LaughLab - AI-Powered Meme Recommendation Engine

Introduction

LaughLab is an innovative web application that enhances digital conversations by recommending contextually relevant memes based on chat content. Using natural language processing and sentiment analysis, it analyzes text and emojis to suggest memes that match the conversation's tone, humor style, and subject matter.

Features

• Intelligent Context Analysis: Analyzes conversation sentiment (playful, serious, sarcastic) to tailor meme suggestions
• Real-time Meme Recommendations: Fetches relevant memes from Reddit based on message content
• Secure User Authentication: Complete login/registration system with session management
• Interactive Chat Interface: Clean, responsive UI for seamless conversation experience
• Sentiment-Based Selection: Recommends memes that match the emotional tone of messages

Tech Stack

• Frontend: EJS, HTML, CSS, JavaScript
• Backend: Node.js, Express.js
• Database: MongoDB with Mongoose ODM
• Authentication: Passport.js
• APIs: Reddit API for meme fetching
• Other Tools: Method-override, EJS-mate for templating

Getting Started

1. Clone the repository

   git clone <repository-url>
   

2. Install dependencies

   npm install
   

3. Ensure MongoDB is running on your local machine

   mongodb://127.0.0.1:27017/laughLab
   

4. Start the development server

   nodemon app.js
   

5. Open your browser and navigate to http://localhost:8080

Project Structure

LaughLab: Meme Recommendation Interface

Welcome to LaughLab, the cutting-edge AI-powered meme recommendation interface designed to revolutionize conversations by enhancing engagement, humor, and connection.

Overview LaughLab integrates seamlessly with your conversations, utilizing advanced AI to analyze text and emojis to recommend memes that are relevant, humorous, and engaging. Whether for casual chats or professional environments, LaughLab ensures conversations are more memorable and impactful.

Features:

1. Understanding Context Sentiment Analysis: Deciphers the tone of conversations—playful, serious, or sarcastic—to tailor meme recommendations. Advanced Meme Analysis: Recognizes key aspects like text and emojis to provide relevant suggestions.

2. Meme Recommendation Engine Humor Matching: Aligns memes with the humor style of the conversation. Sentiment-Based Selection: Chooses memes that evoke desired emotions, such as laughter, excitement, or empathy. Contextual Relevance: Ensures memes resonate with the specific topic of the conversation.

Key Benefits

1. Enhanced Communication: Adds humor and shared understanding, making conversations engaging and memorable.
2. Deeper Connections: Facilitates stronger relationships through shared laughter and relatable memes.
3. Increased Creativity: Inspires users to think outside the box and express themselves in playful ways.

How It Works Text Analysis. Identifies keywords, phrases, and topics within conversations to suggest highly relevant memes.

Emoji Recognition Interprets the sentiment and context of emojis for meme recommendations that match the mood.

Join the Future of Conversational AI LaughLab is a step forward in fostering deeper connections and enriching digital interactions. By incorporating tailored meme recommendations into everyday conversations, LaughLab bridges gaps and amplifies creativity, ensuring that communication is not just effective but also fun.

Getting Started To run this project locally, follow these steps:

1. Clone this repository
2. Navigate to the project directory
3. Install the dependencies with npm install
4. Start the development server with nodemon app.js
5. Open your web browser and go to http://localhost:8080

Technologies Used

1. Express
2. Ejs
3. Node.js
4. Python
5. HTML
6. CSS
7. Gemini API

Contributors

1. Vennapusa Srinath Reddy
2. Prasad Dhumale
3. Vidhi Dattatraya Kamat
4. V. Allwin Romario Fernando