feat: define text generation metrics api

api/app/db/dao/completion_dataset_metrics_dao.py

@@ -0,0 +1,36 @@
+from typing import Optional
+from uuid import UUID
+
+from app.db.database import Database
+from app.db.tables.completion_dataset_metrics_table import CompletionDatasetMetrics
+from app.db.tables.completion_dataset_table import CompletionDataset
+
+
+class CompletionDatasetMetricsDAO:
+    def __init__(self, database: Database) -> None:
+        self.db = database
+
+    def insert_completion_metrics(
+        self, completion_metrics: CompletionDatasetMetrics
+    ) -> CompletionDatasetMetrics:
+        with self.db.begin_session() as session:
+            session.add(completion_metrics)
+            session.flush()
+            return completion_metrics
+
+    def get_completion_metrics_by_model_uuid(
+        self, model_uuid: UUID, completion_uuid: UUID
+    ) -> Optional[CompletionDatasetMetrics]:
+        with self.db.begin_session() as session:
+            return (
+                session.query(CompletionDatasetMetrics)
+                .join(
+                    CompletionDataset,
+                    CompletionDatasetMetrics.completion_uuid == CompletionDataset.uuid,
+                )
+                .where(
+                    CompletionDataset.model_uuid == model_uuid,
+                    CompletionDataset.uuid == completion_uuid,
+                )
+                .one_or_none()
+            )

api/app/main.py

@@ -11,6 +11,7 @@
 
 from app.core import get_config
 from app.db.dao.completion_dataset_dao import CompletionDatasetDAO
+from app.db.dao.completion_dataset_metrics_dao import CompletionDatasetMetricsDAO
 from app.db.dao.current_dataset_dao import CurrentDatasetDAO
 from app.db.dao.current_dataset_metrics_dao import CurrentDatasetMetricsDAO
 from app.db.dao.model_dao import ModelDAO
@@ -56,6 +57,7 @@
 current_dataset_dao = CurrentDatasetDAO(database)
 current_dataset_metrics_dao = CurrentDatasetMetricsDAO(database)
 completion_dataset_dao = CompletionDatasetDAO(database)
+completion_dataset_metrics_dao = CompletionDatasetMetricsDAO(database)
 
 model_service = ModelService(
     model_dao=model_dao,
@@ -94,6 +96,8 @@
     reference_dataset_dao=reference_dataset_dao,
     current_dataset_metrics_dao=current_dataset_metrics_dao,
     current_dataset_dao=current_dataset_dao,
+    completion_dataset_metrics_dao=completion_dataset_metrics_dao,
+    completion_dataset_dao=completion_dataset_dao,
     model_service=model_service,
 )
 spark_k8s_service = SparkK8SService(spark_k8s_client)

api/app/models/dataset_type.py

@@ -4,3 +4,4 @@
 class DatasetType(str, Enum):
     REFERENCE = 'REFERENCE'
     CURRENT = 'CURRENT'
+    COMPLETION = 'COMPLETION'

api/app/models/metrics/model_quality_dto.py

@@ -192,6 +192,39 @@ class CurrentRegressionModelQuality(BaseModel):
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
 
+class TokenProb(BaseModel):
+    prob: float
+    token: str
+
+
+class TokenData(BaseModel):
+    id: str
+    probs: List[TokenProb]
+
+
+class MeanPerFile(BaseModel):
+    prob_tot_mean: float
+    perplex_tot_mean: float
+
+    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
+
+
+class MeanPerPhrase(BaseModel):
+    id: str
+    prob_per_phrase: float
+    perplex_per_phrase: float
+
+    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
+
+
+class CompletionTextGenerationModelQuality(BaseModel):
+    tokens: List[TokenData]
+    mean_per_file: List[MeanPerFile]
+    mean_per_phrase: List[MeanPerPhrase]
+
+    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
+
+
 class ModelQualityDTO(BaseModel):
     job_status: JobStatus
     model_quality: Optional[
@@ -201,6 +234,7 @@ class ModelQualityDTO(BaseModel):
         | CurrentMultiClassificationModelQuality
         | RegressionModelQuality
         | CurrentRegressionModelQuality
+        | CompletionTextGenerationModelQuality
     ]
 
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
@@ -251,6 +285,10 @@ def _create_model_quality(
             return ModelQualityDTO._create_regression_model_quality(
                 dataset_type=dataset_type, model_quality_data=model_quality_data
             )
+        if model_type == ModelType.TEXT_GENERATION:
+            return ModelQualityDTO._create_text_generation_model_quality(
+                dataset_type=dataset_type, model_quality_data=model_quality_data
+            )
         raise MetricsInternalError(f'Invalid model type {model_type}')
 
     @staticmethod
@@ -288,3 +326,13 @@ def _create_regression_model_quality(
         if dataset_type == DatasetType.CURRENT:
             return CurrentRegressionModelQuality(**model_quality_data)
         raise MetricsInternalError(f'Invalid dataset type {dataset_type}')
+
+    @staticmethod
+    def _create_text_generation_model_quality(
+        dataset_type: DatasetType,
+        model_quality_data: Dict,
+    ) -> CompletionTextGenerationModelQuality:
+        """Create a text generation model quality instance based on dataset type."""
+        if dataset_type == DatasetType.COMPLETION:
+            return CompletionTextGenerationModelQuality(**model_quality_data)
+        raise MetricsInternalError(f'Invalid dataset type {dataset_type}')

api/app/routes/metrics_route.py

@@ -151,4 +151,16 @@ def get_current_percentages_by_model_by_uuid(
                 model_uuid, current_uuid
             )
 
+        @router.get(
+            '/{model_uuid}/completion/{completion_uuid}/model-quality',
+            status_code=200,
+            response_model=ModelQualityDTO,
+        )
+        def get_completion_model_quality_by_model_by_uuid(
+            model_uuid: UUID, completion_uuid: UUID
+        ):
+            return metrics_service.get_completion_model_quality_by_model_by_uuid(
+                model_uuid, completion_uuid
+            )
+
         return router

api/app/services/metrics_service.py

@@ -2,10 +2,14 @@
 from typing import Optional
 from uuid import UUID
 
+from app.db.dao.completion_dataset_dao import CompletionDatasetDAO
+from app.db.dao.completion_dataset_metrics_dao import CompletionDatasetMetricsDAO
 from app.db.dao.current_dataset_dao import CurrentDatasetDAO
 from app.db.dao.current_dataset_metrics_dao import CurrentDatasetMetricsDAO
 from app.db.dao.reference_dataset_dao import ReferenceDatasetDAO
 from app.db.dao.reference_dataset_metrics_dao import ReferenceDatasetMetricsDAO
+from app.db.tables.completion_dataset_metrics_table import CompletionDatasetMetrics
+from app.db.tables.completion_dataset_table import CompletionDataset
 from app.db.tables.current_dataset_metrics_table import CurrentDatasetMetrics
 from app.db.tables.current_dataset_table import CurrentDataset
 from app.db.tables.reference_dataset_metrics_table import ReferenceDatasetMetrics
@@ -29,12 +33,16 @@ def __init__(
         reference_dataset_dao: ReferenceDatasetDAO,
         current_dataset_metrics_dao: CurrentDatasetMetricsDAO,
         current_dataset_dao: CurrentDatasetDAO,
+        completion_dataset_metrics_dao: CompletionDatasetMetricsDAO,
+        completion_dataset_dao: CompletionDatasetDAO,
         model_service: ModelService,
     ):
         self.reference_dataset_metrics_dao = reference_dataset_metrics_dao
         self.reference_dataset_dao = reference_dataset_dao
         self.current_dataset_metrics_dao = current_dataset_metrics_dao
         self.current_dataset_dao = current_dataset_dao
+        self.completion_dataset_metrics_dao = completion_dataset_metrics_dao
+        self.completion_dataset_dao = completion_dataset_dao
         self.model_service = model_service
 
     def get_reference_statistics_by_model_by_uuid(
@@ -83,6 +91,19 @@ def get_current_model_quality_by_model_by_uuid(
             missing_status=JobStatus.MISSING_CURRENT,
         )
 
+    def get_completion_model_quality_by_model_by_uuid(
+        self, model_uuid: UUID, completion_uuid: UUID
+    ) -> ModelQualityDTO:
+        """Retrieve completion model quality for a model by its UUID."""
+        return self._get_model_quality_by_model_uuid(
+            model_uuid=model_uuid,
+            dataset_and_metrics_getter=lambda uuid: self.check_and_get_completion_dataset_and_metrics(
+                uuid, completion_uuid
+            ),
+            dataset_type=DatasetType.COMPLETION,
+            missing_status=JobStatus.MISSING_COMPLETION,
+        )
+
     def get_reference_data_quality_by_model_by_uuid(
         self, model_uuid: UUID
     ) -> DataQualityDTO:
@@ -162,12 +183,28 @@ def check_and_get_current_dataset_and_metrics(
             ),
         )
 
+    def check_and_get_completion_dataset_and_metrics(
+        self, model_uuid: UUID, completion_uuid: UUID
+    ) -> tuple[Optional[CompletionDataset], Optional[CompletionDatasetMetrics]]:
+        """Check and retrieve the completion dataset and its metrics for a model by its UUID."""
+        return self._check_and_get_dataset_and_metrics(
+            model_uuid=model_uuid,
+            dataset_getter=lambda uuid: self.completion_dataset_dao.get_completion_dataset_by_model_uuid(
+                uuid, completion_uuid
+            ),
+            metrics_getter=lambda uuid: self.completion_dataset_metrics_dao.get_completion_metrics_by_model_uuid(
+                uuid, completion_uuid
+            ),
+        )
+
     @staticmethod
     def _check_and_get_dataset_and_metrics(
         model_uuid: UUID, dataset_getter, metrics_getter
     ) -> tuple[
-        Optional[ReferenceDataset | CurrentDataset],
-        Optional[ReferenceDatasetMetrics | CurrentDatasetMetrics],
+        Optional[ReferenceDataset | CurrentDataset | CompletionDataset],
+        Optional[
+            ReferenceDatasetMetrics | CurrentDatasetMetrics | CompletionDatasetMetrics
+        ],
     ]:
         """Check and retrieve the dataset and its metrics using the provided getters."""
         dataset = dataset_getter(model_uuid)
@@ -294,8 +331,10 @@ def _create_statistics_dto(
     def _create_model_quality_dto(
         dataset_type: DatasetType,
         model_type: ModelType,
-        dataset: Optional[ReferenceDataset | CurrentDataset],
-        metrics: Optional[ReferenceDatasetMetrics | CurrentDatasetMetrics],
+        dataset: Optional[ReferenceDataset | CurrentDataset | CompletionDataset],
+        metrics: Optional[
+            ReferenceDatasetMetrics | CurrentDatasetMetrics | CompletionDatasetMetrics
+        ],
         missing_status,
     ) -> ModelQualityDTO:
         """Create a ModelQualityDTO from the provided dataset and metrics."""

api/tests/commons/db_mock.py

@@ -2,6 +2,7 @@
 from typing import Dict, List, Optional
 import uuid
 
+from app.db.tables.completion_dataset_metrics_table import CompletionDatasetMetrics
 from app.db.tables.completion_dataset_table import CompletionDataset
 from app.db.tables.current_dataset_metrics_table import CurrentDatasetMetrics
 from app.db.tables.current_dataset_table import CurrentDataset
@@ -545,6 +546,30 @@ def get_sample_completion_dataset(
     },
 }
 
+model_quality_completion_dict = {
+    'tokens': [
+        {
+            'id': 'chatcmpl',
+            'probs': [
+                {'prob': 0.27718424797058105, 'token': 'Sky'},
+                {'prob': 0.8951022028923035, 'token': ' is'},
+                {'prob': 0.7038467526435852, 'token': ' blue'},
+                {'prob': 0.9999753832817078, 'token': '.'},
+            ],
+        }
+    ],
+    'mean_per_file': [
+        {'prob_tot_mean': 0.7190271615982056, 'perplex_tot_mean': 1.5469378232955933}
+    ],
+    'mean_per_phrase': [
+        {
+            'id': 'chatcmpl',
+            'prob_per_phrase': 0.7190271615982056,
+            'perplex_per_phrase': 1.5469378232955933,
+        }
+    ],
+}
+
 
 def get_sample_reference_metrics(
     reference_uuid: uuid.UUID = REFERENCE_UUID,
@@ -576,3 +601,13 @@ def get_sample_current_metrics(
         drift=drift,
         percentages=percentages,
     )
+
+
+def get_sample_completion_metrics(
+    completion_uuid: uuid.UUID = COMPLETION_UUID,
+    model_quality: Dict = model_quality_completion_dict,
+) -> CompletionDatasetMetrics:
+    return CompletionDatasetMetrics(
+        completion_uuid=completion_uuid,
+        model_quality=model_quality,
+    )

api/tests/dao/completion_dataset_metrics_dao_test.py

@@ -0,0 +1,56 @@
+from app.db.dao.completion_dataset_dao import CompletionDatasetDAO
+from app.db.dao.completion_dataset_metrics_dao import CompletionDatasetMetricsDAO
+from app.db.dao.model_dao import ModelDAO
+from app.models.model_dto import ModelType
+from tests.commons.db_integration import DatabaseIntegration
+from tests.commons.db_mock import (
+    get_sample_completion_dataset,
+    get_sample_completion_metrics,
+    get_sample_model,
+)
+
+
+class CompletionDatasetMetricsDAOTest(DatabaseIntegration):
+    @classmethod
+    def setUpClass(cls):
+        super().setUpClass()
+        cls.model_dao = ModelDAO(cls.db)
+        cls.metrics_dao = CompletionDatasetMetricsDAO(cls.db)
+        cls.f_completion_dataset_dao = CompletionDatasetDAO(cls.db)
+
+    def test_insert_completion_dataset_metrics(self):
+        self.model_dao.insert(
+            get_sample_model(
+                model_type=ModelType.TEXT_GENERATION,
+                features=None,
+                target=None,
+                outputs=None,
+                timestamp=None,
+            )
+        )
+        completion_upload = get_sample_completion_dataset()
+        self.f_completion_dataset_dao.insert_completion_dataset(completion_upload)
+        completion_metrics = get_sample_completion_metrics(
+            completion_uuid=completion_upload.uuid
+        )
+        inserted = self.metrics_dao.insert_completion_metrics(completion_metrics)
+        assert inserted == completion_metrics
+
+    def test_get_completion_metrics_by_model_uuid(self):
+        self.model_dao.insert(
+            get_sample_model(
+                model_type=ModelType.TEXT_GENERATION,
+                features=None,
+                target=None,
+                outputs=None,
+                timestamp=None,
+            )
+        )
+        completion = get_sample_completion_dataset()
+        self.f_completion_dataset_dao.insert_completion_dataset(completion)
+        metrics = get_sample_completion_metrics()
+        self.metrics_dao.insert_completion_metrics(metrics)
+        retrieved = self.metrics_dao.get_completion_metrics_by_model_uuid(
+            model_uuid=completion.model_uuid, completion_uuid=completion.uuid
+        )
+        assert retrieved.uuid == metrics.uuid

api/tests/routes/metrics_route_test.py

@@ -200,3 +200,26 @@ def test_get_current_data_quality_by_model_by_uuid(self):
         self.metrics_service.get_current_data_quality_by_model_by_uuid.assert_called_once_with(
             model_uuid, current_uuid
         )
+
+    def test_get_completion_model_quality_by_model_by_uuid(self):
+        model_uuid = uuid.uuid4()
+        completion_uuid = uuid.uuid4()
+        completion_metrics = db_mock.get_sample_completion_metrics()
+        model_quality = ModelQualityDTO.from_dict(
+            dataset_type=DatasetType.COMPLETION,
+            model_type=ModelType.TEXT_GENERATION,
+            job_status=JobStatus.SUCCEEDED,
+            model_quality_data=completion_metrics.model_quality,
+        )
+        self.metrics_service.get_completion_model_quality_by_model_by_uuid = MagicMock(
+            return_value=model_quality
+        )
+
+        res = self.client.get(
+            f'{self.prefix}/{model_uuid}/completion/{completion_uuid}/model-quality'
+        )
+        assert res.status_code == 200
+        assert jsonable_encoder(model_quality) == res.json()
+        self.metrics_service.get_completion_model_quality_by_model_by_uuid.assert_called_once_with(
+            model_uuid, completion_uuid
+        )