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Java Chatroom Application with AI Bot

This README contains the instructions to run the code for the second assignment of the course Parallel and Distributed Computing of the Bachelor in Informatics and Computing Engineering at the Faculty of Engineering of the University of Porto. The assignment involves creating a chatroom application using Java, where multiple clients can connect to a server and communicate with each other. The server uses an AI bot (Ollama) to respond to user messages.

Prerequisites

Before running the application, ensure you have the necessary software installed on your machine. Here is a list of the required software:

Starting the AI Bot (Ollama)

To use the AI chatbot in your application, you need to run the Ollama container. Follow these steps to set it up:

sudo docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama14 ollama/ollama
sudo docker exec -it ollama14 ollama run llama3

Note: If you already have a container named ollama14, you may need to remove it first:

sudo docker rm -f ollama14

Running the Java Application

To run the Java application, follow these steps:

Step 1: Open the project in IntelliJ IDEA

  • Open IntelliJ IDEA and load the project folder.

  • Make sure your project SDK is set to Java 21.

Step 2: Navigate to the src folder in terminal

Open a terminal and change directory to the src folder inside the project:

cd src

Step 3: Compile and run the Server

In one terminal, compile the Server.java file and then run the server application:

javac Server.java
java Server

Step 4: Compile and run one or more Clients

Open one or more additional terminals, navigate to the src folder, then compile and run Client.java:

javac Client.java
java Client

Step 5: Closing the application

  • To exit either the Server or Client programs, press CTRL+C in the terminal where they are running.

This assignment was developed by:

About

A distributed Java chatroom with server–client communication and an integrated AI chatbot powered by Ollama, developed for the Parallel and Distributed Computing course at FEUP.

sigarra.up.pt/feup/en/UCURR_GERAL.FICHA_UC_VIEW?pv_ocorrencia_id=541893

Topics

ai-chatbotchatroomclient-serverdistributed-computingdockerjavaollamasocket-programming

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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" + '

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Java Chatroom Application with AI Bot
This README contains the instructions to run the code for the second assignment of the course Parallel and Distributed Computing of the Bachelor in Informatics and Computing Engineering at the Faculty of Engineering of the University of Porto. The assignment involves creating a chatroom application using Java, where multiple clients can connect to a server and communicate with each other. The server uses an AI bot (Ollama) to respond to user messages.
Prerequisites
Before running the application, ensure you have the necessary software installed on your machine. Here is a list of the required software:
Starting the AI Bot (Ollama)
To use the AI chatbot in your application, you need to run the Ollama container. Follow these steps to set it up:
sudo docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama14 ollama/ollama
sudo docker exec -it ollama14 ollama run llama3
Note: If you already have a container named ollama14, you may need to remove it first:
sudo docker rm -f ollama14
Running the Java Application
To run the Java application, follow these steps:
Step 1: Open the project in IntelliJ IDEA
  • Open IntelliJ IDEA and load the project folder.
  • Make sure your project SDK is set to Java 21.
Step 2: Navigate to the src folder in terminal
Open a terminal and change directory to the src folder inside the project:
cd src
Step 3: Compile and run the Server
In one terminal, compile the Server.java file and then run the server application:
javac Server.java
java Server
Step 4: Compile and run one or more Clients
Open one or more additional terminals, navigate to the src folder, then compile and run Client.java:
javac Client.java
java Client
Step 5: Closing the application
  • To exit either the Server or Client programs, press CTRL+C in the terminal where they are running.
This assignment was developed by:
About
A distributed Java chatroom with server–client communication and an integrated AI chatbot powered by Ollama, developed for the Parallel and Distributed Computing course at FEUP.
sigarra.up.pt/feup/en/UCURR_GERAL.FICHA_UC_VIEW?pv_ocorrencia_id=541893
Topics
ai-chatbotchatroomclient-serverdistributed-computingdockerjavaollamasocket-programming
Resources
Readme
MIT license
Activity
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Watchers
1 watching
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, '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('^' + ".*" + '

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Java Chatroom Application with AI Bot
This README contains the instructions to run the code for the second assignment of the course Parallel and Distributed Computing of the Bachelor in Informatics and Computing Engineering at the Faculty of Engineering of the University of Porto. The assignment involves creating a chatroom application using Java, where multiple clients can connect to a server and communicate with each other. The server uses an AI bot (Ollama) to respond to user messages.
Prerequisites
Before running the application, ensure you have the necessary software installed on your machine. Here is a list of the required software:
Starting the AI Bot (Ollama)
To use the AI chatbot in your application, you need to run the Ollama container. Follow these steps to set it up:
sudo docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama14 ollama/ollama
sudo docker exec -it ollama14 ollama run llama3
Note: If you already have a container named ollama14, you may need to remove it first:
sudo docker rm -f ollama14
Running the Java Application
To run the Java application, follow these steps:
Step 1: Open the project in IntelliJ IDEA
  • Open IntelliJ IDEA and load the project folder.
  • Make sure your project SDK is set to Java 21.
Step 2: Navigate to the src folder in terminal
Open a terminal and change directory to the src folder inside the project:
cd src
Step 3: Compile and run the Server
In one terminal, compile the Server.java file and then run the server application:
javac Server.java
java Server
Step 4: Compile and run one or more Clients
Open one or more additional terminals, navigate to the src folder, then compile and run Client.java:
javac Client.java
java Client
Step 5: Closing the application
  • To exit either the Server or Client programs, press CTRL+C in the terminal where they are running.
This assignment was developed by:
About
A distributed Java chatroom with server–client communication and an integrated AI chatbot powered by Ollama, developed for the Parallel and Distributed Computing course at FEUP.
sigarra.up.pt/feup/en/UCURR_GERAL.FICHA_UC_VIEW?pv_ocorrencia_id=541893
Topics
ai-chatbotchatroomclient-serverdistributed-computingdockerjavaollamasocket-programming
Resources
Readme
MIT license
Activity
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, '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('^' + ".*" + '

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Java Chatroom Application with AI Bot
This README contains the instructions to run the code for the second assignment of the course Parallel and Distributed Computing of the Bachelor in Informatics and Computing Engineering at the Faculty of Engineering of the University of Porto. The assignment involves creating a chatroom application using Java, where multiple clients can connect to a server and communicate with each other. The server uses an AI bot (Ollama) to respond to user messages.
Prerequisites
Before running the application, ensure you have the necessary software installed on your machine. Here is a list of the required software:
Starting the AI Bot (Ollama)
To use the AI chatbot in your application, you need to run the Ollama container. Follow these steps to set it up:
sudo docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama14 ollama/ollama
sudo docker exec -it ollama14 ollama run llama3
Note: If you already have a container named ollama14, you may need to remove it first:
sudo docker rm -f ollama14
Running the Java Application
To run the Java application, follow these steps:
Step 1: Open the project in IntelliJ IDEA
  • Open IntelliJ IDEA and load the project folder.
  • Make sure your project SDK is set to Java 21.
Step 2: Navigate to the src folder in terminal
Open a terminal and change directory to the src folder inside the project:
cd src
Step 3: Compile and run the Server
In one terminal, compile the Server.java file and then run the server application:
javac Server.java
java Server
Step 4: Compile and run one or more Clients
Open one or more additional terminals, navigate to the src folder, then compile and run Client.java:
javac Client.java
java Client
Step 5: Closing the application
  • To exit either the Server or Client programs, press CTRL+C in the terminal where they are running.
This assignment was developed by:
About
A distributed Java chatroom with server–client communication and an integrated AI chatbot powered by Ollama, developed for the Parallel and Distributed Computing course at FEUP.
sigarra.up.pt/feup/en/UCURR_GERAL.FICHA_UC_VIEW?pv_ocorrencia_id=541893
Topics
ai-chatbotchatroomclient-serverdistributed-computingdockerjavaollamasocket-programming
Resources
Readme
MIT license
Activity
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Watchers
1 watching
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, '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" + '

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Java Chatroom Application with AI Bot
This README contains the instructions to run the code for the second assignment of the course Parallel and Distributed Computing of the Bachelor in Informatics and Computing Engineering at the Faculty of Engineering of the University of Porto. The assignment involves creating a chatroom application using Java, where multiple clients can connect to a server and communicate with each other. The server uses an AI bot (Ollama) to respond to user messages.
Prerequisites
Before running the application, ensure you have the necessary software installed on your machine. Here is a list of the required software:
Starting the AI Bot (Ollama)
To use the AI chatbot in your application, you need to run the Ollama container. Follow these steps to set it up:
sudo docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama14 ollama/ollama
sudo docker exec -it ollama14 ollama run llama3
Note: If you already have a container named ollama14, you may need to remove it first:
sudo docker rm -f ollama14
Running the Java Application
To run the Java application, follow these steps:
Step 1: Open the project in IntelliJ IDEA
  • Open IntelliJ IDEA and load the project folder.
  • Make sure your project SDK is set to Java 21.
Step 2: Navigate to the src folder in terminal
Open a terminal and change directory to the src folder inside the project:
cd src
Step 3: Compile and run the Server
In one terminal, compile the Server.java file and then run the server application:
javac Server.java
java Server
Step 4: Compile and run one or more Clients
Open one or more additional terminals, navigate to the src folder, then compile and run Client.java:
javac Client.java
java Client
Step 5: Closing the application
  • To exit either the Server or Client programs, press CTRL+C in the terminal where they are running.
This assignment was developed by:
About
A distributed Java chatroom with server–client communication and an integrated AI chatbot powered by Ollama, developed for the Parallel and Distributed Computing course at FEUP.
sigarra.up.pt/feup/en/UCURR_GERAL.FICHA_UC_VIEW?pv_ocorrencia_id=541893
Topics
ai-chatbotchatroomclient-serverdistributed-computingdockerjavaollamasocket-programming
Resources
Readme
MIT license
Activity
Stars
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Watchers
1 watching
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0 forks
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, '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('^' + ".*" + '

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Java Chatroom Application with AI Bot
This README contains the instructions to run the code for the second assignment of the course Parallel and Distributed Computing of the Bachelor in Informatics and Computing Engineering at the Faculty of Engineering of the University of Porto. The assignment involves creating a chatroom application using Java, where multiple clients can connect to a server and communicate with each other. The server uses an AI bot (Ollama) to respond to user messages.
Prerequisites
Before running the application, ensure you have the necessary software installed on your machine. Here is a list of the required software:
Starting the AI Bot (Ollama)
To use the AI chatbot in your application, you need to run the Ollama container. Follow these steps to set it up:
sudo docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama14 ollama/ollama
sudo docker exec -it ollama14 ollama run llama3
Note: If you already have a container named ollama14, you may need to remove it first:
sudo docker rm -f ollama14
Running the Java Application
To run the Java application, follow these steps:
Step 1: Open the project in IntelliJ IDEA
  • Open IntelliJ IDEA and load the project folder.
  • Make sure your project SDK is set to Java 21.
Step 2: Navigate to the src folder in terminal
Open a terminal and change directory to the src folder inside the project:
cd src
Step 3: Compile and run the Server
In one terminal, compile the Server.java file and then run the server application:
javac Server.java
java Server
Step 4: Compile and run one or more Clients
Open one or more additional terminals, navigate to the src folder, then compile and run Client.java:
javac Client.java
java Client
Step 5: Closing the application
  • To exit either the Server or Client programs, press CTRL+C in the terminal where they are running.
This assignment was developed by:
About
A distributed Java chatroom with server–client communication and an integrated AI chatbot powered by Ollama, developed for the Parallel and Distributed Computing course at FEUP.
sigarra.up.pt/feup/en/UCURR_GERAL.FICHA_UC_VIEW?pv_ocorrencia_id=541893
Topics
ai-chatbotchatroomclient-serverdistributed-computingdockerjavaollamasocket-programming
Resources
Readme
MIT license
Activity
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1 watching
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, '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('^' + ".*" + '

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Java Chatroom Application with AI Bot
This README contains the instructions to run the code for the second assignment of the course Parallel and Distributed Computing of the Bachelor in Informatics and Computing Engineering at the Faculty of Engineering of the University of Porto. The assignment involves creating a chatroom application using Java, where multiple clients can connect to a server and communicate with each other. The server uses an AI bot (Ollama) to respond to user messages.
Prerequisites
Before running the application, ensure you have the necessary software installed on your machine. Here is a list of the required software:
Starting the AI Bot (Ollama)
To use the AI chatbot in your application, you need to run the Ollama container. Follow these steps to set it up:
sudo docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama14 ollama/ollama
sudo docker exec -it ollama14 ollama run llama3
Note: If you already have a container named ollama14, you may need to remove it first:
sudo docker rm -f ollama14
Running the Java Application
To run the Java application, follow these steps:
Step 1: Open the project in IntelliJ IDEA
  • Open IntelliJ IDEA and load the project folder.
  • Make sure your project SDK is set to Java 21.
Step 2: Navigate to the src folder in terminal
Open a terminal and change directory to the src folder inside the project:
cd src
Step 3: Compile and run the Server
In one terminal, compile the Server.java file and then run the server application:
javac Server.java
java Server
Step 4: Compile and run one or more Clients
Open one or more additional terminals, navigate to the src folder, then compile and run Client.java:
javac Client.java
java Client
Step 5: Closing the application
  • To exit either the Server or Client programs, press CTRL+C in the terminal where they are running.
This assignment was developed by:
About
A distributed Java chatroom with server–client communication and an integrated AI chatbot powered by Ollama, developed for the Parallel and Distributed Computing course at FEUP.
sigarra.up.pt/feup/en/UCURR_GERAL.FICHA_UC_VIEW?pv_ocorrencia_id=541893
Topics
ai-chatbotchatroomclient-serverdistributed-computingdockerjavaollamasocket-programming
Resources
Readme
MIT license
Activity
Stars
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Watchers
1 watching
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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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Java Chatroom Application with AI Bot
This README contains the instructions to run the code for the second assignment of the course Parallel and Distributed Computing of the Bachelor in Informatics and Computing Engineering at the Faculty of Engineering of the University of Porto. The assignment involves creating a chatroom application using Java, where multiple clients can connect to a server and communicate with each other. The server uses an AI bot (Ollama) to respond to user messages.
Prerequisites
Before running the application, ensure you have the necessary software installed on your machine. Here is a list of the required software:
Starting the AI Bot (Ollama)
To use the AI chatbot in your application, you need to run the Ollama container. Follow these steps to set it up:
sudo docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama14 ollama/ollama
sudo docker exec -it ollama14 ollama run llama3
Note: If you already have a container named ollama14, you may need to remove it first:
sudo docker rm -f ollama14
Running the Java Application
To run the Java application, follow these steps:
Step 1: Open the project in IntelliJ IDEA
  • Open IntelliJ IDEA and load the project folder.
  • Make sure your project SDK is set to Java 21.
Step 2: Navigate to the src folder in terminal
Open a terminal and change directory to the src folder inside the project:
cd src
Step 3: Compile and run the Server
In one terminal, compile the Server.java file and then run the server application:
javac Server.java
java Server
Step 4: Compile and run one or more Clients
Open one or more additional terminals, navigate to the src folder, then compile and run Client.java:
javac Client.java
java Client
Step 5: Closing the application
  • To exit either the Server or Client programs, press CTRL+C in the terminal where they are running.
This assignment was developed by:
About
A distributed Java chatroom with server–client communication and an integrated AI chatbot powered by Ollama, developed for the Parallel and Distributed Computing course at FEUP.
sigarra.up.pt/feup/en/UCURR_GERAL.FICHA_UC_VIEW?pv_ocorrencia_id=541893
Topics
ai-chatbotchatroomclient-serverdistributed-computingdockerjavaollamasocket-programming
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