Meta-Agent-with-More-Agents

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Meta-Agent-with-More-Agents is an open-source Python-based meta agent framework for orchestrating specialized AI sub-agents. It features task decomposition, inter-agent dialogue, iterative refinement, and feedback loops. By integrating with OpenAI APIs and LangChain, it dynamically assigns roles like data analysis, content creation, and decision making to different agents, enabling automated end-to-end completion of complex multi-step workflows.
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May 09 2025
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Meta-Agent-with-More-Agents

Meta-Agent-with-More-Agents

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Meta-Agent-with-More-Agents
Meta-Agent-with-More-Agents is an open-source Python-based meta agent framework for orchestrating specialized AI sub-agents. It features task decomposition, inter-agent dialogue, iterative refinement, and feedback loops. By integrating with OpenAI APIs and LangChain, it dynamically assigns roles like data analysis, content creation, and decision making to different agents, enabling automated end-to-end completion of complex multi-step workflows.
Added on:
Social & Email:
Platform:
May 09 2025
--
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What is Meta-Agent-with-More-Agents?

Meta-Agent-with-More-Agents is an extensible open-source framework that implements a meta agent architecture allowing multiple specialized sub-agents to collaborate on complex tasks. It leverages LangChain for agent orchestration and OpenAI APIs for natural language processing. Developers can define custom agents for tasks like data extraction, sentiment analysis, decision-making, or content generation. The meta agent coordinates task decomposition, dispatches objectives to appropriate agents, gathers their outputs, and iteratively refines results via feedback loops. Its modular design supports parallel processing, logging, and error handling. Ideal for automating multi-step workflows, research pipelines, and dynamic decision support systems, it simplifies building robust distributed AI systems by abstracting inter-agent communication and lifecycle management.

Who will use Meta-Agent-with-More-Agents?

  • AI researchers
  • Software developers
  • Data scientists
  • Automation engineers
  • DevOps teams

How to use the Meta-Agent-with-More-Agents?

  • Step1: Clone the repository: git clone https://github.com/Jeomon/Meta-Agent-with-More-Agents.git
  • Step2: Navigate into the project directory and install dependencies: pip install -r requirements.txt
  • Step3: Configure your OpenAI API key by setting the OPENAI_API_KEY environment variable
  • Step4: Define or customize sub-agents in the config file (config.yaml or code)
  • Step5: Run the main orchestration script with your task prompt: python main.py --task "Your task here"
  • Step6: Review outputs and logs, then iterate on agent definitions or workflows as needed

Platform

  • mac
  • windows
  • linux

Meta-Agent-with-More-Agents's Core Features & Benefits

The Core Features

  • Meta agent orchestration of multiple sub-agents
  • Dynamic task decomposition and assignment
  • Inter-agent communication and feedback loops
  • Modular custom agent integration
  • LangChain and OpenAI API support
  • Parallel processing and logging

The Benefits

  • Scalable multi-agent workflows
  • Modular and extensible design
  • Automated end-to-end task completion
  • Easy integration with LLMs
  • Improved task accuracy via iterative refinement

Meta-Agent-with-More-Agents's Main Use Cases & Applications

  • Automated data extraction and analysis pipelines
  • Multi-step content generation workflows
  • Research task orchestration and summarization
  • Decision support systems with specialized agents
  • Dynamic customer support ticket processing

FAQs of Meta-Agent-with-More-Agents

Meta-Agent-with-More-Agents Company Information

Meta-Agent-with-More-Agents Reviews

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Meta-Agent-with-More-Agents's Main Competitors and alternatives?

  • LangChain Agents
  • Auto-GPT
  • BabyAGI
  • Microsoft Semantic Kernel
  • AgentSmith

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