Metadata-Version: 2.4
Name: mimicxai
Version: 0.1.0
Summary: Secure foundation model management for robotics — biometrics, LLM reasoning, emotion AI, and neural mind maps.
Project-URL: Homepage, https://github.com/mimicxai/mimicxai
Project-URL: Documentation, https://docs.mimicxai.com
Project-URL: Repository, https://github.com/mimicxai/mimicxai
Project-URL: Issues, https://github.com/mimicxai/mimicxai/issues
Project-URL: Changelog, https://github.com/mimicxai/mimicxai/blob/main/CHANGELOG.md
Author: mimicxai
License-Expression: MIT
License-File: LICENSE
Keywords: biometrics,context-protection,emotion-ai,face-recognition,foundation-models,liveness-detection,llm,mind-map,mlops,model-registry,ollama,rag,robotics,security
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Software Development :: Libraries :: Python Modules
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Description-Content-Type: text/markdown

# mimicxai

**Secure foundation model management for robotics** — biometrics, LLM reasoning, emotion AI, and neural mind maps.

[![PyPI version](https://img.shields.io/pypi/v/mimicxai.svg)](https://pypi.org/project/mimicxai/)
[![Python](https://img.shields.io/pypi/pyversions/mimicxai.svg)](https://pypi.org/project/mimicxai/)
[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)

---

## Overview

mimicxai is a unified Python framework for loading, running, and managing 15 production-ready AI models across three families:

| Family | Models | Capabilities |
|---|---|---|
| **Biometrix** | face, iris, liveness, object_signature, voice_signature | Face/iris recognition, anti-spoofing, object fingerprinting, speaker verification |
| **Darwin** | reasoning, planning, conversation, vision, context_protection, virtual_brain | LLM reasoning via Ollama, task planning, RAG knowledge maps, sensitive data redaction |
| **Emoticore** | text, emotion_face, voice, multimodal | Emotion detection from text, faces, voice, and multimodal fusion |

All models share a single `Model.load()` interface with built-in security (AES-256-GCM encryption, Ed25519 signing, RBAC).

## Quick Start

```bash
pip install mimicxai
```

```python
from mimicxai import Model

# Biometrics
face = Model.load("biometrix", task="face")
result = face.predict("photo.jpg")
match = face.match("photo_a.jpg", "photo_b.jpg")

# Darwin — LLM reasoning (auto-connects to Ollama)
darwin = Model.load("darwin", task="reasoning")
output = darwin.generate("Plan a route to the kitchen and pick up the red cup")

# Context protection — redact sensitive data
cpl = Model.load("darwin", task="context_protection")
protected = cpl.protect("SSN: 123-45-6789", provider="external")

# Virtual Brain — RAG knowledge maps
brain = Model.load("darwin", task="virtual_brain")
brain.predict(["report.pdf", "notes.txt"], action="add_files")
answer = brain.predict("What are the key findings?", action="chat")

# Emotion AI
emo = Model.load("emoticore", task="text")
mood = emo.analyze_emotion(text="I love this!")
```

## Darwin + Ollama

Darwin LLM tasks (reasoning, planning, conversation) auto-connect to [Ollama](https://ollama.com) when available:

```bash
# Pull the Darwin model
ollama pull mimicxai/darwin

# Now Model.load() will use real LLM inference instead of placeholders
darwin = Model.load("darwin", task="reasoning")
```

Backend priority: local weights → Ollama → placeholder.

## Install Extras

```bash
pip install mimicxai                    # core + registry + security
pip install mimicxai[serve]             # + FastAPI server
pip install mimicxai[vision]            # + Pillow, OpenCV
pip install mimicxai[brain]             # + scikit-learn, sentence-transformers
pip install mimicxai[train]             # + transformers, PEFT, datasets
pip install mimicxai[all]               # everything
pip install mimicxai[dev]               # + pytest, ruff, mypy, build, twine
```

## Deployment

```bash
# Local
./deploy/deploy.sh install

# Docker Compose (API + Ollama + Nginx + Prometheus)
./deploy/deploy.sh docker up

# Kubernetes
./deploy/deploy.sh k8s apply

# systemd
sudo cp deploy/mimicxai.service /etc/systemd/system/
sudo systemctl enable --now mimicxai
```

## Architecture

```
mimicxai/
├── models/
│   ├── biometrix/        # face, iris, liveness, object_signature, voice_signature
│   │   ├── face.py       # ArcFace + MTCNN (2,421 lines)
│   │   ├── iris.py       # IrisRecognition (631 lines)
│   │   ├── liveness.py   # VerifakeDetector (507 lines)
│   │   ├── object_signature.py  # ObjectBiometricNet CNN (622 lines)
│   │   └── fusion.py     # BiometricFoundationModel (706 lines)
│   ├── darwin/            # reasoning, planning, conversation, vision, CPL, virtual brain
│   │   ├── engine.py      # Ollama + transformers + GGUF (749 lines)
│   │   ├── cpl.py         # Context Protection Layer (1,085 lines)
│   │   └── virtual_brain.py  # Neural Mind Map + RAG (1,165 lines)
│   └── emoticore/         # text, face, voice, multimodal
├── security/              # AES-256-GCM, Ed25519, keyring, RBAC, audit
├── registry/              # versioning, manifests, metadata
├── serving/               # FastAPI server
├── deploy/                # Docker, K8s, systemd, Ollama, PyPI (2,500+ lines)
└── cli/                   # Typer CLI
```

## CLI

```bash
mimicx init                              # initialize workspace
mimicx keys generate                     # Ed25519 keypair
mimicx registry add my-model ./ckpt      # register model
mimicx registry list                     # list all models
mimicx serve my-model --port 8000        # start API server
```

## Security

Every model artifact is encrypted at rest (AES-256-GCM), signed on publish (Ed25519), and verified on load. The Context Protection Layer detects 17 sensitive data categories and enforces jurisdiction-aware policies (GDPR, CCPA, HIPAA).

## License

MIT

## Links

- [Documentation](https://docs.mimicxai.com)
- [GitHub](https://github.com/mimicxai/mimicxai)
- [Issues](https://github.com/mimicxai/mimicxai/issues)
- [Changelog](https://github.com/mimicxai/mimicxai/blob/main/CHANGELOG.md)
