Update app.py
Browse files
app.py
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@@ -10,7 +10,7 @@ import io
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import re
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import os
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# Embedded call center FAQs (fixed formatting: escaped quotes, consistent rows
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csv_data = """question,answer,call_id,agent_id,timestamp,language
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"How do I reset my password?","Go to the login page, click ""Forgot Password,"" and follow the email instructions.",12345,A001,2025-04-01 10:15:23,en
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"What are your pricing plans?","We offer Basic ($10/month), Pro ($50/month), and Enterprise (custom).",12346,A002,2025-04-01 10:17:45,en
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@@ -87,7 +87,7 @@ except Exception as e:
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# RAG process
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def rag_process(query, k=2):
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if not query.strip() or len(query) < 5:
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return "Invalid query. Please
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start_time = time.perf_counter()
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try:
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@@ -141,7 +141,7 @@ def plot_metrics(metrics):
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plt.close()
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return 'rag_plot.png'
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# Gradio interface
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def chat_interface(query):
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try:
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response, retrieved_faqs, metrics = rag_process(query)
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@@ -165,27 +165,34 @@ def chat_interface(query):
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custom_css = """
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body { background-color: #2a2a2a; color: #e0e0e0; }
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.gr-box { background-color: #3a3a3a; border: 1px solid #4a4a4a; }
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.gr-button { background-color: #1e90ff; color: white; }
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.gr-button:hover { background-color: #1c86ee; }
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"""
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with gr.Blocks(css=custom_css) as demo:
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gr.Markdown("# Customer Experience Bot Demo")
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gr.Markdown("
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with gr.Row():
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response_output = gr.Textbox(label="Bot Response")
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faq_output = gr.Textbox(label="Retrieved FAQs")
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cleanup_output = gr.Textbox(label="Data Cleanup Stats")
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plot_output = gr.Image(label="RAG Pipeline Metrics")
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submit_btn.click(
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fn=chat_interface,
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inputs=query_input,
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outputs=[response_output, faq_output, cleanup_output, plot_output]
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)
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demo.launch()
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import re
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import os
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# Embedded call center FAQs (fixed formatting: escaped quotes, consistent rows)
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csv_data = """question,answer,call_id,agent_id,timestamp,language
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"How do I reset my password?","Go to the login page, click ""Forgot Password,"" and follow the email instructions.",12345,A001,2025-04-01 10:15:23,en
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"What are your pricing plans?","We offer Basic ($10/month), Pro ($50/month), and Enterprise (custom).",12346,A002,2025-04-01 10:17:45,en
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# RAG process
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def rag_process(query, k=2):
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if not query.strip() or len(query) < 5:
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return "Invalid query. Please select a question.", [], {}
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start_time = time.perf_counter()
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try:
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plt.close()
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return 'rag_plot.png'
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# Gradio interface with buttons
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def chat_interface(query):
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try:
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response, retrieved_faqs, metrics = rag_process(query)
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custom_css = """
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body { background-color: #2a2a2a; color: #e0e0e0; }
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.gr-box { background-color: #3a3a3a; border: 1px solid #4a4a4a; }
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.gr-button { background-color: #1e90ff; color: white; margin: 5px; }
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.gr-button:hover { background-color: #1c86ee; }
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"""
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# Get unique questions for buttons (after cleanup)
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unique_questions = faq_data['question'].tolist()
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with gr.Blocks(css=custom_css) as demo:
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gr.Markdown("# Customer Experience Bot Demo")
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gr.Markdown("Select a question to see the bot's response, retrieved FAQs, and call center data cleanup stats.")
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# Create buttons for each question
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with gr.Row():
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for question in unique_questions:
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gr.Button(question).click(
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fn=chat_interface,
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inputs=gr.State(value=question),
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outputs=[
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gr.Textbox(label="Bot Response"),
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gr.Textbox(label="Retrieved FAQs"),
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gr.Textbox(label="Data Cleanup Stats"),
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gr.Image(label="RAG Pipeline Metrics")
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]
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)
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response_output = gr.Textbox(label="Bot Response")
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faq_output = gr.Textbox(label="Retrieved FAQs")
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cleanup_output = gr.Textbox(label="Data Cleanup Stats")
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plot_output = gr.Image(label="RAG Pipeline Metrics")
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demo.launch()
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