Added class DataScienceModelCollection that extends from DataScienceModel

Author: YashPandit4u

ads/model/model_collection.py

@@ -0,0 +1,280 @@
+import json
+import ads.common
+import oci
+import os
+import ads
+from ads.model.datascience_model import DataScienceModel
+from typing import List, Optional
+import logging
+
+logger = logging.getLogger("ads.model_description")
+logger.setLevel(logging.INFO)
+
+
+class DataScienceModelCollection(DataScienceModel):
+    
+    def _auth(self):
+        """
+        Internal method that authenticates the model description instance by initializing OCI clients.
+
+        Parameters:
+        - None
+
+        Returns:
+        - None
+
+        Note:
+        - This method retrieves authentication data using default signer from the `ads.common.auth` module.
+        - The region information is extracted from the authentication data.
+        """
+        authData = ads.common.auth.default_signer()
+        signer = authData["signer"]
+        self.region = authData["config"]["region"]
+
+        # data science client
+        self.data_science_client = oci.data_science.DataScienceClient(
+            {"region": self.region}, signer=signer
+        )
+        # oss client
+        self.object_storage_client = oci.object_storage.ObjectStorageClient(
+            {"region": self.region}, signer=signer
+        )
+
+    def __init__(self, spec: ads.Dict = None, **kwargs) -> None:
+        super().__init__(spec, **kwargs)
+     
+        self.empty_json = {
+            "version": "1.0",
+            "type": "modelOSSReferenceDescription",
+            "models": [],
+        }
+        self.region = ""
+        self._auth()
+
+        self.set_spec(self.CONST_MODEL_FILE_DESCRIPTION, self.empty_json)
+
+    def with_ref_model_id(self, model_ocid: str):
+
+        # if model given then get that as the starting reference point
+        logger.info("Getting model details from backend")
+        try:
+            get_model_artifact_content_response = (
+                self.data_science_client.get_model_artifact_content(
+                    model_id=model_ocid,
+                )
+            )
+            content = get_model_artifact_content_response.data.content
+            self.set_spec(self.CONST_MODEL_FILE_DESCRIPTION, json.loads(content))
+        except json.JSONDecodeError as e:
+            logger.error(f"Error decoding JSON: {e}")
+            raise e
+        except Exception as e:
+            logger.error(f"An unexpected error occurred: {e}")
+            raise e
+        return self
+    
+    def add(self, namespace: str, bucket: str, prefix: Optional[str] =None, files: Optional[List[str]] =None):
+        """
+        Adds information about objects in a specified bucket to the model description JSON.
+
+        Parameters:
+        - namespace (str): The namespace of the object storage.
+        - bucket (str): The name of the bucket containing the objects.
+        - prefix (str, optional): The prefix used to filter objects within the bucket. Defaults to None.
+        - files (list of str, optional): A list of file names to include in the model description.
+        If provided, only objects with matching file names will be included. Defaults to None.
+
+        Returns:
+        - None
+
+        Raises:
+        - ValueError: If no files are found to add to the model description.
+
+        Note:
+        - If `files` is not provided, it retrieves information about all objects in the bucket.
+        If `files` is provided, it only retrieves information about objects with matching file names.
+        - If no objects are found to add to the model description, a ValueError is raised.
+        """
+
+        # Remove if the model already exists
+        self.remove(namespace, bucket, prefix)
+
+        def check_if_file_exists(fileName):
+            isExists = False
+            try:
+                headResponse = self.object_storage_client.head_object(
+                    namespace, bucket, object_name=fileName
+                )
+                if headResponse.status == 200:
+                    isExists = True
+            except Exception as e:
+                if hasattr(e, "status") and e.status == 404:
+                    logger.error(f"File not found in bucket: {fileName}")
+                else:
+                    logger.error(f"An error occured: {e}")
+            return isExists
+
+        # Function to un-paginate the api call with while loop
+        def list_obj_versions_unpaginated():
+            objectStorageList = []
+            has_next_page, opc_next_page = True, None
+            while has_next_page:
+                response = self.object_storage_client.list_object_versions(
+                    namespace_name=namespace,
+                    bucket_name=bucket,
+                    prefix=prefix,
+                    fields="name,size",
+                    page=opc_next_page,
+                )
+                objectStorageList.extend(response.data.items)
+                has_next_page = response.has_next_page
+                opc_next_page = response.next_page
+            return objectStorageList
+
+        # Fetch object details and put it into the objects variable
+        objectStorageList = []
+        if files == None:
+            objectStorageList = list_obj_versions_unpaginated()
+        else:
+            for fileName in files:
+                if check_if_file_exists(fileName=fileName):
+                    objectStorageList.append(
+                        self.object_storage_client.list_object_versions(
+                            namespace_name=namespace,
+                            bucket_name=bucket,
+                            prefix=fileName,
+                            fields="name,size",
+                        ).data.items[0]
+                    )
+
+        objects = [
+            {"name": obj.name, "version": obj.version_id, "sizeInBytes": obj.size}
+            for obj in objectStorageList
+            if obj.size > 0
+        ]
+
+        if len(objects) == 0:
+            error_message = (
+                f"No files to add in the bucket: {bucket} with namespace: {namespace} "
+                f"and prefix: {prefix}. File names: {files}"
+            )
+            logger.error(error_message)
+            raise ValueError(error_message)
+
+        tmp_model_file_description = self.model_file_description
+        tmp_model_file_description['models'].append({
+                "namespace": namespace,
+                "bucketName": bucket,
+                "prefix": prefix,
+                "objects": objects,
+            })
+        self.set_spec(self.CONST_MODEL_FILE_DESCRIPTION, tmp_model_file_description)
+    
+    def remove(self, namespace: str, bucket: str, prefix: Optional[str]=None):
+        """
+        Removes information about objects in a specified bucket from the model description JSON.
+
+        Parameters:
+        - namespace (str): The namespace of the object storage.
+        - bucket (str): The name of the bucket containing the objects.
+        - prefix (str, optional): The prefix used to filter objects within the bucket. Defaults to None.
+
+        Returns:
+        - None
+
+        Note:
+        - This method removes information about objects in the specified bucket from the
+        instance of the ModelDescription.
+        - If a matching model (with the specified namespace, bucket name, and prefix) is found
+        in the model description JSON, it is removed.
+        - If no matching model is found, the method returns without making any changes.
+        """
+
+        def findModelIdx():
+            for idx, model in enumerate(self.model_file_description["models"]):
+                if (
+                    model["namespace"],
+                    model["bucketName"],
+                    (model["prefix"] if ("prefix" in model) else None),
+                ) == (namespace, bucket, prefix):
+                    return idx
+            return -1
+
+        modelSearchIdx = findModelIdx()
+        if modelSearchIdx == -1:
+            return
+        else:
+            # model found case
+            self.model_file_description["models"].pop(modelSearchIdx)
+
+    def create(self):
+        """
+        Saves the model to the Model Catalog of Oracle Cloud Infrastructure (OCI) Data Science service.
+
+        Parameters:
+        - project_ocid (str): The OCID (Oracle Cloud Identifier) of the OCI Data Science project.
+        - compartment_ocid (str): The OCID of the compartment in which the model will be created.
+        - display_name (str, optional): The display name for the created model. If not provided,
+        a default display name indicating the creation timestamp is used. Defaults to None.
+
+        Returns:
+        - str: The OCID of the created model.
+
+        Note:
+        - The display name defaults to a string indicating the creation timestamp if not provided.
+        """
+        tmp_file_path = self.build()
+        self = self.with_artifact(uri=tmp_file_path)
+        created_model = super().create()
+        try:
+            os.remove(tmp_file_path)
+        except Exception as e:
+            logger.error(f"Error occurred while cleaning file: {e}")
+            raise e
+        return created_model.id
+
+    def build(self) -> str:
+        """
+        Builds the model description JSON and writes it to a file.
+
+        Parameters:
+        - None
+
+        Returns:
+        - str: The absolute file path where the model description JSON is stored.
+
+        Note:
+        - This method serializes the current model description attribute to a JSON file named 'resultModelDescription.json' with an indentation of 2 spaces.
+        """
+        logger.info("Building...")
+        file_path = "resultModelDescription.json"
+        try:
+            with open(file_path, "w") as json_file:
+                json.dump(self.model_file_description, json_file, indent=2)
+        except IOError as e:
+            logger.error(
+                f"Error writing to file '{file_path}': {e}"
+            )  # Handle the exception accordingly, e.g., log the error, retry writing, etc.
+        except Exception as e:
+            logger.error(
+                f"An unexpected error occurred: {e}"
+            )  # Handle other unexpected exceptions
+        logger.info("Model Artifact stored successfully.")
+        return os.path.abspath(file_path)
+
+    def show(self):
+        """
+        Displays the current model description JSON in a human-readable format.
+
+        Parameters:
+        - None
+
+        Returns:
+        - str: The json representation of current model artifact
+
+        Note:
+        - The JSON representation of the model description is formatted with an indentation
+        of 4 spaces.
+        """
+        logger.info(json.dumps(self.model_file_description, indent=4))
+        return json.dumps(self.model_file_description, indent=4)