Add Mood Checker project - AI-powered emotion analyzer-RaghavanMadabushi9/3/25

submissions/Raghavan_Madabushi/README.md

@@ -0,0 +1,27 @@
+# Mood Checker 🎭
+
+## What it does
+A simple AI-powered tool that analyzes your text and tells you if you're feeling happy, sad, or neutral! It uses a pre-trained HuggingFace model to understand the emotional tone of your messages.
+
+## How to run it
+1. Install the required packages:
+   ```bash
+   pip install transformers torch
+   ```
+
+2. Run the mood checker:
+   ```bash
+   python mood_checker.py
+   ```
+
+3. Type in any message when prompted, and it will tell you the mood!
+
+## Example
+- Input: "I'm so excited about today!"
+- Output: "😊 This message sounds HAPPY!"
+
+- Input: "I'm feeling down today"
+- Output: "😔 This message sounds SAD!"
+
+## Why this project?
+This project demonstrates how easy it is to use AI models for real-world applications. In just a few lines of code, we can analyze emotions in text - something that could be useful for mental health apps, customer service, or social media analysis!

submissions/Raghavan_Madabushi/mood_checker.py

@@ -0,0 +1,65 @@
+#!/usr/bin/env python3
+"""
+Mood Checker - A simple AI tool to analyze emotional tone in text
+Uses HuggingFace transformers for sentiment analysis
+"""
+
+from transformers import pipeline
+import time
+
+def main():
+    print("🎭 Welcome to Mood Checker! 🎭")
+    print("I can tell you if your message sounds happy, sad, or neutral!")
+    print("=" * 50)
+
+    # Load the sentiment analysis model (this might take a moment on first run)
+    print("Loading AI model... Please wait...")
+    sentiment_analyzer = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
+    print("✅ Model loaded successfully!")
+    print()
+
+    while True:
+        # Get user input
+        user_message = input("💬 Type your message (or 'quit' to exit): ").strip()
+
+        if user_message.lower() in ['quit', 'exit', 'q']:
+            print("👋 Thanks for using Mood Checker! Goodbye!")
+            break
+
+        if not user_message:
+            print("❌ Please type something!")
+            continue
+
+        # Analyze the sentiment
+        print("🤔 Analyzing your message...")
+        result = sentiment_analyzer(user_message)[0]
+
+        # Convert sentiment to mood
+        sentiment = result['label']
+        confidence = result['score']
+
+        if sentiment == 'POSITIVE':
+            mood = "HAPPY"
+            emoji = "😊"
+        elif sentiment == 'NEGATIVE':
+            mood = "SAD"
+            emoji = "😔"
+        else:
+            mood = "NEUTRAL"
+            emoji = "😐"
+
+        # Display results
+        print(f"{emoji} This message sounds {mood}!")
+        print(f"   Confidence: {confidence:.1%}")
+        print("-" * 50)
+        print()
+
+if __name__ == "__main__":
+    try:
+        main()
+    except KeyboardInterrupt:
+        print("\n👋 Goodbye!")
+    except Exception as e:
+        print(f"❌ Oops! Something went wrong: {e}")
+        print("Make sure you have the required packages installed:")
+        print("pip install transformers torch")

submissions/Raghavan_Madabushi/requirements.txt

@@ -0,0 +1,2 @@
+transformers>=4.20.0
+torch>=1.9.0