Showing 4 open source projects for "visual code grepper"

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  • Automate contact and company data extraction Icon
    Automate contact and company data extraction

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  • 1
    Langflow

    Langflow

    Low-code app builder for RAG and multi-agent AI applications

    Langflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database.
    Downloads: 7 This Week
    Last Update:
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  • 2
    Qwen3-VL

    Qwen3-VL

    Qwen3-VL, the multimodal large language model series by Alibaba Cloud

    Qwen3-VL is the latest multimodal large language model series from Alibaba Cloud’s Qwen team, designed to integrate advanced vision and language understanding. It represents a major upgrade in the Qwen lineup, with stronger text generation, deeper visual reasoning, and expanded multimodal comprehension. The model supports dense and Mixture-of-Experts (MoE) architectures, making it scalable from edge devices to cloud deployments, and is available in both instruction-tuned and...
    Downloads: 2 This Week
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  • 3
    LangGraph Studio

    LangGraph Studio

    Desktop app for prototyping and debugging LangGraph applications

    LangGraph Studio offers a new way to develop LLM applications by providing a specialized agent IDE that enables visualization, interaction, and debugging of complex agentic applications. With visual graphs and the ability to edit state, you can better understand agent workflows and iterate faster. LangGraph Studio integrates with LangSmith so you can collaborate with teammates to debug failure modes. While in Beta, LangGraph Studio is available for free to all LangSmith users on any plan...
    Downloads: 37 This Week
    Last Update:
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  • 4
    MGIE

    MGIE

    Guiding Instruction-based Image Editing via Multimodal Large Language

    MGIE—Guiding Instruction-based Image Editing—demonstrates how a multimodal LLM can parse natural-language editing instructions and then drive image transformations accordingly. The project focuses on making edits explainable and controllable: the model interprets text guidance, reasons over image content, and outputs edits aligned with user intent. It’s positioned as an ICLR 2024 Spotlight work, with code and references that show how to connect language planning to concrete image operations....
    Downloads: 0 This Week
    Last Update:
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