Learnable Object Valuation Engine - Ethical governance system for computational decisions
This project has been archived.
The maintainers of this project have marked this project as archived. No new releases are expected.
Project description
💎 LOVE AI - Learnable Object Valuation Engine
Ethical Governance System for Computational Decisions
🎯 What is LOVE?
LOVE is a framework that helps computational systems take ethical decisions about potentially destructive actions, using principles of informational preservation and weighted attention.
Simply put: It protects what is fragile without paralyzing the system.
"Love is the human name for the universal principle of complexity preservation."
🚀 Getting Started
1. 📚 User Documentation
Go here if you want to:
- Install the library
- See code examples (
is_allowed,decide) - Configure thresholds (
heart.txt) - Understand the metrics
2. 🔬 Scientific Paper
Go here if you want to:
- Understand the underlying math (Entropy, Omega, Forgiveness)
- See the experimental validation results
- Read about the philosophical implications of "Machine Love"
⚡ Installation
# Basic installation (offline mode)
pip install love-ai
# With API support (accurate stress analysis)
pip install love-ai[api]
🌍 Beyond Files: Universal Applications
LOVE AI is domain-agnostic. The "Entropy" and "Cluster" concepts can be adapted to any field:
1. DevOps & Infrastructure
- Object: A production server.
- Entropy: CPU load, memory complexity, number of active connections (High = Fragile state).
- Decision: "Should I restart this container?"
- Result: LOVE protects busy servers from accidental restarts by tired engineers.
2. Community Management
- Object: A user account.
- Entropy: Account age, karma, post history complexity.
- Decision: "Should I ban this user?"
- Result: Protecting veteran users (high complexity) from automated ban hammers, while allowing quick bans for zero-entropy spam bots.
3. Robotics
- Object: An obstacle in the path.
- Entropy: Visual complexity (Texture, edges, irregularity).
- Decision: "Should I crush it or go around?"
- Result: A rover might crush a rock (low entropy) but stop before a flower or a lost artifact (high entropy).
📄 License
AGPLv3 - see LICENSE
🙏 Acknowledgements
LOVE is the result of human and multi-AI collaboration:
- Gemini: Architecture and validation
- ChatGPT: Forgiveness concepts
- Claude: Integration and refinement
- Grok: Stochastic exploration ideas
LEGAL NOTICE: This software is free software under AGPLv3 license. If you are a company and wish to integrate this engine into a proprietary commercial product without releasing your source code, contact us for a Commercial License.
📞 Contact
- Commercial: engine.ops.love@gmail.com
- Docs: User Guide
"Preserving what's fragile, allowing what's reversible"
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file love_ai-1.2.0.tar.gz.
File metadata
- Download URL: love_ai-1.2.0.tar.gz
- Upload date:
- Size: 26.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.9.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b0d51c064419e57dc2fad5503409c6767b2eeb63aff8dfbc6100f1e004cd182c
|
|
| MD5 |
1c6c5f76f61a9eaccd416046c2072e80
|
|
| BLAKE2b-256 |
e17334227a907d43c990d244039d751d0812e5d585b53155f05b21a00869e194
|
File details
Details for the file love_ai-1.2.0-py3-none-any.whl.
File metadata
- Download URL: love_ai-1.2.0-py3-none-any.whl
- Upload date:
- Size: 23.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.9.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
faaa13dfa9292469d3ed72dafb8565c9c0eb2ecb02a994b33cf53c44b1d794c6
|
|
| MD5 |
aab91edf41b00c761477e65491457c67
|
|
| BLAKE2b-256 |
be98fe9296d7201985ff4e893ab02f215aa04e7065205d9807d5195ca83e3fae
|