Search Results for "code editor"
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Showing 7 open source projects for "code editor"
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1
Unity MCP
AI-powered bridge connecting LLMs and advanced AI agents
...The project enables AI tools such as coding assistants and autonomous agents to interact directly with Unity projects, allowing them to analyze scenes, modify assets, and generate code within the development environment. By exposing Unity editor functionality through MCP tools, the plugin allows external AI systems to understand the structure of a game project and manipulate it programmatically. Developers can use natural language prompts to instruct AI assistants to create objects, modify scenes, or generate gameplay scripts automatically. ... -
2
Minuet
Dance with Intelligence in Your Code
Minuet-AI.nvim is an open-source Neovim plugin that provides AI-powered code completion by connecting the editor to modern large language models. The project is designed to bring real-time AI assistance directly into the developer’s editing environment while maintaining the speed and flexibility expected from the Neovim ecosystem. Instead of relying on a single provider, the plugin supports a variety of LLM backends, allowing developers to choose among services such as OpenAI, Claude, Gemini, Codestral, Ollama, or local inference engines. ... -
3
Superset LLM
Run an army of Claude Code, Codex, etc. on your machine
Superset is a development environment and terminal-based platform designed to orchestrate multiple AI coding agents simultaneously within a single workspace. The tool enables developers to run many autonomous coding agents in parallel without the typical overhead of manually managing multiple terminals, repositories, or branches. Each agent task is isolated in its own Git worktree, ensuring that code changes from different agents do not interfere with each other while allowing developers to... -
4
llama.vim
Vim plugin for LLM-assisted code/text completion
llama.vim is a lightweight Vim plugin that integrates large language model capabilities directly into the Vim text editor. The plugin enables developers to access AI-assisted text and code completion features without leaving their terminal-based development environment. Instead of relying on remote AI services, the plugin is designed to work with locally running LLM inference engines such as llama.cpp. This approach allows developers to benefit from AI-assisted coding features while maintaining full control over their data and avoiding external API dependencies. ... -
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5
vim-ai
AI-powered code assistant for Vim. OpenAI and ChatGPT plugin for Vim
vim-ai is an AI-powered assistant plugin for Vim and Neovim that brings language-model features directly into the editor. It allows users to generate code or text, edit selections in place, and carry on interactive chat-style conversations without leaving the terminal editing environment. The plugin is built around OpenAI-compatible APIs, which means it can work not only with OpenAI itself but also with compatible proxies and alternative providers. -
6
CodeLlama
Inference code for CodeLlama models
...It targets both general software synthesis and language-specific productivity, offering strong performance among open models at release time. Typical usage includes prompt-driven generation, function or class completion, and zero-shot adherence to natural-language instructions about code changes. The ecosystem provides multiple distributions (e.g., HF format) so developers can integrate with standard toolchains and serving stacks. As part of the broader Llama effort, Code Llama complements instruction-tuned chat models by focusing on code-centric tasks and editor integrations. -
7
AIConfig
AIConfig is a config-based framework to build generative AI apps
AIConfig is an open-source framework designed to simplify the development and management of generative AI applications by separating AI logic from application code. The framework allows prompts, model configurations, and parameters to be stored as structured configuration files that can be version controlled and managed independently from the rest of the software system. This approach improves collaboration between developers, prompt engineers, and machine learning practitioners by turning...
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