Showing 6 open source projects for "deep"

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  • 1
    Vearch

    Vearch

    A distributed system for embedding-based vector retrieval

    Vearch is the vector search infrastructure for deep learning and AI applications. Vearch is a distributed vector storage and retrieval system which can be easily extended to billions scale. Vearch implements a high-performance, lockless real-time vector indexing subsystem that utilizes various optimization techniques to support millisecond vector update and retrieval. End-to-end one-click deployment.
    Downloads: 0 This Week
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  • 2
    Codai

    Codai

    Codai is an AI code assistant that helps developers

    Codai is an AI code assistant designed to help developers efficiently manage their daily tasks through a session-based CLI, such as adding new features, refactoring, and performing detailed code reviews. What makes codai stand out is its deep understanding of the entire context of your project, enabling it to analyze your code base and suggest improvements or new code based on your context. This AI-powered tool supports multiple LLM providers, such as OpenAI, Azure OpenAI, Ollama, Anthropic, and OpenRouter.
    Downloads: 6 This Week
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  • 3
    WeKnora

    WeKnora

    LLM framework for document understanding and semantic retrieval

    WeKnora is an open source framework developed for deep document understanding and semantic information retrieval using large language models. It focuses on analyzing complex and heterogeneous documents by combining multiple processing stages such as multimodal document parsing, vector indexing, and intelligent retrieval. It follows the Retrieval-Augmented Generation (RAG) paradigm, where relevant document segments are retrieved and used by language models to generate accurate, context-aware responses. ...
    Downloads: 5 This Week
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  • 4
    HasMCP

    HasMCP

    Convert API into MCP Server in seconds

    ...For robust security, it includes Secure Secret & Gateway Management to safeguard sensitive credentials in an encrypted vault. MCP Composition enables the construction of high-performance, modular AI systems. Finally, comprehensive Observability & Telemetry tools offer deep insights into tool usages.
    Downloads: 0 This Week
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  • 5
    MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
    Downloads: 0 This Week
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  • 6
    The Google Cloud Developer's Cheat Sheet

    The Google Cloud Developer's Cheat Sheet

    Cheat sheet for Google Cloud developers

    Every product in the Google Cloud family described in <=4 words (with liberal use of hyphens and slashes) by the Google Developer Relations Team. This list only includes products that are publicly available. There are several products in pre-release/private-alpha that will not be included until they go public beta or GA. Many of these products have a free tier. There is also a free trial that will enable you try almost everything. API platforms and ecosystems, developer and management tools,...
    Downloads: 0 This Week
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