add datastore initial code

This commit is contained in:
Ubuntu 2025-03-14 14:45:00 +00:00 committed by raspawar
parent d667a7109f
commit 0a2af0e2f8
9 changed files with 293 additions and 9 deletions

View file

@ -0,0 +1,30 @@
# 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 typing import List
from llama_stack.providers.datatypes import (
AdapterSpec,
Api,
ProviderSpec,
remote_provider_spec,
)
def available_providers() -> List[ProviderSpec]:
return [
remote_provider_spec(
api=Api.datasets,
adapter=AdapterSpec(
adapter_type="nvidia",
pip_packages=[
"datasets",
],
module="llama_stack.providers.remote.datasets.nvidia",
config_class="llama_stack.providers.remote.datasets.nvidia.NvidiaDatasetConfig",
),
),
]

View file

@ -0,0 +1,23 @@
# 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 .config import NvidiaDatasetConfig
async def get_adapter_impl(
config: NvidiaDatasetConfig,
_deps,
):
from .datasets import NvidiaDatasetAdapter
if not isinstance(config, NvidiaDatasetConfig):
raise RuntimeError(f"Unexpected config type: {type(config)}")
impl = NvidiaDatasetAdapter(config)
return impl
__all__ = ["get_adapter_impl", "NvidiaDatasetAdapter"]

View file

@ -0,0 +1,71 @@
# 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.
import os
import warnings
from typing import Any, Dict, Optional
from pydantic import BaseModel, Field
class NvidiaDatasetConfig(BaseModel):
"""Configuration for NVIDIA Dataset implementation."""
api_key: Optional[str] = Field(
default_factory=lambda: os.getenv("NVIDIA_API_KEY"),
description="The NVIDIA API key.",
)
dataset_namespace: Optional[str] = Field(
default_factory=lambda: os.getenv("NVIDIA_DATASET_NAMESPACE", "default"),
description="The NVIDIA dataset namespace.",
)
access_policies: Optional[dict] = Field(
default_factory=lambda: os.getenv("NVIDIA_ACCESS_POLICIES", {}),
description="The NVIDIA access policies.",
)
project_id: Optional[str] = Field(
default_factory=lambda: os.getenv("NVIDIA_PROJECT_ID", "test-project"),
description="The NVIDIA project ID.",
)
datasets_url: str = Field(
default_factory=lambda: os.getenv("NVIDIA_DATASETS_URL", "http://nemo.test"),
description="Base URL for the NeMo Dataset API",
)
# warning for default values
def __post_init__(self):
default_values = []
if os.getenv("NVIDIA_PROJECT_ID") is None:
default_values.append("project_id='test-project'")
if os.getenv("NVIDIA_DATASET_NAMESPACE") is None:
default_values.append("dataset_namespace='default'")
if os.getenv("NVIDIA_ACCESS_POLICIES") is None:
default_values.append("access_policies='{}'")
if os.getenv("NVIDIA_DATASETS_URL") is None:
default_values.append("datasets_url='http://nemo.test'")
if default_values:
warnings.warn(
f"Using default values: {', '.join(default_values)}. \
Please set the environment variables to avoid this default behavior.",
stacklevel=2,
)
@classmethod
def sample_run_config(cls, **kwargs) -> Dict[str, Any]:
return {
"api_key": "${env.NVIDIA_API_KEY:}",
"user_id": "${env.NVIDIA_USER_ID:llama-stack-user}",
"dataset_namespace": "${env.NVIDIA_DATASET_NAMESPACE:default}",
"access_policies": "${env.NVIDIA_ACCESS_POLICIES:}",
"project_id": "${env.NVIDIA_PROJECT_ID:test-project}",
"customizer_url": "${env.NVIDIA_CUSTOMIZER_URL:}",
"output_model_dir": "${env.NVIDIA_OUTPUT_MODEL_DIR:test-example-model@v1}",
}

View file

@ -0,0 +1,148 @@
# 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 datetime import datetime
from typing import Any, Dict, Literal, Optional
import aiohttp
from llama_stack.apis.common.content_types import URL
from llama_stack.apis.common.type_system import ParamType
from llama_stack.apis.datasets.datasets import Dataset, ListDatasetsResponse
from llama_stack.apis.resource import ResourceType
from llama_stack.schema_utils import webmethod
from .config import NvidiaDatasetConfig
class NvidiaDatasetAdapter:
"""Nvidia NeMo Dataset API."""
type: Literal[ResourceType.dataset.value] = ResourceType.dataset.value
def __init__(self, config: NvidiaDatasetConfig):
self.config = config
self.headers = {}
if config.api_key:
self.headers["Authorization"] = f"Bearer {config.api_key}"
async def _make_request(
self,
method: str,
path: str,
headers: Optional[Dict[str, Any]] = None,
params: Optional[Dict[str, Any]] = None,
json: Optional[Dict[str, Any]] = None,
**kwargs,
) -> Dict[str, Any]:
"""Helper method to make HTTP requests to the Customizer API."""
url = f"{self.config.datasets_url}{path}"
request_headers = self.headers.copy() # Create a copy to avoid modifying the original
if headers:
request_headers.update(headers)
# Add content-type header for JSON requests
if json and "Content-Type" not in request_headers:
request_headers["Content-Type"] = "application/json"
async with aiohttp.ClientSession(headers=request_headers) as session:
async with session.request(method, url, params=params, json=json, **kwargs) as response:
if response.status >= 400:
error_data = await response.json()
raise Exception(f"API request failed: {error_data}")
return await response.json()
@webmethod(route="/datasets", method="POST")
async def register_dataset(
self,
dataset_id: str,
dataset_schema: Dict[str, ParamType],
url: URL,
provider_dataset_id: Optional[str] = None,
provider_id: Optional[str] = None,
metadata: Optional[Dict[str, Any]] = None,
) -> None:
"""Register a new dataset.
Args:
dataset_id: The ID of the dataset.
dataset_schema: The schema of the dataset.
url: The URL of the dataset.
provider_dataset_id: The ID of the provider dataset.
provider_id: The ID of the provider.
metadata: The metadata of the dataset.
Returns:
None
"""
...
@webmethod(route="/datasets/{dataset_id:namespace}", method="GET")
async def get_dataset(
self,
dataset_id: str,
) -> Optional[Dataset]:
dataset_id, namespace = dataset_id.split(":")
dataset = await self._make_request(
method="GET",
path=f"/v1/datasets/{namespace}/{dataset_id}",
)
created_at = datetime.fromisoformat(dataset.pop("created_at")) if "created_at" in dataset else datetime.now()
identifier = dataset.pop("name")
url = URL(uri=dataset.pop("files_url"))
return Dataset(
identifier=identifier,
provider_id="nvidia", # confirm this
url=url,
dataset_schema={}, # ToDo: get schema from the dataset
created_at=created_at,
metadata=dataset,
)
@webmethod(route="/datasets", method="GET")
async def list_datasets(
self,
) -> ListDatasetsResponse:
## ToDo: add pagination
response = await self._make_request(method="GET", path="/v1/datasets")
datasets = []
for dataset in response["data"]:
created_at = (
datetime.fromisoformat(dataset.pop("created_at")) if "created_at" in dataset else datetime.now()
)
identifier = dataset.pop("name")
url = URL(uri=dataset.pop("files_url"))
datasets.append(
Dataset(
identifier=identifier,
provider_id="nvidia", # confirm this
url=url,
dataset_schema={},
created_at=created_at,
metadata=dataset,
)
) # add remaining fields as metadata
return ListDatasetsResponse(data=datasets)
@webmethod(route="/datasets/{dataset_id:path}", method="POST")
async def update_dataset(
self,
dataset_id: str,
dataset_schema: Dict[str, ParamType],
url: URL,
provider_dataset_id: Optional[str] = None,
provider_id: Optional[str] = None,
metadata: Optional[Dict[str, Any]] = None,
) -> None: ...
@webmethod(route="/datasets/{dataset_id:path}", method="DELETE")
async def unregister_dataset(
self,
dataset_id: str,
namespace: Optional[str] = "default",
) -> None: ...