tests/test_monitoring.py

import json
import tempfile
import unittest
from pathlib import Path
from unittest.mock import patch

import numpy as np
import cv2
from fastapi.testclient import TestClient

from app import main
from monitoring import feedback as feedback_mod
from monitoring import metrics as metrics_mod


class TestFeedbackRecording(unittest.TestCase):
    def setUp(self):
        self._tmpdir = tempfile.TemporaryDirectory()
        self.tmp_path = Path(self._tmpdir.name)
        self.feedback_path = self.tmp_path / "feedback.jsonl"

    def tearDown(self):
        self._tmpdir.cleanup()

    def test_record_feedback_appends_entry(self):
        entry = feedback_mod.record_feedback(
            "abc.jpg", {"prix": 10000, "volume": 14.28},
            corrected_by="pompiste-7", feedback_path=self.feedback_path,
        )
        self.assertEqual(entry["photo_reference"], "abc.jpg")
        self.assertFalse(entry["converted"])

        entries = feedback_mod.load_feedback_entries(self.feedback_path)
        self.assertEqual(len(entries), 1)
        self.assertEqual(entries[0]["corrected_fields"]["prix"], 10000)

    def test_record_feedback_rejects_unknown_field(self):
        with self.assertRaises(ValueError):
            feedback_mod.record_feedback(
                "abc.jpg", {"montant_total": 10000}, feedback_path=self.feedback_path,
            )

    def test_record_feedback_rejects_empty_corrections(self):
        with self.assertRaises(ValueError):
            feedback_mod.record_feedback("abc.jpg", {}, feedback_path=self.feedback_path)

    def test_load_feedback_entries_missing_file_returns_empty(self):
        entries = feedback_mod.load_feedback_entries(self.tmp_path / "nope.jsonl")
        self.assertEqual(entries, [])


class TestFeedbackConversion(unittest.TestCase):
    def setUp(self):
        self._tmpdir = tempfile.TemporaryDirectory()
        self.tmp_path = Path(self._tmpdir.name)
        self.photos_dir = self.tmp_path / "photos"
        self.photos_dir.mkdir()
        self.feedback_path = self.tmp_path / "feedback.jsonl"
        self.annotations_path = self.tmp_path / "annotations.json"
        self.crops_dir = self.tmp_path / "crops"

        img = np.full((200, 400, 3), 30, dtype=np.uint8)
        cv2.imwrite(str(self.photos_dir / "photo1.jpg"), img)

    def tearDown(self):
        self._tmpdir.cleanup()

    def test_convert_creates_pending_review_annotation(self):
        feedback_mod.record_feedback(
            "photo1.jpg", {"prix": 10000, "volume": 14.28, "prix_litre": 700},
            corrected_by="pompiste-7", feedback_path=self.feedback_path,
        )

        count = feedback_mod.convert_feedback_to_annotations(
            photos_dir=self.photos_dir, feedback_path=self.feedback_path,
            annotations_path=self.annotations_path, crops_dir=self.crops_dir,
        )
        self.assertEqual(count, 1)

        with open(self.annotations_path, "r", encoding="utf-8") as f:
            annotations = json.load(f)
        self.assertIn("photo1.jpg", annotations)
        entry = annotations["photo1.jpg"]
        self.assertEqual(entry["status"], "pending_review")
        self.assertEqual(entry["fields"]["prix"], "10000")
        self.assertEqual(entry["fields"]["volume"], "14.28")

        entries = feedback_mod.load_feedback_entries(self.feedback_path)
        self.assertTrue(entries[0]["converted"])

    def test_convert_is_idempotent_for_already_converted_entries(self):
        feedback_mod.record_feedback(
            "photo1.jpg", {"prix": 10000}, feedback_path=self.feedback_path,
        )
        feedback_mod.convert_feedback_to_annotations(
            photos_dir=self.photos_dir, feedback_path=self.feedback_path,
            annotations_path=self.annotations_path, crops_dir=self.crops_dir,
        )
        second_count = feedback_mod.convert_feedback_to_annotations(
            photos_dir=self.photos_dir, feedback_path=self.feedback_path,
            annotations_path=self.annotations_path, crops_dir=self.crops_dir,
        )
        self.assertEqual(second_count, 0)

    def test_convert_skips_missing_photo(self):
        feedback_mod.record_feedback(
            "ghost.jpg", {"prix": 10000}, feedback_path=self.feedback_path,
        )
        count = feedback_mod.convert_feedback_to_annotations(
            photos_dir=self.photos_dir, feedback_path=self.feedback_path,
            annotations_path=self.annotations_path, crops_dir=self.crops_dir,
        )
        self.assertEqual(count, 0)


class TestMetrics(unittest.TestCase):
    def setUp(self):
        self._tmpdir = tempfile.TemporaryDirectory()
        self.log_path = Path(self._tmpdir.name) / "api.log"

    def tearDown(self):
        self._tmpdir.cleanup()

    def _write_log_line(self, payload):
        with open(self.log_path, "a", encoding="utf-8") as f:
            f.write(f"2026-07-07 10:00:00,000 | INFO | {json.dumps(payload, ensure_ascii=False)}\n")

    def test_compute_metrics_on_missing_log_returns_zero(self):
        m = metrics_mod.compute_metrics(self.log_path)
        self.assertEqual(m["total_requests"], 0)
        self.assertIsNone(m["success_rate"])

    def test_compute_metrics_aggregates_success_and_blocking(self):
        self._write_log_line({
            "model_version": "v2",
            "response": {"success": True, "confidence_score": 0.9, "image_quality": "valid", "message": "ok"},
        })
        self._write_log_line({
            "model_version": "v2",
            "response": {"success": False, "confidence_score": 0.2, "image_quality": "blurry", "message": "Photo floue, veuillez reprendre la photo."},
        })
        with open(self.log_path, "a", encoding="utf-8") as f:
            f.write("2026-07-07 10:00:01,000 | INFO | Modèle CRNN chargé sur cpu.\n")

        m = metrics_mod.compute_metrics(self.log_path)
        self.assertEqual(m["total_requests"], 2)
        self.assertEqual(m["success_rate"], 0.5)
        self.assertAlmostEqual(m["avg_confidence_score"], 0.55)
        self.assertEqual(m["blocking_causes"]["Photo floue, veuillez reprendre la photo."], 1)
        self.assertEqual(m["image_quality_distribution"]["valid"], 1)

    def test_list_failed_requests_returns_only_failures_most_recent_first(self):
        self._write_log_line({
            "response": {"success": True, "photo_reference": "ok.jpg", "message": "ok"},
        })
        self._write_log_line({
            "response": {"success": False, "photo_reference": "first-fail.jpg",
                        "message": "Photo floue, veuillez reprendre la photo.",
                        "image_quality": "blurry", "confidence_score": 0.1},
        })
        self._write_log_line({
            "response": {"success": False, "photo_reference": "second-fail.jpg",
                        "message": "Incohérence détectée entre montant, litres et prix.",
                        "image_quality": "valid", "confidence_score": 0.4},
        })

        failures = metrics_mod.list_failed_requests(self.log_path)
        self.assertEqual(len(failures), 2)
        self.assertEqual(failures[0]["photo_reference"], "second-fail.jpg")
        self.assertEqual(failures[1]["photo_reference"], "first-fail.jpg")
        self.assertNotIn("filename", failures[0])

    def test_list_failed_requests_respects_limit(self):
        for i in range(5):
            self._write_log_line({
                "response": {"success": False, "photo_reference": f"fail{i}.jpg", "message": "x"},
            })
        failures = metrics_mod.list_failed_requests(self.log_path, limit=2)
        self.assertEqual(len(failures), 2)


class TestFeedbackAndMetricsEndpoints(unittest.TestCase):
    def setUp(self):
        self.client = TestClient(main.app)
        self._tmpdir = tempfile.TemporaryDirectory()
        self.fake_photos_dir = Path(self._tmpdir.name)
        (self.fake_photos_dir / "photo.jpg").write_bytes(b"fake")
        self._patch_photos_dir = patch.object(main, "PHOTOS_DIR", self.fake_photos_dir)
        self._patch_photos_dir.start()

    def tearDown(self):
        self._patch_photos_dir.stop()
        self._tmpdir.cleanup()

    def test_feedback_rejects_unknown_photo_reference(self):
        resp = self.client.post(
            "/feedback",
            data={"photo_reference": "does-not-exist.jpg", "corrected_prix": "10000"},
        )
        self.assertEqual(resp.status_code, 404)

    def test_feedback_rejects_no_corrections(self):
        resp = self.client.post("/feedback", data={"photo_reference": "photo.jpg"})
        self.assertEqual(resp.status_code, 400)

    def test_feedback_success_records_entry(self):
        fake_entry = {"feedback_id": "fake-id"}
        with patch.object(main, "record_feedback", return_value=fake_entry) as mock_record:
            resp = self.client.post(
                "/feedback",
                data={"photo_reference": "photo.jpg", "corrected_prix": "10000", "corrected_by": "pompiste-7"},
            )
        self.assertEqual(resp.status_code, 200)
        body = resp.json()
        self.assertTrue(body["success"])
        self.assertEqual(body["feedback_id"], "fake-id")
        mock_record.assert_called_once()
        args, kwargs = mock_record.call_args
        self.assertEqual(args[0], "photo.jpg")
        self.assertEqual(args[1], {"prix": 10000.0})

    def test_metrics_endpoint_returns_aggregate(self):
        fake_metrics = {"total_requests": 0, "success_rate": None,
                        "avg_confidence_score": None, "blocking_causes": {},
                        "image_quality_distribution": {}}
        with patch.object(main, "compute_metrics", return_value=fake_metrics):
            resp = self.client.get("/metrics")
        self.assertEqual(resp.status_code, 200)
        self.assertEqual(resp.json(), fake_metrics)

    def test_failures_endpoint_returns_list(self):
        fake_failures = [{"photo_reference": "photo.jpg", "message": "Photo floue."}]
        with patch.object(main, "list_failed_requests", return_value=fake_failures):
            resp = self.client.get("/failures")
        self.assertEqual(resp.status_code, 200)
        self.assertEqual(resp.json(), fake_failures)

    def test_get_photo_returns_file(self):
        resp = self.client.get("/photos/photo.jpg")
        self.assertEqual(resp.status_code, 200)
        self.assertEqual(resp.content, b"fake")

    def test_get_photo_unknown_reference_returns_404(self):
        resp = self.client.get("/photos/does-not-exist.jpg")
        self.assertEqual(resp.status_code, 404)

    def test_get_photo_rejects_path_traversal(self):
        outside_file = Path(self._tmpdir.name).parent / "secret.txt"
        outside_file.write_text("should not be servable")
        try:
            resp = self.client.get("/photos/..%2Fsecret.txt")
            self.assertEqual(resp.status_code, 404)
        finally:
            outside_file.unlink(missing_ok=True)


if __name__ == "__main__":
    unittest.main()