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A professional, modular framework for building and orchestrating autonomous AI agents.

Project description

Cognitive Agent Orchestrator

A professional, modular framework for building and orchestrating autonomous AI agents with persistent memory and tool use.

Overview

Cognitive Agent Orchestrator is a research-grade framework designed to coordinate multiple specialized Large Language Model (LLM) agents. It provides:

  • Multi-Agent Coordination: Seamless handoffs between Strategic Planners, Research Analysts, and Quality Reviewers.
  • Persistent Memory: SQLite-backed storage for long-term interaction history and semantic lookup.
  • Parallel Reasoning: Concurrently evaluate logical, creative, and critical perspectives.
  • Human-in-the-Loop Tools: Safe execution of file operations and calculations with mandatory approval hooks.

Installation

pip install cognitive-agent-orchestrator

Quick Start

  1. Set your API keys:

    export OPENAI_API_KEY="sk-..."
    # Alternatively, set ANTHROPIC_API_KEY or GROQ_API_KEY
    
  2. Run the CLI:

    python -m cognitive_agent_orchestrator -q "Plan a strategy for a global marketing campaign."
    
  3. Interactive Mode:

    python -m cognitive_agent_orchestrator --interactive
    

Package Structure

  • core/: Multi-agent system, memory handling, and tool execution.
  • interfaces/: CLI and user-facing interaction modules.
  • utils/: Logging and configuration management.

Enterprise Features & License

This project is licensed under the Business Source License 1.1 (BSL 1.1).

  • Non-Commercial Use: Free for personal, educational, and research purposes.
  • Commercial/Production Use: Requires a commercial license from the licensor.
  • Conversion: On 2030-02-11, the license for specific versions will automatically convert to the Apache License 2.0.

For licensing inquiries and enterprise support, please contact: shivaysinghrajputofficial@gmail.com.

Disclaimer

This software is for educational and research purposes only. The authors are not responsible for any output generated by the underlying LLMs or actions taken by the agents.

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