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11bedd8 93954b7 11bedd8 93954b7 11bedd8 5e04dcc 93954b7 | 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 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 | import pytest
from fastapi.testclient import TestClient
from app.main import app
import app.middleware.security as _security
client = TestClient(app)
@pytest.fixture(autouse=True)
def reset_rate_limiter():
_security._ip_usage.clear()
yield
_security._ip_usage.clear()
def test_health():
response = client.get("/api/health")
assert response.status_code == 200
assert response.json() == {"status": "ok"}
def test_parse_linkedin_rejects_non_pdf():
response = client.post(
"/api/parse-linkedin",
files={"file": ("test.txt", b"not a pdf", "text/plain")},
)
assert response.status_code == 400
from unittest.mock import patch, MagicMock
from app.models import (
Profile, Offer, Experience, Education, OfferRequirement,
GapAnalysis, ChatMessage, ChatResponse, CVData, RewrittenExperience,
)
def _sample_profile():
return Profile(
name="Marie Dupont", title="Product Manager", summary="8 years PM",
experiences=[Experience(title="PM", company="X", dates="2022-now", description="Led team", bullets=["Led team"])],
education=[Education(degree="MSc", school="HEC", year="2018")],
skills=["SQL"],
)
def _sample_offer():
return Offer(
title="Senior PM", company="BigTech", description="Looking for PM",
requirements=[OfferRequirement(text="5+ years", category="required")],
)
@patch("app.routers.chat.get_llm")
def test_analyze_endpoint(mock_get_llm):
mock_llm = MagicMock()
mock_get_llm.return_value = mock_llm
mock_llm.analyze.return_value = GapAnalysis(
matched_skills=["SQL"], gaps=["AI"], questions=["Tell me about AI?"]
)
response = client.post("/api/analyze", json={
"profile": _sample_profile().model_dump(),
"offer": _sample_offer().model_dump(),
})
assert response.status_code == 200
data = response.json()
assert "matched_skills" in data
assert "questions" in data
@patch("app.routers.chat.get_llm")
def test_chat_endpoint(mock_get_llm):
mock_llm = MagicMock()
mock_get_llm.return_value = mock_llm
mock_llm.generate_next_question.return_value = ChatResponse(
message="Tell me more about leadership", is_complete=False
)
response = client.post("/api/chat", json={
"profile": _sample_profile().model_dump(),
"offer": _sample_offer().model_dump(),
"gap_analysis": {"matched_skills": ["SQL"], "gaps": ["AI"], "questions": ["AI?"]},
"messages": [],
})
assert response.status_code == 200
assert response.json()["message"] != ""
@patch("app.routers.generate.get_llm")
def test_generate_cv_endpoint(mock_get_llm):
mock_llm = MagicMock()
mock_get_llm.return_value = mock_llm
mock_llm.generate_cv.return_value = CVData(
name="Marie Dupont", title="Senior PM", summary="Expert PM",
experiences=[RewrittenExperience(title="PM", company="X", dates="2022", bullets=["Led team"])],
education=[Education(degree="MSc", school="HEC", year="2018")],
skills=["SQL"],
)
response = client.post("/api/generate-cv", json={
"profile": _sample_profile().model_dump(),
"offer": _sample_offer().model_dump(),
"gap_analysis": {"matched_skills": ["SQL"], "gaps": [], "questions": []},
"messages": [{"role": "user", "content": "I led 12 engineers"}],
})
assert response.status_code == 200
assert response.json()["name"] == "Marie Dupont"
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