Merge branch 'main' into ODSC-66822/allow_cache_delete

Author: VipulMascarenhas

.github/workflows/run-forecast-unit-tests.yml

@@ -56,6 +56,6 @@ jobs:
           $CONDA/bin/conda init
           source /home/runner/.bashrc
           pip install -r test-requirements-operators.txt
-          pip install "oracle-automlx[forecasting]>=24.4.0"
+          pip install "oracle-automlx[forecasting]>=24.4.1"
           pip install pandas>=2.2.0
           python -m pytest -v -p no:warnings --durations=5 tests/operators/forecast

ads/aqua/common/enums.py

@@ -52,6 +52,9 @@ class InferenceContainerTypeFamily(str, metaclass=ExtendedEnumMeta):
     AQUA_VLLM_CONTAINER_FAMILY = "odsc-vllm-serving"
     AQUA_TGI_CONTAINER_FAMILY = "odsc-tgi-serving"
     AQUA_LLAMA_CPP_CONTAINER_FAMILY = "odsc-llama-cpp-serving"
+
+
+class CustomInferenceContainerTypeFamily(str, metaclass=ExtendedEnumMeta):
     AQUA_TEI_CONTAINER_FAMILY = "odsc-tei-serving"
 
 

ads/aqua/extension/model_handler.py

@@ -8,6 +8,9 @@
 from tornado.web import HTTPError
 
 from ads.aqua.common.decorator import handle_exceptions
+from ads.aqua.common.enums import (
+    CustomInferenceContainerTypeFamily,
+)
 from ads.aqua.common.errors import AquaRuntimeError, AquaValueError
 from ads.aqua.common.utils import (
     get_hf_model_info,
@@ -169,7 +172,9 @@ def put(self, id):
             raise HTTPError(400, Errors.NO_INPUT_DATA)
 
         inference_container = input_data.get("inference_container")
+        inference_container_uri = input_data.get("inference_container_uri")
         inference_containers = AquaModelApp.list_valid_inference_containers()
+        inference_containers.extend(CustomInferenceContainerTypeFamily.values())
         if (
             inference_container is not None
             and inference_container not in inference_containers
@@ -182,7 +187,13 @@ def put(self, id):
         task = input_data.get("task")
         app = AquaModelApp()
         self.finish(
-            app.edit_registered_model(id, inference_container, enable_finetuning, task)
+            app.edit_registered_model(
+                id,
+                inference_container,
+                inference_container_uri,
+                enable_finetuning,
+                task,
+            )
         )
         app.clear_model_details_cache(model_id=id)
 

ads/aqua/model/model.py

@@ -15,6 +15,7 @@
 from ads.aqua import ODSC_MODEL_COMPARTMENT_OCID, logger
 from ads.aqua.app import AquaApp
 from ads.aqua.common.enums import (
+    CustomInferenceContainerTypeFamily,
     FineTuningContainerTypeFamily,
     InferenceContainerTypeFamily,
     Tags,
@@ -377,8 +378,10 @@ def delete_model(self, model_id):
                 f"Failed to delete model:{model_id}. Only registered models or finetuned model can be deleted."
             )
 
-    @telemetry(entry_point="plugin=model&action=delete", name="aqua")
-    def edit_registered_model(self, id, inference_container, enable_finetuning, task):
+    @telemetry(entry_point="plugin=model&action=edit", name="aqua")
+    def edit_registered_model(
+        self, id, inference_container, inference_container_uri, enable_finetuning, task
+    ):
         """Edits the default config of unverified registered model.
 
         Parameters
@@ -387,6 +390,8 @@ def edit_registered_model(self, id, inference_container, enable_finetuning, task
             The model OCID.
         inference_container: str.
             The inference container family name
+        inference_container_uri: str
+            The inference container uri for embedding models
         enable_finetuning: str
             Flag to enable or disable finetuning over the model. Defaults to None
         task:
@@ -402,19 +407,44 @@ def edit_registered_model(self, id, inference_container, enable_finetuning, task
         if ds_model.freeform_tags.get(Tags.BASE_MODEL_CUSTOM, None):
             if ds_model.freeform_tags.get(Tags.AQUA_SERVICE_MODEL_TAG, None):
                 raise AquaRuntimeError(
-                    f"Failed to edit model:{id}. Only registered unverified models can be edited."
+                    "Only registered unverified models can be edited."
                 )
             else:
                 custom_metadata_list = ds_model.custom_metadata_list
                 freeform_tags = ds_model.freeform_tags
                 if inference_container:
-                    custom_metadata_list.add(
-                        key=ModelCustomMetadataFields.DEPLOYMENT_CONTAINER,
-                        value=inference_container,
-                        category=MetadataCustomCategory.OTHER,
-                        description="Deployment container mapping for SMC",
-                        replace=True,
-                    )
+                    if (
+                        inference_container in CustomInferenceContainerTypeFamily
+                        and inference_container_uri is None
+                    ):
+                        raise AquaRuntimeError(
+                            "Inference container URI must be provided."
+                        )
+                    else:
+                        custom_metadata_list.add(
+                            key=ModelCustomMetadataFields.DEPLOYMENT_CONTAINER,
+                            value=inference_container,
+                            category=MetadataCustomCategory.OTHER,
+                            description="Deployment container mapping for SMC",
+                            replace=True,
+                        )
+                if inference_container_uri:
+                    if (
+                        inference_container in CustomInferenceContainerTypeFamily
+                        or inference_container is None
+                    ):
+                        custom_metadata_list.add(
+                            key=ModelCustomMetadataFields.DEPLOYMENT_CONTAINER_URI,
+                            value=inference_container_uri,
+                            category=MetadataCustomCategory.OTHER,
+                            description=f"Inference container URI for {ds_model.display_name}",
+                            replace=True,
+                        )
+                    else:
+                        raise AquaRuntimeError(
+                            f"Inference container URI can be edited only with container values: {CustomInferenceContainerTypeFamily.values()}"
+                        )
+
                 if enable_finetuning is not None:
                     if enable_finetuning.lower() == "true":
                         custom_metadata_list.add(
@@ -449,9 +479,7 @@ def edit_registered_model(self, id, inference_container, enable_finetuning, task
                 )
                 AquaApp().update_model(id, update_model_details)
         else:
-            raise AquaRuntimeError(
-                f"Failed to edit model:{id}. Only registered unverified models can be edited."
-            )
+            raise AquaRuntimeError("Only registered unverified models can be edited.")
 
     def _fetch_metric_from_metadata(
         self,
@@ -870,8 +898,7 @@ def _create_model_catalog_entry(
             # only add cmd vars if inference container is not an SMC
             if (
                 inference_container not in smc_container_set
-                and inference_container
-                == InferenceContainerTypeFamily.AQUA_TEI_CONTAINER_FAMILY
+                and inference_container in CustomInferenceContainerTypeFamily.values()
             ):
                 cmd_vars = generate_tei_cmd_var(os_path)
                 metadata.add(

ads/model/__init__.py

@@ -1,29 +1,26 @@
 #!/usr/bin/env python
-# -*- coding: utf-8 -*--
 
-# Copyright (c) 2021, 2023 Oracle and/or its affiliates.
+# Copyright (c) 2021, 2025 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
-from ads.model.generic_model import GenericModel, ModelState
 from ads.model.datascience_model import DataScienceModel
-from ads.model.model_properties import ModelProperties
+from ads.model.deployment.model_deployer import ModelDeployer
+from ads.model.deployment.model_deployment import ModelDeployment
+from ads.model.deployment.model_deployment_properties import ModelDeploymentProperties
 from ads.model.framework.automl_model import AutoMLModel
+from ads.model.framework.embedding_onnx_model import EmbeddingONNXModel
+from ads.model.framework.huggingface_model import HuggingFacePipelineModel
 from ads.model.framework.lightgbm_model import LightGBMModel
 from ads.model.framework.pytorch_model import PyTorchModel
 from ads.model.framework.sklearn_model import SklearnModel
+from ads.model.framework.spark_model import SparkPipelineModel
 from ads.model.framework.tensorflow_model import TensorFlowModel
 from ads.model.framework.xgboost_model import XGBoostModel
-from ads.model.framework.spark_model import SparkPipelineModel
-from ads.model.framework.huggingface_model import HuggingFacePipelineModel
-
-from ads.model.deployment.model_deployer import ModelDeployer
-from ads.model.deployment.model_deployment import ModelDeployment
-from ads.model.deployment.model_deployment_properties import ModelDeploymentProperties
-
+from ads.model.generic_model import GenericModel, ModelState
+from ads.model.model_properties import ModelProperties
+from ads.model.model_version_set import ModelVersionSet, experiment
 from ads.model.serde.common import SERDE
 from ads.model.serde.model_input import ModelInputSerializer
-
-from ads.model.model_version_set import ModelVersionSet, experiment
 from ads.model.service.oci_datascience_model_version_set import (
     ModelVersionSetNotExists,
     ModelVersionSetNotSaved,
@@ -42,6 +39,7 @@
     "XGBoostModel",
     "SparkPipelineModel",
     "HuggingFacePipelineModel",
+    "EmbeddingONNXModel",
     "ModelDeployer",
     "ModelDeployment",
     "ModelDeploymentProperties",

ads/model/artifact.py

@@ -1,28 +1,28 @@
 #!/usr/bin/env python
-# -*- coding: utf-8 -*--
 
-# Copyright (c) 2022, 2023 Oracle and/or its affiliates.
+# Copyright (c) 2022, 2025 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
 import fnmatch
 import importlib
 import os
-import sys
 import shutil
+import sys
 import tempfile
 import uuid
-import fsspec
+from datetime import datetime
 from typing import Dict, Optional, Tuple
+
+import fsspec
+from jinja2 import Environment, PackageLoader
+
+from ads import __version__
 from ads.common import auth as authutil
 from ads.common import logger, utils
 from ads.common.object_storage_details import ObjectStorageDetails
 from ads.config import CONDA_BUCKET_NAME, CONDA_BUCKET_NS
 from ads.model.runtime.env_info import EnvInfo, InferenceEnvInfo, TrainingEnvInfo
 from ads.model.runtime.runtime_info import RuntimeInfo
-from jinja2 import Environment, PackageLoader
-import warnings
-from ads import __version__
-from datetime import datetime
 
 MODEL_ARTIFACT_VERSION = "3.0"
 REQUIRED_ARTIFACT_FILES = ("runtime.yaml", "score.py")
@@ -378,6 +378,45 @@ def prepare_score_py(
         ) as f:
             f.write(scorefn_template.render(context))
 
+    def prepare_schema(self, schema_name: str):
+        """Copies schema to artifact directory.
+
+        Parameters
+        ----------
+        schema_name: str
+            The schema name
+
+        Returns
+        -------
+        None
+
+        Raises
+        ------
+        FileExistsError
+            If `schema_name` doesn't exist.
+        """
+        uri_src = os.path.join(
+            os.path.abspath(os.path.join(os.path.dirname(__file__), "..")),
+            "templates",
+            "schemas",
+            f"{schema_name}",
+        )
+
+        if not os.path.exists(uri_src):
+            raise FileExistsError(
+                f"{schema_name} does not exists. "
+                "Ensure the schema name is valid or specify a different one."
+            )
+
+        uri_dst = os.path.join(self.artifact_dir, os.path.basename(uri_src))
+
+        utils.copy_file(
+            uri_src=uri_src,
+            uri_dst=uri_dst,
+            force_overwrite=True,
+            auth=self.auth,
+        )
+
     def reload(self):
         """Syncs the `score.py` to reload the model and predict function.
 

ads/model/extractor/embedding_onnx_extractor.py

@@ -0,0 +1,80 @@
+#!/usr/bin/env python
+
+# Copyright (c) 2025 Oracle and/or its affiliates.
+# Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
+
+from ads.common.decorator.runtime_dependency import (
+    OptionalDependency,
+    runtime_dependency,
+)
+from ads.model.extractor.model_info_extractor import ModelInfoExtractor
+from ads.model.model_metadata import Framework
+
+
+class EmbeddingONNXExtractor(ModelInfoExtractor):
+    """Class that extract model metadata from EmbeddingONNXModel models.
+
+    Attributes
+    ----------
+    model: object
+        The model to extract metadata from.
+
+    Methods
+    -------
+    framework(self) -> str
+        Returns the framework of the model.
+    algorithm(self) -> object
+        Returns the algorithm of the model.
+    version(self) -> str
+        Returns the version of framework of the model.
+    hyperparameter(self) -> dict
+        Returns the hyperparameter of the model.
+    """
+
+    def __init__(self, model=None):
+        self.model = model
+
+    @property
+    def framework(self):
+        """Extracts the framework of the model.
+
+        Returns
+        ----------
+        str:
+           The framework of the model.
+        """
+        return Framework.EMBEDDING_ONNX
+
+    @property
+    def algorithm(self):
+        """Extracts the algorithm of the model.
+
+        Returns
+        ----------
+        object:
+           The algorithm of the model.
+        """
+        return "Embedding_ONNX"
+
+    @property
+    @runtime_dependency(module="onnxruntime", install_from=OptionalDependency.ONNX)
+    def version(self):
+        """Extracts the framework version of the model.
+
+        Returns
+        ----------
+        str:
+           The framework version of the model.
+        """
+        return onnxruntime.__version__
+
+    @property
+    def hyperparameter(self):
+        """Extracts the hyperparameters of the model.
+
+        Returns
+        ----------
+        dict:
+           The hyperparameters of the model.
+        """
+        return None