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elliottsax/autocoder-implementation-worker

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App README

Autocoder Implementation Worker ⚙️

24/7 Autonomous Code Implementation Worker

This Hugging Face Space runs continuous code implementation, generating code based on analysis and test planning results.

Features

  • —✅ Continuous Implementation - Runs 24/7 automatically
  • —✅ 6 Thinking Stages - Deep analysis before coding
  • —✅ Cloud Storage - Results pushed to HF Datasets
  • —✅ Real-time Monitoring - Live status dashboard
  • —✅ Free Tier Compatible - Runs on HF free infrastructure

How It Works

  1. 1.Analysis Loop - Worker runs continuous implementation iterations
  2. 2.Deep Thinking - 6 stages of analysis before each code change
  3. 3.Code Generation - Generates implementation code
  4. 4.Result Storage - Pushes code to HF Dataset
  5. 5.Monitoring - UI updates every 5 seconds

Implementation Stages

  1. 1.Deep Understanding - What is the REAL problem?
  2. 2.Architectural Analysis - How does this fit in the system?
  3. 3.Approach Evaluation - Compare different solutions
  4. 4.Risk Analysis - Identify and mitigate risks
  5. 5.Testing Strategy - Plan comprehensive tests
  6. 6.Implementation Plan - Step-by-step roadmap

Configuration

Required Secrets

Add these in Space Settings → Repository Secrets:

  • —HF_TOKEN - Your Hugging Face access token (write permission)
  • —HF_USERNAME - Your HF username (optional, defaults to 'autocoder')

Dataset Output

Results are saved to: {HF_USERNAME}/autocoder-implementation-results

Usage

Via UI

  1. 1.Visit this Space
  2. 2.View real-time status
  3. 3.Start/stop worker as needed
  4. 4.View implementation logs

Programmatically

python
from datasets import load_dataset

# Load all implementation results
dataset = load_dataset("autocoder/autocoder-implementation-results")

# Get latest results
latest = dataset["train"][-1]
print(latest)

Integration with Other Workers

This worker consumes data from:

  • —Analysis Worker (code insights)
  • —Test Planning Worker (test specifications)

And produces:

  • —Implementation code
  • —Integration patches
  • —Test implementations

Local Development

bash
# Install dependencies
pip install -r requirements.txt

# Set environment variables
export HF_TOKEN="your_token"
export HF_USERNAME="your_username"

# Run locally
python app.py

Deployment

  1. 1.Fork this Space or create new
  2. 2.Configure secrets
  3. 3.Space will auto-start worker

Monitoring

  • —Status Updates: Every 5 seconds
  • —Implementation Iterations: Every 120 seconds
  • —Dataset Uploads: After each iteration

Output Generated

Each iteration produces:

  • —Problem analysis
  • —Architectural review
  • —Solution comparison
  • —Risk assessment
  • —Implementation code
  • —Test code

Cost

  • —Free Tier: Fully compatible
  • —Persistent: Space keeps running 24/7
  • —Storage: Dataset grows over time (monitor quota)

Support

For issues or questions, open an issue in the main repository.

License

MIT License - See LICENSE file