# PrimisAI Nexus
 
PrimisAI Nexus is a powerful and flexible Python package for managing AI agents and coordinating complex tasks using LLMs. It provides a robust framework for creating, managing, and interacting with multiple specialized AI agents under the supervision of a central coordinator.
## Features
- **AI Base Class**: A foundational class for AI interactions.
- **Agent Class**: Extends the AI base class with additional features for specialized tasks.
- **Supervisor Class**: Manages multiple agents, coordinates tasks, and handles user interactions.
- **Debugger Utility**: Integrated debugging capabilities for logging and troubleshooting.
- **Flexible Configuration**: Easy-to-use configuration options for language models and agents.
- **Interactive Sessions**: Built-in support for interactive chat sessions with the AI system.
## Installation
You can install PrimisAI Nexus directly from PyPI using pip:
```bash
pip install primisai
```
### Building from Source
If you prefer to build the package from source, clone the repository and install it with pip:
```bash
git clone git@github.com:PrimisAI/nexus.git
cd nexus
pip install -e .
```
## Quick Start
Here's a simple example to get you started with Nexus:
```python
from primisai.nexus.core import AI, Agent, Supervisor
from primisai.nexus.utils.debugger import Debugger
# Configure your OpenAI API key
llm_config = {
"api_key": "your-api-key-here",
"model": "gpt-4o",
"base_url": "https://api.openai.com/v1",
}
# Create a supervisor
supervisor = Supervisor("MainSupervisor", llm_config)
# Create and register agents
agent1 = Agent("Agent1", llm_config, system_message="You are a helpful assistant.")
agent2 = Agent("Agent2", llm_config, system_message="You are a creative writer.")
supervisor.register_agent(agent1)
supervisor.register_agent(agent2)
# Start an interactive session
supervisor.display_agent_graph()
supervisor.start_interactive_session()
```
## Documentation
For detailed documentation on each module and class, please refer to the inline docstrings in the source code.
## Advanced Usage
PrimisAI Nexus allows for complex interactions between multiple agents. You can create specialized agents for different tasks, register them with a supervisor, and let the supervisor manage the flow of information and task delegation.
```python
# Example of creating a specialized agent with tools
tools = [
{
"metadata": {
"name": "search_tool",
"description": "Searches the internet for information"
},
"tool": some_search_function
}
]
research_agent = Agent("Researcher", llm_config, tools=tools, system_message="You are a research assistant.", use_tools=True)
supervisor.register_agent(research_agent)
```
## License
This project is licensed under the MIT License.
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"description": "# PrimisAI Nexus\n\n \n \n\n\nPrimisAI Nexus is a powerful and flexible Python package for managing AI agents and coordinating complex tasks using LLMs. It provides a robust framework for creating, managing, and interacting with multiple specialized AI agents under the supervision of a central coordinator.\n\n## Features\n\n- **AI Base Class**: A foundational class for AI interactions.\n- **Agent Class**: Extends the AI base class with additional features for specialized tasks.\n- **Supervisor Class**: Manages multiple agents, coordinates tasks, and handles user interactions.\n- **Debugger Utility**: Integrated debugging capabilities for logging and troubleshooting.\n- **Flexible Configuration**: Easy-to-use configuration options for language models and agents.\n- **Interactive Sessions**: Built-in support for interactive chat sessions with the AI system.\n\n## Installation\n\nYou can install PrimisAI Nexus directly from PyPI using pip:\n\n```bash\npip install primisai\n```\n\n### Building from Source\n\nIf you prefer to build the package from source, clone the repository and install it with pip:\n\n```bash\ngit clone git@github.com:PrimisAI/nexus.git\ncd nexus\npip install -e .\n```\n\n## Quick Start\n\nHere's a simple example to get you started with Nexus:\n\n```python\nfrom primisai.nexus.core import AI, Agent, Supervisor\nfrom primisai.nexus.utils.debugger import Debugger\n\n# Configure your OpenAI API key\nllm_config = {\n \"api_key\": \"your-api-key-here\",\n \"model\": \"gpt-4o\",\n \"base_url\": \"https://api.openai.com/v1\",\n}\n\n# Create a supervisor\nsupervisor = Supervisor(\"MainSupervisor\", llm_config)\n\n# Create and register agents\nagent1 = Agent(\"Agent1\", llm_config, system_message=\"You are a helpful assistant.\")\nagent2 = Agent(\"Agent2\", llm_config, system_message=\"You are a creative writer.\")\n\nsupervisor.register_agent(agent1)\nsupervisor.register_agent(agent2)\n\n# Start an interactive session\nsupervisor.display_agent_graph()\nsupervisor.start_interactive_session()\n```\n\n## Documentation\n\nFor detailed documentation on each module and class, please refer to the inline docstrings in the source code.\n\n\n## Advanced Usage\n\nPrimisAI Nexus allows for complex interactions between multiple agents. You can create specialized agents for different tasks, register them with a supervisor, and let the supervisor manage the flow of information and task delegation.\n\n```python\n# Example of creating a specialized agent with tools\ntools = [\n {\n \"metadata\": {\n \"name\": \"search_tool\",\n \"description\": \"Searches the internet for information\"\n },\n \"tool\": some_search_function\n }\n]\n\nresearch_agent = Agent(\"Researcher\", llm_config, tools=tools, system_message=\"You are a research assistant.\", use_tools=True)\nsupervisor.register_agent(research_agent)\n```\n\n## License\n\nThis project is licensed under the MIT License.\n",
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