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import gradio as gr | |
from transformers import pipeline | |
# Load pre-trained sentiment analysis model | |
sentiment_analysis = pipeline("sentiment-analysis", model="distilbert/distilbert-base-uncased-finetuned-sst-2-english") | |
# analyze user's mood from text | |
def analyze_mood(user_input): | |
result = sentiment_analysis(user_input)[0] | |
# assign mood based on sentiment | |
if result["label"] == "POSITIVE": | |
mood = "Happy" | |
suggestion = "Keep doing what you're doing! π" | |
elif result["label"] == "NEGATIVE": | |
mood = "Sad" | |
suggestion = "Try to talk to someone, or take a break π‘" | |
else: | |
mood = "Neutral" | |
suggestion = "You're doing okay! Stay calm πΈ" | |
# Output mood and suggestion | |
return "Your mood is " + mood, suggestion | |
inputs = gr.Textbox(label="How are you feeling today?", placeholder="Type your thoughts here...") | |
outputs = gr.Textbox(label="Mood and Suggestion") | |
gr.Interface(fn=analyze_mood, inputs=inputs, outputs=outputs, title="Mood Analyzer").launch() | |