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import sys
import os
from sqlalchemy import select, desc
from uuid import uuid4
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
# Add src to path
sys.path.append(os.path.join(os.path.dirname(__file__), ".."))
from src.backend.database.candidates.models import Candidate, CVScreeningResult, Base
from src.backend.database.candidates.client import SessionLocal, engine
from src.backend.agents.voice_screening.utils.questions import get_screening_questions
def verify_integration():
print("Verifying integration...")
# Create tables if not exist (for test)
Base.metadata.create_all(bind=engine)
# Create a dummy candidate
candidate_id = uuid4()
candidate = Candidate(
id=candidate_id,
full_name="Test Candidate",
email=f"test_{candidate_id}@example.com",
status="applied"
)
# Create a dummy CV result
cv_result = CVScreeningResult(
candidate_id=candidate_id,
job_title="Senior Python Engineer",
skills_match_score=0.9,
experience_match_score=0.8,
education_match_score=0.9,
overall_fit_score=0.85,
llm_feedback="Good fit",
reasoning_trace={}
)
try:
with SessionLocal() as db:
db.add(candidate)
db.add(cv_result)
db.commit()
print(f"Created test candidate: {candidate_id}")
# Simulate the logic in proxy.py
fetched_candidate = db.execute(
select(Candidate).where(Candidate.id == candidate_id)
).scalar_one_or_none()
if fetched_candidate:
print(f"Fetched candidate: {fetched_candidate.full_name}")
fetched_cv_result = db.execute(
select(CVScreeningResult)
.where(CVScreeningResult.candidate_id == candidate_id)
.order_by(desc(CVScreeningResult.timestamp))
.limit(1)
).scalar_one_or_none()
job_title = fetched_cv_result.job_title if fetched_cv_result else "the position"
print(f"Fetched job title: {job_title}")
questions = get_screening_questions(job_title)
print(f"Generated {len(questions)} questions")
instructions = (
f"You are a friendly HR assistant conducting a phone screening interview with {fetched_candidate.full_name} "
f"for the position of {job_title}. "
f"Greet the candidate warmly by name. "
f"Your goal is to ask the following questions to assess their fit:\n\n"
)
for i, q in enumerate(questions, 1):
instructions += f"{i}. {q}\n"
instructions += (
"\nAsk one question at a time. Wait for their response before moving to the next. "
"Be professional but conversational. If they ask clarifying questions, answer them briefly."
)
print("\nGenerated Instructions:")
print("-" * 40)
print(instructions)
print("-" * 40)
# Clean up
db.delete(cv_result)
db.delete(candidate)
db.commit()
print("Cleaned up test data")
except Exception as e:
print(f"Verification failed: {e}")
import traceback
traceback.print_exc()
if __name__ == "__main__":
verify_integration()
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