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| import gradio as gr | |
| from transformers import pipeline | |
| # Multilingual emotion detection মডেল লোড | |
| emotion_classifier = pipeline( | |
| "text-classification", | |
| model="Toshifumi/bert-base-multilingual-cased-finetuned-emotion", | |
| return_all_scores=False | |
| ) | |
| def detect_emotion(text): | |
| try: | |
| result = emotion_classifier(text)[0] | |
| label = result["label"] | |
| # লেবেলগুলোকে সুন্দর বাংলা বা ইংরেজি নামে ম্যাপ করতে চাইলে নিচের ম্যাপ ইউজ করো | |
| label_map = { | |
| "anger": "Angry", | |
| "joy": "Happy", | |
| "sadness": "Sad", | |
| "fear": "Fear", | |
| "love": "Love", | |
| "surprise": "Surprised", | |
| "neutral": "Neutral" | |
| } | |
| return label_map.get(label.lower(), label) | |
| except Exception: | |
| return "Unknown" | |
| # Gradio UI সেটআপ | |
| interface = gr.Interface( | |
| fn=detect_emotion, | |
| inputs=gr.Textbox(lines=4, placeholder="বাংলা বা English-এ লিখুন এখানে...", label="আপনার টেক্সট"), | |
| outputs=gr.Textbox(label="Emotion Detected"), | |
| title="Bilingual Emotion Detector", | |
| description="বাংলা ও ইংরেজি টেক্সট থেকে আবেগ শনাক্ত করে একটি প্রশিক্ষিত মডেল।" | |
| ) | |
| interface.launch() |