mirror of
https://github.com/BerriAI/litellm.git
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feat - import batches in __init__
This commit is contained in:
Ishaan Jaff
parent
04aace73e6
commit
4dc7bfebd4
5 changed files with 539 additions and 20 deletions
239
litellm/batches/main.py
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239
litellm/batches/main.py
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"""
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Main File for Batches API implementation
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https://platform.openai.com/docs/api-reference/batch
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- create_batch()
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- retrieve_batch()
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- cancel_batch()
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- list_batch()
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"""
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from typing import Iterable
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import os
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import litellm
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from openai import OpenAI
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import httpx
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from litellm import client
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from litellm.utils import supports_httpx_timeout
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from ..types.router import *
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from ..llms.openai import OpenAIBatchesAPI, OpenAIFilesAPI
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from ..types.llms.openai import (
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CreateBatchRequest,
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RetrieveBatchRequest,
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CancelBatchRequest,
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CreateFileRequest,
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FileTypes,
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FileObject,
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)
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from typing import Literal, Optional, Dict
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####### ENVIRONMENT VARIABLES ###################
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openai_batches_instance = OpenAIBatchesAPI()
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openai_files_instance = OpenAIFilesAPI()
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#################################################
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def create_file(
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file: FileTypes,
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purpose: Literal["assistants", "batch", "fine-tune"],
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custom_llm_provider: Literal["openai"] = "openai",
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extra_headers: Optional[Dict[str, str]] = None,
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extra_body: Optional[Dict[str, str]] = None,
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**kwargs,
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) -> FileObject:
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try:
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optional_params = GenericLiteLLMParams(**kwargs)
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if custom_llm_provider == "openai":
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# for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there
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api_base = (
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optional_params.api_base
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or litellm.api_base
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or os.getenv("OPENAI_API_BASE")
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or "https://api.openai.com/v1"
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)
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organization = (
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optional_params.organization
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or litellm.organization
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or os.getenv("OPENAI_ORGANIZATION", None)
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or None # default - https://github.com/openai/openai-python/blob/284c1799070c723c6a553337134148a7ab088dd8/openai/util.py#L105
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)
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# set API KEY
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api_key = (
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optional_params.api_key
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or litellm.api_key # for deepinfra/perplexity/anyscale we check in get_llm_provider and pass in the api key from there
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or litellm.openai_key
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or os.getenv("OPENAI_API_KEY")
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)
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### TIMEOUT LOGIC ###
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timeout = (
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optional_params.timeout or kwargs.get("request_timeout", 600) or 600
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)
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# set timeout for 10 minutes by default
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if (
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timeout is not None
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and isinstance(timeout, httpx.Timeout)
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and supports_httpx_timeout(custom_llm_provider) == False
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):
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read_timeout = timeout.read or 600
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timeout = read_timeout # default 10 min timeout
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elif timeout is not None and not isinstance(timeout, httpx.Timeout):
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timeout = float(timeout) # type: ignore
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elif timeout is None:
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timeout = 600.0
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_create_file_request = CreateFileRequest(
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file=file,
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purpose=purpose,
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extra_headers=extra_headers,
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extra_body=extra_body,
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)
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response = openai_files_instance.create_file(
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api_base=api_base,
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api_key=api_key,
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timeout=timeout,
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max_retries=optional_params.max_retries,
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organization=organization,
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create_file_data=_create_file_request,
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)
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else:
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raise litellm.exceptions.BadRequestError(
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message="LiteLLM doesn't support {} for 'create_batch'. Only 'openai' is supported.".format(
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custom_llm_provider
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),
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model="n/a",
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llm_provider=custom_llm_provider,
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response=httpx.Response(
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status_code=400,
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content="Unsupported provider",
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request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"), # type: ignore
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),
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)
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return response
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except Exception as e:
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raise e
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def create_batch(
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completion_window: Literal["24h"],
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endpoint: Literal["/v1/chat/completions", "/v1/embeddings", "/v1/completions"],
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input_file_id: str,
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custom_llm_provider: Literal["openai"] = "openai",
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metadata: Optional[Dict[str, str]] = None,
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extra_headers: Optional[Dict[str, str]] = None,
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extra_body: Optional[Dict[str, str]] = None,
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**kwargs,
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):
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"""
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Creates and executes a batch from an uploaded file of request
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LiteLLM Equivalent of POST: https://api.openai.com/v1/batches
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"""
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try:
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optional_params = GenericLiteLLMParams(**kwargs)
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if custom_llm_provider == "openai":
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# for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there
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api_base = (
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optional_params.api_base
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or litellm.api_base
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or os.getenv("OPENAI_API_BASE")
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or "https://api.openai.com/v1"
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)
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organization = (
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optional_params.organization
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or litellm.organization
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or os.getenv("OPENAI_ORGANIZATION", None)
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or None # default - https://github.com/openai/openai-python/blob/284c1799070c723c6a553337134148a7ab088dd8/openai/util.py#L105
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)
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# set API KEY
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api_key = (
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optional_params.api_key
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or litellm.api_key # for deepinfra/perplexity/anyscale we check in get_llm_provider and pass in the api key from there
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or litellm.openai_key
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or os.getenv("OPENAI_API_KEY")
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)
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### TIMEOUT LOGIC ###
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timeout = (
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optional_params.timeout or kwargs.get("request_timeout", 600) or 600
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)
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# set timeout for 10 minutes by default
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if (
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timeout is not None
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and isinstance(timeout, httpx.Timeout)
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and supports_httpx_timeout(custom_llm_provider) == False
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):
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read_timeout = timeout.read or 600
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timeout = read_timeout # default 10 min timeout
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elif timeout is not None and not isinstance(timeout, httpx.Timeout):
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timeout = float(timeout) # type: ignore
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elif timeout is None:
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timeout = 600.0
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_create_batch_request = CreateBatchRequest(
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completion_window=completion_window,
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endpoint=endpoint,
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input_file_id=input_file_id,
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metadata=metadata,
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extra_headers=extra_headers,
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extra_body=extra_body,
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)
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response = openai_batches_instance.create_batch(
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api_base=api_base,
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api_key=api_key,
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organization=organization,
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create_batch_data=_create_batch_request,
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timeout=timeout,
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max_retries=optional_params.max_retries,
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)
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else:
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raise litellm.exceptions.BadRequestError(
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message="LiteLLM doesn't support {} for 'create_batch'. Only 'openai' is supported.".format(
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custom_llm_provider
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),
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model="n/a",
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llm_provider=custom_llm_provider,
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response=httpx.Response(
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status_code=400,
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content="Unsupported provider",
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request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"), # type: ignore
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),
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)
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return response
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except Exception as e:
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raise e
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def retrieve_batch():
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pass
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def cancel_batch():
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pass
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def list_batch():
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pass
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# Async Functions
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async def acreate_batch():
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pass
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async def aretrieve_batch():
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pass
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async def acancel_batch():
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pass
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async def alist_batch():
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pass
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