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#!/usr/bin/env python3
"""
Test Conversational Voice Bot Features
Demonstrates how the bot now asks for clarification like your friend's bot
"""
import asyncio
import logging
# Setup logging
logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')
logger = logging.getLogger(__name__)
async def test_conversational_features():
"""Test the conversational clarity detection"""
print("🎯 Testing Conversational Voice Bot Features")
print("=" * 60)
print("This demonstrates how your bot now asks for clarification")
print("just like your friend's superior voice bot!")
print()
try:
from conversational_service import conversational_service
# Test queries that should trigger clarification
test_cases = [
{
"query": "pension",
"description": "Vague pension query",
"expected": "Should ask for specific pension topic"
},
{
"query": "what",
"description": "Too generic query",
"expected": "Should ask what topic user wants help with"
},
{
"query": "help",
"description": "General help request",
"expected": "Should provide topic options"
},
{
"query": "tender",
"description": "Vague procurement query",
"expected": "Should ask about specific procurement aspect"
},
{
"query": "What are the pension rules?",
"description": "Clear specific query",
"expected": "Should proceed with search (no clarification needed)"
}
]
for i, test_case in enumerate(test_cases, 1):
print(f"🔍 Test {i}: {test_case['description']}")
print(f"Query: \"{test_case['query']}\"")
print(f"Expected: {test_case['expected']}")
print("-" * 50)
# Analyze query clarity
clarity_analysis = conversational_service.analyze_query_clarity(
test_case['query'],
[] # Empty search results for testing
)
if clarity_analysis['clarification_needed']:
print("✅ RESULT: Bot will ask for clarification")
print("🤖 Bot response:")
print()
for question in clarity_analysis['clarification_questions']:
print(f" {question}")
print()
if 'suggested_responses' in clarity_analysis:
for suggestion in clarity_analysis['suggested_responses']:
print(f" {suggestion}")
else:
print("✅ RESULT: Query is clear, will proceed with search")
print(f"🎯 Confidence: {clarity_analysis['confidence']:.2f}")
print()
print("=" * 60)
print()
except ImportError as e:
print(f"❌ Import error: {e}")
print("💡 Make sure you're running from the PensionBot directory")
except Exception as e:
print(f"❌ Test error: {e}")
def demonstrate_conversation_flow():
"""Demonstrate a full conversation flow"""
print("💬 Conversation Flow Demonstration")
print("=" * 40)
print("Here's how a conversation now works:")
print()
conversation = [
{"speaker": "👤 User", "message": "pension"},
{"speaker": "🤖 Bot", "message": """I can help with pension-related questions! To give you the most accurate information, could you specify:
📋 What specifically about pension?
• How to calculate pension amount?
• Pension eligibility criteria?
• How to apply for pension?
• Family pension benefits?
• Commutation of pension?
Please let me know which aspect interests you most!"""},
{"speaker": "👤 User", "message": "calculation"},
{"speaker": "🤖 Bot", "message": """Here's the pension calculation formula:
**Formula**: (Last drawn basic pay + DA) × service years ÷ 70
**Minimum pension**: ₹9,000 per month
**Maximum pension**: No upper limit
**Example calculation**:
- Last basic pay: ₹50,000
- DA: ₹25,000 (50% of basic)
- Service years: 30
- Pension = (50,000 + 25,000) × 30 ÷ 70 = ₹32,143 per month
Would you like me to help with a specific pension calculation for your situation?"""}
]
for exchange in conversation:
print(f"{exchange['speaker']}: {exchange['message']}")
print()
print("🎯 Key Improvements:")
print("✅ Bot asks for clarification instead of guessing")
print("✅ Provides structured options for user to choose")
print("✅ Follows up with specific, detailed information")
print("✅ Encourages further conversation")
print()
print("This is exactly how your friend's bot works! 🎉")
if __name__ == "__main__":
print("🎯 Conversational Voice Bot Test")
print("Testing enhanced conversational features")
print()
# Run the tests
asyncio.run(test_conversational_features())
print("\n" + "="*60)
demonstrate_conversation_flow() |