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agents

Framework for training self-evolving language agents.

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What is agents?

agents is framework for training self-evolving language agents.

About

Agents 2.0 is a symbolic learning framework designed for training language agents using a systematic approach inspired by neural network training. It enables agents to learn and evolve through a process that includes loss evaluation, back-propagation, and weight updates, allowing for the optimization of both single and multi-agent systems. This tool is ideal for researchers and developers looking to implement advanced language-based AI solutions.

Strengths

  • Supports symbolic learning for language agents.
  • Allows for custom loss functions and optimizations.
  • Facilitates multi-agent system training.

Limitations

  • Requires understanding of both symbolic AI and neural networks.
  • Installation may be complex for beginners.
  • Limited community support compared to more established frameworks.

Use Cases

Training language agents for specific tasks.Optimizing multi-agent systems for collaborative tasks.Implementing custom loss functions for agent evaluation.

Integrations

PythonTensorFlowPyTorch