Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

HERMES AGENT CAN CREATE VIDEOS. NOT WITH AN API CALL. IT WRITES THE CODE, RENDERS THE SCENES, AND STITCHES THEM INTO AN MP4. the video attached to this post was generated by Hermes Agent using manim-video skill. three bundled video skills most people skip: 1. MANIM VIDEO 3Blue1Brown-style animated...

33,817 görüntüleme • 4 ay önce •via X (Twitter)

25 Yorum

Johnny Nel | AI for Founders profil fotoğrafı
Johnny Nel | AI for Founders4 ay önce

most founders miss this... AI agents writing their own code without you lifting a finger is the real leverage

YanXbt profil fotoğrafı
YanXbt4 ay önce

@JohnnyNel_ It really is. I have my Hermes multiple tasks with different models which suits better for every task and I went to enjoy my day while he was working for me 😍

Alviss Ambassador to NAF0 profil fotoğrafı
Alviss Ambassador to NAF04 ay önce

MANIM

YanXbt profil fotoğrafı
YanXbt4 ay önce

please open your dm i can`t send you a message

Alviss Ambassador to NAF0 profil fotoğrafı
Alviss Ambassador to NAF04 ay önce

done

YanXbt profil fotoğrafı
YanXbt4 ay önce

all done🚀

ţară ♿☸🎡 { 𝔅ℜ𝔊 } profil fotoğrafı
ţară ♿☸🎡 { 𝔅ℜ𝔊 }4 ay önce

MANIM

YanXbt profil fotoğrafı
YanXbt4 ay önce

check your DM 🚀

Nahid profil fotoğrafı
Nahid4 ay önce

manim-style videos with zero GPU sounds wild

YanXbt profil fotoğrafı
YanXbt4 ay önce

It is wild you need to try it yourself

KHOA AI | HILL profil fotoğrafı
KHOA AI | HILL4 ay önce

MANIM

YanXbt profil fotoğrafı
YanXbt4 ay önce

Check your dm 🚀

Alexandre Nascimento profil fotoğrafı
Alexandre Nascimento4 ay önce

MANIN

YanXbt profil fotoğrafı
YanXbt4 ay önce

check your dm 🚀

Charlie · 云马AI · 免🪜稳连 Claude/GPT/Gemini API profil fotoğrafı
Charlie · 云马AI · 免🪜稳连 Claude/GPT/Gemini API4 ay önce

这个我挺认同的,视频生成不一定非得端到端黑盒。像 manim 这种让代理写代码再渲染,反而更可控,改一个公式、一个镜头都很清楚,特别适合做解释类内容。

YanXbt profil fotoğrafı
YanXbt4 ay önce

especially for video with technical/process explanations and workflow showcases

T. Dawei profil fotoğrafı
T. Dawei4 ay önce

MANIM

YanXbt profil fotoğrafı
YanXbt4 ay önce

Check your inbox 🚀

Renan Silverio profil fotoğrafı
Renan Silverio4 ay önce

Manim

YanXbt profil fotoğrafı
YanXbt4 ay önce

Check your dm 🚀

Nick Venturi profil fotoğrafı
Nick Venturi4 ay önce

writing python to render videos directly is so much better than spamming prompts 😅

hodeehum profil fotoğrafı
hodeehum4 ay önce

MANIM

GonAI profil fotoğrafı
GonAI3 ay önce

MANIM

ib profil fotoğrafı
ib4 ay önce

Manim

Red Pak🛸 profil fotoğrafı
Red Pak🛸3 ay önce

manim

Benzer Videolar

this is pure f*cking treasure Netflix engineers posted 20 GitHub repos that turn your Opus 5.5 into a f*cking motion empire: built for Opus 5.5 1. claude-motion: taste, checks its own frames, sound written in code. the author built it for Opus 5.5 2. claude-motion-design: HTML, Playwright and ffmpeg, no Remotion. the demo was made on Opus 5.5 3. motion-graphics-skills: 13 skills for launch videos. the README tells you to run it on Opus 5.5 4. claude-remotion-skill: a Remotion editor from one prompt. captions, B-roll, sound 5. klik-anim-skill-creation: the laws of animation and camera, built on Opus 6. hyperframes-motion-reel-skill: a showreel cut to the beat at 120 BPM, on HyperFrames 7. product-launch-motion: a full launch film. voice-over, camera, color grade 8. animate: a short clip in one canvas file, storyboarded as it goes 9. motion-design-skills: timing, color, typography, logos, Remotion 10. hyperframes-student-kit: 14 skills and 406 motion graphics cards the engines these skills render with 11. hyperframes: HTML to MP4. the one almost everyone installs 12. remotion: video written in React 13. remotion skills: the official Remotion skills for your agent 14. GSAP: the timelines HyperFrames runs on. skills: npx skills add greensock/gsap-skills taste and everything around it 15. motion-design-skill: motion principles that work with any engine 16. awesome-motion-design-agent-skills: a map of GSAP, Remotion, Lottie and Rive skills 17. motion-graphics: B-roll built straight from your transcript 18. motion-dev-animations-skill: web animation on not video 19. motion: Motion itself, formerly Framer Motion 20. lottie-web: when you need Lottie, not MP4 the stack in one line: Opus 5.5 writes the code, a skill sets the timing and the camera, an engine renders the MP4. check each repo before you install. save this.

NO1ennn

510,032 görüntüleme • 23 gün önce

The more agents and projects you have running, the harder it gets to keep track of everything through chat alone. This is where Hermes Kanban comes in. Here's how Hermes Kanban works, why it's worth using, and how I'd recommend setting it up: Chat is where you work with an agent. Kanban is where you manage the work across agents. Hermes Kanban gives you a visual dashboard for tracking tasks across your agents and projects. But it's much more than a task board. Here's what you can do with it: • Create tasks and assign them to specific Hermes agents. • Track what's ready, running, blocked, or completed. • Set dependencies so tasks wait for other work to finish. • Coordinate handoffs between specialized agents. • Review progress and see where something needs your attention. And with the dispatcher, Hermes can pick up tasks that are ready to run and launch the appropriate agent to handle them. Now, here's something I'd recommend: **Create a separate Kanban board for each major project.** For example: 📌 Content production Research → Drafting → Review → Assets → Done 📌 Software development Bugs → Features → Testing → Review → Done 📌 Business operations Research → Waiting → In Progress → Blocked → Done Hermes supports multiple isolated boards, so each project can have its own tasks, workspaces, logs, and agent workflows. You can also connect a board to a Hermes Project to keep the work tied to the right project context. The more work you hand off to Hermes, the more valuable this becomes. Instead of digging through conversations trying to figure out what every agent is doing, give each project its own board and manage the work from one place. 🎥 Video credit: Tom

Hermes Release Watch

27,640 görüntüleme • 21 gün önce

this is pure f*cking treasure ex.Antrophic engineer put together 20 GitHub repos to build a f*cking motion empire, with 1m+ combined stars: taste: > LottieFiles/motion-design-skill: timing, easing, choreography + Disney principles > iart-ai/motion-design-skills: timing, type, color, composition, logos > frankxai/awesome-motion-design-agent-skills: curated GSAP, Motion, Remotion, Lottie, Rive > ismoshushi/awesome-opus-video-skills: index of open video skills for Opus 5.5 web motion: > whaleyxbt/claude-motion: a motion design toolkit for coding agents 06 freshtechbro/claudedesignskills: 3D, animation and interactive web > 199-biotechnologies/motion-dev-animations-skill: 120fps, springs, scroll > greensock/gsap-skills: official GSAP skills, 16.6K stars video in code: > remotion-dev/skills: Remotion's own agent skills > haidrrrry/claude-remotion-skill: B-roll, captions, sound design from one prompt > Liamrjohnston/remotion-motion-graphics-skill: production-ready Remotion graphics > wilwaldon/Claude-Code-Video-Toolkit: Remotion, Manim, screen capture, FFmpeg reels & launch: > iart-ai/motion-skills: 50 skills, 14 packs, from kinetic type to WebGL > kaventro/motion-designer: your real UI, cut to music, rendered locally > Sunwood-ai-labs/hyperframes-motion-reel-skill: beat-synced reels, 120 BPM, 60 FPS > charlie947/motion-graphics-skills: 13 skills, launch-grade, no After Effects opus 5.5 pipeline: > howseen-ai/claude-motion-design: pure-code video, HTML + Playwright + ffmpeg > tuzhechen2005/opus-video-skills: hand-painted animation, kinetic type > siyuanfeng636-cpu/agentic-motion-graphics: code-to-video with Whisper + TTS > Lob0Garou/opus-visual-motion-engine: deterministic seek(t), render QA, MP4 export start at floor 01. then climb.

NO1ennn

19,287 görüntüleme • 13 gün önce

HERMES AGENT LEARNS FROM ITS OWN MISTAKES. UPDATES ITS MEMORY. CREATES ITS OWN SKILLS. NO CLOUD. EVERYTHING STORED LOCALLY. THIS IS HOW THE SELF-IMPROVING LOOP WORKS. most agents start from zero every session. Hermes carries forward what it learned. THREE MEMORY SYSTEMS: 1. PROCEDURAL MEMORY (how to act) stored in ~/.hermes/skills/ as SKILL.md files. when the agent repeats a complex workflow, it saves the procedure as a reusable skill. next time the same task comes up, it follows the skill instead of figuring it out again. you can also create skills explicitly: "create a skill called video-prep that captures how I format my video scripts. spoken english, define jargon inline, no em-dashes, close with a catchphrase." the agent writes the SKILL.md. available as a slash command from that moment. Hermes ships with 90+ skills. the number grows the longer you use it. 2. SEMANTIC MEMORY (durable facts about you) stored in ~/.hermes/memory/memory.md the agent scans conversations for facts worth remembering. preferences, habits, corrections, project details. real example from the video: agent tried to scrape a YouTube channel. URL was wrong. it failed. it updated memory.md with the correct URL pattern so it never makes the same mistake again. you can also save explicitly: "save to memory that my favorite testing framework is pytest" the agent updates memory.md immediately. this file loads into context on every session. the agent knows you better every week. 3. EPISODIC MEMORY (chat history) stored in ~/.hermes/state.db (local SQLite). every conversation. every tool call. every result. searchable with FTS5 full-text search. "search our past sessions. what was the first thing I ever said to you?" the agent queries state.db and finds it. over time, auxiliary models consolidate episodic memory into semantic memory. distilling recurring patterns into durable facts. THE SELF-IMPROVING LOOP: every agent run follows this cycle: → you send a prompt → working memory loads: SOUL.md + memory.md + relevant skills + chat history → agent calls tools (terminal, browser, delegate_task) → agent completes the task, replies to you → AFTER the reply: agent checks "did I learn something worth saving?" → if yes: updates memory.md or creates a new skill → next session starts smarter than the last this happens automatically. you don't ask the agent to learn. it decides what to remember on its own. WHAT MAKES THIS DIFFERENT FROM CLAUDE CODE: Claude Code has memory too. but Hermes stores everything locally. no cloud. your data never leaves your machine. Claude Code doesn't auto-create skills from experience. Hermes turns repeated workflows into reusable procedures. Claude Code memory is instruction-based. Hermes memory is conversational and self-updating. over months of usage, Hermes builds a knowledge base of your preferences, your projects, your mistakes, and the procedures that work for your specific workflow. the agent that remembers your birthday also remembers why your last deploy failed. NO EMBEDDINGS. PLAIN TEXT. Hermes does not use embeddings or RAG for memory. skill and memory search runs on plain text keyword matching. simpler. faster. no vector database to maintain. works entirely offline on your local machine. DELEGATE TO CLAUDE CODE: Hermes can spawn a sub-agent that runs Claude Code in headless mode: "spawn a sub-agent using Claude CLI to build a Python script that fetches the top 5 Hacker News stories to markdown." Hermes delegates. Claude Code writes the code. result returns to Hermes. Hermes runs the script and delivers the output. use Hermes for orchestration. use Claude Code for heavy coding. both tools. not competitors. WHAT HERMES DOES NOT HAVE: no built-in eval or LMOps system. no LangSmith, no LangFuse integration out of the box. trajectory export and logs exist but there is no automated quality tracking. if you need eval, build it yourself or connect external tools. the loop is self-improving. measuring how well it improves is on you. comment LOOP and I'll send you the configs that control how fast Hermes learns and what it remembers. memory limits, skill auto-creation triggers, and the auxiliary model that runs the learning. Replace your entire team with 8 hermes agents👇

YanXbt

23,088 görüntüleme • 3 ay önce

You may recall that a few months ago, I posted about yet another project of mine where I decided to make a ground-up, memory-safe Rust implementation of the manim math animation system used by 3Blue1Brown to make all his awesome math explainer videos on YouTube (see quoted post below). The original manim project is a sort of dog's breakfast amalgamation of a bunch of random software, including LaTeX and a bunch of Python and other stuff. I got rid of ALL of that and did everything from scratch, including all the typesetting. That's almost absurdly ambitious if you dig into the details. No LaTeX! All that stuff is done from scratch as part of my FrankenMarkdown project, all the numerical stuff (using FrankenNumpy and FrankenPandas and other projects of mine), etc. The one thing I decided to not reinvent is the video encoding, where it calls out to ffmpeg. Everything else is part of one compact rust cli tool and library, which weighs in at just 12.4 megabytes. Well anyway, I started the project around 3 months ago and made sure to always keep it going every single day with a few agents, as I do with over 100+ other projects I have going on at any given time. The thing is, I'm so busy with other projects, I just can't get into the weeds for stuff like this on a day-to-day basis. Once the plan is completed and turned into beads, it's basically just auto-pilot. It's already I run my /reality-check-for-project skill on all my projects a few times per week, so I knew in the abstract that the project was getting pretty close to finished, and then today I decided to dig in a bit and see where things stood. To test it, I asked Claude Opus 5.5 to build the latest FrankenManim version on my Mac and then use it to create a nice 3b1b-style explainer video about one of my favorite things in math, Hoeffding's D. I had the nice idea of using FrankenTTS to provide the narration rather than just have a silent video, which added a nice dimension to it. Anyway, everything works just amazingly well and I'm totally blown away by how good it is and how dramatically better and faster this new toolchain is than using the "agglomeration of junk" approach from the legacy manim system (no offense, that's just the reality of it... just downloading all the software used by legacy manim is many, many gigs of software written in tons of different languages, filled with bugs and weird compatibility gotchas and bound together with digital duct tape and bailing wire: "legacy manim plus MacTeX, which its docs recommend, is a 7.0 GB download and 10.9 GB installed"). By comparison, FrankenManim is one single memory-safe Rust binary that's just 12.4mb and that does it ALL (other than video encoding), that's cross-platform, that can even be compiled into wasm and run in a browser (try doing THAT with legacy manim!). And it's fast: the whole 30,431-frame 4K60 video renders in 141 seconds on my Threadripper with two 4090s GPUs. This is the way of the future. And the entire FrankenManim project is built out of my other projects: asupersync as the foundation, FrankenMarkdown, FrankenNumpy, FrankenPandas, FrankenSciPy, FrankenNetworkX, FrankenTorch, the list goes on and on. Everything is cumulative and builds on itself. I didn't even have FrankenTTS when I created the plan for FrankenManim, but now that I do, I think I'll bundle that in (it's also distributed as a library) to make it easier to add narration to your explainer videos. I'll also make a skill soon for my skills site that automates the entire process end to end of making an explainer video like this. You can either supply the script yourself or just say what you want covered and any other details and the agent can do the rest itself, fully autonomously. Perhaps it's time that people start paying attention to my approach and master plan here instead of dismissing it all as "slop" and "AI psychosis." I don't see my critics replacing all of manim with a single tiny binary, or really doing anything interesting or valuable to anyone for that matter.

Jeffrey Emanuel

19,473 görüntüleme • 24 gün önce