structure saas with tools
This commit is contained in:
Davidson Gomes
@@ -0,0 +1,210 @@
|
||||
"""
|
||||
Azure Batches API Handler
|
||||
"""
|
||||
|
||||
from typing import Any, Coroutine, Optional, Union, cast
|
||||
|
||||
import httpx
|
||||
|
||||
from litellm.llms.azure.azure import AsyncAzureOpenAI, AzureOpenAI
|
||||
from litellm.types.llms.openai import (
|
||||
Batch,
|
||||
CancelBatchRequest,
|
||||
CreateBatchRequest,
|
||||
RetrieveBatchRequest,
|
||||
)
|
||||
from litellm.types.utils import LiteLLMBatch
|
||||
|
||||
from ..common_utils import BaseAzureLLM
|
||||
|
||||
|
||||
class AzureBatchesAPI(BaseAzureLLM):
|
||||
"""
|
||||
Azure methods to support for batches
|
||||
- create_batch()
|
||||
- retrieve_batch()
|
||||
- cancel_batch()
|
||||
- list_batch()
|
||||
"""
|
||||
|
||||
def __init__(self) -> None:
|
||||
super().__init__()
|
||||
|
||||
async def acreate_batch(
|
||||
self,
|
||||
create_batch_data: CreateBatchRequest,
|
||||
azure_client: AsyncAzureOpenAI,
|
||||
) -> LiteLLMBatch:
|
||||
response = await azure_client.batches.create(**create_batch_data)
|
||||
return LiteLLMBatch(**response.model_dump())
|
||||
|
||||
def create_batch(
|
||||
self,
|
||||
_is_async: bool,
|
||||
create_batch_data: CreateBatchRequest,
|
||||
api_key: Optional[str],
|
||||
api_base: Optional[str],
|
||||
api_version: Optional[str],
|
||||
timeout: Union[float, httpx.Timeout],
|
||||
max_retries: Optional[int],
|
||||
client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None,
|
||||
litellm_params: Optional[dict] = None,
|
||||
) -> Union[LiteLLMBatch, Coroutine[Any, Any, LiteLLMBatch]]:
|
||||
azure_client: Optional[
|
||||
Union[AzureOpenAI, AsyncAzureOpenAI]
|
||||
] = self.get_azure_openai_client(
|
||||
api_key=api_key,
|
||||
api_base=api_base,
|
||||
api_version=api_version,
|
||||
client=client,
|
||||
_is_async=_is_async,
|
||||
litellm_params=litellm_params or {},
|
||||
)
|
||||
if azure_client is None:
|
||||
raise ValueError(
|
||||
"OpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
|
||||
)
|
||||
|
||||
if _is_async is True:
|
||||
if not isinstance(azure_client, AsyncAzureOpenAI):
|
||||
raise ValueError(
|
||||
"OpenAI client is not an instance of AsyncOpenAI. Make sure you passed an AsyncOpenAI client."
|
||||
)
|
||||
return self.acreate_batch( # type: ignore
|
||||
create_batch_data=create_batch_data, azure_client=azure_client
|
||||
)
|
||||
response = cast(AzureOpenAI, azure_client).batches.create(**create_batch_data)
|
||||
return LiteLLMBatch(**response.model_dump())
|
||||
|
||||
async def aretrieve_batch(
|
||||
self,
|
||||
retrieve_batch_data: RetrieveBatchRequest,
|
||||
client: AsyncAzureOpenAI,
|
||||
) -> LiteLLMBatch:
|
||||
response = await client.batches.retrieve(**retrieve_batch_data)
|
||||
return LiteLLMBatch(**response.model_dump())
|
||||
|
||||
def retrieve_batch(
|
||||
self,
|
||||
_is_async: bool,
|
||||
retrieve_batch_data: RetrieveBatchRequest,
|
||||
api_key: Optional[str],
|
||||
api_base: Optional[str],
|
||||
api_version: Optional[str],
|
||||
timeout: Union[float, httpx.Timeout],
|
||||
max_retries: Optional[int],
|
||||
client: Optional[AzureOpenAI] = None,
|
||||
litellm_params: Optional[dict] = None,
|
||||
):
|
||||
azure_client: Optional[
|
||||
Union[AzureOpenAI, AsyncAzureOpenAI]
|
||||
] = self.get_azure_openai_client(
|
||||
api_key=api_key,
|
||||
api_base=api_base,
|
||||
api_version=api_version,
|
||||
client=client,
|
||||
_is_async=_is_async,
|
||||
litellm_params=litellm_params or {},
|
||||
)
|
||||
if azure_client is None:
|
||||
raise ValueError(
|
||||
"OpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
|
||||
)
|
||||
|
||||
if _is_async is True:
|
||||
if not isinstance(azure_client, AsyncAzureOpenAI):
|
||||
raise ValueError(
|
||||
"OpenAI client is not an instance of AsyncOpenAI. Make sure you passed an AsyncOpenAI client."
|
||||
)
|
||||
return self.aretrieve_batch( # type: ignore
|
||||
retrieve_batch_data=retrieve_batch_data, client=azure_client
|
||||
)
|
||||
response = cast(AzureOpenAI, azure_client).batches.retrieve(
|
||||
**retrieve_batch_data
|
||||
)
|
||||
return LiteLLMBatch(**response.model_dump())
|
||||
|
||||
async def acancel_batch(
|
||||
self,
|
||||
cancel_batch_data: CancelBatchRequest,
|
||||
client: AsyncAzureOpenAI,
|
||||
) -> Batch:
|
||||
response = await client.batches.cancel(**cancel_batch_data)
|
||||
return response
|
||||
|
||||
def cancel_batch(
|
||||
self,
|
||||
_is_async: bool,
|
||||
cancel_batch_data: CancelBatchRequest,
|
||||
api_key: Optional[str],
|
||||
api_base: Optional[str],
|
||||
api_version: Optional[str],
|
||||
timeout: Union[float, httpx.Timeout],
|
||||
max_retries: Optional[int],
|
||||
client: Optional[AzureOpenAI] = None,
|
||||
litellm_params: Optional[dict] = None,
|
||||
):
|
||||
azure_client: Optional[
|
||||
Union[AzureOpenAI, AsyncAzureOpenAI]
|
||||
] = self.get_azure_openai_client(
|
||||
api_key=api_key,
|
||||
api_base=api_base,
|
||||
api_version=api_version,
|
||||
client=client,
|
||||
_is_async=_is_async,
|
||||
litellm_params=litellm_params or {},
|
||||
)
|
||||
if azure_client is None:
|
||||
raise ValueError(
|
||||
"OpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
|
||||
)
|
||||
response = azure_client.batches.cancel(**cancel_batch_data)
|
||||
return response
|
||||
|
||||
async def alist_batches(
|
||||
self,
|
||||
client: AsyncAzureOpenAI,
|
||||
after: Optional[str] = None,
|
||||
limit: Optional[int] = None,
|
||||
):
|
||||
response = await client.batches.list(after=after, limit=limit) # type: ignore
|
||||
return response
|
||||
|
||||
def list_batches(
|
||||
self,
|
||||
_is_async: bool,
|
||||
api_key: Optional[str],
|
||||
api_base: Optional[str],
|
||||
api_version: Optional[str],
|
||||
timeout: Union[float, httpx.Timeout],
|
||||
max_retries: Optional[int],
|
||||
after: Optional[str] = None,
|
||||
limit: Optional[int] = None,
|
||||
client: Optional[AzureOpenAI] = None,
|
||||
litellm_params: Optional[dict] = None,
|
||||
):
|
||||
azure_client: Optional[
|
||||
Union[AzureOpenAI, AsyncAzureOpenAI]
|
||||
] = self.get_azure_openai_client(
|
||||
api_key=api_key,
|
||||
api_base=api_base,
|
||||
api_version=api_version,
|
||||
client=client,
|
||||
_is_async=_is_async,
|
||||
litellm_params=litellm_params or {},
|
||||
)
|
||||
if azure_client is None:
|
||||
raise ValueError(
|
||||
"OpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
|
||||
)
|
||||
|
||||
if _is_async is True:
|
||||
if not isinstance(azure_client, AsyncAzureOpenAI):
|
||||
raise ValueError(
|
||||
"OpenAI client is not an instance of AsyncOpenAI. Make sure you passed an AsyncOpenAI client."
|
||||
)
|
||||
return self.alist_batches( # type: ignore
|
||||
client=azure_client, after=after, limit=limit
|
||||
)
|
||||
response = azure_client.batches.list(after=after, limit=limit) # type: ignore
|
||||
return response
|
||||
Reference in New Issue
Block a user