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GitHub
AI Image·2025
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RapidRAW

CyberTimon (Timon Käch)

GPU-accelerated, non-destructive RAW photo editor designed for fast, low-footprint desktop workflows (<20MB). Built with Rust/WGPU/Tauri, it offers real-time 32-bit GPU processing, AI-assisted masking and optional ComfyUI integration for generative edits, plus presets and batch export.

#rust#ai-image#image#ai-tools#github+1
GitHub
AI Infra·2025
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Project N.O.M.A.D.

Crosstalk-Solutions

Offline-first knowledge server that bundles local AI chat (Ollama + vector RAG), offline Wikipedia/education/maps, and utility tools behind a Dockerized management UI — designed to keep searchable knowledge available without cloud access.

#docker#RAG#embeddings#ai-tools#llm+3
GitHub
AI Client·2025
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MonkeyCode

chaitin

Browser-based AI development platform that runs tasks inside isolated cloud development environments: natural-language agents read code, run commands, modify files, and integrate results back into Git. Key features include per-task sandboxes, multi-model selection, and an enterprise private-deploy option.

#ai-client#ai-agent#ai-coding#github#LLM+3
GitHub
AI Agent·2025
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Coze Studio

Coze (coze-dev)

Provides a visual, low-code environment to build, debug, and deploy AI agents—integrates model services (OpenAI, Volcengine), RAG, plugins, workflows, and a Chat SDK for embedding agents into apps.

#ai-agent#ai-workflow#plugin#RAG#llm+4
GitHub
AI Infra·2025
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OpenRAG

langflow-ai·Langflow

Bundles Langflow, Docling, and OpenSearch into one installable package so you can ingest messy documents, run agentic retrieval with re-ranking, and chat over your own knowledge base. Ships Python/TS SDKs and a built-in MCP server at /mcp.

#RAG#ai-workflow#mcp-server#python#typescript+5
AI Agent·2025
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Kiro: Agentic AI development from prototype to production

Amazon Web Services (AWS)

Spec-driven agentic dev platform that turns a prompt into requirements, a design doc, and sequenced tasks before any code is written, then implements from the spec. Runs across IDE, CLI, web, and mobile; validates output with property-based tests.

#vibe-coding#mcp#agent-skills#ai-coding#ai-development+5
GitHub
AI Video·2025
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VideoAgent

Hengji Zhou, Lingxuan Huang +5·South China University of Technology, The University of Hong Kong +2

An agentic framework that analyzes, plans, and executes multi-step video understanding and editing workflows using multimodal LLM-driven agents—features intent decomposition, graph-based workflow orchestration, and automated shot planning for long-form video tasks.

#video#ai-video#multimodal#ai-agent#LLM+7
GitHub
AI Coding·2025
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OpenSpec

Fission-AI

Adds a lightweight, spec-driven workflow so AI coding assistants agree on requirements before code is produced — creates per-change artifacts (proposal, specs, design, tasks), exposes CLI slash-commands, and integrates with 20+ tools for repeatable AI-driven development.

#ai-coding#ai-workflow#ai-tools#github#agent-skills
GitHub
AI Agent·2025
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GitHub Agentic Workflows

GitHub

Write repository automation as natural-language markdown that compiles into deterministic GitHub Actions workflows running AI agents. Agents run read-only by default and write only via sanitized safe-outputs. Works with Copilot, Claude, Codex, or Gemini.

#github#ai-agent#ai-workflow#agent-skills#mcp+4
GitHub
AI Agent·2025
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OpenAgents Control (OAC)

Darren Hinde

Wraps the OpenCode CLI with a plan-first workflow: agents propose a plan you approve before any code is written, and a ContextScout step loads your repo's existing patterns so output matches house style, not generic boilerplate.

#ai-agent#ai-coding#opencode#agent-skills#ai-workflow+2
GitHub
AI Agent·2025
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Spec Kit

GitHub

Makes the spec an executable artifact: you write intent in structured markdown and AI agents generate the plan, task breakdown, and code from it. A specify CLI and slash commands drive a constitution-plan-tasks-implement workflow across 30+ coding agents.

#agent-skills#ai-coding#cli#gitHub#ai-agent+3
GitHub
AI Agent·2025
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Wegent

WeCode-AI Team·WeCode-AI

Composes AI agent teams from a Ghost+Shell+Model formula: each Bot pairs a prompt/MCP/Skills Ghost with a Chat, ClaudeCode, or Dify shell and a model like Claude or DeepSeek. Bots form Teams that run as traceable Tasks, wired to GitHub and DingTalk.

#ai-agent#mlops#github#claude#gemini+5
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