🧠 TinyAGI (Preview Version)
TinyAGI is a modular, extensible, and lightweight framework for building Artificial General Intelligence (AGI) systems. TinyAGI allows you to create and manage AI agents, plugins, modules, and tools within a flexible, scalable architecture, supporting multiple model backends like OpenAI, Llama.cpp, Ollama, AlpacaX, and Tabitha.
Disclaimer: This is a preview release (version 0.0.2). TinyAGI is currently under active development, and this version is intended for testing, feedback, and early experimentation. Expect frequent updates and potential changes to the API.
🧩 Key Features
- Multi-Model Support: Integrate with OpenAI, Llama.cpp, Ollama, AlpacaX, and Tabitha, providing flexibility for various tasks.
- Modular Architecture: Add, update, or remove agents and plugins with ease.
- Dynamic Plugin System: Extend functionality with plugins for tasks like text summarization, content formatting, and more.
- CLI and API Interfaces: Interact with TinyAGI using the command-line interface or RESTful API.
- AgentX System: Manage multiple AI agents with unique configurations and specialized behaviors.
- Task Automation: Orchestrate agents, plugins, and tools to automate complex workflows.
📦 Installation
Install TinyAGI with pip (Python 3.8 or higher required):
pip install TinyAGI
For the latest development version, you can clone the repository:
git clone https://github.com/SullyGreene/TinyAGI.git
cd TinyAGI
pip install -e .
🚀 Getting Started
-
Create a Configuration File: Define your agent and model parameters in a JSON file.
{ "agent": { "name": "TinyAGI Agent", "version": "0.0.2" }, "model": { "type": "llama_cpp", "name": "Llama-2-7B", "parameters": { "model_path": "models/llama-2-7b.ggmlv3.q4_0.bin", "temperature": 0.7, "max_tokens": 512 } } }
-
Run the Agent: Create a Python script to initialize and run the agent.
from TinyAGI.agent import Agent if __name__ == '__main__': agent = Agent(config_file='config/agent_config.json') agent.run()
-
Interact with Your Agent: Use the command-line interface or API to execute tasks, generate text, and more.
🛠 Example Use Cases
- Content Generation: Generate articles, summaries, or encyclopedia entries using specialized plugins.
- Data Analysis: Automate data processing, summarization, and report generation.
- Interactive Chatbots: Create engaging chatbots that integrate knowledge retrieval and sentiment analysis.
📝 Contributing
Contributions are welcome! Please see our contribution guidelines to get started. TinyAGI Hub is also available for community plugins, agents, and tools at TinyAGI Hub.
🛡 License
This project is licensed under the MIT License. See the LICENSE file for details.
Disclaimer
This release is version 0.0.2 and is a preview for testing and feedback. The framework is in active development, so expect frequent updates and possible changes to the API and functionality.
Ready to experiment? Install TinyAGI today and help shape the future of AGI development! 🚀
Metadata
Release files for TinyAGI 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| TinyAGI-0.0.2.tar.gz | 20.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| TinyAGI-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 67.6 kB
Release files / TinyAGI-0.0.2.tar.gz
| Download URL | TinyAGI-0.0.2.tar.gz |
|---|---|
| Size | 20.9 kB |
| Tags | Source |
|
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No |
| Uploaded via |
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Release files / TinyAGI-0.0.2-py3-none-any.whl
| Download URL | TinyAGI-0.0.2-py3-none-any.whl |
|---|---|
| Size | 46.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.10.12
|