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  • 1
    BruteForceAI

    BruteForceAI

    Advanced LLM-powered brute-force tool combining AI intelligence

    ...The repository emphasizes features such as threaded execution, logging, and notification integrations, which position it as an automation-oriented project for controlled security assessment environments. From a software design perspective, its distinguishing idea is the use of language models as a front-end analysis layer that interprets a target page before the rest of the workflow proceeds.
    Downloads: 254 This Week
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  • 2
    ReCall

    ReCall

    Learning to Reason with Search for LLMs via Reinforcement Learning

    ReCall is an open-source framework designed to train and evaluate language models that can reason through complex problems by interacting with external tools. The project builds on earlier work focused on teaching models how to search for information during reasoning tasks and extends that idea to a broader system where models can call a variety of external tools such as APIs, databases, or computation engines. Instead of relying purely on static knowledge stored inside the model, ReCall allows the language model to dynamically decide when it should retrieve information or invoke external capabilities during the reasoning process. ...
    Downloads: 2 This Week
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  • 3
    WeClone

    WeClone

    One-stop solution for creating your digital avatar from chat history

    ...Developers can use the resulting model to create chatbots that simulate a specific user’s communication patterns for testing or research purposes. Overall, WeClone explores the idea of digital identity replication through machine learning and conversational modeling.
    Downloads: 0 This Week
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  • 4
    DeepSearcher

    DeepSearcher

    Open Source Deep Research Alternative to Reason and Search

    DeepSearcher is an open-source “deep research” style system that combines retrieval with evaluation and reasoning to answer complex questions using private or enterprise data. It is designed around the idea that high-quality answers require more than top-k retrieval, so it orchestrates multi-step search, evidence collection, and synthesis into a comprehensive response. The project integrates with vector databases (including Milvus and related options) so organizations can index internal documents and query them with semantic retrieval. ...
    Downloads: 0 This Week
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  • 5
    ML Ferret

    ML Ferret

    Refer and Ground Anything Anywhere at Any Granularity

    Ferret is Apple’s end-to-end multimodal large language model designed specifically for flexible referring and grounding: it can understand references of any granularity (boxes, points, free-form regions) and then ground open-vocabulary descriptions back onto the image. The core idea is a hybrid region representation that mixes discrete coordinates with continuous visual features, so the model can fluidly handle “any-form” referring while maintaining precise spatial localization. The repo presents the vision-language pipeline, model assets, and paper resources that show how Ferret answers questions, follows instructions, and returns grounded outputs rather than just text. ...
    Downloads: 0 This Week
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  • 6
    LangChain-Chatchat

    LangChain-Chatchat

    Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge

    LangChain-Chatchat (formerly Langchain-ChatGLM): A local knowledge base question answering application implementation based on large language models such as Langchain and ChatGLM. The knowledge base information of the current project is stored in the database, please initialize the database before running the project officially (we strongly recommend that you back up your knowledge files before performing operations). Relying on the open-source LLM and Embedding models supported by this...
    Downloads: 0 This Week
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  • 7
    autollm

    autollm

    Ship RAG based LLM web apps in seconds

    ...The project focuses on simplifying the usual stack of model selection, document ingestion, vector storage, querying, and API deployment into a more unified developer experience. Its core idea is that a developer can create a query engine from a document set in just a few lines and then turn that same engine into a FastAPI application almost instantly. AutoLLM supports a broad range of language models and vector databases, which makes it useful for teams that want flexibility without rewriting their application architecture every time they switch providers. ...
    Downloads: 1 This Week
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