feat: convert Datasets API to use FastAPI router (#4359)

# What does this PR do?

Convert the Datasets API from webmethod decorators to FastAPI router
pattern.

Fixes: https://github.com/llamastack/llama-stack/issues/4344

## Test Plan
CI

Signed-off-by: Sébastien Han <seb@redhat.com>

src/llama_stack_api/datasets/models.py

@@ -0,0 +1,152 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+"""Pydantic models for Datasets API requests and responses.
+
+This module defines the request and response models for the Datasets API
+using Pydantic with Field descriptions for OpenAPI schema generation.
+"""
+
+from enum import Enum, StrEnum
+from typing import Annotated, Any, Literal
+
+from pydantic import BaseModel, Field
+
+from llama_stack_api.resource import Resource, ResourceType
+from llama_stack_api.schema_utils import json_schema_type, register_schema
+
+
+class DatasetPurpose(StrEnum):
+    """Purpose of the dataset. Each purpose has a required input data schema."""
+
+    post_training_messages = "post-training/messages"
+    """The dataset contains messages used for post-training."""
+    eval_question_answer = "eval/question-answer"
+    """The dataset contains a question column and an answer column."""
+    eval_messages_answer = "eval/messages-answer"
+    """The dataset contains a messages column with list of messages and an answer column."""
+
+
+class DatasetType(Enum):
+    """Type of the dataset source."""
+
+    uri = "uri"
+    """The dataset can be obtained from a URI."""
+    rows = "rows"
+    """The dataset is stored in rows."""
+
+
+@json_schema_type
+class URIDataSource(BaseModel):
+    """A dataset that can be obtained from a URI."""
+
+    type: Literal["uri"] = Field(default="uri", description="The type of data source.")
+    uri: str = Field(
+        ...,
+        description='The dataset can be obtained from a URI. E.g. "https://mywebsite.com/mydata.jsonl", "lsfs://mydata.jsonl", "data:csv;base64,{base64_content}"',
+    )
+
+
+@json_schema_type
+class RowsDataSource(BaseModel):
+    """A dataset stored in rows."""
+
+    type: Literal["rows"] = Field(default="rows", description="The type of data source.")
+    rows: list[dict[str, Any]] = Field(
+        ...,
+        description='The dataset is stored in rows. E.g. [{"messages": [{"role": "user", "content": "Hello, world!"}, {"role": "assistant", "content": "Hello, world!"}]}]',
+    )
+
+
+DataSource = Annotated[
+    URIDataSource | RowsDataSource,
+    Field(discriminator="type"),
+]
+register_schema(DataSource, name="DataSource")
+
+
+class CommonDatasetFields(BaseModel):
+    """Common fields for a dataset."""
+
+    purpose: DatasetPurpose = Field(..., description="Purpose of the dataset indicating its intended use")
+    source: DataSource = Field(..., description="Data source configuration for the dataset")
+    metadata: dict[str, Any] = Field(
+        default_factory=dict,
+        description="Any additional metadata for this dataset",
+    )
+
+
+@json_schema_type
+class Dataset(CommonDatasetFields, Resource):
+    """Dataset resource for storing and accessing training or evaluation data."""
+
+    type: Literal[ResourceType.dataset] = Field(
+        default=ResourceType.dataset,
+        description="Type of resource, always 'dataset' for datasets",
+    )
+
+    @property
+    def dataset_id(self) -> str:
+        return self.identifier
+
+    @property
+    def provider_dataset_id(self) -> str | None:
+        return self.provider_resource_id
+
+
+@json_schema_type
+class ListDatasetsResponse(BaseModel):
+    """Response from listing datasets."""
+
+    data: list[Dataset] = Field(..., description="List of datasets")
+
+
+# Request models for each endpoint
+
+
+@json_schema_type
+class RegisterDatasetRequest(BaseModel):
+    """Request model for registering a dataset."""
+
+    purpose: DatasetPurpose = Field(..., description="The purpose of the dataset.")
+    source: DataSource = Field(..., description="The data source of the dataset.")
+    metadata: dict[str, Any] | None = Field(
+        default=None,
+        description="The metadata for the dataset.",
+    )
+    dataset_id: str | None = Field(
+        default=None,
+        description="The ID of the dataset. If not provided, an ID will be generated.",
+    )
+
+
+@json_schema_type
+class GetDatasetRequest(BaseModel):
+    """Request model for getting a dataset by ID."""
+
+    dataset_id: str = Field(..., description="The ID of the dataset to get.")
+
+
+@json_schema_type
+class UnregisterDatasetRequest(BaseModel):
+    """Request model for unregistering a dataset."""
+
+    dataset_id: str = Field(..., description="The ID of the dataset to unregister.")
+
+
+__all__ = [
+    "CommonDatasetFields",
+    "Dataset",
+    "DatasetPurpose",
+    "DatasetType",
+    "DataSource",
+    "RowsDataSource",
+    "URIDataSource",
+    "ListDatasetsResponse",
+    "RegisterDatasetRequest",
+    "GetDatasetRequest",
+    "UnregisterDatasetRequest",
+]