Загрузка видео...

Не удалось загрузить видео

На главную

ollama + DeepSeek v4 pro handled entire monthly dev reports on Eigent. github prs → word doc → slack message → sent to product-release channel. in just one prompt. fully local. the full walkthrough is in the thread. try the same loop on open source cowork Eigent, byo model!

Eigent_AI's profile picture

Eigent AI

3,001 subscribers

11,141 просмотров • 1 месяц назад •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Powering the future of open-source agentic work. Proud to support Eigent AI, the open-source alternative to Cowork. Thanks Guohao Li 🐫 & team! Start now:
1:02

Powering the future of open-source agentic work. Proud to support Eigent AI, the open-source alternative to Cowork. Thanks Guohao Li 🐫 & team! Start now:

Z.ai

166,564 просмотров • 5 месяцев назад

Claude Cowork is becoming a new WorkOS. We are building a 100% local and open source WorkOS, try Eigent with any models, any skills, and any connectors
1:02

Claude Cowork is becoming a new WorkOS. We are building a 100% local and open source WorkOS, try Eigent with any models, any skills, and any connectors

Guohao Li 🐫

22,338 просмотров • 3 месяцев назад

Introducing Eigent — the first multi-agent workforce on your desktop. Eigent is a team of AI agents collaborating to complete complex tasks in parallel. It is your long-term working partner with fullly customizable workers and MCPs. Public beta available to download for MacOS, Windows. 100% open-source on Github. Comment for 500 extra credits.
2:03

Introducing Eigent — the first multi-agent workforce on your desktop. Eigent is a team of AI agents collaborating to complete complex tasks in parallel. It is your long-term working partner with fullly customizable workers and MCPs. Public beta available to download for MacOS, Windows. 100% open-source on Github. Comment for 500 extra credits.

Guohao Li 🐫

220,920 просмотров • 10 месяцев назад

Eigent day 0 supports MiniMax (official) M2.5! Try M2.5 on your open source cowork! With Chinese New Year (Horse) coming, we asked Eigent to generate 10 complete HTML/CSS/JS games (no libraries) across arcade, puzzle, runner, strategy, memory, idle and more. The Developer Agent called the Terminal Toolkit, generated all 10 games, and saved them locally. Games are insanely fun and you can play them directly inside Eigent. Try it out today!
1:18

Eigent day 0 supports MiniMax (official) M2.5! Try M2.5 on your open source cowork! With Chinese New Year (Horse) coming, we asked Eigent to generate 10 complete HTML/CSS/JS games (no libraries) across arcade, puzzle, runner, strategy, memory, idle and more. The Developer Agent called the Terminal Toolkit, generated all 10 games, and saved them locally. Games are insanely fun and you can play them directly inside Eigent. Try it out today!

Eigent AI

13,816 просмотров • 4 месяцев назад

Eigent × Qwen 3.5 Plus We upload a Spring Festival Gala robot performance video and ask our open source Cowork, powered by Qwen 3.5 Plus, to turn it into a complete single-file 3D interactive Three.js game. Recreates the characters, movements, and festive stage. Full Eigent breakdown in the video.👇 Now live with BYOK, bring your own Qwen 3.5 Plus key and run it directly in Eigent.
2:52

Eigent × Qwen 3.5 Plus We upload a Spring Festival Gala robot performance video and ask our open source Cowork, powered by Qwen 3.5 Plus, to turn it into a complete single-file 3D interactive Three.js game. Recreates the characters, movements, and festive stage. Full Eigent breakdown in the video.👇 Now live with BYOK, bring your own Qwen 3.5 Plus key and run it directly in Eigent.

Eigent AI

29,748 просмотров • 3 месяцев назад

Eigent × Kimi.ai K2.5 We ran a real-world sales performance evaluation on Eigent using Kimi K2.5. Given a production sales dataset, Eigent coordinated multiple agents end to end: - The document agent extracts information from the source files - The terminal agent analyzes the data and generates an HTML report All results are stored locally! Try Eigent with Kimi K2.5 today.
1:11

Eigent × Kimi.ai K2.5 We ran a real-world sales performance evaluation on Eigent using Kimi K2.5. Given a production sales dataset, Eigent coordinated multiple agents end to end: - The document agent extracts information from the source files - The terminal agent analyzes the data and generates an HTML report All results are stored locally! Try Eigent with Kimi K2.5 today.

Eigent AI

25,263 просмотров • 4 месяцев назад

Gemini 3.5 flash + Gemini managed agents api just audited a real megatron-lm ci failure inside Eigent. root cause in minutes! watch the handoff: coordinator agent plans the audit, developer agent loads the ml-failure-audit skill and gathers the evidence, then gemini agent steps in as a remote sub-agent for the heavy reasoning. gemini managed agents api and gemini 3.5 flash now live on our open-source cowork Eigent! Google AI Developers Google AI Studio
1:30

Gemini 3.5 flash + Gemini managed agents api just audited a real megatron-lm ci failure inside Eigent. root cause in minutes! watch the handoff: coordinator agent plans the audit, developer agent loads the ml-failure-audit skill and gathers the evidence, then gemini agent steps in as a remote sub-agent for the heavy reasoning. gemini managed agents api and gemini 3.5 flash now live on our open-source cowork Eigent! Google AI Developers Google AI Studio

Eigent AI

16,335 просмотров • 1 месяц назад

Can an iPhone hold its own against a Mac? 💻📱 Ollama is running DeepSeek R1 Distill Llama 8B on a 16GB M2 MacBook Air, while the iPhone 15 Pro (8GB A17 Pro) runs the same model. Same model. Same sampling temperature. Same system prompt. While the iPhone is a bit slower, the 3-bit OmniQuant model reasons just as well as the 4-bit RTN model on the Mac. 🤯
1:07

Can an iPhone hold its own against a Mac? 💻📱 Ollama is running DeepSeek R1 Distill Llama 8B on a 16GB M2 MacBook Air, while the iPhone 15 Pro (8GB A17 Pro) runs the same model. Same model. Same sampling temperature. Same system prompt. While the iPhone is a bit slower, the 3-bit OmniQuant model reasons just as well as the 4-bit RTN model on the Mac. 🤯

Private LLM

26,440 просмотров • 1 год назад

The second year of my fully open-source graduate computational physics course is now underway NaturalSciences @ UT Oden Institute We invite students anywhere in the world to participate. Mods/Issues/PRs on GitHub welcome! (vid: condensate forms in turbulence)
0:50

The second year of my fully open-source graduate computational physics course is now underway NaturalSciences @ UT Oden Institute We invite students anywhere in the world to participate. Mods/Issues/PRs on GitHub welcome! (vid: condensate forms in turbulence)

William Gilpin

20,705 просмотров • 2 лет назад

ClickUp is working on a Cowork feature 👀 > Cowork can help users build, edit, and take action alongside them, and other agents at the same time > Sessions are persistent, so context carries across the entire workday > Multiple users can collaborate in the same Brain session simultaneously Brain Cowork can proactively work in the channel just like a human teammate, drafting docs and setting reminders in the same thread where the team is actively working.
0:20

ClickUp is working on a Cowork feature 👀 > Cowork can help users build, edit, and take action alongside them, and other agents at the same time > Sessions are persistent, so context carries across the entire workday > Multiple users can collaborate in the same Brain session simultaneously Brain Cowork can proactively work in the channel just like a human teammate, drafting docs and setting reminders in the same thread where the team is actively working.

🚨 AI News | TestingCatalog

24,249 просмотров • 19 дней назад

𝗚𝗲𝗺𝗺𝗮 𝟰 + 𝗢𝗹𝗹𝗮𝗺𝗮 + 𝗢𝗽𝗲𝗻𝗖𝗹𝗮𝘄 𝗶𝘀 𝗮 𝗳𝘂𝗹𝗹𝘆 𝗹𝗼𝗰𝗮𝗹 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁 𝘁𝗵𝗮𝘁 𝗿𝘂𝗻𝘀 𝗳𝗿𝗲𝗲 𝗳𝗼𝗿𝗲𝘃𝗲𝗿. #3 open model in the world. Runs on your laptop. Zero API costs. Zero data leaving your machine. Setup in 3 steps: → Install Ollama and run "ollama pull gemma4" — downloads the model → Install OpenClaw and select Ollama as your provider → Connect Telegram — message your agent from anywhere, completely local One prompt built a working SEO calculator — HTML, CSS, JavaScript, no debugging. Coding benchmark jumped from 110 to 2,150 vs the previous Gemma. Apache 2.0. No restrictions. No monthly bill. No surprises. Want the full setup guide? DM me.
9:07

𝗚𝗲𝗺𝗺𝗮 𝟰 + 𝗢𝗹𝗹𝗮𝗺𝗮 + 𝗢𝗽𝗲𝗻𝗖𝗹𝗮𝘄 𝗶𝘀 𝗮 𝗳𝘂𝗹𝗹𝘆 𝗹𝗼𝗰𝗮𝗹 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁 𝘁𝗵𝗮𝘁 𝗿𝘂𝗻𝘀 𝗳𝗿𝗲𝗲 𝗳𝗼𝗿𝗲𝘃𝗲𝗿. #3 open model in the world. Runs on your laptop. Zero API costs. Zero data leaving your machine. Setup in 3 steps: → Install Ollama and run "ollama pull gemma4" — downloads the model → Install OpenClaw and select Ollama as your provider → Connect Telegram — message your agent from anywhere, completely local One prompt built a working SEO calculator — HTML, CSS, JavaScript, no debugging. Coding benchmark jumped from 110 to 2,150 vs the previous Gemma. Apache 2.0. No restrictions. No monthly bill. No surprises. Want the full setup guide? DM me.

Julian Goldie SEO

76,735 просмотров • 2 месяцев назад

Just Replaced 30 engineers with 30 agents to build an entire codebase in 12 days The agents handled everything: - 44K lines of TypeScript - 175 PRs opened - 1,500+ tests written - All CI failures self-corrected fully open source, link to code below
1:14

Just Replaced 30 engineers with 30 agents to build an entire codebase in 12 days The agents handled everything: - 44K lines of TypeScript - 175 PRs opened - 1,500+ tests written - All CI failures self-corrected fully open source, link to code below

Karan Vaidya

483,504 просмотров • 3 месяцев назад

I rebuilt most of OpenClaw's core in a single workflow: - 25 blocks - 29 connections - Short + long-term memory - Multi-channel (Telegram + Slack) Didn't build it manually. Stack is fully open-source. Self-host, run local models, own it end-to-end. Full walkthrough: Chapters: 00:00 - Intro 01:00 - SimClaw in action: planning my day, finding meetings, sending email 04:05 - Long-term memory capability 05:52 - Inside the workflow: how it's wired 12:09 - The plot twist 12:50 - Building an entire workflow using a single prompt 15:42 - Why this is an OS for your AI workforce 17:00 - Try it yourself If you want to see the open-source stack that powers all of this, check out Sim on GitHub and drop a star if you find it useful:
17:21

I rebuilt most of OpenClaw's core in a single workflow: - 25 blocks - 29 connections - Short + long-term memory - Multi-channel (Telegram + Slack) Didn't build it manually. Stack is fully open-source. Self-host, run local models, own it end-to-end. Full walkthrough: Chapters: 00:00 - Intro 01:00 - SimClaw in action: planning my day, finding meetings, sending email 04:05 - Long-term memory capability 05:52 - Inside the workflow: how it's wired 12:09 - The plot twist 12:50 - Building an entire workflow using a single prompt 15:42 - Why this is an OS for your AI workforce 17:00 - Try it yourself If you want to see the open-source stack that powers all of this, check out Sim on GitHub and drop a star if you find it useful:

Akshay 🚀

65,291 просмотров • 1 месяц назад

DeepSeek released R1, the best open-source reasoning model that is on par with OpenAI's o1! I have built a RAG app to chat with your PDF files using the DeepSeek R1 model, running locally on your computer. 100% Open Source
0:50

DeepSeek released R1, the best open-source reasoning model that is on par with OpenAI's o1! I have built a RAG app to chat with your PDF files using the DeepSeek R1 model, running locally on your computer. 100% Open Source

Sumanth

678,561 просмотров • 1 год назад

Yesterday I dropped a guide on setting up Claude Cowork that blew up. One question kept coming up: how do I use all of this on my phone? Cowork doesn't have a mobile app yet. But there's a simple workaround. Push your Cowork workspace to a private GitHub repo. Open Claude Code on the Anthropic mobile app. Connect the repo. Done. Now every skill file, brain file, and writing style you built for Cowork is accessible on the go. No coding. 5 minutes to set up. Two things to know: This syncs your files and skills, not your connectors (Slack, Gmail, etc.) When you update files locally, push to GitHub to keep mobile current Full walkthrough below. Original Cowork setup guide (with the prompt to build your own system) is reposted below as well. Enjoy!!
5:45

Yesterday I dropped a guide on setting up Claude Cowork that blew up. One question kept coming up: how do I use all of this on my phone? Cowork doesn't have a mobile app yet. But there's a simple workaround. Push your Cowork workspace to a private GitHub repo. Open Claude Code on the Anthropic mobile app. Connect the repo. Done. Now every skill file, brain file, and writing style you built for Cowork is accessible on the go. No coding. 5 minutes to set up. Two things to know: This syncs your files and skills, not your connectors (Slack, Gmail, etc.) When you update files locally, push to GitHub to keep mobile current Full walkthrough below. Original Cowork setup guide (with the prompt to build your own system) is reposted below as well. Enjoy!!

JJ Englert

55,449 просмотров • 3 месяцев назад

Still can’t believe this wasn’t a reshoot. Just an edit. Runway Aleph 2.0 swapped the bag while keeping the entire scene intact. Same movement. Same lighting. Same cinematic vibe. One prompt. New product. #MadeWithRunway #ad Try Aleph 2.0 on Runway: Use code ALEPH2 for 22% off Runway Pro. Runway
0:32

Still can’t believe this wasn’t a reshoot. Just an edit. Runway Aleph 2.0 swapped the bag while keeping the entire scene intact. Same movement. Same lighting. Same cinematic vibe. One prompt. New product. #MadeWithRunway #ad Try Aleph 2.0 on Runway: Use code ALEPH2 for 22% off Runway Pro. Runway

zen.

21,549 просмотров • 22 дней назад

We deployed a fully private AI agent on NuNet in under 5 minutes 🚀 OpenClaw🦞 running Qwen through ollama , one of the hottest open source model families right now, entirely on decentralized compute. No cloud. No API keys. No data leaving the machine. This is what private AI looks like when you actually build it instead of just talking about it. Your model. Your hardware. Your rules. Full walkthrough showing exactly how it works: What should we deploy next?
12:59

We deployed a fully private AI agent on NuNet in under 5 minutes 🚀 OpenClaw🦞 running Qwen through ollama , one of the hottest open source model families right now, entirely on decentralized compute. No cloud. No API keys. No data leaving the machine. This is what private AI looks like when you actually build it instead of just talking about it. Your model. Your hardware. Your rules. Full walkthrough showing exactly how it works: What should we deploy next?

NuNet 🌐

87,520 просмотров • 2 месяцев назад

Open Source is truely winning this time, Kimi literally cooked claude design on this... and it's 7x cheaper and 100% open source see the same prompt in the comments👇
0:25

Open Source is truely winning this time, Kimi literally cooked claude design on this... and it's 7x cheaper and 100% open source see the same prompt in the comments👇

Chidanand Tripathi

78,631 просмотров • 1 месяц назад

I have been testing DeepSeek-V4-Pro with the Pi coding agent. I am mindblown by how well it works out of the box. A few notes: I spent a few hours building an LLM wiki with an agent powered entirely by DeepSeek-V4-Pro on Fireworks AI inference. This is the first time I feel like there is an open-weight model that can reason at the level of Claude and Codex. And it does this in a cost-effective way with support for 1M context length. To be clear, I am using DeepSeek-V4-Pro inside of Pi without any special configuration. It works out of the box. It's exciting that there is a model that can just be plugged into a basic harness like Pi, and it just works. I've never seen that before. Most models require lots of configuration and setup. DeepSeek's DeepSeek-V4-Pro is clearly good at agentic coding (probably the best from the open-weight models), but the model is also great on knowledge-intensive tasks where reasoning matters. The agent pulled agentic engineering best practices from different company docs (Anthropic, OpenAI, Google, Stripe, Meta, Modal, DeepSeek, Mistral, Cohere), searched and digested Reddit and HN threads, summarized arxiv papers, and surfaced trending GitHub repos. Then it distilled everything into actionable tips across categories. I love the Wiki it built. The quality is really good. Here is a snapshot of what the wiki looks like: DeepSeek-V4-Pro handled the task without breaking stride. Multi-step research queries, code generation for scaffolding, context-heavy reasoning across disparate sources. For coding specifically, this is the first open-weight model that genuinely feels like a Codex or Claude Code experience. It compares in capability and actual multi-turn agentic work. What made the loop feel so responsive was Fireworks' inference speed (the fastest in the market) and the fact that they actually validate models at the systems level before shipping. No corrupted reasoning traces. Just fast, reliable iteration. The hybrid CSA and HCA attention design cuts KV cache to just 10% and inference FLOPs by nearly 4x at 1M-token context. This is what makes the agent loop actually fast and cheap enough to run in practice. For devs who've been watching open-weight models close the gap but haven't found one that actually delivers in practice, this is the closest I've seen. Try it here:
0:31

I have been testing DeepSeek-V4-Pro with the Pi coding agent. I am mindblown by how well it works out of the box. A few notes: I spent a few hours building an LLM wiki with an agent powered entirely by DeepSeek-V4-Pro on Fireworks AI inference. This is the first time I feel like there is an open-weight model that can reason at the level of Claude and Codex. And it does this in a cost-effective way with support for 1M context length. To be clear, I am using DeepSeek-V4-Pro inside of Pi without any special configuration. It works out of the box. It's exciting that there is a model that can just be plugged into a basic harness like Pi, and it just works. I've never seen that before. Most models require lots of configuration and setup. DeepSeek's DeepSeek-V4-Pro is clearly good at agentic coding (probably the best from the open-weight models), but the model is also great on knowledge-intensive tasks where reasoning matters. The agent pulled agentic engineering best practices from different company docs (Anthropic, OpenAI, Google, Stripe, Meta, Modal, DeepSeek, Mistral, Cohere), searched and digested Reddit and HN threads, summarized arxiv papers, and surfaced trending GitHub repos. Then it distilled everything into actionable tips across categories. I love the Wiki it built. The quality is really good. Here is a snapshot of what the wiki looks like: DeepSeek-V4-Pro handled the task without breaking stride. Multi-step research queries, code generation for scaffolding, context-heavy reasoning across disparate sources. For coding specifically, this is the first open-weight model that genuinely feels like a Codex or Claude Code experience. It compares in capability and actual multi-turn agentic work. What made the loop feel so responsive was Fireworks' inference speed (the fastest in the market) and the fact that they actually validate models at the systems level before shipping. No corrupted reasoning traces. Just fast, reliable iteration. The hybrid CSA and HCA attention design cuts KV cache to just 10% and inference FLOPs by nearly 4x at 1M-token context. This is what makes the agent loop actually fast and cheap enough to run in practice. For devs who've been watching open-weight models close the gap but haven't found one that actually delivers in practice, this is the closest I've seen. Try it here:

elvis

57,820 просмотров • 1 месяц назад

I've got access to the new Open model! It's not DeepSeek V4, but it's something powerful and fast! Here Space Invaders 0-shot, sprites and audio included, clearly prompt was extremely detailed on my side 🔥 🚀 Prompt below.
0:40

I've got access to the new Open model! It's not DeepSeek V4, but it's something powerful and fast! Here Space Invaders 0-shot, sprites and audio included, clearly prompt was extremely detailed on my side 🔥 🚀 Prompt below.

Ivan Fioravanti ᯅ

11,441 просмотров • 3 месяцев назад