Tools Bench.

Product launches and open-source repos with enough signal to earn a second look.

Last Brew Time: Jun 5, 2026, 7:36 AM PT

Insight

People are building the picks-and-shovels around AI agents rather than the agents themselves

01.TOKEN AND COST REDUCTION

02.PERSISTENT AGENT MEMORY AND DOCUMENT CONTEXT

03.DATA EXTRACTION AND AGENT EYES ON THE INTERNET

04.THE UI / RUNTIME LAYER THAT DROPS AGENTS INTO REAL APPS

Featured

GitHub80.4K

PaddlePaddle/PaddleOCR

Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.

youtube
How to Fine-tune LayoutLMv3 with Annotated Documents Using PaddleOCR | Part-1: Annonate using paddle

Market Signal

Why It Has Market Pull

PaddleOCR is one of the most widely adopted open-source document-to-text toolkits, with 80K+ GitHub stars and 10K+ forks, and it has been actively repositioning itself as the OCR layer feeding LLMs and agents. The May 2026 PaddleOCR-VL-1.6 release hit 96.3% on OmniDocBench v1.6 and the April 3.5.0 release added flexible inference backends and a browser SDK — a strong signal that the project is still iterating on real production demand.

  • 80,410 GitHub stars, 10,625 forks — one of the largest open-source OCR projects on GitHub
  • PaddleOCR-VL-1.6 (May 2026) reports 96.3% accuracy on OmniDocBench v1.6 for document parsing
  • Version 3.5.0 (April 2026) introduced switchable Paddle / Transformers backends across 20 major models
  • New official PaddleOCR.js browser inference SDK lowers the barrier for web-side document parsing
  • Backed by Baidu's PaddlePaddle team and supports 100+ languages, with continued community Swift / Go ports

feedbacks

What People Are Saying

  • "Turn any PDF or image document into structured data for your AI."GitHub README

  • "PaddleOCR VL + RAG: Revolutionize Complex Data Extraction (Open-Source)"YouTube post

  • "How to Fine-tune LayoutLMv3 with Annotated Documents Using PaddleOCR"YouTube post

  • "EasyOCR vs PaddleOCR — which is the best OCR tool?"YouTube post

  • "PaddleOCR-VL document parsing finished — this is the one"YouTube post

  • "PaddleOCR Guide 2026: PP-OCRv3, v4, v5 for Developers"Tenorshare article

  • "Community Swift port and document-preprocessing platforms updated for PaddleOCR-VL in Feb/Mar 2026"GitHub topic

GitHub32.4K

CopilotKit/CopilotKit

The Frontend Stack for Agents & Generative UI. React + Angular. Makers of the AG-UI Protocol

youtube
Build a Full-Stack AI Agent with CopilotKit & CrewAI (Next.js + FastAPI) | Complete Tutorial

Market Signal

Why It Has Market Pull

CopilotKit is the React/Angular frontend stack for AI agents and the maintainer of the AG-UI protocol, which has been adopted by Google, Microsoft, AWS, Oracle, LangChain, PydanticAI, Mastra, and Agno. With 32K+ GitHub stars, a $27M round, and millions of weekly installs powering tens of millions of agent-user interactions, it has become a default choice for teams gluing agents into real apps.

  • 32,475 GitHub stars, 4,182 forks, 527 open issues — high engagement for a developer SDK
  • AG-UI protocol adopted by Google, Microsoft, AWS, Oracle, LangChain, Mastra, PydanticAI, Agno, AG2
  • Raised $27M to build the interface layer between humans and AI agents
  • Open-source repos drive millions of weekly installs and power tens of millions of agent-user interactions weekly
  • First-class React + Angular support with built-in Generative UI patterns

feedbacks

What People Are Saying

  • "The Frontend Stack for Agents & Generative UI. React + Angular. Makers of the AG-UI Protocol"GitHub README

  • "CopilotKit Soars Beyond 10,000 Stars on GitHub"Dev.to article

  • "Build a Full-Stack AI Agent with CopilotKit & CrewAI (Next.js + FastAPI)"YouTube post

  • "Google A2UI: Agent-to-User Interface — Build AI Generated Apps EASILY! (CopilotKit AG-UI)"YouTube post

  • "Build a RAG AI Agent with REAL-TIME Source Validation (CopilotKit + Pydantic AI)"YouTube post

  • "Solving the last-mile problem for AI agents"VirtusLab GitHub All-Stars feature

  • "Build an Agentic AI Travel App with CopilotKit and LangGraph"YouTube post

GitHub9.3K

NVIDIA/cosmos

NVIDIA Cosmos is an open platform of world models, datasets, and tools that enables developers to build Physical AI for robots, autonomous vehicles, smart infrastructure, and more.

youtube
NVIDIA's New AI Just Made Real Physics Look Slow

Market Signal

Why It Has Market Pull

NVIDIA Cosmos is NVIDIA's open world-foundation-model platform for physical AI — robotics, autonomous vehicles, smart infrastructure. The recently announced Cosmos 3 is positioned as the first fully open omnimodel with native vision reasoning and multimodal generation across text, image, video, sound, and action. With NVIDIA-scale distribution behind it and existing usage inside ComfyUI image-to-video pipelines, it is a credible long-horizon bet for builders touching physical-AI or simulated-data workflows.

  • 9,329 GitHub stars, 595 forks, only 8 open issues — small surface but actively maintained by NVIDIA
  • Cosmos 3 launched as the first fully open omnimodel with native vision reasoning + multimodal generation
  • Trained on 9,000 trillion tokens with measured 3D-consistency and physics-alignment metrics
  • Already integrated into ComfyUI workflows for image-to-video generation
  • Two Minute Papers coverage at 378K and 89K views — independent technical channels treat it as state-of-the-art

feedbacks

What People Are Saying

  • "NVIDIA's New AI Just Made Real Physics Look Slow"YouTube post

  • "NVIDIA Cosmos — A Video AI…For Free!"YouTube post

  • "Image to Video with Nvidia Cosmos in ComfyUI!"YouTube post

  • "An open platform of world models, datasets, and tools that enables developers to build Physical AI"GitHub README

  • "NVIDIA Launches Cosmos 3, the Open Frontier Foundation Model for Physical AI"NVIDIA newsroom

  • "Cosmos World Foundation Model Platform for Physical AI"arXiv paper

  • "NVIDIA's New AI: Wow, Video Games Become Reality!"YouTube post

HF Spaces5.1K likes

Wan2.2 Animate

Wan2.2 Animate is a Hugging Face Space tagged with gradio, region:us. It has 5118 likes on Hugging Face.

youtube
AI Character Swap: Turn 1 Photo into a Full Video with Wan 2.2 Animate

Market Signal

Why It Has Market Pull

Wan2.2-Animate is Alibaba Tongyi Wanxiang's open-source character animation and replacement model, released September 2025 and now sitting at 5,118 likes on its Hugging Face Space. It is reportedly state-of-the-art versus open-source peers (StableAnimator, LivePortrait) on quality, subject consistency, and perceptual loss, and is the active driver of the WAN family video tools that creators are using in ComfyUI pipelines.

  • 5,118 likes on Hugging Face Space — among the top character-animation Spaces
  • Alibaba Cloud Tongyi Wanxiang open-source release (Sept 19, 2025) with weights on HF, GitHub, and Moda
  • Reported to surpass StableAnimator and LivePortrait and approach closed-source Runway Act-Two in subjective evals
  • Two main modes — action imitation and role replacement — with skeleton + implicit-feature signals
  • Active creator coverage with multiple 269K+ to 613K-view YouTube tutorials within months of launch

feedbacks

What People Are Saying

  • "AI Character Swap: Turn 1 Photo into a Full Video with Wan 2.2 Animate"YouTube post

  • "WAN Animate just broke the internet (Open-Source Character Replacement)"YouTube post

  • "How To Use WAN 2.2 in ComfyUI: The BEST FREE AI Video Model"YouTube post

  • "WAN 2.2 Animate Tutorial | FREE AI Tool for Face Swap & Character Replacement"YouTube post

  • "Tongyi Wanxiang's New Action Generation Model Wan2.2-Animate Officially Open-Sourced"AIbase article

  • "Wan2.2-Animate Model Test with 4 Cases"Medium article

  • "Wan2.2-Animate | Character animation and replacement"AI Films Studio article

Product Hunt281

Google Gemma 4 12B

Gemma 4 12B processes text, vision, and audio natively without separate encoders, running on 16GB VRAM. For developers building local agentic applications who need multimodal capability without cloud dependency.

youtube
Google Gemma 4 Tutorial - Run AI Locally for Free

Market Signal

Why It Has Market Pull

Gemma 4 12B is Google DeepMind's June 2026 release — the first medium open model to natively process text, vision, and audio without separate encoders, sized to run on a 16GB-VRAM laptop. Apache 2.0 licensed with day-one Unsloth and Ollama runners, it is already drawing hundreds of thousands of views on independent local-AI channels, which is a strong early signal for adoption in the local-agent stack.

  • Released June 3, 2026 by Google DeepMind under an Apache 2.0 license
  • First medium open model with native text + image + audio + video, no separate encoders
  • Runs on 16GB VRAM — fits a typical enterprise laptop or single mid-range GPU
  • Benchmarks close to Google's larger 26B MoE variant on reasoning and agentic workflows
  • Two-week-old YouTube tutorials already at 363K+ and 323K+ views (Teacher's Tech, Zero to MVP)

feedbacks

What People Are Saying

  • "Gemma 4 12B processes text, vision, and audio natively without separate encoders, running on 16GB VRAM"Product Hunt post

  • "Google Gemma 4 Tutorial - Run AI Locally for Free"YouTube post

  • "Gemma 4 on Raspberry Pi 5: A Surprisingly Usable Local AI Setup"YouTube post

  • "The real reason Google gave away Gemma 4"YouTube post

  • "Google's new open source Gemma 4 12B analyzes audio, video — and runs entirely locally on a typical 16GB enterprise laptop"VentureBeat article

  • "Introducing Gemma 4 12B: a unified, encoder-free multimodal model"Google blog

  • "Gemma 4 - I Tested it on My Laptop and Desktop"YouTube post

Sources

GitHub

affaan-m/ECC

208.0K

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

aquasecurity/trivy

35.8K

Find vulnerabilities, misconfigurations, secrets, SBOM in containers, Kubernetes, code repositories, clouds and more

mvanhorn/last30days-skill

28.0K

AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary

lfnovo/open-notebook

25.6K

An Open Source implementation of Notebook LM with more flexibility and features

Product Hunt

Astra Autonomous Pentest

397

Astra Autonomous Pentesting makes self-healing software the new standard, a category we’re defining after 8 years and 5,000+ real-world pentests. An army of offensive pentesters and bounty hunter agents that discovers complex chained vulnerabilities, an independent validator layer drives false positives to near-zero, and AI-fix agents deliver remediation as native Cursor, Copilot, and Claude Code prompts. The reactive pentest era is over.

Empromptu AI

320

Most AI apps launch on someone else’s model and stay there forever. Empromptu AI turns live AI features into custom models you own. As your app runs, Empromptu AI captures real-world usage, human corrections, and edge cases from live AI workflows, then uses that signal to train a custom model you own. Improve accuracy, lower inference costs, and stop depending forever on rented intelligence from the same providers moving into your category.

AppWizzy

200

AppWizzy gives you a private VM with Codex installed where you build, run, and host production web apps by chatting with AI. Your code is yours, the workspace persists, and the app lives in the same environment where it was created. Pay only for AI usage, hosting days, and optional templates

Build Club Campus

191

Build Club Campus is a fun, gamified and community-driven virtual AI school for learning AI by building with it. Static courses get old fast in AI, so Campus helps you stay current through bite-sized courses, real projects, role-based use cases and community templates that evolve with the tools. Earn certifications in OpenAI, Claude, Copilot and more, and become great at AI fast - for work, startups or side hustles. It’s 100% free, as part of our mission to enable anyone to build with AI.

Novus

138

Novus is the product agent built for teams that ship fast. Connect your codebase and Novus automatically instruments, analyzes, and improves your product — no manual setup. It monitors continuously, flags usability issues proactively, and delivers intelligence for engineers and PMs.

Koji by Brilliant

120

This isn’t just a feature launch, it’s an evolution of our entire product experience. Brilliant is now a superintelligent tutor designed to work like the best human tutors. It asks the right questions, sketches right on your screen, and adapts to how you learn best.

Hacker News

Formally verified polygon intersection – Opus 4.8 oneshots, prev failed

45 pts

To my knowledge, this is the first formally verified implementation of an intersection algorithm for polygons. The experience of working with AI agents on this project changed a lot with recent model releases, as I describe in the readme. Opus 4.8 is able to provide algorithm implementation with formal proof in one shot, whereas previous models required me to provide proof strategies in multiple steps. Trust in the correctness comes entirely from the Lean checker and human review of a small spec... (45 points, 12 comments).

I Made a Claude Skill for Spec-Driven Development (SDD)

40 pts

At my work they provided a single Claude subscription for everyone on the team. To be honest I like kiro better as it provides a way better SDD management. But the company can't provide it and I can't afford it yet. Turns out I had the skill creator skill in my claude instance so I made use of it to create this Skill. I made it fully by using Claude but I wanted to make it open source, so I asked it to help me make tests and preparations for it, even a CI to run python tests. Well, we got this r... (40 points, 17 comments).

Lowfat – pluggable CLI filter that saved 91.8% of my LLM tokens

37 pts

Hi HN, Not sure if anyone would be interested. But, just wanted to share that I've been maintaining my small tool called 'lowfat' that helps me filters some of my verbose CLI output. It's a single binary, works as an agent hook or a shell wrapper. It has a plugin system to customize filters per command. The idea is pretty simple: agents don't need the full kubectl get -o yaml or any 10k-line dump to make decisions. So that lowfat sits in between, strips the noise, and passes through what matters... (37 points, 22 comments).

Cost.dev (YC W21) – making agents cost-aware and cheaper to call

33 pts

We launched Infracost on HN five years ago ( https://news.ycombinator.com/item?id=26064588 ) where our CLI generated cost estimates for infra-as-code, e.g. "this Terraform PR adds $400/mo". The idea was to shift cloud costs (FinOps) left, so engineers get visibility of costs before deployment and make better decisions. Earlier this year we started seeing agent traffic in our logs and it looked like coding agents were calling our CLI. But that CLI wasn't designed with coding agents in mind. We we... (33 points, 17 comments).

Prisma Next – data contracts, migration graphs, agent DX

13 pts

Hey I'm Will from the Prisma team, engineering manager and also the lead developer on Prisma Next. I'd like to introduce you all to the next version of Prisma: a full rewrite in TypeScript that builds on the established patterns in Prisma and comes with a family of skills that integrate it into whatever AI tooling you're using in 2026. (Read the announcement on our blog here: https://pris.ly/pn-ea ) The three topics in the title are brand new concepts in Prisma Next so let me give you a quick ru... (13 points, 2 comments).

HF Spaces

Open LLM Leaderboard

14.0K likes

Track, rank and evaluate open LLMs and chatbots Modern React interface for comparing Large Language Models (LLMs) in an open and reproducible way. 📊 Interactive table with advanced sorting and filtering 🔍 Semantic model search 📌 Pin models for comparison 📱 Responsive and modern interface 🎨 Dark/Light mode ⚡️ Optimized performance with virtualization The project is split into two main parts: React Material-UI TanStack Table & Virtual Express.js FastAPI Hugging Face API Docker The application is containerized using Docker and can be run using: Open LLM Leaderboard is a Hugging Face Space tagged with docker, leaderboard, modality:text, submission:automatic, test:public. It has 14002 likes on Hu...

AI Comic Factory

11.1K likes

Create your own AI comic with a single prompt Last release: AI Comic Factory 1.2 The AI Comic Factory has an official website: aicomicfactory.app For more information about my other projects please check linktr.ee/FLNGR. If you like the AI Comic Factory, let me know! I am always creating new spaces and exploring new ideas for demos, meaning I don't have much time to take care of all of them (I wish I could clone myself or ask robots to do it). If you appreciate the AI Comic Factory and would like to leave a tip, that would be very kind 🫶 First, I would like to highlight that everything is open-source (see here, here, here, here). However the project isn't a monolithic Space that can be dupli...

Kolors Virtual Try-On

10.1K likes

Kolors Virtual Try-On is a Hugging Face Space tagged with gradio, region:us. It has 10099 likes on Hugging Face.

MusicGen

5.1K likes

AudioCraft is a PyTorch library for deep learning research on audio generation. AudioCraft contains inference and training code for two state-of-the-art AI generative models producing high-quality audio: AudioGen and MusicGen. Installation AudioCraft requires Python 3.9, PyTorch 2.0.0. To install AudioCraft, you can run the following: We also recommend having ffmpeg installed, either through your system or Anaconda: At the moment, AudioCraft contains the training code and inference code for: MusicGen: A state-of-the-art controllable text-to-music model. AudioGen: A state-of-the-art text-to-sound model. EnCodec: A state-of-the-art high fidelity neural audio codec. Multi Band Diffusion: An EnC...

Arena Leaderboard

4.9K likes

Arena Leaderboard is a Hugging Face Space tagged with static, leaderboard, region:us. It has 4905 likes on Hugging Face.

The Ultra-Scale Playbook

3.9K likes

The ultimate guide to training LLM on large GPU Clusters Instruction to install and run locally Loading HTML fragments: There are two way to load HTML fragments: Compile them into html during build time Fetch them and insert them during run-time When to use what Use compile time fragments only on parts which you want to ensure are seen by every user right after page load (e.g logo) Use run-time fragments for everything else so that the final HTML is of reasonable size (<1MB idealy) How to add a new fragment Add it to the src/fragments folder (e.g. src/fragments/banner.html) For run-time fragments, add {{{fragment-name}}} to appropriate place in src/index.html (e.g. {{{fragment-banner}}}) For...