Metadata-Version: 2.1
Name: sentientone
Version: 0.1.0
Summary: An Adaptive Intelligent Systems Framework
Home-page: https://github.com/Saxanth/SentientOne
Author: SentientOne Research
Author-email: research@kirigen.co
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: asyncio
Requires-Dist: typing-extensions
Requires-Dist: dataclasses
Requires-Dist: numpy
Requires-Dist: pydantic
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: mypy; extra == "dev"
Requires-Dist: flake8; extra == "dev"
Requires-Dist: black; extra == "dev"

# SentientOne Framework

<div align="center">
  <img src="docs/assets/logo.png" alt="SentientOne Logo" width="200"/>
  <br/>
  <strong>Building Intelligence Beyond import ai</strong>
  <br/>
  <em>A Project by Kirigen.co</em>
</div>

## 🚧 Project Status: Early Development 🚧

**IMPORTANT: This project is in its INITIAL DEVELOPMENT STAGE**
(Yes, that means exactly what you think it means - we're still catching edge cases)

- Currently a Minimum Viable Product (Think iterative improvement)
- Actively evolving and under construction
- Expect significant changes and iterations
- Not yet production-ready (Unless you enjoy debugging in production)
- Seeking early-stage collaborators and researchers

### Current Development Phase
- Framework architecture being established
- Core providers being implemented
- Experimental and research-focused
- Rapid prototyping and conceptual validation

## Overview

SentientOne is what happens when you let computer scientists dream too big. We're building the kind of framework that makes traditional AI look like a calculator watching a quantum computing lecture.

### The Vision
Building AI systems that can:
- Think independently (But we keep the docs handy)
- Learn from experience (Not just from training data)
- Adapt to change (Faster than your deployment scripts)
- Secure itself (No more default credentials)
- Evolve over time (Darwin would be proud)

### What Makes Us Different

#### 1. True Cognitive Architecture
While others build neural networks, we're building neural neighborhoods:
- **Advanced Memory Systems**: Beyond simple state management - our agents maintain dynamic memory hierarchies with short-term, long-term, and working memory integration
- **Adaptive Learning Loops**: Real-time skill acquisition that makes traditional learning look slow
- **Context-Aware Processing**: Because understanding the context requires more than just processing power
- **Meta-Learning Framework**: Systems that learn to learn, because if you're going to improve, you might as well do it properly

#### 2. Multi-Agent Orchestration
Distributed intelligence that would make distributed systems developers actually smile:
- **Emergent Intelligence**: Collective behavior patterns that emerge from individual agent interactions
- **Dynamic Role Optimization**: Agents that evolve their roles based on system needs
- **Collaborative Problem Solving**: Because sometimes the best solution requires more than one perspective
- **Organizational Learning**: Knowledge sharing that makes collaboration look easy

#### 3. Enterprise Innovation
Production-ready features that won't keep your SRE team up at night:
- **Scalable Architecture**: From development to production without breaking a sweat
- **Security By Design**: Because "it works on my machine" isn't a security protocol
- **Compliance Framework**: Regulatory requirements built-in, not bolted-on
- **Enterprise Integration**: Plays nicely with your existing stack

### Real-World Impact

Our framework is designed to revolutionize:
- 🏢 **Enterprise Operations**: Self-optimizing business processes
- 🔬 **Scientific Research**: Accelerated discovery and analysis
- 🎮 **Interactive Systems**: Dynamic, adaptive user experiences
- 🤖 **Robotics**: Sophisticated behavioral control
- 📊 **Data Analysis**: Intelligent pattern recognition
- 🎯 **Decision Support**: Context-aware recommendation systems

### Technical Innovation

We're building what's next:

- **Neural-Symbolic Integration**: Combining traditional logic with modern learning. The best of both worlds, without the complexity of either.

- **Distributed Cognition**: True parallel intelligence. Multiple agents working together, sharing knowledge, and actually getting things done.

- **Explainable Intelligence**: Clear reasoning, transparent decisions. When your AI makes a choice, you'll know why.

### Core Providers

- **Agent Provider**: Manages the complete lifecycle of intelligent agents. From creation to retirement, with all the complexity handled for you.

- **Communication Provider**: Structured information exchange between agents. Clear protocols, reliable delivery, no lost messages.

- **Learning Provider**: Real-time adaptation and improvement. Learning from experience, not just from training data.

- **Memory Provider**: Reliable, consistent information storage. What goes in is what comes out, exactly when you need it.

- **Persona Provider**: Contextual behavior management. The right personality for the right situation.

- **Reasoning Provider**: Practical problem-solving capabilities. From simple logic to complex decisions, always with clear reasoning.

- **Security Provider**: Comprehensive protection by default. Because security shouldn't be an afterthought.

- **Services Provider**: Efficient resource discovery and management. The right service at the right time.

- **Storage Provider**: Dependable data persistence. Your information, exactly where and how you expect it.

- **Tools Provider**: Essential utilities for AI operations. Everything you need, nothing you don't.

- **Workflow Provider**: Intelligent process management. Complex flows made manageable.

## Features

### Is This For Me?

### Perfect For
- **AI Researchers**: Exploring cognitive architectures and multi-agent systems
- **Software Engineers**: Building intelligent applications with modular components
- **Tech Startups**: Developing AI-powered products and services
- **Academic Projects**: Studying adaptive intelligence and agent behaviors
- **Hobbyists**: Learning about AI systems through hands-on development

### Not Recommended For
- Production-ready enterprise systems (yet)
- Mission-critical applications
- Real-time processing requirements
- Systems requiring formal AI safety guarantees

## Licensing

### Key Licensing Tiers
- **Tier 0: Personal and Research Use (Free)**
  * For when your AI needs more than a requirements.txt
  * Perfect for academic pursuits (and late-night debugging sessions)
  * Experiment without explaining the GPU costs to your professor

- **Tier 1: Creator's License**
  * For startups who've graduated from proof-of-concept
  * When your MVP needs more than just a prototype
  * Early-stage product development (bugs included as features)

### Commercial Use Thresholds
Required when your project goes from development to production:
- Annual revenue exceeds $50,000
- Concurrent users surpass 50
- Total user base exceeds 1,000
- Significant computational resource usage

### Usage Example
```python
# Basic Agency Example (No edge cases were harmed in the making of this code)
from basic_agency import Agency, config

# Initialize with basic configuration (Easier than setting up a new project)
agency = Agency(config)

# Add departments (Like modules, but they actually work together)
agency.add_department("research")
agency.add_department("development")

# Start processing (No bottlenecks involved)
agency.start()

# Advanced Agency Example (No boilerplate required)
from advanced_agency import Agency, ExecutiveTeam, SRDepartment

# Initialize with advanced features (It's not rocket science, but close)
agency = Agency()
executive = ExecutiveTeam(agency)
sr_dept = SRDepartment(agency)

# Configure departments (Better than managing dependencies)
agency.add_department("engineering")
agency.add_department("operations")

# Start with full management (No manual intervention needed)
agency.start()
executive.start_monitoring()
```

## Resources & Community

### Documentation
- [Getting Started Guide](docs/getting-started.md) (More than just a quick start)
- [Template Guides](docs/templates/) (Better than your code comments)
- [API Reference](docs/api/) (Comprehensive and up-to-date)
- [Examples](docs/examples/) (Not just hello world)

### Community
- [Discord Server](https://discord.gg/sentientone) (Where AI enthusiasts meet)
- [Research Forum](https://forum.sentient-ai.kirigen.co) (Deep learning, deeper discussions)
- [Blog](https://blog.sentient-ai.kirigen.co) (Better than reading the news)

### Support
- [FAQ](docs/faq.md) (Questions we get after troubleshooting)
- [Troubleshooting](docs/troubleshooting.md) (Have you tried restarting?)
- [Stack Overflow Tag](https://stackoverflow.com/questions/tagged/sentientone) (Less cryptic than error messages)

## Contributing
Please read [CONTRIBUTING.md](CONTRIBUTING.md) for details on our code of conduct and the process for submitting pull requests.

## Research and Collaboration
We're actively seeking researchers, developers, and organizations who think outside the box:

- 🔬 Cognitive Computing Research (Beyond the basics)
- 🤖 Advanced AI Systems (No, not another chatbot)
- 🧮 Complex Adaptive Systems (More complex than a simple algorithm)
- 🔄 Machine Learning (But actually learning, not just optimizing)
- 🧠 Neural Architecture (Brain-inspired, not just brain-dead)

Join us in building something that makes future AI systems say "Wow, that's intelligent!"
