[Ready To Merge][AQUA] Mutli-Model Deployment

README-development.md

@@ -248,7 +248,7 @@ All the unit tests can be found [here](https://github.com/oracle/accelerated-dat
 The following commands detail how the unit tests can be run.
 ```
 # Run all tests in AQUA project
-python -m pytest -q tests/unitary/with_extras/aqua/test_deployment.py
+python -m pytest -q tests/unitary/with_extras/aqua/*
 
 # Run all tests specific to a module within in AQUA project (ex. test_deployment.py, test_model.py, etc.)
 python -m pytest -q tests/unitary/with_extras/aqua/test_deployment.py

ads/aqua/app.py

@@ -6,9 +6,11 @@
 import os
 import traceback
 from dataclasses import fields
+from datetime import datetime, timedelta
 from typing import Any, Dict, Optional, Union
 
 import oci
+from cachetools import TTLCache, cached
 from oci.data_science.models import UpdateModelDetails, UpdateModelProvenanceDetails
 
 from ads import set_auth
@@ -269,6 +271,7 @@ def if_artifact_exist(self, model_id: str, **kwargs) -> bool:
                 logger.info(f"Artifact not found in model {model_id}.")
                 return False
 
+    @cached(cache=TTLCache(maxsize=1, ttl=timedelta(minutes=1), timer=datetime.now))
     def get_config(
         self,
         model_id: str,
@@ -337,6 +340,9 @@ def get_config(
         config_file_path = os.path.join(config_path, config_file_name)
         if is_path_exists(config_file_path):
             try:
+                logger.debug(
+                    f"Loading config: `{config_file_name}` from `{config_path}`"
+                )
                 config = load_config(
                     config_path,
                     config_file_name=config_file_name,

ads/aqua/common/entities.py

@@ -2,10 +2,14 @@
 # Copyright (c) 2024, 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 re
 from typing import Any, Dict, Optional
 
 from oci.data_science.models import Model
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, Field, model_validator
+
+from ads.aqua import logger
+from ads.aqua.config.utils.serializer import Serializable
 
 
 class ContainerSpec:
@@ -25,7 +29,6 @@ class ContainerSpec:
 class ModelConfigResult(BaseModel):
     """
     Represents the result of getting the AQUA model configuration.
-
     Attributes:
         model_details (Dict[str, Any]): A dictionary containing model details extracted from OCI.
         config (Dict[str, Any]): A dictionary of the loaded configuration.
@@ -42,3 +45,222 @@ class Config:
         extra = "ignore"
         arbitrary_types_allowed = True
         protected_namespaces = ()
+
+
+class GPUSpecs(Serializable):
+    """
+    Represents the GPU specifications for a compute instance.
+    """
+
+    gpu_memory_in_gbs: Optional[int] = Field(
+        default=None, description="The amount of GPU memory available (in GB)."
+    )
+    gpu_count: Optional[int] = Field(
+        default=None, description="The number of GPUs available."
+    )
+    gpu_type: Optional[str] = Field(
+        default=None, description="The type of GPU (e.g., 'V100, A100, H100')."
+    )
+
+
+class GPUShapesIndex(Serializable):
+    """
+    Represents the index of GPU shapes.
+
+    Attributes
+    ----------
+    shapes (Dict[str, GPUSpecs]): A mapping of compute shape names to their GPU specifications.
+    """
+
+    shapes: Dict[str, GPUSpecs] = Field(
+        default_factory=dict,
+        description="Mapping of shape names to GPU specifications.",
+    )
+
+
+class ComputeShapeSummary(Serializable):
+    """
+    Represents the specifications of a compute instance's shape.
+    """
+
+    core_count: Optional[int] = Field(
+        default=None, description="The number of CPU cores available."
+    )
+    memory_in_gbs: Optional[int] = Field(
+        default=None, description="The amount of memory (in GB) available."
+    )
+    name: Optional[str] = Field(
+        default=None, description="The name identifier of the compute shape."
+    )
+    shape_series: Optional[str] = Field(
+        default=None, description="The series or category of the compute shape."
+    )
+    gpu_specs: Optional[GPUSpecs] = Field(
+        default=None,
+        description="The GPU specifications associated with the compute shape.",
+    )
+
+    @model_validator(mode="after")
+    @classmethod
+    def set_gpu_specs(cls, model: "ComputeShapeSummary") -> "ComputeShapeSummary":
+        """
+        Validates and populates GPU specifications if the shape_series indicates a GPU-based shape.
+
+        - If the shape_series contains "GPU", the validator first checks if the shape name exists
+          in the GPU_SPECS dictionary. If found, it creates a GPUSpecs instance with the corresponding data.
+        - If the shape is not found in the GPU_SPECS, it attempts to extract the GPU count from the shape name
+          using a regex pattern (looking for a number following a dot at the end of the name).
+
+        The information about shapes is taken from: https://docs.oracle.com/en-us/iaas/data-science/using/supported-shapes.htm
+
+        Returns:
+            ComputeShapeSummary: The updated instance with gpu_specs populated if applicable.
+        """
+        try:
+            if (
+                model.shape_series
+                and "GPU" in model.shape_series.upper()
+                and model.name
+                and not model.gpu_specs
+            ):
+                # Try to extract gpu_count from the shape name using a regex (e.g., "VM.GPU3.2" -> gpu_count=2)
+                match = re.search(r"\.(\d+)$", model.name)
+                if match:
+                    gpu_count = int(match.group(1))
+                    model.gpu_specs = GPUSpecs(gpu_count=gpu_count)
+        except Exception as err:
+            logger.debug(
+                f"Error occurred in attempt to extract GPU specification for the f{model.name}. "
+                f"Details: {err}"
+            )
+        return model
+
+
+class AquaMultiModelRef(Serializable):
+    """
+    Lightweight model descriptor used for multi-model deployment.
+
+    This class only contains essential details
+    required to fetch complete model metadata and deploy models.
+
+    Attributes
+    ----------
+    model_id : str
+        The unique identifier of the model.
+    model_name : Optional[str]
+        The name of the model.
+    gpu_count : Optional[int]
+        Number of GPUs required for deployment.
+    env_var : Optional[Dict[str, Any]]
+        Optional environment variables to override during deployment.
+    artifact_location : Optional[str]
+        Artifact path of model in the multimodel group.
+    """
+
+    model_id: str = Field(..., description="The model OCID to deploy.")
+    model_name: Optional[str] = Field(None, description="The name of model.")
+    gpu_count: Optional[int] = Field(
+        None, description="The gpu count allocation for the model."
+    )
+    env_var: Optional[dict] = Field(
+        default_factory=dict, description="The environment variables of the model."
+    )
+    artifact_location: Optional[str] = Field(
+        None, description="Artifact path of model in the multimodel group."
+    )
+
+    class Config:
+        extra = "ignore"
+        protected_namespaces = ()
+
+
+class ContainerPath(Serializable):
+    """
+    Represents a parsed container path, extracting the path, name, and version.
+
+    This model is designed to parse a container path string of the format
+    '<image_path>:<version>'. It extracts the following components:
+    - `path`: The full path up to the version.
+    - `name`: The last segment of the path, representing the image name.
+    - `version`: The version number following the final colon.
+
+    Example Usage:
+    --------------
+    >>> container = ContainerPath(full_path="iad.ocir.io/ociodscdev/odsc-llm-evaluate:0.1.2.9")
+    >>> container.path
+    'iad.ocir.io/ociodscdev/odsc-llm-evaluate'
+    >>> container.name
+    'odsc-llm-evaluate'
+    >>> container.version
+    '0.1.2.9'
+
+    >>> container = ContainerPath(full_path="custom-scheme://path/to/versioned-model:2.5.1")
+    >>> container.path
+    'custom-scheme://path/to/versioned-model'
+    >>> container.name
+    'versioned-model'
+    >>> container.version
+    '2.5.1'
+
+    Attributes
+    ----------
+    full_path : str
+        The complete container path string to be parsed.
+    path : Optional[str]
+        The full path up to the version (e.g., 'iad.ocir.io/ociodscdev/odsc-llm-evaluate').
+    name : Optional[str]
+        The image name, which is the last segment of `path` (e.g., 'odsc-llm-evaluate').
+    version : Optional[str]
+        The version number following the final colon in the path (e.g., '0.1.2.9').
+
+    Methods
+    -------
+    validate(values: Any) -> Any
+        Validates and parses the `full_path`, extracting `path`, `name`, and `version`.
+    """
+
+    full_path: str
+    path: Optional[str] = None
+    name: Optional[str] = None
+    version: Optional[str] = None
+
+    @model_validator(mode="before")
+    @classmethod
+    def validate(cls, values: Any) -> Any:
+        """
+        Validates and parses the full container path, extracting the image path, image name, and version.
+
+        Parameters
+        ----------
+        values : dict
+            The dictionary of values being validated, containing 'full_path'.
+
+        Returns
+        -------
+        dict
+            Updated values dictionary with extracted 'path', 'name', and 'version'.
+        """
+        full_path = values.get("full_path", "").strip()
+
+        # Regex to parse <image_path>:<version>
+        match = re.match(
+            r"^(?P<image_path>.+?)(?::(?P<image_version>[\w\.]+))?$", full_path
+        )
+
+        if not match:
+            raise ValueError(
+                "Invalid container path format. Expected format: '<image_path>:<version>'"
+            )
+
+        # Extract image_path and version
+        values["path"] = match.group("image_path")
+        values["version"] = match.group("image_version")
+
+        # Extract image_name as the last segment of image_path
+        values["name"] = values["path"].split("/")[-1]
+
+        return values
+
+    class Config:
+        extra = "ignore"
+        protected_namespaces = ()

ads/aqua/common/enums.py

@@ -25,6 +25,7 @@ class Tags(ExtendedEnum):
     AQUA_TAG = "OCI_AQUA"
     AQUA_SERVICE_MODEL_TAG = "aqua_service_model"
     AQUA_FINE_TUNED_MODEL_TAG = "aqua_fine_tuned_model"
+    AQUA_MODEL_ID_TAG = "aqua_model_id"
     AQUA_MODEL_NAME_TAG = "aqua_model_name"
     AQUA_EVALUATION = "aqua_evaluation"
     AQUA_FINE_TUNING = "aqua_finetuning"
@@ -34,6 +35,7 @@ class Tags(ExtendedEnum):
     AQUA_EVALUATION_MODEL_ID = "evaluation_model_id"
     MODEL_FORMAT = "model_format"
     MODEL_ARTIFACT_FILE = "model_file"
+    MULTIMODEL_TYPE_TAG = "aqua_multimodel"
 
 
 class InferenceContainerType(ExtendedEnum):
@@ -44,6 +46,7 @@ class InferenceContainerType(ExtendedEnum):
 
 class InferenceContainerTypeFamily(ExtendedEnum):
     AQUA_VLLM_CONTAINER_FAMILY = "odsc-vllm-serving"
+    AQUA_VLLM_V1_CONTAINER_FAMILY = "odsc-vllm-serving-v1"
     AQUA_TGI_CONTAINER_FAMILY = "odsc-tgi-serving"
     AQUA_LLAMA_CPP_CONTAINER_FAMILY = "odsc-llama-cpp-serving"