Showing 4 open source projects for "text based rpg engine"

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    GraphRAG

    GraphRAG

    A modular graph-based Retrieval-Augmented Generation (RAG) system

    The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs.
    Downloads: 2 This Week
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  • 2
    marqo

    marqo

    Tensor search for humans

    ...It can seamlessly handle image-to-image, image-to-text and text-to-image search and analytics. Marqo adapts and stores your data in a fully schemaless manner. It combines tensor search with a query DSL that provides efficient pre-filtering. Tensor search allows you to go beyond keyword matching and search based on the meaning of text, images and other unstructured data. Be a part of the tribe and help us revolutionize the future of search.
    Downloads: 0 This Week
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  • 3
    OmAgent

    OmAgent

    Build multimodal language agents for fast prototype and production

    OmAgent is an open-source Python framework designed to simplify the development of multimodal language agents that can reason, plan, and interact with different types of data sources. 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. ...
    Downloads: 0 This Week
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  • 4
    SeaGOAT

    SeaGOAT

    local-first semantic code search engine

    SeaGOAT is an open-source semantic code search engine designed to help developers explore and understand large codebases more efficiently. Instead of relying solely on traditional keyword search, it uses vector embeddings to represent the meaning of code and queries, allowing users to perform semantic searches that find relevant code even when the exact keywords are not present. The tool runs locally on a developer’s machine and processes repositories using a combination of embedding models and conventional search utilities, enabling both semantic and text-based retrieval methods. ...
    Downloads: 0 This Week
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