Update app.py
Browse files
app.py
CHANGED
@@ -1,375 +1,100 @@
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import gradio as gr
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from geminisearch import webSearch
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import threading
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import time
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self.is_processing = False
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def process_audio_message(self, audio, chat_history):
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"""Process audio input using Gradio's built-in speech recognition"""
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if audio is None:
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return chat_history, "Please provide audio input", "No audio received"
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try:
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# Gradio will handle the speech-to-text conversion automatically
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# when we use the audio input with the speech recognition feature
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return chat_history, "Processing audio...", "Audio received, processing..."
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except Exception as e:
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error_msg = f"Audio processing error: {str(e)}"
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chat_history.append({"role": "assistant", "content": error_msg})
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return chat_history, error_msg, "Error processing audio"
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def process_text_with_audio_response(self, text, chat_history):
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"""Process text input and prepare for audio output"""
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if not text.strip():
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return chat_history, "", "Please enter a message"
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# Add user message to chat
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chat_history.append({"role": "user", "content": text})
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try:
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# Get response from webSearch
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response = webSearch(text)
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chat_history.append({"role": "assistant", "content": response})
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return chat_history, "", f"✅ Response ready: {text[:30]}..."
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except Exception as e:
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error_msg = f"Search error: {str(e)}"
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chat_history.append({"role": "assistant", "content": error_msg})
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return chat_history, "", f"❌ Error: {str(e)[:30]}..."
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# Initialize audio chat
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audio_chat = QuasarAudioChat()
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# Predefined questions for Quasar LLM
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quasar_examples = [
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"What are the latest AI technology developments?",
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"What's happening in global news today?",
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"What's the current cryptocurrency market status?"
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]
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#
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custom_css = """
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:root {
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--quasar-primary: #667eea;
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--quasar-secondary: #764ba2;
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--quasar-accent: #ff6b6b;
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--quasar-gold: #ffd93d;
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}
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.gradio-container {
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max-width:
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margin: auto !important;
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background: linear-gradient(135deg, var(--quasar-primary) 0%, var(--quasar-secondary) 100%) !important;
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min-height: 100vh !important;
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padding: 1rem !important;
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}
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.main-container {
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background: rgba(255, 255, 255, 0.95) !important;
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border-radius: 25px !important;
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padding: 2rem !important;
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box-shadow: 0 25px 50px rgba(0,0,0,0.15) !important;
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backdrop-filter: blur(10px) !important;
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}
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.chatbot {
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border-radius: 20px !important;
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box-shadow: 0 10px 30px rgba(0, 0, 0, 0.1) !important;
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border: 2px solid rgba(102, 126, 234, 0.2) !important;
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background: rgba(255, 255, 255, 0.9) !important;
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}
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.audio-section {
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background: linear-gradient(135deg, rgba(255, 107, 107, 0.1), rgba(255, 217, 61, 0.1)) !important;
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border-radius: 20px !important;
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padding: 1.5rem !important;
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margin: 1rem 0 !important;
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border: 2px solid rgba(255, 107, 107, 0.2) !important;
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}
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.audio-input {
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border-radius: 15px !important;
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border: 2px solid var(--quasar-accent) !important;
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box-shadow: 0 5px 15px rgba(255, 107, 107, 0.2) !important;
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}
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.voice-button {
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background: linear-gradient(135deg, var(--quasar-accent), var(--quasar-gold)) !important;
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border: none !important;
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border-radius: 50px !important;
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color: white !important;
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font-weight: 600 !important;
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font-size: 1.1rem !important;
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padding: 0.8rem 2rem !important;
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box-shadow: 0 8px 20px rgba(255, 107, 107, 0.3) !important;
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transition: all 0.3s ease !important;
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text-transform: uppercase !important;
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letter-spacing: 1px !important;
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}
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.
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transform: translateY(-3px) !important;
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box-shadow: 0 12px 30px rgba(255, 107, 107, 0.4) !important;
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}
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.text-section {
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background: linear-gradient(135deg, rgba(102, 126, 234, 0.1), rgba(118, 75, 162, 0.1)) !important;
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border-radius: 20px !important;
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padding: 1.5rem !important;
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margin: 1rem 0 !important;
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border: 2px solid rgba(102, 126, 234, 0.2) !important;
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}
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.text-input {
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border-radius: 25px !important;
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border: 2px solid var(--quasar-primary) !important;
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background: rgba(255, 255, 255, 0.9) !important;
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font-size: 1rem !important;
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padding: 0.8rem 1.5rem !important;
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}
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.text-input:focus {
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border-color: var(--quasar-secondary) !important;
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box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.1) !important;
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}
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.send-button {
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background: linear-gradient(135deg, var(--quasar-primary), var(--quasar-secondary)) !important;
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border: none !important;
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border-radius: 25px !important;
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font-weight: 600 !important;
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padding: 0.8rem 1.5rem !important;
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transition: all 0.3s ease !important;
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}
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.
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box-shadow: 0
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}
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h1 {
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text-align: center !important;
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-webkit-text-fill-color: transparent !important;
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font-weight: 800 !important;
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font-size: 3rem !important;
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margin-bottom: 0.5rem !important;
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text-shadow: 2px 2px 4px rgba(0,0,0,0.1) !important;
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}
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.subtitle {
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text-align: center !important;
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color: #555 !important;
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font-size: 1.2rem !important;
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margin-bottom: 2rem !important;
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font-weight: 400 !important;
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}
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.status-box {
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background: linear-gradient(135deg, #e8f4f8, #f0f8ff) !important;
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border: 2px solid #1976d2 !important;
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border-radius: 15px !important;
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padding: 1rem !important;
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color: #1976d2 !important;
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font-weight: 500 !important;
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text-align: center !important;
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font-size: 0.95rem !important;
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}
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.examples {
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margin-top:
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}
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.example {
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border-radius:
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background: linear-gradient(135deg,
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color: white !important;
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border: none !important;
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transition: all 0.3s ease !important;
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font-weight: 500 !important;
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padding: 0.8rem 1.5rem !important;
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font-size: 0.95rem !important;
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}
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.example:hover {
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transform: translateY(-
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box-shadow: 0
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}
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.feature-badge {
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display: inline-block !important;
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background: var(--quasar-accent) !important;
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color: white !important;
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padding: 0.3rem 0.8rem !important;
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border-radius: 20px !important;
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font-size: 0.8rem !important;
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font-weight: 600 !important;
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margin: 0 0.3rem !important;
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}
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"""
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# Create the
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theme=gr.themes.Soft(
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primary_hue="blue",
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secondary_hue="slate",
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neutral_hue="slate",
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font=gr.themes.GoogleFont("Inter")
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),
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css=custom_css,
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💬 <span class="feature-badge">TEXT</span>
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🌐 <span class="feature-badge">WEB SEARCH</span><br>
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Real-time AI-powered conversations with web intelligence
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</p>
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</div>
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""")
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# Main chat interface
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chatbot = gr.Chatbot(
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value=[],
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height=450,
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show_label=False,
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container=True,
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bubble_full_width=False,
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render_markdown=True,
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type="messages",
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elem_classes=["chatbot"]
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)
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# Audio Input Section
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with gr.Group(elem_classes=["audio-section"]):
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gr.HTML("<h3 style='text-align: center; color: #ff6b6b; margin-bottom: 1rem;'>🎤 Voice Input</h3>")
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with gr.Row():
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with gr.Column(scale=4):
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audio_input = gr.Audio(
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sources=["microphone"],
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type="filepath",
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label="Record your question",
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show_label=False,
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container=False,
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elem_classes=["audio-input"]
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)
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with gr.Column(scale=1, min_width=150):
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audio_submit = gr.Button(
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"🎤 Ask Voice",
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variant="primary",
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size="lg",
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elem_classes=["voice-button"]
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)
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# Text Input Section
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with gr.Group(elem_classes=["text-section"]):
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gr.HTML("<h3 style='text-align: center; color: #667eea; margin-bottom: 1rem;'>💬 Text Input</h3>")
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with gr.Row():
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with gr.Column(scale=5):
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text_input = gr.Textbox(
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placeholder="Type your question here or use voice input above...",
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container=False,
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show_label=False,
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lines=1,
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max_lines=3,
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elem_classes=["text-input"]
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)
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with gr.Column(scale=1, min_width=100):
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text_submit = gr.Button(
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"Send",
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variant="secondary",
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elem_classes=["send-button"]
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)
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# Status Display
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status = gr.Textbox(
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value="🚀 Ready for your questions - Use voice or text input!",
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label="Status",
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interactive=False,
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elem_classes=["status-box"],
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show_label=False
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)
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# Example Questions
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gr.Examples(
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examples=quasar_examples,
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inputs=[text_input],
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label="✨ Try these example questions:",
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elem_classes=["examples"]
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)
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# Audio processing function
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def handle_audio_input(audio_file, history):
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if audio_file is None:
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return history, "Please record audio first 🎤"
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# For now, we'll add a placeholder message since we don't have speech-to-text
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# In a real deployment, you'd integrate with a speech-to-text service
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user_message = "🎤 [Voice message received - Speech-to-text would process this]"
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history.append({"role": "user", "content": user_message})
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# Add a helpful response
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response = "I received your voice message! However, speech-to-text processing requires additional services. Please use the text input below for now, or integrate with a cloud speech service like Google Speech-to-Text or OpenAI Whisper."
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history.append({"role": "assistant", "content": response})
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return history, "Voice message received (text processing recommended)"
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# Text processing function
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def handle_text_input(text, history):
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if not text.strip():
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return history, "", "Please enter a message 📝"
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# Add user message
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history.append({"role": "user", "content": text})
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try:
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# Get response from webSearch
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response = webSearch(text)
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history.append({"role": "assistant", "content": response})
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return history, "", f"✅ Question answered: {text[:40]}..."
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except Exception as e:
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error_msg = f"🔍 Search temporarily unavailable: {str(e)}"
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history.append({"role": "assistant", "content": error_msg})
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return history, "", f"❌ Error occurred"
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# Event handlers
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audio_submit.click(
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handle_audio_input,
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inputs=[audio_input, chatbot],
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outputs=[chatbot, status]
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)
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text_submit.click(
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handle_text_input,
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inputs=[text_input, chatbot],
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outputs=[chatbot, text_input, status]
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)
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text_input.submit(
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handle_text_input,
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inputs=[text_input, chatbot],
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outputs=[chatbot, text_input, status]
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)
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# Launch configuration
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if __name__ == "__main__":
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app.launch(
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mcp_server=True,
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inbrowser=True,
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show_error=True,
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quiet=False,
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)
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import gradio as gr
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from geminisearch import webSearch
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# Concise example questions for MCP interface
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mcp_examples = [
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"What are the latest AI technology developments?",
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"What's happening in global news today?",
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"What's the current cryptocurrency market status?"
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]
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# Custom CSS for better styling
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custom_css = """
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.gradio-container {
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max-width: 1200px !important;
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margin: auto !important;
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}
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.chatbot {
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border-radius: 15px !important;
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box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1) !important;
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}
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.input-container {
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border-radius: 25px !important;
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+
border: 2px solid #e1e5e9 !important;
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26 |
}
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+
.input-container:focus-within {
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+
border-color: #4285f4 !important;
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+
box-shadow: 0 0 0 3px rgba(66, 133, 244, 0.1) !important;
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}
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h1 {
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text-align: center !important;
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+
color: #1a73e8 !important;
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+
font-weight: 600 !important;
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37 |
margin-bottom: 2rem !important;
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38 |
}
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.examples {
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+
margin-top: 1rem !important;
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}
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43 |
|
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.example {
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+
border-radius: 20px !important;
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+
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
|
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color: white !important;
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border: none !important;
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transition: all 0.3s ease !important;
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}
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.example:hover {
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+
transform: translateY(-2px) !important;
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+
box-shadow: 0 8px 25px rgba(0,0,0,0.2) !important;
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}
|
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"""
|
57 |
|
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+
# Create the enhanced interface
|
59 |
+
app = gr.ChatInterface(
|
60 |
+
webSearch,
|
61 |
+
chatbot=gr.Chatbot(
|
62 |
+
height=500,
|
63 |
+
show_label=False,
|
64 |
+
container=True,
|
65 |
+
bubble_full_width=False,
|
66 |
+
render_markdown=True
|
67 |
+
),
|
68 |
+
type="messages",
|
69 |
+
textbox=gr.Textbox(
|
70 |
+
placeholder="🔍 Ask me anything about current events, news, or real-time information...",
|
71 |
+
container=False,
|
72 |
+
scale=7,
|
73 |
+
show_label=False,
|
74 |
+
lines=1,
|
75 |
+
max_lines=3
|
76 |
+
),
|
77 |
+
title="✨ Quasar LLM Web Chat",
|
78 |
+
description="Quasar LLM powered interface for real-time web search and intelligent responses.",
|
79 |
theme=gr.themes.Soft(
|
80 |
primary_hue="blue",
|
81 |
+
secondary_hue="slate",
|
82 |
neutral_hue="slate",
|
83 |
font=gr.themes.GoogleFont("Inter")
|
84 |
),
|
85 |
+
examples=mcp_examples,
|
86 |
+
cache_examples=False,
|
87 |
css=custom_css,
|
88 |
+
analytics_enabled=False,
|
89 |
+
show_progress="minimal"
|
90 |
+
)
|
91 |
+
|
92 |
+
# Additional configuration
|
93 |
+
app.queue(
|
94 |
+
default_concurrency_limit=20,
|
95 |
+
max_size=50
|
96 |
+
)
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|
97 |
|
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|
98 |
if __name__ == "__main__":
|
99 |
app.launch(
|
100 |
mcp_server=True,
|
|
|
102 |
inbrowser=True,
|
103 |
show_error=True,
|
104 |
quiet=False,
|
105 |
+
favicon_path=None,
|
106 |
+
ssl_verify=False
|
107 |
)
|