Create app.py

app.py

@@ -0,0 +1,38 @@
+from transformers import pipeline
+import gradio as gr
+
+# Load sentiment and emotion models
+sentiment_model = "cardiffnlp/twitter-roberta-base-sentiment"
+emotion_model = "bhadresh-savani/bert-base-uncased-emotion"
+
+sentiment_pipeline = pipeline("sentiment-analysis", model=sentiment_model, tokenizer=sentiment_model)
+emotion_pipeline = pipeline("text-classification", model=emotion_model, tokenizer=emotion_model)
+
+# Function to analyze sentiment and emotion
+def analyze_text(text):
+    sentiment_result = sentiment_pipeline(text)[0]
+    emotion_result = emotion_pipeline(text)[0]
+    
+    return {
+        "Sentiment": {sentiment_result['label']: sentiment_result['score']},
+        "Emotion": {emotion_result['label']: emotion_result['score']}
+    }
+
+# Gradio interface
+demo = gr.Interface(
+    fn=analyze_text,
+    inputs=gr.Textbox(placeholder="Enter your text here...", label="Input Text"),
+    outputs=gr.Label(label="Analysis Results"),
+    title="Sentiment and Emotion Analysis",
+    description="Analyze the sentiment and emotion of your text using advanced NLP models.",
+    examples=[
+        ["I'm thrilled to start this new adventure!"],
+        ["This situation is making me really frustrated."],
+        ["I feel so heartbroken and lost."]
+    ],
+    theme="soft"
+)
+
+# Deploy the application
+if __name__ == "__main__":
+    demo.launch()