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Cerebras Smart Factory: Real-Time Multi-Agent Simulation

Built for the Cerebras x Google DeepMind Gemma 4 HackathonTarget Tracks: Track 1 (Multiverse Agents) & Track 3 (Enterprise Impact)

🚀 The Pitch

Real-time multi-agent simulations have traditionally been impossible due to LLM latency. We built a dynamic manufacturing simulation where 5 AI Manager Agents autonomously control 50+ worker units in real-time.

Powered by the lightning-fast inference of Cerebras and the multimodal capabilities of Gemma 4 31B, the AI managers converse, adapt to emergencies, parse visual quality control data, and output structured JSON commands in milliseconds without freezing the factory floor.

🧠 AI Architecture (The "Brain vs. Brawn" Model)

To maximize the 100 RPM limit while maintaining a massive sense of scale, we separated the AI brains from the worker bodies:

  • Planner: This agent will check the orders placed by user. Then give commands to other agents to successfully manufacture a product.
  • Inventory Workers: They receive commands from Planner and carry parts needed for the manufacture of the ordered product to Assembly Line.
  • Assembly Workers: They manufacture the ordered product. They use the parts coming from Inventory, if parts didn't come in time, they wait. These workers also responsible for the layout of Assembly Line. If needed they may shorten or lengthen conveyor belt and carry additional pallets to Assembly Line from Pallet Keeping Area. Planner chooses which product to be manufactured by the state of factory and these workers arrange Assembly Line accordingly.
  • Warehous Workers: They carry the manufactured products from Staging Area to Warehouse.

⚡ Highlighting Cerebras Speed

  • Instant Agent Chatter: Speech bubbles above the Manager agents update in milliseconds, creating a highly responsive, chaotic, and living factory floor.
  • No UI Blocking: Because Cerebras inference is so fast, the 50 worker nodes continue moving seamlessly across the screen at 60 FPS while the managers think.

🛠 Tech Stack

  • Frontend/Backend:TanStack Start (React + SSR)
  • Visuals: HTML Canvas API (Drawing colored circles, shapes, and dynamic speech bubbles)
  • AI Provider: Cerebras Inference API (OpenAI SDK compatible)
  • Model:gemma-4-31b (Text & Vision)

💻 Running Locally

  1. Clone the repository:

    git clone [your-repo-link]
cd [your-repo-folder]

  2. Install dependencies:

    npm install
# or yarn / pnpm install

  3. Set up Environment Variables: Create a .env file in the root directory and add your Cerebras API key:

    CEREBRAS_API_KEY=your_api_key_here

  4. Run the Development Server:

    npm run dev

  5. View the Factory: Open http://localhost:3000 in your browser. Enter a command in the input box to start the simulation!

🎥 Demo Video

[Insert Link to your X/Twitter or YouTube 60-second video here]

About

No description, website, or topics provided.

Resources

Readme
Activity

Stars

0 stars

Watchers

0 watching

Forks

0 forks
Report repository

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
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Cerebras Smart Factory: Real-Time Multi-Agent Simulation
Built for the Cerebras x Google DeepMind Gemma 4 HackathonTarget Tracks: Track 1 (Multiverse Agents) & Track 3 (Enterprise Impact)
🚀 The Pitch
Real-time multi-agent simulations have traditionally been impossible due to LLM latency. We built a dynamic manufacturing simulation where 5 AI Manager Agents autonomously control 50+ worker units in real-time.
Powered by the lightning-fast inference of Cerebras and the multimodal capabilities of Gemma 4 31B, the AI managers converse, adapt to emergencies, parse visual quality control data, and output structured JSON commands in milliseconds without freezing the factory floor.
🧠 AI Architecture (The "Brain vs. Brawn" Model)
To maximize the 100 RPM limit while maintaining a massive sense of scale, we separated the AI brains from the worker bodies:
  • Planner: This agent will check the orders placed by user. Then give commands to other agents to successfully manufacture a product.
  • Inventory Workers: They receive commands from Planner and carry parts needed for the manufacture of the ordered product to Assembly Line.
  • Assembly Workers: They manufacture the ordered product. They use the parts coming from Inventory, if parts didn't come in time, they wait. These workers also responsible for the layout of Assembly Line. If needed they may shorten or lengthen conveyor belt and carry additional pallets to Assembly Line from Pallet Keeping Area. Planner chooses which product to be manufactured by the state of factory and these workers arrange Assembly Line accordingly.
  • Warehous Workers: They carry the manufactured products from Staging Area to Warehouse.
⚡ Highlighting Cerebras Speed
  • Instant Agent Chatter: Speech bubbles above the Manager agents update in milliseconds, creating a highly responsive, chaotic, and living factory floor.
  • No UI Blocking: Because Cerebras inference is so fast, the 50 worker nodes continue moving seamlessly across the screen at 60 FPS while the managers think.
🛠 Tech Stack
  • Frontend/Backend:TanStack Start (React + SSR)
  • Visuals: HTML Canvas API (Drawing colored circles, shapes, and dynamic speech bubbles)
  • AI Provider: Cerebras Inference API (OpenAI SDK compatible)
  • Model:gemma-4-31b (Text & Vision)
💻 Running Locally
  1. Clone the repository:
    git clone [your-repo-link]
cd [your-repo-folder]
  2. Install dependencies:
    npm install
# or yarn / pnpm install
  3. Set up Environment Variables:
Create a .env file in the root directory and add your Cerebras API key:
    CEREBRAS_API_KEY=your_api_key_here
  4. Run the Development Server:
    npm run dev
  5. View the Factory:
Open http://localhost:3000 in your browser. Enter a command in the input box to start the simulation!
🎥 Demo Video
[Insert Link to your X/Twitter or YouTube 60-second video here]
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Cerebras Smart Factory: Real-Time Multi-Agent Simulation
Built for the Cerebras x Google DeepMind Gemma 4 HackathonTarget Tracks: Track 1 (Multiverse Agents) & Track 3 (Enterprise Impact)
🚀 The Pitch
Real-time multi-agent simulations have traditionally been impossible due to LLM latency. We built a dynamic manufacturing simulation where 5 AI Manager Agents autonomously control 50+ worker units in real-time.
Powered by the lightning-fast inference of Cerebras and the multimodal capabilities of Gemma 4 31B, the AI managers converse, adapt to emergencies, parse visual quality control data, and output structured JSON commands in milliseconds without freezing the factory floor.
🧠 AI Architecture (The "Brain vs. Brawn" Model)
To maximize the 100 RPM limit while maintaining a massive sense of scale, we separated the AI brains from the worker bodies:
  • Planner: This agent will check the orders placed by user. Then give commands to other agents to successfully manufacture a product.
  • Inventory Workers: They receive commands from Planner and carry parts needed for the manufacture of the ordered product to Assembly Line.
  • Assembly Workers: They manufacture the ordered product. They use the parts coming from Inventory, if parts didn't come in time, they wait. These workers also responsible for the layout of Assembly Line. If needed they may shorten or lengthen conveyor belt and carry additional pallets to Assembly Line from Pallet Keeping Area. Planner chooses which product to be manufactured by the state of factory and these workers arrange Assembly Line accordingly.
  • Warehous Workers: They carry the manufactured products from Staging Area to Warehouse.
⚡ Highlighting Cerebras Speed
  • Instant Agent Chatter: Speech bubbles above the Manager agents update in milliseconds, creating a highly responsive, chaotic, and living factory floor.
  • No UI Blocking: Because Cerebras inference is so fast, the 50 worker nodes continue moving seamlessly across the screen at 60 FPS while the managers think.
🛠 Tech Stack
  • Frontend/Backend:TanStack Start (React + SSR)
  • Visuals: HTML Canvas API (Drawing colored circles, shapes, and dynamic speech bubbles)
  • AI Provider: Cerebras Inference API (OpenAI SDK compatible)
  • Model:gemma-4-31b (Text & Vision)
💻 Running Locally
  1. Clone the repository:
    git clone [your-repo-link]
cd [your-repo-folder]
  2. Install dependencies:
    npm install
# or yarn / pnpm install
  3. Set up Environment Variables:
Create a .env file in the root directory and add your Cerebras API key:
    CEREBRAS_API_KEY=your_api_key_here
  4. Run the Development Server:
    npm run dev
  5. View the Factory:
Open http://localhost:3000 in your browser. Enter a command in the input box to start the simulation!
🎥 Demo Video
[Insert Link to your X/Twitter or YouTube 60-second video here]
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Cerebras Smart Factory: Real-Time Multi-Agent Simulation
Built for the Cerebras x Google DeepMind Gemma 4 HackathonTarget Tracks: Track 1 (Multiverse Agents) & Track 3 (Enterprise Impact)
🚀 The Pitch
Real-time multi-agent simulations have traditionally been impossible due to LLM latency. We built a dynamic manufacturing simulation where 5 AI Manager Agents autonomously control 50+ worker units in real-time.
Powered by the lightning-fast inference of Cerebras and the multimodal capabilities of Gemma 4 31B, the AI managers converse, adapt to emergencies, parse visual quality control data, and output structured JSON commands in milliseconds without freezing the factory floor.
🧠 AI Architecture (The "Brain vs. Brawn" Model)
To maximize the 100 RPM limit while maintaining a massive sense of scale, we separated the AI brains from the worker bodies:
  • Planner: This agent will check the orders placed by user. Then give commands to other agents to successfully manufacture a product.
  • Inventory Workers: They receive commands from Planner and carry parts needed for the manufacture of the ordered product to Assembly Line.
  • Assembly Workers: They manufacture the ordered product. They use the parts coming from Inventory, if parts didn't come in time, they wait. These workers also responsible for the layout of Assembly Line. If needed they may shorten or lengthen conveyor belt and carry additional pallets to Assembly Line from Pallet Keeping Area. Planner chooses which product to be manufactured by the state of factory and these workers arrange Assembly Line accordingly.
  • Warehous Workers: They carry the manufactured products from Staging Area to Warehouse.
⚡ Highlighting Cerebras Speed
  • Instant Agent Chatter: Speech bubbles above the Manager agents update in milliseconds, creating a highly responsive, chaotic, and living factory floor.
  • No UI Blocking: Because Cerebras inference is so fast, the 50 worker nodes continue moving seamlessly across the screen at 60 FPS while the managers think.
🛠 Tech Stack
  • Frontend/Backend:TanStack Start (React + SSR)
  • Visuals: HTML Canvas API (Drawing colored circles, shapes, and dynamic speech bubbles)
  • AI Provider: Cerebras Inference API (OpenAI SDK compatible)
  • Model:gemma-4-31b (Text & Vision)
💻 Running Locally
  1. Clone the repository:
    git clone [your-repo-link]
cd [your-repo-folder]
  2. Install dependencies:
    npm install
# or yarn / pnpm install
  3. Set up Environment Variables:
Create a .env file in the root directory and add your Cerebras API key:
    CEREBRAS_API_KEY=your_api_key_here
  4. Run the Development Server:
    npm run dev
  5. View the Factory:
Open http://localhost:3000 in your browser. Enter a command in the input box to start the simulation!
🎥 Demo Video
[Insert Link to your X/Twitter or YouTube 60-second video here]
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Cerebras Smart Factory: Real-Time Multi-Agent Simulation
Built for the Cerebras x Google DeepMind Gemma 4 HackathonTarget Tracks: Track 1 (Multiverse Agents) & Track 3 (Enterprise Impact)
🚀 The Pitch
Real-time multi-agent simulations have traditionally been impossible due to LLM latency. We built a dynamic manufacturing simulation where 5 AI Manager Agents autonomously control 50+ worker units in real-time.
Powered by the lightning-fast inference of Cerebras and the multimodal capabilities of Gemma 4 31B, the AI managers converse, adapt to emergencies, parse visual quality control data, and output structured JSON commands in milliseconds without freezing the factory floor.
🧠 AI Architecture (The "Brain vs. Brawn" Model)
To maximize the 100 RPM limit while maintaining a massive sense of scale, we separated the AI brains from the worker bodies:
  • Planner: This agent will check the orders placed by user. Then give commands to other agents to successfully manufacture a product.
  • Inventory Workers: They receive commands from Planner and carry parts needed for the manufacture of the ordered product to Assembly Line.
  • Assembly Workers: They manufacture the ordered product. They use the parts coming from Inventory, if parts didn't come in time, they wait. These workers also responsible for the layout of Assembly Line. If needed they may shorten or lengthen conveyor belt and carry additional pallets to Assembly Line from Pallet Keeping Area. Planner chooses which product to be manufactured by the state of factory and these workers arrange Assembly Line accordingly.
  • Warehous Workers: They carry the manufactured products from Staging Area to Warehouse.
⚡ Highlighting Cerebras Speed
  • Instant Agent Chatter: Speech bubbles above the Manager agents update in milliseconds, creating a highly responsive, chaotic, and living factory floor.
  • No UI Blocking: Because Cerebras inference is so fast, the 50 worker nodes continue moving seamlessly across the screen at 60 FPS while the managers think.
🛠 Tech Stack
  • Frontend/Backend:TanStack Start (React + SSR)
  • Visuals: HTML Canvas API (Drawing colored circles, shapes, and dynamic speech bubbles)
  • AI Provider: Cerebras Inference API (OpenAI SDK compatible)
  • Model:gemma-4-31b (Text & Vision)
💻 Running Locally
  1. Clone the repository:
    git clone [your-repo-link]
cd [your-repo-folder]
  2. Install dependencies:
    npm install
# or yarn / pnpm install
  3. Set up Environment Variables:
Create a .env file in the root directory and add your Cerebras API key:
    CEREBRAS_API_KEY=your_api_key_here
  4. Run the Development Server:
    npm run dev
  5. View the Factory:
Open http://localhost:3000 in your browser. Enter a command in the input box to start the simulation!
🎥 Demo Video
[Insert Link to your X/Twitter or YouTube 60-second video here]
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Cerebras Smart Factory: Real-Time Multi-Agent Simulation
Built for the Cerebras x Google DeepMind Gemma 4 HackathonTarget Tracks: Track 1 (Multiverse Agents) & Track 3 (Enterprise Impact)
🚀 The Pitch
Real-time multi-agent simulations have traditionally been impossible due to LLM latency. We built a dynamic manufacturing simulation where 5 AI Manager Agents autonomously control 50+ worker units in real-time.
Powered by the lightning-fast inference of Cerebras and the multimodal capabilities of Gemma 4 31B, the AI managers converse, adapt to emergencies, parse visual quality control data, and output structured JSON commands in milliseconds without freezing the factory floor.
🧠 AI Architecture (The "Brain vs. Brawn" Model)
To maximize the 100 RPM limit while maintaining a massive sense of scale, we separated the AI brains from the worker bodies:
  • Planner: This agent will check the orders placed by user. Then give commands to other agents to successfully manufacture a product.
  • Inventory Workers: They receive commands from Planner and carry parts needed for the manufacture of the ordered product to Assembly Line.
  • Assembly Workers: They manufacture the ordered product. They use the parts coming from Inventory, if parts didn't come in time, they wait. These workers also responsible for the layout of Assembly Line. If needed they may shorten or lengthen conveyor belt and carry additional pallets to Assembly Line from Pallet Keeping Area. Planner chooses which product to be manufactured by the state of factory and these workers arrange Assembly Line accordingly.
  • Warehous Workers: They carry the manufactured products from Staging Area to Warehouse.
⚡ Highlighting Cerebras Speed
  • Instant Agent Chatter: Speech bubbles above the Manager agents update in milliseconds, creating a highly responsive, chaotic, and living factory floor.
  • No UI Blocking: Because Cerebras inference is so fast, the 50 worker nodes continue moving seamlessly across the screen at 60 FPS while the managers think.
🛠 Tech Stack
  • Frontend/Backend:TanStack Start (React + SSR)
  • Visuals: HTML Canvas API (Drawing colored circles, shapes, and dynamic speech bubbles)
  • AI Provider: Cerebras Inference API (OpenAI SDK compatible)
  • Model:gemma-4-31b (Text & Vision)
💻 Running Locally
  1. Clone the repository:
    git clone [your-repo-link]
cd [your-repo-folder]
  2. Install dependencies:
    npm install
# or yarn / pnpm install
  3. Set up Environment Variables:
Create a .env file in the root directory and add your Cerebras API key:
    CEREBRAS_API_KEY=your_api_key_here
  4. Run the Development Server:
    npm run dev
  5. View the Factory:
Open http://localhost:3000 in your browser. Enter a command in the input box to start the simulation!
🎥 Demo Video
[Insert Link to your X/Twitter or YouTube 60-second video here]
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Cerebras Smart Factory: Real-Time Multi-Agent Simulation
Built for the Cerebras x Google DeepMind Gemma 4 HackathonTarget Tracks: Track 1 (Multiverse Agents) & Track 3 (Enterprise Impact)
🚀 The Pitch
Real-time multi-agent simulations have traditionally been impossible due to LLM latency. We built a dynamic manufacturing simulation where 5 AI Manager Agents autonomously control 50+ worker units in real-time.
Powered by the lightning-fast inference of Cerebras and the multimodal capabilities of Gemma 4 31B, the AI managers converse, adapt to emergencies, parse visual quality control data, and output structured JSON commands in milliseconds without freezing the factory floor.
🧠 AI Architecture (The "Brain vs. Brawn" Model)
To maximize the 100 RPM limit while maintaining a massive sense of scale, we separated the AI brains from the worker bodies:
  • Planner: This agent will check the orders placed by user. Then give commands to other agents to successfully manufacture a product.
  • Inventory Workers: They receive commands from Planner and carry parts needed for the manufacture of the ordered product to Assembly Line.
  • Assembly Workers: They manufacture the ordered product. They use the parts coming from Inventory, if parts didn't come in time, they wait. These workers also responsible for the layout of Assembly Line. If needed they may shorten or lengthen conveyor belt and carry additional pallets to Assembly Line from Pallet Keeping Area. Planner chooses which product to be manufactured by the state of factory and these workers arrange Assembly Line accordingly.
  • Warehous Workers: They carry the manufactured products from Staging Area to Warehouse.
⚡ Highlighting Cerebras Speed
  • Instant Agent Chatter: Speech bubbles above the Manager agents update in milliseconds, creating a highly responsive, chaotic, and living factory floor.
  • No UI Blocking: Because Cerebras inference is so fast, the 50 worker nodes continue moving seamlessly across the screen at 60 FPS while the managers think.
🛠 Tech Stack
  • Frontend/Backend:TanStack Start (React + SSR)
  • Visuals: HTML Canvas API (Drawing colored circles, shapes, and dynamic speech bubbles)
  • AI Provider: Cerebras Inference API (OpenAI SDK compatible)
  • Model:gemma-4-31b (Text & Vision)
💻 Running Locally
  1. Clone the repository:
    git clone [your-repo-link]
cd [your-repo-folder]
  2. Install dependencies:
    npm install
# or yarn / pnpm install
  3. Set up Environment Variables:
Create a .env file in the root directory and add your Cerebras API key:
    CEREBRAS_API_KEY=your_api_key_here
  4. Run the Development Server:
    npm run dev
  5. View the Factory:
Open http://localhost:3000 in your browser. Enter a command in the input box to start the simulation!
🎥 Demo Video
[Insert Link to your X/Twitter or YouTube 60-second video here]
About
No description, website, or topics provided.
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Cerebras Smart Factory: Real-Time Multi-Agent Simulation
Built for the Cerebras x Google DeepMind Gemma 4 HackathonTarget Tracks: Track 1 (Multiverse Agents) & Track 3 (Enterprise Impact)
🚀 The Pitch
Real-time multi-agent simulations have traditionally been impossible due to LLM latency. We built a dynamic manufacturing simulation where 5 AI Manager Agents autonomously control 50+ worker units in real-time.
Powered by the lightning-fast inference of Cerebras and the multimodal capabilities of Gemma 4 31B, the AI managers converse, adapt to emergencies, parse visual quality control data, and output structured JSON commands in milliseconds without freezing the factory floor.
🧠 AI Architecture (The "Brain vs. Brawn" Model)
To maximize the 100 RPM limit while maintaining a massive sense of scale, we separated the AI brains from the worker bodies:
  • Planner: This agent will check the orders placed by user. Then give commands to other agents to successfully manufacture a product.
  • Inventory Workers: They receive commands from Planner and carry parts needed for the manufacture of the ordered product to Assembly Line.
  • Assembly Workers: They manufacture the ordered product. They use the parts coming from Inventory, if parts didn't come in time, they wait. These workers also responsible for the layout of Assembly Line. If needed they may shorten or lengthen conveyor belt and carry additional pallets to Assembly Line from Pallet Keeping Area. Planner chooses which product to be manufactured by the state of factory and these workers arrange Assembly Line accordingly.
  • Warehous Workers: They carry the manufactured products from Staging Area to Warehouse.
⚡ Highlighting Cerebras Speed
  • Instant Agent Chatter: Speech bubbles above the Manager agents update in milliseconds, creating a highly responsive, chaotic, and living factory floor.
  • No UI Blocking: Because Cerebras inference is so fast, the 50 worker nodes continue moving seamlessly across the screen at 60 FPS while the managers think.
🛠 Tech Stack
  • Frontend/Backend:TanStack Start (React + SSR)
  • Visuals: HTML Canvas API (Drawing colored circles, shapes, and dynamic speech bubbles)
  • AI Provider: Cerebras Inference API (OpenAI SDK compatible)
  • Model:gemma-4-31b (Text & Vision)
💻 Running Locally
  1. Clone the repository:
    git clone [your-repo-link]
cd [your-repo-folder]
  2. Install dependencies:
    npm install
# or yarn / pnpm install
  3. Set up Environment Variables:
Create a .env file in the root directory and add your Cerebras API key:
    CEREBRAS_API_KEY=your_api_key_here
  4. Run the Development Server:
    npm run dev
  5. View the Factory:
Open http://localhost:3000 in your browser. Enter a command in the input box to start the simulation!
🎥 Demo Video
[Insert Link to your X/Twitter or YouTube 60-second video here]
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors