ghostai1 commited on
Commit
3ac78f9
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1 Parent(s): 94378be

Update app.py

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Files changed (1) hide show
  1. app.py +20 -13
app.py CHANGED
@@ -10,7 +10,7 @@ import io
10
  import re
11
  import os
12
 
13
- # Embedded call center FAQs (fixed formatting: escaped quotes, consistent rows, no trailing newline)
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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
@@ -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 enter a valid question.", [], {}
91
 
92
  start_time = time.perf_counter()
93
  try:
@@ -141,7 +141,7 @@ def plot_metrics(metrics):
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  plt.close()
142
  return 'rag_plot.png'
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144
- # 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)
@@ -165,27 +165,34 @@ def chat_interface(query):
165
  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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172
  with gr.Blocks(css=custom_css) as demo:
173
  gr.Markdown("# Customer Experience Bot Demo")
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- gr.Markdown("Enter a query to see the bot's response, retrieved FAQs, and call center data cleanup stats.")
175
 
 
176
  with gr.Row():
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- query_input = gr.Textbox(label="Your Query", placeholder="e.g., How do I reset my password?")
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- submit_btn = gr.Button("Submit")
 
 
 
 
 
 
 
 
 
179
 
180
  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")
183
  plot_output = gr.Image(label="RAG Pipeline Metrics")
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-
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- submit_btn.click(
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- fn=chat_interface,
187
- inputs=query_input,
188
- outputs=[response_output, faq_output, cleanup_output, plot_output]
189
- )
190
 
191
  demo.launch()
 
10
  import re
11
  import os
12
 
13
+ # Embedded call center FAQs (fixed formatting: escaped quotes, consistent rows)
14
  csv_data = """question,answer,call_id,agent_id,timestamp,language
15
  "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
16
  "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
 
87
  # RAG process
88
  def rag_process(query, k=2):
89
  if not query.strip() or len(query) < 5:
90
+ return "Invalid query. Please select a question.", [], {}
91
 
92
  start_time = time.perf_counter()
93
  try:
 
141
  plt.close()
142
  return 'rag_plot.png'
143
 
144
+ # Gradio interface with buttons
145
  def chat_interface(query):
146
  try:
147
  response, retrieved_faqs, metrics = rag_process(query)
 
165
  custom_css = """
166
  body { background-color: #2a2a2a; color: #e0e0e0; }
167
  .gr-box { background-color: #3a3a3a; border: 1px solid #4a4a4a; }
168
+ .gr-button { background-color: #1e90ff; color: white; margin: 5px; }
169
  .gr-button:hover { background-color: #1c86ee; }
170
  """
171
 
172
+ # Get unique questions for buttons (after cleanup)
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+ unique_questions = faq_data['question'].tolist()
174
+
175
  with gr.Blocks(css=custom_css) as demo:
176
  gr.Markdown("# Customer Experience Bot Demo")
177
+ gr.Markdown("Select a question to see the bot's response, retrieved FAQs, and call center data cleanup stats.")
178
 
179
+ # Create buttons for each question
180
  with gr.Row():
181
+ for question in unique_questions:
182
+ gr.Button(question).click(
183
+ fn=chat_interface,
184
+ inputs=gr.State(value=question),
185
+ outputs=[
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+ gr.Textbox(label="Bot Response"),
187
+ gr.Textbox(label="Retrieved FAQs"),
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+ gr.Textbox(label="Data Cleanup Stats"),
189
+ gr.Image(label="RAG Pipeline Metrics")
190
+ ]
191
+ )
192
 
193
  response_output = gr.Textbox(label="Bot Response")
194
  faq_output = gr.Textbox(label="Retrieved FAQs")
195
  cleanup_output = gr.Textbox(label="Data Cleanup Stats")
196
  plot_output = gr.Image(label="RAG Pipeline Metrics")
 
 
 
 
 
 
197
 
198
  demo.launch()