Showing 3 open source projects for "node graph"

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    LangGraph Studio

    LangGraph Studio

    Desktop app for prototyping and debugging LangGraph applications

    LangGraph Studio offers a new way to develop LLM applications by providing a specialized agent IDE that enables visualization, interaction, and debugging of complex agentic applications. With visual graphs and the ability to edit state, you can better understand agent workflows and iterate faster. LangGraph Studio integrates with LangSmith so you can collaborate with teammates to debug failure modes. While in Beta, LangGraph Studio is available for free to all LangSmith users on any plan...
    Downloads: 30 This Week
    Last Update:
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  • 2
    OmAgent

    OmAgent

    Build multimodal language agents for fast prototype and production

    ...The framework provides abstractions and infrastructure for building AI agents that operate on text, images, video, and audio while maintaining a relatively simple interface for developers. Instead of forcing developers to implement complex orchestration logic manually, the system manages task scheduling, worker coordination, and node optimization behind the scenes. Its architecture uses a graph-based workflow engine where tasks are represented as nodes in a directed workflow, enabling modular composition of complex reasoning pipelines. The framework also includes support for various reasoning strategies commonly used in language agents, such as chain-of-thought prompting, self-consistency reasoning, and ReAct-style decision loops.
    Downloads: 6 This Week
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  • 3
    Agents 2.0

    Agents 2.0

    An Open-source Framework for Data-centric Language Agents

    Agents is an open-source framework designed to build and train autonomous language agents through a data-centric and learning-oriented architecture. The project introduces a concept known as agent symbolic learning, which treats an agent pipeline similarly to a neural network computational graph. In this framework, each node in the pipeline represents a step in the reasoning or action process, while prompts and tools act as adjustable parameters analogous to neural network weights. During training, the system performs a forward execution where the agent completes a task and records the trajectory of prompts, outputs, and tool usage. ...
    Downloads: 0 This Week
    Last Update:
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