combine datatypes.py and endpoints.py into api.py

llama_toolchain/dataset/api/__init__.py

@@ -4,5 +4,4 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from .datatypes import *  # noqa: F401 F403
-from .endpoints import *  # noqa: F401 F403
+from .api import *  # noqa: F401 F403

llama_toolchain/dataset/api/api.py

@@ -4,13 +4,34 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from typing import Protocol
+from enum import Enum
+from typing import Any, Dict, Optional, Protocol
+
+from llama_models.llama3.api.datatypes import URL
 
 from llama_models.schema_utils import json_schema_type, webmethod
 
 from pydantic import BaseModel
 
-from .datatypes import *  # noqa: F403
+
+@json_schema_type
+class TrainEvalDatasetColumnType(Enum):
+    dialog = "dialog"
+    text = "text"
+    media = "media"
+    number = "number"
+    json = "json"
+
+
+@json_schema_type
+class TrainEvalDataset(BaseModel):
+    """Dataset to be used for training or evaluating language models."""
+
+    # TODO(ashwin): figure out if we need to add an enum for a "dataset type"
+
+    columns: Dict[str, TrainEvalDatasetColumnType]
+    content_url: URL
+    metadata: Optional[Dict[str, Any]] = None
 
 
 @json_schema_type

llama_toolchain/dataset/api/datatypes.py

@@ -1,34 +0,0 @@
-# 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.
-
-from enum import Enum
-from typing import Any, Dict, Optional
-
-from llama_models.llama3.api.datatypes import URL
-
-from llama_models.schema_utils import json_schema_type
-
-from pydantic import BaseModel
-
-
-@json_schema_type
-class TrainEvalDatasetColumnType(Enum):
-    dialog = "dialog"
-    text = "text"
-    media = "media"
-    number = "number"
-    json = "json"
-
-
-@json_schema_type
-class TrainEvalDataset(BaseModel):
-    """Dataset to be used for training or evaluating language models."""
-
-    # TODO(ashwin): figure out if we need to add an enum for a "dataset type"
-
-    columns: Dict[str, TrainEvalDatasetColumnType]
-    content_url: URL
-    metadata: Optional[Dict[str, Any]] = None