Vana Satya Proof of Contribution - Python Template

This repository serves as a template for creating a proof of contribution tasks using Python. It is executed on Vana's Satya Network, a group of highly confidential and secure compute nodes that can validate data without revealing its contents to the node operator.

Overview

This template provides a basic structure for building proof tasks that:

1. Read input files from the /input directory.
2. Process the data securely, running any necessary validations to prove the data authentic, unique, high quality, etc.
3. Write proof results to the /output/results.json file in the following format:

{
  "dlp_id": 1234, // DLP ID is found in the Root Network contract after the DLP is registered
  "valid": false, // A single boolean to summarize if the file is considered valid in this DLP
  "score": 0.7614457831325301, // A score between 0 and 1 for the file, used to determine how valuable the file is. This can be an aggregation of the individual scores below.
  "authenticity": 1.0, // A score between 0 and 1 to rate if the file has been tampered with
  "ownership": 1.0, // A score between 0 and 1 to verify the ownership of the file
  "quality": 0.6024096385542169, // A score between 0 and 1 to show the quality of the file
  "uniqueness": 0, // A score between 0 and 1 to show unique the file is, compared to others in the DLP
  "attributes": { // Custom attributes that can be added to the proof to provide extra context about the encrypted file
    "total_score": 0.5,
    "score_threshold": 0.83,
    "email_verified": true
  }
}

The project is designed to work with Intel TDX (Trust Domain Extensions), providing hardware-level isolation and security guarantees for confidential computing workloads.

Project Structure

• my_proof/: Contains the main proof logic
  • proof.py: Implements the proof generation logic
  • __main__.py: Entry point for the proof execution
  • models/: Data models for the proof system
• demo/: Contains sample input and output for testing
• Dockerfile: Defines the container image for the proof task
• requirements.txt: Python package dependencies

Getting Started

To use this template:

1. Fork this repository
2. Modify the my_proof/proof.py file to implement your specific proof logic
3. Update the project dependencies in requirements.txt if needed
4. Commit your changes and push to your repository

Customizing the Proof Logic

The main proof logic is implemented in my_proof/proof.py. To customize it, update the Proof.generate() function to change how input files are processed.

The proof can be configured using environment variables:

• USER_EMAIL: The email address of the data contributor, to verify data ownership

If you want to use a language other than Python, you can modify the Dockerfile to install the necessary dependencies and build the proof task in the desired language.

Local Development

To run the proof locally for testing, you can use Docker:

docker build -t my-proof .
docker run \
  --rm \
  --volume $(pwd)/input:/input \
  --volume $(pwd)/output:/output \
  --env [email protected] \
  my-proof

Running with Intel TDX

Intel TDX (Trust Domain Extensions) provides hardware-based memory encryption and integrity protection for virtual machines. To run this container in a TDX-enabled environment, follow your infrastructure provider's specific instructions for deploying confidential containers.

Common volume mounts and environment variables:

docker run \
  --rm \
  --volume /path/to/input:/input \
  --volume /path/to/output:/output \
  --env [email protected] \
  my-proof

Remember to populate the /input directory with the files you want to process.

Security Features

This template leverages several security features:

1. Hardware-based Isolation: The proof runs inside a TDX-protected environment, isolating it from the rest of the system
2. Input/Output Isolation: Input and output directories are mounted separately, ensuring clear data flow boundaries
3. Minimal Container: Uses a minimal Python base image to reduce attack surface

Customization

Feel free to modify any part of this template to fit your specific needs. The goal is to provide a starting point that can be easily adapted to various proof tasks.

Contributing

If you have suggestions for improving this template, please open an issue or submit a pull request.

License

MIT License