ToolAI.io · GitHubチャンネル
GitHub上のToolAIにあるオープンソースAIプロジェクトの完全なディレクトリを、トピック、言語、ライセンス別にご覧ください。
公開リポジトリのデータ
microsoft/markitdown
Python tool for converting files and office documents to Markdown
openai/whisper
Robust Speech Recognition via Large-Scale Weak Supervision
deepseek-ai/DeepSeek-V3
An open-source project focused on large language model research and inference.
deepseek-ai/DeepSeek-R1
An open-source project focused on reasoning model research and evaluation.
anthropics/skills
Public repository for Agent Skills
anthropics/claude-code
Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands
nousresearch/hermes-agent
A self-improving AI agent built by Nous Research that features a closed learning loop, multi-platform messaging integration, and flexible model provider switching. It is designed to run on low-cost VPS, GPU clusters, or serverless infrastructure.
huggingface/transformers
A model-definition framework for state-of-the-art machine learning models across text, vision, audio, and multimodal domains, supporting both inference and training.
firecrawl/firecrawl
An open-source web context API to search, scrape, and interact with the web at scale, converting web data into clean Markdown or structured JSON for AI agents and LLMs.
langgenius/dify
Dify is an LLM application development platform for visually building workflows, RAG pipelines, and tool-using agents. It combines model management, prompt development, observability, and application APIs in a collaborative workspace that can be used as a hosted service or self-hosted.
langchain-ai/langchain
An open-source Python framework for building LLM-powered applications and agents through interoperable, chainable components and third-party integrations.
graphify-labs/graphify
Graphify is a local-first CLI tool and AI assistant skill that parses codebases, docs, SQL schemas, and PDFs into a queryable knowledge graph using deterministic AST parsing, eliminating the need for vector stores or embeddings.
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