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Update app.py
Browse files
app.py
CHANGED
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@@ -159,18 +159,18 @@ def get_health_professionals_and_map(location, query):
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# Main Application Logic
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def app_function(user_input, location, query, history):
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chatbot_history, _ = generate_chatbot_response(user_input, history)
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sentiment_result = analyze_sentiment(user_input)
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emotion_result, cleaned_emotion = detect_emotion(user_input)
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suggestions = generate_suggestions(cleaned_emotion)
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professionals, map_html = get_health_professionals_and_map(location, query)
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return chatbot_history, sentiment_result, emotion_result, suggestions, professionals, map_html
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#
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custom_css = """
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body {
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font-family: 'Roboto', sans-serif;
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background: linear-gradient(135deg, #0d0d0d, #ff5722);
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color: white;
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}
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@@ -215,9 +215,9 @@ textarea:hover, input:hover {
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border-radius: 10px;
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padding: 10px;
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font-size: 14px;
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max-height: 400px;
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height: auto;
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overflow-y: auto;
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}
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"""
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@@ -231,6 +231,10 @@ with gr.Blocks(css=custom_css) as app:
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chatbot = gr.Chatbot(label="Chat History")
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sentiment = gr.Textbox(label="Detected Sentiment")
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emotion = gr.Textbox(label="Detected Emotion")
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suggestions = gr.DataFrame(headers=["Title", "Link"]) # Table for suggestions
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professionals = gr.Textbox(label="Nearby Professionals", lines=6)
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map_html = gr.HTML(label="Interactive Map")
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# Main Application Logic
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def app_function(user_input, location, query, history):
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chatbot_history, _ = generate_chatbot_response(user_input, history)
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sentiment_result = analyze_sentiment(user_input)
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emotion_result, cleaned_emotion = detect_emotion(user_input)
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suggestions = generate_suggestions(cleaned_emotion)
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professionals, map_html = get_health_professionals_and_map(location, query)
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return chatbot_history, sentiment_result, emotion_result, suggestions, professionals, map_html
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# CSS Styling
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custom_css = """
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body {
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font-family: 'Roboto', sans-serif;
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background: linear-gradient(135deg, #0d0d0d, #ff5722);
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color: white;
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}
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border-radius: 10px;
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padding: 10px;
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font-size: 14px;
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max-height: 400px;
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height: auto;
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overflow-y: auto;
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}
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"""
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chatbot = gr.Chatbot(label="Chat History")
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sentiment = gr.Textbox(label="Detected Sentiment")
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emotion = gr.Textbox(label="Detected Emotion")
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# Adding Suggestions Title
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gr.Markdown("### Suggestions", elem_id="suggestions-title")
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suggestions = gr.DataFrame(headers=["Title", "Link"]) # Table for suggestions
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professionals = gr.Textbox(label="Nearby Professionals", lines=6)
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map_html = gr.HTML(label="Interactive Map")
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