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A framework for collecting a large human-sourced chain-of-thoughts dataset

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Headlong is a framework for human users to create and curate high quality chain-of-thought datasets and use them in AI Agents.

The webapp frontend is in packages/webapp - it's a vite Typescript project.

The environment daemon is in packages/env - a Python process that runs the agent loop (Claude + tools) and serves the thought streaming API. It uses tmux for terminal management and Claude for LLM reasoning with native tool use.

The webapp communicates with the environment via a Supabase thoughts table and Supabase's realtime system.

Install and run

1. Set up environment variables

Copy or edit .env in the project root. Required keys:

ANTHROPIC_API_KEY=sk-ant-...
SUPABASE_URL_HEADLONG=...
SUPABASE_SERVICE_ROLE_KEY_HEADLONG=...
SERPAPI_API_KEY=...
TELEGRAM_BOT_TOKEN=...      # optional, for messaging
TELEGRAM_CHAT_ID=...         # optional, for messaging

2. Start the env daemon (Python)

cd packages/env
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python main.py <agentName>

This starts the agent loop and the thought streaming API on port 8000.

Requires: tmux installed (brew install tmux on macOS).

3. Start the webapp

# in a new terminal
cd packages/webapp
npm install
npm run dev

The webapp runs on http://localhost:5173.

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A framework for collecting a large human-sourced chain-of-thoughts dataset

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