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Update app.py
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app.py
CHANGED
@@ -5,65 +5,195 @@ import functools
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# Cache the pipeline so it loads only once
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@functools.lru_cache(maxsize=1)
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def load_pipeline():
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def dental_chatbot_response(message, history):
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"""
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Generates responses
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"""
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prompt = (
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"You are a highly knowledgeable and friendly dental expert chatbot. "
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"Provide detailed and accurate explanations of dental terms, procedures, and treatments. "
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"If the query is not dental-related, respond helpfully and informatively
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f"User: {message}
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)
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gen_pipe = load_pipeline()
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generated = gen_pipe(
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prompt,
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max_length=200,
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num_return_sequences=1,
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do_sample=True,
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top_p=0.9,
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top_k=50
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)
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generated_text = generated[0]["generated_text"]
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# Safely extract the chatbot's response
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if "Chatbot:" in generated_text:
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ai_response = generated_text.split("Chatbot:")[1].strip()
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else:
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ai_response = generated_text.strip()
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return ai_response
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# Custom CSS
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custom_css = """
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body {
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background: #
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font-family: Arial, sans-serif;
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}
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background: #ffffff;
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border-radius:
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box-shadow: 0
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padding: 20px;
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}
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text-align: center;
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}
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"""
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#
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if __name__ == "__main__":
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demo.launch()
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# Cache the pipeline so it loads only once
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@functools.lru_cache(maxsize=1)
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def load_pipeline():
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# Using google/flan-t5-base which is instruction-tuned for improved responses.
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return pipeline("text2text-generation", model="google/flan-t5-base", device=-1)
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def dental_chatbot_response(message, history):
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"""
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Generates responses with dental expertise using google/flan-t5-base.
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"""
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prompt = (
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"You are a highly knowledgeable and friendly dental expert chatbot. "
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"Provide detailed and accurate explanations of dental terms, procedures, and treatments. "
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"If the query is not dental-related, respond helpfully and informatively. "
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f"User: {message}"
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)
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gen_pipe = load_pipeline()
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generated = gen_pipe(
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prompt,
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max_length=200,
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do_sample=True,
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top_p=0.9,
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top_k=50,
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)
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ai_response = generated[0]["generated_text"].strip()
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return ai_response
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# Custom CSS for a colorful, modern look with icons and visual effects.
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custom_css = """
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/* Overall background with a pleasant gradient */
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body {
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background: linear-gradient(135deg, #ff9a9e, #fad0c4);
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font-family: Arial, sans-serif;
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margin: 0;
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padding: 0;
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}
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/* Main container styling */
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.container {
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background: #ffffff;
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border-radius: 20px;
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box-shadow: 0 8px 16px rgba(0,0,0,0.2);
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max-width: 800px;
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margin: 40px auto;
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padding: 20px;
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}
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/* Header styling */
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.header {
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text-align: center;
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margin-bottom: 20px;
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}
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.header h1 {
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font-size: 2.5rem;
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margin: 0;
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color: #d81b60;
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}
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.header p {
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font-size: 1.2rem;
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color: #555555;
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}
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/* Chat message styling */
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.chat-msg {
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display: flex;
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margin: 10px 0;
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align-items: flex-start;
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}
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.chat-msg.user {
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justify-content: flex-start;
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}
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.chat-msg.bot {
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justify-content: flex-end;
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}
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.msg-content {
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max-width: 70%;
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padding: 10px 15px;
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border-radius: 15px;
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position: relative;
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font-size: 1rem;
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line-height: 1.3;
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}
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/* User message bubble */
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.chat-msg.user .msg-content {
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background: #ffe0b2;
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color: #5d4037;
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margin-left: 40px;
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}
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/* Bot message bubble */
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.chat-msg.bot .msg-content {
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background: #c5e1a5;
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color: #33691e;
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margin-right: 40px;
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}
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/* Icon styling for messages (using emojis) */
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.msg-icon {
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font-size: 1.5rem;
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width: 30px;
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text-align: center;
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}
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.chat-msg.user .msg-icon {
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color: #d81b60;
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}
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.chat-msg.bot .msg-icon {
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color: #2e7d32;
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}
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/* Input area styling */
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#input-area {
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display: flex;
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margin-top: 20px;
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}
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#input-area textarea {
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flex: 1;
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padding: 10px;
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font-size: 1rem;
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border: 2px solid #ffe0b2;
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border-radius: 10px;
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outline: none;
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}
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#input-area button {
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background: #d81b60;
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color: #fff;
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border: none;
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padding: 0 20px;
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margin-left: 10px;
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border-radius: 10px;
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cursor: pointer;
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transition: background 0.3s ease;
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font-size: 1rem;
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}
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#input-area button:hover {
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background: #ff5252;
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}
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"""
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# Build the custom Blocks interface
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with gr.Blocks(css=custom_css) as demo:
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with gr.Container(elem_classes=["container"]):
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# Header with a dental icon in the title
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with gr.Column(elem_classes=["header"]):
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gr.Markdown("## 🦷 Advanced Dental Terminology Chatbot")
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gr.Markdown("Ask me anything about dental terms, procedures, and treatments! This chatbot is powered by an instruction-tuned LLM for accurate and detailed answers.")
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# Chat display area
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chatbot = gr.HTML("<div id='chat-box'></div>")
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chat_state = gr.State([]) # To store chat history as a list of (user, bot) pairs
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# Input area
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with gr.Row(elem_id="input-area"):
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user_input = gr.Textbox(show_label=False, placeholder="Type your message here...", lines=2)
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send_btn = gr.Button("Send")
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def update_chat(user_message, history):
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# Append the user's message to the chat history.
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history = history + [(user_message, None)]
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# Generate bot response.
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bot_reply = dental_chatbot_response(user_message, history)
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history[-1] = (user_message, bot_reply)
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# Build HTML for the updated chat box with icons.
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chat_html = ""
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for user_msg, bot_msg in history:
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# User message bubble with a smiley icon.
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chat_html += f"""
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<div class='chat-msg user'>
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<div class='msg-icon'>🙂</div>
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<div class='msg-content'>{user_msg}</div>
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</div>
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"""
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if bot_msg:
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# Bot message bubble with a dental icon.
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chat_html += f"""
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<div class='chat-msg bot'>
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<div class='msg-content'>{bot_msg}</div>
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<div class='msg-icon'>🦷</div>
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</div>
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"""
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return chat_html, history, ""
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# Wire up interactions: when the textbox is submitted or the send button is clicked.
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user_input.submit(
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update_chat,
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inputs=[user_input, chat_state],
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outputs=[chatbot, chat_state, user_input]
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)
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send_btn.click(
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update_chat,
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inputs=[user_input, chat_state],
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outputs=[chatbot, chat_state, user_input]
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)
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if __name__ == "__main__":
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demo.launch()
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