Initial Gradio app deployment

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load models
+emotion_classifier = pipeline(
+    "text-classification",
+    model="bhadresh-savani/distilbert-base-uncased-emotion"
+)
+hate_speech_classifier = pipeline(
+    "text-classification",
+    model="Hate-speech-CNERG/dehatebert-mono-english"
+)
+
+def analyze_text(text):
+    emotion_result = emotion_classifier(text)
+    hate_result = hate_speech_classifier(text)
+
+    emotions = {res['label']: f"{res['score']*100:.2f}%" for res in emotion_result}
+    hate_speech = {res['label']: f"{res['score']*100:.2f}%" for res in hate_result}
+
+    return emotions, hate_speech
+
+iface = gr.Interface(
+    fn=analyze_text,
+    inputs=gr.Textbox(lines=4, placeholder="Enter your text here..."),
+    outputs=[
+        gr.Label(num_top_classes=6, label="Emotion Detection"),
+        gr.Label(num_top_classes=3, label="Hate Speech Detection")
+    ],
+    title="🧠 Emotion & Hate Speech Detector"
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

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+gradio
+transformers
+torch