Showing 3 open source projects for "component"

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  • Context for your AI agents Icon
    Context for your AI agents

    Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.

    Build data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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  • Automated RMM Tools | RMM Software Icon
    Automated RMM Tools | RMM Software

    Proactively monitor, manage, and support client networks with ConnectWise Automate

    Out-of-the-box scripts. Around-the-clock monitoring. Unmatched automation capabilities. Start doing more with less and exceed service delivery expectations.
    Learn More
  • 1
    Flowise

    Flowise

    Drag & drop UI to build your customized LLM flow

    Open source UI visual tool to build your customized LLM flow using LangchainJS, written in Node Typescript/Javascript. Conversational agent for a chat model which utilizes chat-specific prompts and buffer memory. Open source is the core of Flowise, and it will always be free for commercial and personal usage. Flowise support different environment variables to configure your instance. You can specify the following variables in the .env file inside the packages/server folder.
    Downloads: 15 This Week
    Last Update:
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  • 2
    Automated Interpretability

    Automated Interpretability

    Code for Language models can explain neurons in language models paper

    ...Instead of relying purely on manual, ad hoc interpretability probing, this repo aims to scale interpretability by using algorithmic methods that produce candidate explanations and assess their quality. It includes a “neuron explainer” component that, given a target neuron or latent feature, proposes natural language explanations or heuristics (e.g. “this neuron activates when the input has property X”) and then simulates activation behavior across example inputs to test whether the explanation holds. The project also contains a “neuron viewer” web component for browsing neurons, explanations, and activation patterns, making it more interactive and exploratory.
    Downloads: 2 This Week
    Last Update:
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  • 3
    spacy-llm

    spacy-llm

    Integrating LLMs into structured NLP pipelines

    Large Language Models (LLMs) feature powerful natural language understanding capabilities. With only a few (and sometimes no) examples, an LLM can be prompted to perform custom NLP tasks such as text categorization, named entity recognition, coreference resolution, information extraction and more. This package integrates Large Language Models (LLMs) into spaCy, featuring a modular system for fast prototyping and prompting, and turning unstructured responses into robust outputs for various...
    Downloads: 1 This Week
    Last Update:
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