Showing 5 open source projects for "graphs"

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  • 1
    TrustGraph

    TrustGraph

    Deploy reasoning AI agents powered by agentic graph RAG in minutes

    TrustGraph is an AI-driven framework designed to assess and visualize trust relationships within networks, aiding in the analysis of trustworthiness and influence among entities.
    Downloads: 6 This Week
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  • 2
    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 tier. LangGraph Studio requires docker-compose version 2.22.0+ or higher. ...
    Downloads: 19 This Week
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  • 3
    Langchainrb

    Langchainrb

    Build LLM-powered applications in Ruby

    LangchainRB is a Ruby implementation of LangChain, allowing developers to build AI-driven applications using large language models (LLMs) and knowledge graphs.
    Downloads: 1 This Week
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  • 4
    LangGraph

    LangGraph

    Build resilient language agents as graphs

    LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application,...
    Downloads: 11 This Week
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    Ship Agents Faster

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  • 5
    cognee

    cognee

    Deterministic LLMs Outputs for AI Applications and AI Agents

    Cognee implements scalable, modular data pipelines that allow for creating the LLM-enriched data layer using graph and vector stores. Cognee acts a semantic memory layer, unveiling hidden connections within your data and infusing it with your company's language and principles. This self-optimizing process ensures ultra-relevant, personalized, and contextually aware LLM retrievals. Any kind of data works; unstructured text or raw media files, PDFs, tables, presentations, JSON files, and so...
    Downloads: 1 This Week
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