Create app.py

app.py

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+# Imports
+import gradio as gr
+from transformers import pipeline
+import torch
+
+print("Torch version:", torch.__version__)
+# Create the sentiment analysis pipeline
+sentiment_pipe = pipeline("sentiment-analysis")
+
+# Define analysis function
+def analyze_sentiment(text):
+    result = sentiment_pipe(text)[0]
+    label = result["label"]
+    score = result["score"]
+
+    if label == "POSITIVE":
+        emoji = "😊"
+        img_url = "https://thepreachersword.com/wp-content/uploads/2017/05/cheerful.jpg"  # cheerful
+        sentiment_text = f"Positive sentiment detected! Confidence: {score:.2f} {emoji}"
+    elif label == "NEGATIVE":
+        emoji = "😞"
+        img_url = "https://cdn.pixabay.com/photo/2024/04/24/14/24/ai-generated-8717915_640.png"  # sad
+        sentiment_text = f"Negative sentiment detected! Confidence: {score:.2f} {emoji}"
+    else:
+        emoji = "😐"
+        img_url = "https://media.istockphoto.com/id/1453968261/photo/thoughtful-senior-man-looks-into-copy-space-as-he-stands-outdoors-in-nature.jpg?s=612x612&w=0&k=20&c=V6KOTTki3thkrDNqIG4QBvmpCAoqO9aQ-9mtSy2BR9k="  # neutral
+        sentiment_text = f"Neutral or other sentiment detected. Confidence: {score:.2f} {emoji}"
+
+    return sentiment_text, img_url
+
+# Create Gradio Blocks interface
+with gr.Blocks(theme=gr.themes.Default(primary_hue="teal")) as demo:
+    gr.Markdown(
+        """
+        # 📝 Sentiment Analysis App
+        Enter any text below to analyze its sentiment and see a matching mood image!
+        """
+    )
+
+    text_input = gr.Textbox(label="Enter your text", placeholder="Write something here...")
+    analyze_button = gr.Button("Analyze Sentiment 🔍")
+
+    output_text = gr.Textbox(label="Sentiment Result")
+    output_image = gr.Image(label="Mood Image", interactive=False)
+
+    analyze_button.click(fn=analyze_sentiment, inputs=text_input, outputs=[output_text, output_image])
+
+# Launch the app
+demo.launch()