛠 Usage Guide

Basic Operation

Set Initial Prompt
Describe your prompy in the input box (e.g., "Explain quantum computing basics")
Adjust Cognitive Parameters
- ⏱ Thought Sync Throughput: tokens/sec - 5:Read-aloud, 10:Follow-along, 50:Skim
- 📏 Human Thinking Cadence: Auto-pause every X paragraphs (Default off - recommended for active learning)
Interactive Workflow
- Click Generate to start co-thinking, follow the thinking process
- Edit AI's reasoning when it pauses - or pause it anytime with Shift+Enter
- Use Shift+Enter to hand over to AI again

🧠 Design Philosophy

Cognitive Load Optimization
Information chunking (Chunking) adapts to working memory limits, serialized information presentation reduces cognitive load from visual searching
Active Learning Enhancement
Direct manipulation interface promotes deeper cognitive engagement
Distributed Cognition
Explore hybrid human-AI problem-solving paradiam

📥 Installation & Deployment

Local deployment is (currently) required if you want to work with locally hosted LLMs.

Prerequisites: Python 3.11+ | Valid Deepseek API Key or OPENAI chat.completions compatible API.

# Clone repository
git clone https://github.com/Intelligent-Internet/CoT-Lab
cd CoT-Lab

# Install dependencies
pip install -r requirements.txt

# Configure environment
API_KEY=sk-****
API_URL=https://api.deepseek.com/beta
API_MODEL=deepseek-reasoner

# Launch application
python app.py

API Settings for serving

You can set environment variable API_KEY to hide the key from frontend. Only OPENAI chat.completions compatible API is supported now.

📄 License

Contact

[email protected] (Dango233)