File size: 1,937 Bytes
9df97a2 | 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 | import os
os.environ.setdefault("DATABASE_URL", "sqlite:///./ai_talent_finder.db")
os.environ.setdefault("USE_AI_PROFILE_GENERATOR", "false")
from fastapi.testclient import TestClient
from app.main import app
from ai_module.nlp.profile_generator import ProfileGenerator
from ai_module.matching.semantic_matcher import SemanticSkillMatcher
from ai_module.nlp.enhanced_skill_extractor import EnhancedSkillExtractor
def main() -> None:
client = TestClient(app)
r = client.get("/health")
print("health", r.status_code, r.json())
r = client.post(
"/api/matching/generate-profile",
json={
"job_title": "Senior Python Developer",
"description": "Senior Python FastAPI engineer, 5 years experience, bachelor degree, english and french.",
},
)
print("generate_profile", r.status_code, sorted(r.json().keys()))
r = client.post(
"/api/matching/generate-and-match",
json={
"job_title": "Data Engineer",
"description": "Need Python, SQL, ETL and cloud skills.",
},
)
body = r.json()
print("generate_and_match", r.status_code, "ideal_profile" in body, isinstance(body.get("matches"), list))
p = ProfileGenerator.generate_from_text("Python lead with 6 years and master degree, english language")
print("profile_ok", isinstance(p, dict), len(p.get("ideal_skills", [])))
m = SemanticSkillMatcher.match_candidate_skills(
["Python", "FastAPI", "Docker"],
[{"name": "Python", "weight": 100}, {"name": "Django", "weight": 70}],
)
print("semantic_ok", round(float(m.get("score", 0)), 2), m.get("total_matches"))
ex = EnhancedSkillExtractor(load_ner=False)
sk = ex.extract_skills_hybrid("Python FastAPI Docker Kubernetes communication leadership English")
print("skill_extractor_ok", len(sk), sk[0]["name"] if sk else "none")
if __name__ == "__main__":
main()
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