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    Ship Agents Faster

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  • 1
    Farfalle

    Farfalle

    AI search engine - self-host with local or cloud LLMs

    Farfalle is an open-source AI-powered search engine designed to provide an answer-centric search experience similar to modern conversational search systems. The project integrates large language models with multiple search APIs so that the system can gather information from external sources and synthesize responses into concise answers. It can run either with local language models or with cloud-based providers, allowing developers to deploy it privately or integrate with hosted AI services. ...
    Downloads: 0 This Week
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  • 2
    LangGraph.js

    LangGraph.js

    Framework to build resilient language agents as graphs

    LangGraphJS is a JavaScript framework designed to build stateful AI applications and autonomous agents using graph-based execution models. Developed as part of the LangChain ecosystem, the framework allows developers to represent complex AI workflows as graphs where nodes represent tasks and edges define the flow of execution. This structure makes it easier to implement long-running agents, multi-step reasoning pipelines, and workflows that require persistent state. LangGraphJS supports...
    Downloads: 0 This Week
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  • 3
    node-llama-cpp

    node-llama-cpp

    Run AI models locally on your machine with node.js bindings for llama

    ...Developers can use the library to perform tasks such as text generation, conversational chat, embedding generation, and structured output generation. Because it runs models locally, the platform is particularly useful for privacy-sensitive environments or offline AI deployments.
    Downloads: 9 This Week
    Last Update:
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  • 4
    dataline

    dataline

    AI data analysis and visualization on CSV, Postgres, MySQL, Snowflake

    ...Once connected, users can generate tables, charts, and reports automatically based on queries produced by the AI engine. The platform is designed with a privacy-first architecture that stores data locally on the user’s device rather than sending it to external cloud services by default. It can also hide sensitive data from language models during processing, ensuring that only necessary metadata is used for query generation.
    Downloads: 1 This Week
    Last Update:
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    Go from Code to Production URL in Seconds

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  • 5
    wllama

    wllama

    WebAssembly binding for llama.cpp - Enabling on-browser LLM inference

    wllama is a WebAssembly-based library that enables large language model inference directly inside a web browser. Built as a binding for the llama.cpp inference engine, the project allows developers to run LLM models locally without requiring a server backend or dedicated GPU hardware. The library leverages WebAssembly SIMD capabilities to achieve efficient execution within modern browsers while maintaining compatibility across platforms. By running models locally on the user’s device, wllama enables privacy-preserving AI applications that do not require sending data to remote servers. ...
    Downloads: 3 This Week
    Last Update:
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  • 6
    PasteGuard

    PasteGuard

    Masks sensitive data and secrets before they reach AI

    ...PasteGuard supports two primary modes: mask mode, which anonymizes data and still uses external APIs; and route mode, which forwards sensitive requests to a local LLM inference engine while sending the rest to the cloud. It can be self-hosted via Docker, works with a wide range of SDKs and tools, and includes a browser extension for automatic protection in everyday AI chats.
    Downloads: 3 This Week
    Last Update:
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