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import gradio as gr |
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from transformers import AutoTokenizer, AutoModelForSequenceClassification |
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from torch.nn.functional import softmax |
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import torch |
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model_name = "bhadresh-savani/distilbert-base-uncased-emotion" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForSequenceClassification.from_pretrained(model_name) |
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emotion_icons = { |
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"admiration": "😍", |
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"amusement": "😅", |
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"anger": "😡", |
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"annoyance": "😑", |
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"approval": "👍", |
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"caring": "💗", |
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"confusion": "🤔", |
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"curiosity": "😮", |
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"desire": "🤤", |
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"disappointment": "😞", |
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"disapproval": "👎", |
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"disgust": "🤮", |
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"embarrassment": "😳", |
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"excitement": "🎉", |
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"fear": "😱", |
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"gratitude": "🙏", |
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"grief": "😭", |
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"joy": "😃", |
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"love": "❤️", |
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"nervousness": "🤧", |
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"optimism": "😊", |
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"pride": "😎", |
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"realization": "🤯", |
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"relief": "😌", |
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"remorse": "😔", |
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"sadness": "😢", |
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"surprise": "😲", |
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"neutral": "😐" |
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} |
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def get_emotion(text): |
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inputs = tokenizer(text, return_tensors="pt") |
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outputs = model(**inputs) |
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probs = softmax(outputs.logits, dim=1) |
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predicted_class = torch.argmax(probs).item() |
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label = model.config.id2label[predicted_class] |
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icon = emotion_icons.get(label, "") |
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return f"{icon} {label.capitalize()}" |
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custom_css = """ |
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body { |
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background: linear-gradient(to right, #f9f9f9, #d4ecff); |
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font-family: 'Segoe UI', sans-serif; |
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} |
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.gr-button { |
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background-color: #007BFF !important; |
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color: white !important; |
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border-radius: 8px !important; |
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font-weight: bold; |
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} |
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.gr-button:hover { |
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background-color: #0056b3 !important; |
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} |
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.gr-textbox { |
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border-radius: 8px !important; |
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border: 1px solid #ccc !important; |
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padding: 10px !important; |
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} |
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.output-textbox { |
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font-size: 1.5rem; |
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font-weight: bold; |
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color: #333; |
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background-color: #f1f9ff; |
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border-radius: 8px; |
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padding: 10px; |
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border: 1px solid #007BFF; |
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} |
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""" |
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demo = gr.Interface( |
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fn=get_emotion, |
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inputs=gr.Textbox(lines=3, placeholder="What's on your mind today?", label="Your Text"), |
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outputs=gr.Textbox(label="Detected Emotion", elem_classes=["output-textbox"]), |
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title="🥰 Emotion Detector", |
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description="Type a sentence below and hit Submit to reveal the emotion behind your words.", |
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theme="default", |
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css=custom_css |
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) |
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demo.launch() |
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