Trending AI GitHub Repos
Trending open source AI and machine learning repositories on GitHub.
Showing 50 of 60 items
microsoft/qlib
An AI-first quant finance platform for research and live trading. It bundles data handling, model training, and reinforcement-learning-style strategies in one toolkit.
ggml-org/whisper.cpp
A fast C/C++ port of OpenAI’s Whisper that runs on laptops, phones, and edge devices. It’s the go-to option when you need offline speech transcription.
chidiwilliams/buzz
A desktop app that wraps Whisper for local transcription and translation. It turns powerful speech models into a one-click tool for creators and analysts.
activepieces/activepieces
A no-code workflow engine built around AI agents and MCP servers. It connects hundreds of tools so you can wire up agent workflows without writing glue code.
labring/sealos
An "AI-native" cloud OS on Kubernetes that lets you spin up full stacks for modern AI apps. It targets teams that want their own mini-cloud for models and data.
jomjol/AI-on-the-edge-device
Firmware that reads analog meters and similar devices with a tiny on-device vision model. It’s a practical template for bringing AI to legacy hardware.
OpenBB-finance/OpenBB
A terminal and SDK that gives analysts and AI agents clean access to financial data. It’s becoming a default backend for quant dashboards and research bots.
upscayl/upscayl
A cross‑platform image upscaler that uses open models to sharpen low-res photos. It’s a simple way to add high-quality upscaling to creative pipelines.
nautechsystems/nautilus_trader
A high-performance trading backtester and live engine used in many ML-driven strategies. It’s battle-tested infrastructure if you want to train and deploy quant agents.
huggingface/transformers
The standard library for state-of-the-art models in text, vision, audio, and combined formats. If you build with open models, you almost certainly depend on this already.
iOfficeAI/AionUi
AionUi is a local "cowork" interface for many coding agents like Gemini CLI, Claude Code, Opencode, and others. It unifies chat, tools, and project context in one desktop-style workspace.
bytedance/UI-TARS-desktop
UI‑TARS is a full desktop stack for multimodal AI agents, connecting top models with tools, memory, and UI. If you want to ship serious agent apps, this gives you infrastructure instead of starting from scratch.
anomalyco/opencode
OpenCode is an open-source coding agent that edits and writes code for you, wired into modern tooling. Use it as a local, hackable alternative to proprietary AI dev environments.
frankbria/ralph-claude-code
Ralph wraps Claude Code in an autonomous development loop that runs tasks, monitors progress, and decides when to stop. It’s a concrete testbed for hands-free agent workflows on real codebases.
gyoridavid/ai_agents_az
This repo is a curated directory of AI agents and tools, organized A–Z. It’s useful as a scouting map when you’re picking stacks or comparing agent frameworks.
anthropics/claude-code
Claude Code runs as a terminal-native coding agent that understands your repo and executes commands. It blurs the line between shell, IDE, and assistant, and it’s quickly becoming a default tool for power users.
davila7/claude-code-templates
A CLI and template pack that wires Claude Code into common project setups. It turns spinning up an AI-augmented repo into a one-command operation instead of hours of manual glue.
simstudioai/sim
Sim is an open platform for building and deploying AI agent workflows end to end. It focuses on visual orchestration, so teams can compose tools, models, and memory without hand-rolling brittle pipelines.
ChromeDevTools/chrome-devtools-mcp
This project exposes Chrome DevTools as a tool that coding agents can call. It lets AI debuggers inspect the DOM, network, and performance directly, instead of guessing from page text.
openai/openai-cookbook
The OpenAI cookbook is a large set of worked examples for building with OpenAI’s API. Treat it as a pattern library for chat apps, agents, RAG systems, and fine-grained evaluations.
ourongxing/newsnow
NewsNow is a slick news reader that pulls in real-time headlines with a modern web UI. It’s useful as a front-end shell if you want to plug in your own AI summarizer or ranking models.
virattt/ai-hedge-fund
This repo packages an "AI hedge fund team" with code for data pipelines, model training, and strategy backtesting. It’s a starting point if you want to prototype AI-driven trading rather than wiring everything from scratch.
sgl-project/mini-sglang
A slimmed-down version of the SGLang runtime aimed at easier experimentation. It focuses on fast text generation pipelines for modern language models in Python. ([github.com](https://github.com/trending))
pollen-robotics/reachy_mini
SDK for the Reachy Mini robot, giving Python hooks into perception and control. It’s a practical playground for connecting language models to real-world robot arms. ([github.com](https://github.com/trending))
cocoindex-io/cocoindex
A high-performance data transformation engine built for AI pipelines. It focuses on incremental processing, so you can keep large feature stores and training datasets in sync cheaply. ([github.com](https://github.com/trending))
cloudcommunity/Free-Certifications
A massive list of free tech and cloud courses with certifications. It’s trending as many developers reskill for AI-heavy roles without big training budgets. ([github.com](https://github.com/trending))
trimstray/the-book-of-secret-knowledge
A huge curated index of cheatsheets, tools, and guides for systems, networking, security, and more. Many AI engineers lean on it to understand the stacks they’re automating. ([github.com](https://github.com/trending))
swisskyrepo/PayloadsAllTheThings
A giant, curated list of exploit payloads and bypass tricks for web security and CTFs. It’s becoming the default knowledge base security-focused AI tools plug into. ([github.com](https://github.com/trending))
exo-explore/exo
Exo turns a pile of Macs or PCs into one AI cluster so you can run huge models at home. It auto-discovers devices, shards models across them, and uses high-speed links like Thunderbolt to get near data-center performance. ([github.com](https://github.com/trending))
GreyDGL/PentestGPT
PentestGPT wraps GPT-based models in a workflow for penetration testing. It helps security engineers generate payloads, reason about attack paths, and automate parts of red-team work. ([github.com](https://github.com/trending))
daytonaio/daytona
Daytona provides secure, elastic environments for running AI-generated code. If you're worried about letting agents touch prod, study this isolation model.
letta-ai/letta
Letta is a framework for long-lived agents with memory and tools. Use it to build assistants that actually remember projects over weeks, not prompts.
resemble-ai/chatterbox
Chatterbox is a state-of-the-art open source text-to-speech stack. If you need production-quality voices without a SaaS bill, start here.
cpacker/MemGPT
MemGPT explores memory systems for language agents, mixing long-term and short-term storage. Steal ideas from here before reinventing your own memory manager.
dinoki-ai/osaurus
Osaurus is a native macOS server for local and cloud LLMs with OpenAI- and Anthropic-style APIs. Mac developers can swap providers without rewriting code.
vectorize-io/hindsight
Hindsight provides a human-like memory layer for agents, inspired by cognitive science. Use it to move past naive "stuff everything in context" strategies.
alexfazio/viral-clips-crew
CrewAI-powered video editing workflow aimed at making viral clips. Content creators can copy the stack rather than wiring agents and editors from scratch.
thedotmack/claude-mem
A Claude Code plugin that logs your coding sessions, compresses them with Claude via the agent SDK, and feeds back relevant context into future sessions. In practice it acts like a persistent, AI-managed memory of your projects, making the assistant far more ‘aware’ of the codebase and past conversations. It’s a concrete, production-friendly take on the “long-term memory for coding agents” idea.
openai/codex
A lightweight coding agent that runs directly in your terminal, wiring OpenAI models into a loop that edits files, runs tests, and applies patches. Compared to IDE plugins, it’s closer to a shell-native ‘pair programmer’ that can operate on entire repos and workflows. Given its rapid adoption and tight integration with existing CLIs, it’s poised to become a reference design for terminal-first code agents.
ZJU-LLMs/Foundations-of-LLMs
An open book and course materials on the foundations of large language models, covering theory, architectures, training, and deployment. With >14k stars, it’s quickly becoming a go‑to learning resource for people trying to move from ‘user’ to ‘builder’ of LLMs. If you want a structured, code-linked path into the guts of modern LMs, this is a strong candidate.
GPT-SoVITS
GPT-SoVITS is a hugely popular WebUI and pipeline for few-shot TTS and voice conversion, enabling convincing voice cloning with as little as 5 seconds to 1 minute of audio, plus dataset prep tools (separation, ASR, labeling) and multi-lingual support (EN/JA/KO/ZH/Cantonese). If you’re experimenting with custom voices, VTuber-style content, or rapid TTS prototyping on consumer GPUs, this is effectively the community standard toolkit. ([github.com](https://github.com/RVC-Boss/GPT-SoVITS?utm_source=openai))
geoai
geoai is a Python package from the opengeos ecosystem that integrates deep-learning frameworks (PyTorch, Transformers, segmentation models) with geospatial tooling to handle everything from remote-sensing data download and tiling to training, inference, and interactive map visualization. It’s aimed at practitioners who want a higher-level, batteries-included stack for tasks like land-cover classification, building footprint extraction, and change detection, without reinventing all the GIS + ML plumbing. ([github.com](https://github.com/opengeos/geoai?utm_source=openai))
tinker-cookbook
tinker-cookbook provides practical, end‑to‑end examples of post‑training LLMs using Tinker, a managed fine‑tuning API from Thinking Machines Lab that handles distributed training while you control the algorithms and data. The repo includes recipes for instruction tuning, math reasoning, RLHF-style preference learning, tool use, prompt distillation, and multi-agent setups, making it a strong starting point if you want to fine‑tune open-weight models like Llama or Qwen without building your own training stack. ([github.com](https://github.com/thinking-machines-lab/tinker-cookbook?utm_source=openai))
pandas-ai
pandas-ai turns DataFrames and SQL/CSV/Parquet sources into a conversational interface, translating natural-language questions into code or SQL, running them in a (configurable) sandbox, and optionally using RAG and semantic schemas to answer more complex queries. It’s attractive for quickly giving analysts or business users an LLM front-end on top of existing data, though you do need to pay attention to security configurations given its history of prompt-injection/RCE issues that were later mitigated with new settings. ([github.com](https://github.com/sinaptik-ai/pandas-ai?utm_source=openai))
stable-diffusion-webui
stable-diffusion-webui by AUTOMATIC1111 is the de facto standard local web interface for Stable Diffusion, providing a massive feature set—txt2img, img2img, inpainting/outpainting, upscaling, LoRA/embeddings support, training utilities, and a huge extension ecosystem—on top of consumer GPUs. If you’re doing any kind of image generation or fine-tuning with Stable Diffusion in a local or lab environment, this is usually the first tool people reach for and the one most community workflows target. ([github.com](https://github.com/AUTOMATIC1111/stable-diffusion-webui?utm_source=openai))
next-ai-draw-io
A Next.js web app that layers natural-language-driven AI editing on top of draw.io diagrams, letting you create and modify diagrams through prompts. Great if your team lives in diagrams and you want AI to help refactor system designs. ([github.com](https://github.com/trending?since=daily))
dify
A very popular production-ready platform for building agentic workflows and applications, with UI, orchestration, and deployment all in one. Given its star growth, it’s becoming a de facto choice for many teams moving beyond simple RAG bots. ([github.com](https://github.com/trending?since=daily))
hello-agents
A Chinese-language tutorial project titled "从零开始构建智能体" (Building Agents from Scratch), walking through agent principles and practical implementations. Good onboarding material if you want to upskill teammates on modern agentic patterns. ([github.com](https://github.com/trending?since=daily))
Depixelization_poc
A proof-of-concept attack showing how pixelated screenshots can be reverse-engineered to recover underlying text using computer vision. A stark reminder that naive anonymization in UIs is often not privacy-safe. ([github.com](https://github.com/trending?since=daily))
agents.md
Defines AGENTS.md, a simple open format for describing coding agents: their tools, capabilities, and expectations. It’s trying to do for agents what README and OpenAPI did for repos and APIs—standardize how we document them. ([github.com](https://github.com/trending?since=daily))