| import io |
| import unittest |
| from fastapi.testclient import TestClient |
| from PIL import Image |
|
|
| from backend.main import app |
| from backend.knowledge_base import DISEASE_KNOWLEDGE_BASE |
|
|
|
|
| class TestCropAIGeminiBackend(unittest.TestCase): |
| @classmethod |
| def setUpClass(cls): |
| cls.client = TestClient(app) |
|
|
| def test_health_check(self): |
| """Verify health endpoint returns status healthy, Gemini engine info, and headers.""" |
| response = self.client.get("/health") |
| self.assertEqual(response.status_code, 200) |
| data = response.json() |
| self.assertEqual(data["status"], "healthy") |
| self.assertIn("ai_engine", data) |
| self.assertTrue(data["gemini_active"]) |
| self.assertGreater(data["knowledge_base_entries"], 0) |
| self.assertIn("x-request-id", response.headers) |
| self.assertIn("x-process-time-ms", response.headers) |
|
|
| def test_model_info_endpoint(self): |
| """Verify /api/v1/model-info returns Google Gemini metadata.""" |
| response = self.client.get("/api/v1/model-info") |
| self.assertEqual(response.status_code, 200) |
| data = response.json() |
| self.assertEqual(data["ai_model"], "Google Gemini 3.8 Flash") |
| self.assertEqual(data["primary_model"], "gemini-3.8-flash") |
| self.assertIn("Universal", data["supported_crops"]) |
|
|
| def test_api_status(self): |
| """Verify status endpoint returns online status and environment.""" |
| response = self.client.get("/api/v1/status") |
| self.assertEqual(response.status_code, 200) |
| self.assertEqual(response.json()["status"], "online") |
| self.assertTrue(response.json()["gemini_active"]) |
|
|
| def test_get_supported_crops(self): |
| """Verify supported crops list contains Tomato, Potato, Apple, Rice, etc.""" |
| response = self.client.get("/api/v1/crops") |
| self.assertEqual(response.status_code, 200) |
| data = response.json() |
| self.assertGreaterEqual(data["total_crops"], 5) |
| self.assertGreaterEqual(data["total_classes"], 15) |
| crop_names = [c["crop_name"] for c in data["crops"]] |
| self.assertIn("Tomato", crop_names) |
| self.assertIn("Rice (Paddy)", crop_names) |
|
|
| def test_get_disease_details(self): |
| """Verify fetching details for a specific disease class.""" |
| response = self.client.get("/api/v1/diseases/Tomato___Early_blight") |
| self.assertEqual(response.status_code, 200) |
| data = response.json() |
| self.assertEqual(data["name"], "Tomato Early Blight") |
| self.assertEqual(data["crop"], "Tomato") |
| self.assertGreater(len(data["symptoms"]), 0) |
| self.assertGreater(len(data["treatment"]["immediate_action"]), 0) |
|
|
| def test_expert_ticket_lifecycle(self): |
| """Test creating and retrieving expert consultation tickets.""" |
| payload = { |
| "farmer_name": "Ramesh Patel", |
| "phone_number": "+919876543210", |
| "location": "Nashik, Maharashtra", |
| "crop": "Tomato", |
| "disease_suspected": "Late Blight", |
| "notes": "Leaves showing brown oily spots after 2 days of rain." |
| } |
| create_resp = self.client.post("/api/v1/expert-tickets", json=payload) |
| self.assertEqual(create_resp.status_code, 200) |
| data = create_resp.json() |
| self.assertTrue(data["ticket_id"].startswith("TICK-")) |
| self.assertEqual(data["status"], "PENDING_REVIEW") |
| self.assertIn("Ramesh Patel", data["message"]) |
|
|
| |
| list_resp = self.client.get("/api/v1/expert-tickets?limit=5") |
| self.assertEqual(list_resp.status_code, 200) |
| list_data = list_resp.json() |
| self.assertGreaterEqual(list_data["total_returned"], 1) |
|
|
| def test_invalid_image_upload(self): |
| """Test rejection of non-image files.""" |
| response = self.client.post( |
| "/api/v1/analyze", |
| files={"file": ("notes.txt", b"not an image", "text/plain")} |
| ) |
| self.assertEqual(response.status_code, 400) |
|
|
| def test_integrated_datasets_endpoint(self): |
| """Verify /api/v1/datasets/platforms returns multi-platform Hugging Face & Indian dataset metadata.""" |
| response = self.client.get("/api/v1/datasets/platforms") |
| self.assertEqual(response.status_code, 200) |
| data = response.json() |
| self.assertEqual(data["status"], "synchronized") |
| self.assertGreaterEqual(data["total_datasets"], 14) |
| self.assertGreaterEqual(data["total_image_samples"], 338000) |
| self.assertIn("Hugging Face Hub", data["platforms_supported"]) |
| self.assertIn("IP102 Insect Recognition Benchmark", data["platforms_supported"]) |
| self.assertIn("DeepWeeds Agricultural Herbicide Benchmark", data["platforms_supported"]) |
|
|
|
|
| if __name__ == "__main__": |
| unittest.main() |
|
|
