Merge commit '5487f6243528d0b31338484002837507642266c0' from develop

Author: qiuosier

.github/workflows/run-unittests-default_setup.yml

@@ -8,6 +8,7 @@ on:
       - develop
     paths:
       - "ads/**"
+      - "!ads/ads_version.json"
       - setup.py
       - "**requirements.txt"
       - .github/workflows/run-unittests.yml

.github/workflows/run-unittests.yml

@@ -8,6 +8,7 @@ on:
       - develop
     paths:
       - "ads/**"
+      - "!ads/ads_version.json"
       - setup.py
       - "**requirements.txt"
       - .github/workflows/run-unittests.yml

ads/ads_version.json

@@ -1,3 +1,3 @@
 {
-  "version": "2.8.3"
+  "version": "2.8.4"
 }

ads/dataflow/dataflow.py

@@ -63,7 +63,7 @@ class SPARK_VERSION(str):
 class DataFlow:
     @deprecated(
         "2.6.3",
-        details="Use ads.jobs.DataFlow class for creating DataFlow applications and runs. Check https://accelerated-data-science.readthedocs.io/en/latest/user_guide/apachespark/dataflow.html#create-run-data-flow-application-using-ads-python-sdk",
+        details="Use ads.jobs.DataFlow class for creating Data Flow applications and runs. Check https://accelerated-data-science.readthedocs.io/en/latest/user_guide/apachespark/dataflow.html#create-run-data-flow-application-using-ads-python-sdk",
     )
     def __init__(
         self,

ads/opctl/backend/base.py

@@ -21,7 +21,7 @@ class Backend:
 
     def __init__(self, config: Dict) -> None:
         self.config = config
-        self.auth_type = config["execution"].get("auth")
+        self.auth_type = config["execution"].get("auth", "api_key")
         self.profile = config["execution"].get("oci_profile", None)
         self.oci_config = config["execution"].get("oci_config", None)
 

ads/opctl/backend/local.py

@@ -52,6 +52,7 @@
 )
 from ads.pipeline.ads_pipeline import Pipeline, PipelineStep
 from ads.common.oci_client import OCIClientFactory
+from ads.config import NO_CONTAINER
 
 class CondaPackNotFound(Exception):  # pragma: no cover
     pass
@@ -218,6 +219,7 @@ def _run_with_conda_pack(
             )
             if os.path.exists(os.path.join(conda_pack_path, "spark-defaults.conf")):
                 env_vars["SPARK_CONF_DIR"] = os.path.join(DEFAULT_IMAGE_CONDA_DIR, slug)
+            logger.info(f"Running with conda pack in a container with command {command}")
             return self._activate_conda_env_and_run(
                 image, slug, command, bind_volumes, env_vars
             )
@@ -679,9 +681,11 @@ def predict(self) -> None:
         None
             Nothing.
         """
+        
+        # model artifact in artifact directory
         artifact_directory = self.config["execution"].get("artifact_directory")
         ocid = self.config["execution"].get("ocid")
-        data = self.config["execution"].get("payload")
+        
         model_folder = os.path.expanduser(
             self.config["execution"].get("model_save_folder", DEFAULT_MODEL_FOLDER)
         )
@@ -698,79 +702,72 @@ def predict(self) -> None:
             )
 
             _download_model(
-                oci_auth=self.oci_auth,
+                auth=self.auth_type,
+                profile=self.profile,
                 ocid=ocid,
                 artifact_directory=artifact_directory,
                 region=region,
                 bucket_uri=bucket_uri,
                 timeout=timeout,
                 force_overwrite=True,
             )
-        conda_slug, conda_path = None, None
-        if ocid:
+                
+        # conda
+        conda_slug, conda_path = self.config["execution"].get("conda_slug"), self.config["execution"].get("conda_path")
+        if not conda_slug and not conda_path and ocid:
             conda_slug, conda_path = self._get_conda_info_from_custom_metadata(ocid)
-        if not conda_path:
-            if (
-                not os.path.exists(artifact_directory)
-                or len(os.listdir(artifact_directory)) == 0
-            ):
-                raise ValueError(
-                    f"`artifact_directory` {artifact_directory} does not exist or is empty."
-                )
+        if not conda_slug and not conda_path:
             conda_slug, conda_path = self._get_conda_info_from_runtime(
                 artifact_dir=artifact_directory
             )
-        if not conda_path or not conda_slug:
-            raise ValueError("Conda information cannot be detected.")
-        compartment_id = self.config["execution"].get(
-            "compartment_id", self.config["infrastructure"].get("compartment_id")
-        )
-        project_id = self.config["execution"].get(
-            "project_id", self.config["infrastructure"].get("project_id")
-        )
-        if not compartment_id or not project_id:
-            raise ValueError("`compartment_id` and `project_id` must be provided.")
-        extra_cmd = (
-            DEFAULT_MODEL_DEPLOYMENT_FOLDER
-            + " "
-            + data
-            + " "
-            + compartment_id
-            + " "
-            + project_id
-        )
+        if 'conda_slug' not in self.config["execution"]:
+            self.config["execution"]["conda_slug"] = conda_path.split("/")[-1] if conda_path else conda_slug 
+
+        self.config["execution"]["image"] = ML_JOB_IMAGE
+        
+        # bind_volumnes
         bind_volumes = {}
+        SCRIPT = "script.py"
+        dir_path = os.path.dirname(os.path.realpath(__file__))
         if not is_in_notebook_session():
             bind_volumes = {
                 os.path.expanduser(
                     os.path.dirname(self.config["execution"]["oci_config"])
                 ): {"bind": os.path.join(DEFAULT_IMAGE_HOME_DIR, ".oci")}
             }
-            dir_path = os.path.dirname(os.path.realpath(__file__))
-            script = "script.py"
+            
             self.config["execution"]["source_folder"] = os.path.abspath(
                 os.path.join(dir_path, "..")
             )
-            self.config["execution"]["entrypoint"] = script
+            self.config["execution"]["entrypoint"] = SCRIPT
             bind_volumes[artifact_directory] = {"bind": DEFAULT_MODEL_DEPLOYMENT_FOLDER}
-        if self.config["execution"].get("conda_slug", conda_slug):
-            self.config["execution"]["image"] = ML_JOB_IMAGE
-            if not self.config["execution"].get("conda_slug"):
-                self.config["execution"]["conda_slug"] = conda_slug
-                self.config["execution"]["slug"] = conda_slug
-            self.config["execution"]["conda_path"] = conda_path
-            exit_code = self._run_with_conda_pack(
-                bind_volumes, extra_cmd, install=True, conda_uri=conda_path
-            )
+        
+        # extra cmd
+        data = self.config["execution"].get("payload")
+        extra_cmd = f"--payload '{data}' " + f"--auth {self.auth_type} "
+        if self.auth_type != "resource_principal":
+            extra_cmd += f"--profile {self.profile}"
+        
+        if is_in_notebook_session() or NO_CONTAINER:
+            # _run_with_conda_pack has code to handle notebook session case,
+            # however, it activate the conda pack and then run the script. 
+            # For the deployment, we just take the current conda env and run it.
+            # Hence we just handle the notebook case directly here.
+            script_path = os.path.join(os.path.join(dir_path, ".."), SCRIPT)
+            cmd = f"python {script_path} " + f"--artifact-directory {artifact_directory} " + extra_cmd
+            logger.info(f"Running in a notebook or NO_CONTAINER with command {cmd}")
+            run_command(cmd=cmd, shell=True)
         else:
-            raise ValueError("Either conda pack info or image should be specified.")
-
-        if exit_code != 0:
-            raise RuntimeError(
-                f"`predict` did not complete successfully. Exit code: {exit_code}. "
-                f"Run with the --debug argument to view container logs."
-            )
-
+            extra_cmd = f"--artifact-directory {DEFAULT_MODEL_DEPLOYMENT_FOLDER} "+ extra_cmd
+            exit_code = self._run_with_conda_pack(
+                    bind_volumes, extra_cmd, install=True, conda_uri=conda_path
+                )
+            if exit_code != 0:
+                raise RuntimeError(
+                    f"`predict` did not complete successfully. Exit code: {exit_code}. "
+                    f"Run with the --debug argument to view container logs."
+                )
+                
     def _get_conda_info_from_custom_metadata(self, ocid):
         """
         Get conda env info from custom metadata from model catalog.

ads/opctl/cli.py

@@ -16,6 +16,7 @@
 import ads.opctl.model.cli
 import ads.opctl.spark.cli
 from ads.common import auth as authutil
+from ads.common.auth import AuthType
 from ads.opctl.cmds import activate as activate_cmd
 from ads.opctl.cmds import cancel as cancel_cmd
 from ads.opctl.cmds import configure as configure_cmd
@@ -29,12 +30,8 @@
 from ads.opctl.cmds import run_diagnostics as run_diagnostics_cmd
 from ads.opctl.cmds import watch as watch_cmd
 from ads.opctl.config.merger import ConfigMerger
-from ads.opctl.constants import (
-    BACKEND_NAME,
-    DEFAULT_MODEL_FOLDER,
-    RESOURCE_TYPE,
-    RUNTIME_TYPE,
-)
+from ads.opctl.constants import (BACKEND_NAME, DEFAULT_MODEL_FOLDER,
+                                 RESOURCE_TYPE, RUNTIME_TYPE)
 from ads.opctl.utils import build_image as build_image_cmd
 from ads.opctl.utils import publish_image as publish_image_cmd
 from ads.opctl.utils import suppress_traceback
@@ -544,6 +541,7 @@ def init(debug: bool, **kwargs: Dict[str, Any]) -> None:
     suppress_traceback(debug)(init_cmd)(**kwargs)
 
 
+@commands.command()
 @click.option(
     "--ocid",
     nargs=1,
@@ -597,7 +595,13 @@ def init(debug: bool, **kwargs: Dict[str, Any]) -> None:
     "--conda-slug",
     nargs=1,
     required=False,
-    help="The conda env used to load the model and conduct the prediction. This is only used when model id is passed to `ocid` and a local predict is conducted. It should match the inference conda env specified in the runtime.yaml file which is the conda pack being used when conducting real model deployment.",
+    help="The conda slug used to load the model and conduct the prediction. This is only used when model id is passed to `ocid` and a local predict is conducted. It should match the inference conda env specified in the runtime.yaml file which is the conda pack being used when conducting real model deployment.",
+)
+@click.option(
+    "--conda-path",
+    nargs=1,
+    required=False,
+    help="The conda path used to load the model and conduct the prediction. This is only used when model id is passed to `ocid` and a local predict is conducted. It should match the inference conda env specified in the runtime.yaml file which is the conda pack being used when conducting real model deployment.",
 )
 @click.option(
     "--model-version",
@@ -611,10 +615,22 @@ def init(debug: bool, **kwargs: Dict[str, Any]) -> None:
     required=False,
     help="When the `inference_server='triton'`, the name of the model to invoke. This can only be used when model deployment id is passed in. For the other cases, it will be ignored.",
 )
+@click.option(
+    "--auth",
+    "-a",
+    help="authentication method",
+    type=click.Choice(AuthType.values()),
+    default=None,
+)
+@click.option(
+    "--oci-profile",
+    help="oci profile",
+    default=None,
+)
 @click.option("--debug", "-d", help="set debug mode", is_flag=True, default=False)
 def predict(**kwargs):
     """
-    Deactivates a data science service.
+    Make prediction using the model with the payload.
     """
     suppress_traceback(kwargs["debug"])(predict_cmd)(**kwargs)
 

ads/opctl/model/cmds.py

@@ -1,12 +1,12 @@
 import os
 import shutil
 
-from ads.common.auth import create_signer
+from ads.common.auth import AuthContext
 from ads.model.datascience_model import DataScienceModel
 from ads.opctl import logger
-from ads.opctl.constants import DEFAULT_MODEL_FOLDER
 from ads.opctl.config.base import ConfigProcessor
 from ads.opctl.config.merger import ConfigMerger
+from ads.opctl.constants import DEFAULT_MODEL_FOLDER
 
 
 def download_model(**kwargs):
@@ -15,12 +15,6 @@ def download_model(**kwargs):
 
     auth_type = p.config["execution"].get("auth")
     profile = p.config["execution"].get("oci_profile", None)
-    oci_config = p.config["execution"].get("oci_config", None)
-    oci_auth = create_signer(
-        auth_type,
-        oci_config,
-        profile,
-    )
     model_folder = os.path.expanduser(
         p.config["execution"].get("model_save_folder", DEFAULT_MODEL_FOLDER)
     )
@@ -44,7 +38,8 @@ def download_model(**kwargs):
             bucket_uri=bucket_uri,
             timeout=timeout,
             force_overwrite=force_overwrite,
-            oci_auth=oci_auth,
+            auth=auth_type,
+            profile=profile
         )
     else:
         logger.error(f"Model already exists. Set `force_overwrite=True` to overwrite.")
@@ -54,23 +49,24 @@ def download_model(**kwargs):
 
 
 def _download_model(
-    ocid, artifact_directory, oci_auth, region, bucket_uri, timeout, force_overwrite
+    ocid, artifact_directory, region, bucket_uri, timeout, force_overwrite, auth, profile=None
 ):
     os.makedirs(artifact_directory, exist_ok=True)
-    os.chmod(artifact_directory, 777)
-
+    kwargs = {"auth": auth}
+    if profile:
+        kwargs["profile"] = profile
     try:
-        dsc_model = DataScienceModel.from_id(ocid)
-        dsc_model.download_artifact(
-            target_dir=artifact_directory,
-            force_overwrite=force_overwrite,
-            overwrite_existing_artifact=True,
-            remove_existing_artifact=True,
-            auth=oci_auth,
-            region=region,
-            timeout=timeout,
-            bucket_uri=bucket_uri,
-        )
+        with AuthContext(**kwargs):
+            dsc_model = DataScienceModel.from_id(ocid)
+            dsc_model.download_artifact(
+                target_dir=artifact_directory,
+                force_overwrite=force_overwrite,
+                overwrite_existing_artifact=True,
+                remove_existing_artifact=True,
+                region=region,
+                timeout=timeout,
+                bucket_uri=bucket_uri,
+            )
     except Exception as e:
         print(type(e))
         shutil.rmtree(artifact_directory, ignore_errors=True)

ads/opctl/script.py

@@ -1,31 +1,37 @@
+import argparse
 import json
-import sys
-import tempfile
 
+from ads.common.auth import AuthContext
 from ads.model.generic_model import GenericModel
 
 
-def verify(artifact_dir, data, compartment_id, project_id): # pragma: no cover
-    with tempfile.TemporaryDirectory() as td:
+def verify(artifact_dir, payload, auth, profile): # pragma: no cover
+    kwargs = {"auth": auth}
+    if profile != 'None':
+        kwargs["profile"] = profile
+    with AuthContext(**kwargs):
         model = GenericModel.from_model_artifact(
             uri=artifact_dir,
             artifact_dir=artifact_dir,
             force_overwrite=True,
-            compartment_id=compartment_id,
-            project_id=project_id,
         )
 
         try:
-            data = json.loads(data)
+            payload = json.loads(payload)
         except:
             pass
-        print(model.verify(data, auto_serialize_data=False))
+        print(model.verify(payload, auto_serialize_data=False))
 
 
 def main(): # pragma: no cover
-    args = sys.argv[1:]
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--payload", type=str, required=True)
+    parser.add_argument("--artifact-directory", type=str, required=True)
+    parser.add_argument("--auth", type=str, required=True)
+    parser.add_argument("--profile", type=str,required=False)
+    args = parser.parse_args()
     verify(
-        artifact_dir=args[0], data=args[1], compartment_id=args[2], project_id=args[3]
+        artifact_dir=args.artifact_directory, payload=args.payload, auth=args.auth, profile=args.profile
     )
     return 0