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a43ebba | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 | import requests
import time
import subprocess
import os
def start_server():
print("Starting FastAPI server...")
proc = subprocess.Popen(["python", "main.py"], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
# Wait until the server responds or timeout
for _ in range(15):
time.sleep(1)
try:
r = requests.get("http://localhost:7860/health")
if r.status_code == 200:
print("Server started successfully.")
return proc
except requests.exceptions.ConnectionError:
pass
print("Server failed to start in time. stderr output:")
print(proc.stderr.read().decode())
return proc
def test_cgpa_simulator():
url = "http://localhost:7860/predict"
base_data = {
"Age": 22,
"Gender": "Male",
"Stream": "Computer Science",
"Internships": 1,
"Hostel": 1,
"HistoryOfBacklogs": 0,
"skills": ["Python", "Machine Learning"],
"desired_role": "Data Scientist"
}
print("Running CGPA Simulator Test (7.5 to 7.8)")
prev_prob = None
for cgpa in [7.5, 7.6, 7.7, 7.8]:
data = base_data.copy()
data["CGPA"] = cgpa
response = requests.post(url, json=data)
result = response.json()
prob = result["probability_percentage"]
print(f"CGPA: {cgpa} -> Probability: {prob}%")
if prev_prob is not None:
if prob == prev_prob:
print(f"Note: Probability stayed exactly at {prob}% between steps")
prev_prob = prob
print("CGPA Simulator Test completed (checked for general progression).\n")
def test_shap_alignment():
print("Running SHAP Alignment Test")
url_predict = "http://localhost:7860/predict"
url_explain = "http://localhost:7860/explain"
data = {
"Age": 21,
"Gender": "Female",
"Stream": "Information Technology",
"Internships": 3,
"CGPA": 8.5,
"Hostel": 0,
"HistoryOfBacklogs": 0,
"skills": [],
"desired_role": ""
}
# Get Prediction
pred_res = requests.post(url_predict, json=data).json()
print(f"Prediction Probability: {pred_res['probability_percentage']}%")
# Get Explanation
explain_res = requests.post(url_explain, json=data).json()
factors = explain_res["top_contributing_factors"]
# Check if Internships is a positive driver
internships_impact = next((f for f in factors if f["feature"] == "Internships"), None)
if internships_impact:
print(f"Internships Impact: {internships_impact['impact']}")
assert internships_impact["impact"] > 0, "Internships should be a positive driver!"
else:
print("Internships not in top factors, but that's okay. Factors:")
for f in factors:
print(f" {f['feature']}: {f['impact']}")
print("SHAP Alignment Test Passed!\n")
def test_graph_traversal():
print("Running Graph Traversal Test")
from routing_engine import RoutingEngine
engine = RoutingEngine("Tech_Data_Cleaned.csv")
path_info = engine.get_career_transition_path("Backend Developer", "ML Research Scientist")
print(f"Path: {path_info['path']}")
print(f"Skills to learn: {path_info['skills_to_learn']}")
print(f"Stepping stones: {path_info['stepping_stones']}")
assert "Backend Developer" in path_info['path']
assert "ML Research Scientist" in path_info['path']
assert len(path_info['skills_to_learn']) > 0
print("Graph Traversal Test Passed!\n")
if __name__ == "__main__":
proc = start_server()
try:
test_cgpa_simulator()
test_shap_alignment()
test_graph_traversal()
finally:
proc.terminate()
proc.wait()
print("Server stopped.")
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