tessera-hypernetwork 0.2.1

Generate per-session LoRA adapters for inference tasks

Tessera Hypernetwork

Generate per-session LoRA adapters for inference tasks. This is the Python hypernetwork service component of Tessera, which works alongside the Rust core to provide LoRA adapter generation via hypernetwork synthesis.

Features

• Doc-to-LoRA with SHINE: Generate adapters from document content using SHINE (ICML 2026) for long-context internalization
• Text-to-LoRA: Generate adapters from natural language descriptions
• Metadata-to-LoRA: Generate adapters from structured user metadata
• OpenAI-compatible API: Easy integration with existing tooling
• FastAPI: Modern async Python web framework

Installation

pip install tessera-hypernetwork

Usage

Start the hypernetwork server:

python -m tessera_hypernetwork.server

Or use the CLI:

tessera-hypernetwork serve

API

The hypernetwork service provides a FastAPI server with the following endpoints:

• POST /v1/generate - Generate a LoRA adapter for a given prompt
• GET /health - Health check endpoint

Development

Install development dependencies:

pip install tessera-hypernetwork[dev]

Run tests:

pytest

Integration with Tessera

This hypernetwork service is designed to work with the Tessera Rust core. The Rust core handles semantic caching, vector similarity search, and adapter composition, while this Python service handles the actual LoRA adapter generation via hypernetwork synthesis.

For the complete Tessera system, see: https://github.com/theoddden/Tessera

License

Apache-2.0