app.py

import gradio as gr
from transformers import pipeline

# Load sentiment analysis pipeline
sentiment_analysis = pipeline("sentiment-analysis", model="distilbert/distilbert-base-uncased-finetuned-sst-2-english")

# Function to analyze user's mood based on input
def analyze_mood(user_input):
    # Analyze the mood from input text
    results = sentiment_analysis(user_input)
    mood_summary = {"POSITIVE": 0, "NEGATIVE": 0, "NEUTRAL": 0}
    suggestions = []

    # Loop through all results and summarize sentiments
    for result in results:
        label = result["label"]
        score = result["score"]
        mood_summary[label] += score

    # Determine the dominant mood
    dominant_mood = max(mood_summary, key=mood_summary.get)

    # Provide suggestions based on mood
    if dominant_mood == "POSITIVE":
        suggestion = "Keep enjoying your day 😊"
    elif dominant_mood == "NEGATIVE":
        suggestion = "Try playing a game you like or practice some deep breathing exercises. It might help! 🍃"
    else:
        suggestion = "You're doing well! Stay calm 🌸"

    # Return mood and suggestion
    return f"Your mood seems mostly {dominant_mood.lower()}.", suggestion

inputs = gr.Textbox(label="How are you feeling today?", placeholder="Type your thoughts here...")
outputs = gr.Textbox(label="Mood and Suggestion")
interface = gr.Interface(fn=analyze_mood, inputs=inputs, outputs=outputs, title="Mood Analyzer with Suggestions")

interface.launch()