Welcome to AGI, the cutting-edge project dedicated to building the core components of Artificial General Intelligence. At Agora, we are focusing on research-driven methodologies to design scalable, efficient, and adaptable AGI systems that can learn, reason, and perform across multiple domains.
While AGI remains in active development, our goal is to establish the foundational capabilities that will enable AGI to become a transformative technology in enterprise applications, from automation to strategic planning.
We believe these 10 must-have components are critical for creating robust and effective AGI systems. The following features are currently being researched and developed:
AGI systems must continuously learn and adapt from new data in real time, allowing them to stay relevant in rapidly changing environments without requiring retraining.
The ability to detect and autonomously correct internal errors will ensure AGI systems maintain uptime, reliability, and operational integrity without human intervention.
AGI will be capable of interfacing with external tools to generate and organize structured outputs, making it a key component in automation and decision-making processes within business and industry.
Using advanced reasoning algorithms such as Multi-Agent Temporal Sequential Cognition (MTSC) and Dynamic Prompt Optimization (DPO), AGI will be able to plan and reason over extended timeframes, making it suitable for strategic applications in business, finance, and more.
Efficiency is a key priority. AGI will be lightweight and optimized for minimal computational resource usage, enabling large-scale deployment in enterprise environments with high performance.
AGI systems will integrate multi-modal inputs—including visual, auditory, and textual data—to form a cohesive understanding of their environment, allowing them to perform complex perception tasks.
AGI must not only execute tasks but also generate creative solutions and ideas, fostering innovation in industries that require design, strategy, and novel problem-solving approaches.
AGI will output across various media types, including text, images, video, and audio, enabling its application across numerous domains, from content creation to strategic reporting.
A sophisticated memory system will allow AGI to retain and recall previous interactions, making it more effective at tasks that require context retention and long-term reasoning.
AGI will employ a flexible, liquid learning framework that enables continuous adaptation to new information, improving its decision-making and performance over time without the need for predefined data sets.
To run or contribute to AGI development, ensure that your environment meets the following requirements:
- Python 3.10 or above
- PyTorch 2.0 or above
- CUDA (for GPU acceleration, if applicable)
- Relevant Python libraries (listed in
requirements.txt)
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Clone the repository:
git clone https://github.com/agora/agi.git cd agi -
Install the necessary dependencies:
pip install -r requirements.txt
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Run initial setup scripts to configure environments:
python setup.py
You can start experimenting with AGI by launching the core modules under development. We recommend starting with the following scripts:
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Real-Time Learning Module:
python run_real_time_learning.py
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Self-Healing Module:
python run_self_healing.py
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Multi-Modal Input and Output Integration:
python run_multimodal_io.py
Please note that AGI is in the early stages of development. These modules represent prototype functionalities that will evolve over time.
We welcome contributions from the research and developer community. To contribute:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Submit a pull request following our contribution guidelines.
Ensure that all code is well-documented and adheres to our coding standards. We use Pydantic for data validation and schema creation, and expect contributions to include clear types and explanations.
We are continuously working to enhance AGI’s capabilities. Some upcoming milestones include:
- Improved Memory Systems: Expanding the scope and efficiency of embedding storage.
- Advanced Reasoning Modules: Extending MTSC and DPO frameworks for long-term strategic applications.
- Scalability: Optimizing the system for large-scale enterprise deployment.
This project is licensed under the MIT License. See the LICENSE file for more details.
Agora is not just building AGI; we are fostering a community of innovators, researchers, and developers dedicated to advancing open-source AGI. Join us on our journey to the future:
🔗 Join the Agora Discord: https://discord.com/servers/agora-999382051935506503
For inquiries and support, reach out to us at [email protected].
Let’s build the future of intelligence together.