Search Results for "context" - Page 4
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Showing 91 open source projects for "context"
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kimaki
Like openclaw but on top of opencode. all opencode features
...Each Discord channel is mapped to a specific project directory, and messages sent within that channel trigger AI-driven actions such as editing files, running commands, or searching the codebase. The system is designed to streamline development workflows by eliminating context switching between communication tools and coding environments. Kimaki supports both quick setup through a shared bot and more advanced self-hosted configurations, offering flexibility for different user needs. -
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CUDA Agent
Large-Scale Agentic RL for High-Performance CUDA Kernel Generation
CUDA Agent is a research-driven agentic reinforcement learning system designed to automatically generate and optimize high-performance CUDA kernels for GPU workloads. The project addresses the long-standing challenge that efficient CUDA programming typically requires deep hardware expertise by training an autonomous coding agent capable of iterative improvement through execution feedback. Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment,... -
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MiniMax-M2
MiniMax-M2, a model built for Max coding & agentic workflows
...Benchmarks show that it achieves highly competitive scores on a wide range of intelligence and agent benchmarks, including SWE-Bench variants, Terminal-Bench, BrowseComp, GAIA, and several long-context reasoning suites. -
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Qwen2.5-Coder
Qwen2.5-Coder is the code version of Qwen2.5, the large language model
...The model supports over 92 programming languages and offers exceptional performance in generating code, debugging, and mathematical problem-solving. Qwen2.5-Coder, with its long context length of 128K tokens, is ideal for a variety of use cases, from simple code assistants to complex programming scenarios, matching the capabilities of models like GPT-4o. -
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Mermaid.js to SVG Converter
Visualize the diagrams of your projects
While coding with AI assist, I noticed bigger projects need something more rigid as context so the AI coder doesn't stray away when I try to add new features. You know, to keeps its memory fresh and not change the stuff that already works. The trick is to ask the AI to write a diagram in Mermaid.js format that solidifies the structure of the project and then use that as context to keep the AI reminded at all times what the project is as a whole. -
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Gemini of Death is a desktop coding assistant with GUI powered by the Googles Gemini API. Users supply their own API key — all billing is handled directly with Google.
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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.
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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.
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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.
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$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
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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.
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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. ... -
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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. -
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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. -
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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. -
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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. -
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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.
