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1813edc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | """Response quality validation"""
from orchestration.state import ConversationState
from typing import Dict, Any
import logging
from orchestration.latency_tracker import get_tracker
logger = logging.getLogger(__name__)
def validation_node(state: ConversationState) -> Dict[str, Any]:
"""
Validate generated response against quality criteria:
1. Length checks (not too short, not too long)
2. Tone-sentiment consistency
3. Basic sanity checks
Returns:
state update with validation_passed boolean
"""
tracker = get_tracker()
tracker.start("validation")
response = state.get('response', '')
sentiment = state.get('sentiment', {}).get('label', 'NEUTRAL')
# Check 1: Response length (between 50-500 characters)
response_length = len(response)
length_valid = 50 <= response_length <= 500
# Check 2: Tone-sentiment consistency
tone_checks = {
"NEGATIVE": {
"forbidden_words": ["happy", "excellent", "amazing"],
"required_sentiment": ["understand", "apologize", "help"]
},
"POSITIVE": {
"forbidden_words": ["sorry", "problem", "issue"],
"required_sentiment": ["great", "happy", "enjoy"]
}
}
response_lower = response.lower()
tone_valid = True
if sentiment in tone_checks:
checks = tone_checks[sentiment]
# Check forbidden words aren't present
forbidden_present = any(word in response_lower for word in checks.get("forbidden_words", []))
tone_valid = not forbidden_present
# Check 3: Response not empty
content_valid = len(response.strip()) > 0
# Overall validation
validation_passed = length_valid and content_valid and tone_valid
logger.info(f"✓ Validation: length={response_length} ({length_valid}), content={content_valid}, tone={tone_valid} -> {'PASS' if validation_passed else 'FAIL'}")
tracker.end("validation")
return {"validation_passed": validation_passed}
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