L2MAC
Visit WebsiteGeneral Purpose
Open Source
Facilitates the creation of extensive outputs, such as complete codebases or entire books, by leveraging multiple LLM agents working collaboratively.
About
L2MAC (Large Language Model Automatic Computer) is an open-source framework designed to overcome the fixed context limitations of individual large language models (LLMs). By orchestrating multiple LLM agents, L2MAC enables the generation of extensive and coherent outputs, making it suitable for complex tasks like developing large codebases or authoring comprehensive texts. The framework incorporates advanced memory handling, self-generating prompt programs, and tool integration for error checking and execution, ensuring high-quality and consistent results.
Features
- Multi-Agent Collaboration: Coordinates multiple LLM agents to perform complex tasks, surpassing the context limitations of individual models.
- Extensive Output Generation: Capable of producing large outputs, such as complete codebases or entire books, from a single prompt.
- Advanced Memory Handling: Utilizes sophisticated memory systems that allow agents to store, recall, and apply past interactions, enhancing task consistency and depth.
- Self-Generating Prompt Programs: Automatically creates and executes sequential prompt programs, guiding LLM agents through intricate tasks without manual intervention.
- Tool Integration and Error Handling: Integrates external tools for syntax checking and test execution, ensuring outputs are high-quality and error-free.
- Customizable Task Execution: Adaptable to various domains through customizable task execution steps, offering versatility and broad applicability.
Tags
Multi-Agent Systems
Large-Scale Simulations
Collaborative Environments