Showing 85 open source projects for "context"

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  • 1
    GPT of Death
    GPT of Death is a desktop coding assistant with GUI powered by the OpenAI API. Users supply their own API key — all billing is handled directly with OpenAI.
    Downloads: 2 This Week
    Last Update:
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  • 2
    Qwen-of-Death
    Qwen of Death is a desktop coding assistant with GUI powered by the Qwen API. Users supply their own API key — all billing is handled directly with Openrouter.ai.
    Downloads: 0 This Week
    Last Update:
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  • 3
    Grok of Death
    Grok of Death is a desktop coding assistant with GUI powered by the Grok API. Users supply their own API key — all billing is handled directly with xAI.
    Downloads: 1 This Week
    Last Update:
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  • 4
    Claude of Death
    Claude of Death is a desktop coding assistant with GUI powered by the Anthropic Claude API. Users supply their own API key — all billing is handled directly with Anthropic.
    Downloads: 0 This Week
    Last Update:
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  • 5
    Frontman

    Frontman

    AI coding agent for visual frontend fixes in your browser

    ...Unlike IDE-only coding tools, Frontman sees the live DOM, component tree, computed CSS, routes, source maps, screenshots, console output, and server logs. That runtime context helps product managers, designers, and frontend teams fix copy, spacing, colors, layout bugs, and internal UI polish without guessing which file owns a rendered element. Works with Next.js, Astro, Vite, React, Vue, Svelte, and SvelteKit. BYOK model support includes OpenAI, Anthropic, OpenRouter, Google, xAI, Fireworks, NVIDIA, and more. ...
    Downloads: 11 This Week
    Last Update:
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  • 6
    Mentat

    Mentat

    Mentat - The AI Coding Assistant

    Mentat is the AI tool that assists you with any coding task, right from your command line. Unlike Copilot, Mentat coordinates edits across multiple locations and files. And unlike ChatGPT, Mentat already has the context of your project, no copy and pasting is required. Run Mentat from within your project directory. Mentat uses Git, so if your project doesn't already have Git set up, run git init. List the files you would like Mentat to read and edit as arguments. Mentat will add each of them to context, so be careful not to exceed the GPT-4 token context limit.
    Downloads: 0 This Week
    Last Update:
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  • 7
    bloop

    bloop

    bloop is a fast code search engine written in Rust

    Bloop is an AI-powered code search tool designed to help developers quickly find relevant code snippets, documentation, and usage examples within large repositories. It provides natural language search capabilities and AI-enhanced recommendations for improving code discovery.
    Downloads: 1 This Week
    Last Update:
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  • 8
    Aide

    Aide

    The open source AI-native IDE

    ...Built to act as a full-stack collaborator, it understands multi-file projects, detects dependency relationships, and can generate consistent updates across files and frameworks. It supports multiple backends—including OpenAI, Anthropic, and open-source models—and can route requests based on task type or latency requirements. Aide stores context efficiently, caching embeddings of codebases to accelerate reasoning and maintain memory across sessions. Developers can query Aide for explanations, generate docstrings, fix bugs, or scaffold full modules, all while preserving project structure. With a modular architecture, Aide can run locally for privacy-sensitive work or connect to managed servers for collaborative environments.
    Downloads: 6 This Week
    Last Update:
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  • 9
    LongCat-2.0

    LongCat-2.0

    Trillion-parameter MoE model for coding and million-token reasoning

    ...The model was pretrained on more than 35 trillion tokens and trained entirely on a large-scale cluster of domestically developed AI accelerators, demonstrating stable frontier-scale training without rollback events. LongCat-2.0 introduces LongCat Sparse Attention and extensive 1M-context training, enabling native processing of million-token inputs for long-document analysis, repository-scale coding, and complex multi-step reasoning. Dedicated post-training further strengthens coding and agent performance, producing competitive benchmark results against leading proprietary models.
    Downloads: 0 This Week
    Last Update:
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    Cut Data Warehouse Costs by 54%

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  • 10
    Kimi K2.7 Code

    Kimi K2.7 Code

    Coding-focused Kimi model for long-horizon agent workflows

    ...It improves end-to-end task completion across real-world programming scenarios while reducing thinking-token usage by about 30% compared with K2.6. Architecturally, it uses a 1T-parameter Mixture-of-Experts design with 32B activated parameters, 61 layers, 384 experts, a 256K-token context window, and a MoonViT vision encoder. The model supports image and video input, native INT4 quantization, interleaved thinking, and multi-step tool calling. It also forces preserve-thinking mode by default, retaining full reasoning context across multi-turn interactions to improve coding-agent consistency. K2.7 Code is recommended for use through Kimi Code CLI and can be deployed with vLLM, SGLang, or KTransformers.
    Downloads: 0 This Week
    Last Update:
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