mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-25 10:44:24 +00:00
421 lines
14 KiB
Python
421 lines
14 KiB
Python
"""
|
|
Main File for Batches API implementation
|
|
|
|
https://platform.openai.com/docs/api-reference/batch
|
|
|
|
- create_batch()
|
|
- retrieve_batch()
|
|
- cancel_batch()
|
|
- list_batch()
|
|
|
|
"""
|
|
|
|
import os
|
|
import asyncio
|
|
from functools import partial
|
|
import contextvars
|
|
from typing import Literal, Optional, Dict, Coroutine, Any, Union
|
|
import httpx
|
|
|
|
import litellm
|
|
from litellm import client
|
|
from litellm.utils import supports_httpx_timeout
|
|
from ..types.router import *
|
|
from ..llms.openai import OpenAIBatchesAPI, OpenAIFilesAPI
|
|
from ..types.llms.openai import (
|
|
CreateBatchRequest,
|
|
RetrieveBatchRequest,
|
|
CancelBatchRequest,
|
|
CreateFileRequest,
|
|
FileTypes,
|
|
FileObject,
|
|
Batch,
|
|
)
|
|
|
|
####### ENVIRONMENT VARIABLES ###################
|
|
openai_batches_instance = OpenAIBatchesAPI()
|
|
openai_files_instance = OpenAIFilesAPI()
|
|
#################################################
|
|
|
|
|
|
async def acreate_file(
|
|
file: FileTypes,
|
|
purpose: Literal["assistants", "batch", "fine-tune"],
|
|
custom_llm_provider: Literal["openai"] = "openai",
|
|
extra_headers: Optional[Dict[str, str]] = None,
|
|
extra_body: Optional[Dict[str, str]] = None,
|
|
**kwargs,
|
|
) -> Coroutine[Any, Any, FileObject]:
|
|
"""
|
|
Files are used to upload documents that can be used with features like Assistants, Fine-tuning, and Batch API.
|
|
|
|
LiteLLM Equivalent of POST: POST https://api.openai.com/v1/files
|
|
"""
|
|
try:
|
|
loop = asyncio.get_event_loop()
|
|
kwargs["acreate_file"] = True
|
|
|
|
# Use a partial function to pass your keyword arguments
|
|
func = partial(
|
|
create_file,
|
|
file,
|
|
purpose,
|
|
custom_llm_provider,
|
|
extra_headers,
|
|
extra_body,
|
|
**kwargs,
|
|
)
|
|
|
|
# Add the context to the function
|
|
ctx = contextvars.copy_context()
|
|
func_with_context = partial(ctx.run, func)
|
|
init_response = await loop.run_in_executor(None, func_with_context)
|
|
if asyncio.iscoroutine(init_response):
|
|
response = await init_response
|
|
else:
|
|
response = init_response # type: ignore
|
|
|
|
return response
|
|
except Exception as e:
|
|
raise e
|
|
|
|
|
|
def create_file(
|
|
file: FileTypes,
|
|
purpose: Literal["assistants", "batch", "fine-tune"],
|
|
custom_llm_provider: Literal["openai"] = "openai",
|
|
extra_headers: Optional[Dict[str, str]] = None,
|
|
extra_body: Optional[Dict[str, str]] = None,
|
|
**kwargs,
|
|
) -> Union[FileObject | Coroutine[Any, Any, FileObject]]:
|
|
"""
|
|
Files are used to upload documents that can be used with features like Assistants, Fine-tuning, and Batch API.
|
|
|
|
LiteLLM Equivalent of POST: POST https://api.openai.com/v1/files
|
|
"""
|
|
try:
|
|
optional_params = GenericLiteLLMParams(**kwargs)
|
|
if custom_llm_provider == "openai":
|
|
# for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there
|
|
api_base = (
|
|
optional_params.api_base
|
|
or litellm.api_base
|
|
or os.getenv("OPENAI_API_BASE")
|
|
or "https://api.openai.com/v1"
|
|
)
|
|
organization = (
|
|
optional_params.organization
|
|
or litellm.organization
|
|
or os.getenv("OPENAI_ORGANIZATION", None)
|
|
or None # default - https://github.com/openai/openai-python/blob/284c1799070c723c6a553337134148a7ab088dd8/openai/util.py#L105
|
|
)
|
|
# set API KEY
|
|
api_key = (
|
|
optional_params.api_key
|
|
or litellm.api_key # for deepinfra/perplexity/anyscale we check in get_llm_provider and pass in the api key from there
|
|
or litellm.openai_key
|
|
or os.getenv("OPENAI_API_KEY")
|
|
)
|
|
### TIMEOUT LOGIC ###
|
|
timeout = (
|
|
optional_params.timeout or kwargs.get("request_timeout", 600) or 600
|
|
)
|
|
# set timeout for 10 minutes by default
|
|
|
|
if (
|
|
timeout is not None
|
|
and isinstance(timeout, httpx.Timeout)
|
|
and supports_httpx_timeout(custom_llm_provider) == False
|
|
):
|
|
read_timeout = timeout.read or 600
|
|
timeout = read_timeout # default 10 min timeout
|
|
elif timeout is not None and not isinstance(timeout, httpx.Timeout):
|
|
timeout = float(timeout) # type: ignore
|
|
elif timeout is None:
|
|
timeout = 600.0
|
|
|
|
_create_file_request = CreateFileRequest(
|
|
file=file,
|
|
purpose=purpose,
|
|
extra_headers=extra_headers,
|
|
extra_body=extra_body,
|
|
)
|
|
|
|
_is_async = kwargs.pop("acreate_file", False) is True
|
|
|
|
response = openai_files_instance.create_file(
|
|
_is_async=_is_async,
|
|
api_base=api_base,
|
|
api_key=api_key,
|
|
timeout=timeout,
|
|
max_retries=optional_params.max_retries,
|
|
organization=organization,
|
|
create_file_data=_create_file_request,
|
|
)
|
|
else:
|
|
raise litellm.exceptions.BadRequestError(
|
|
message="LiteLLM doesn't support {} for 'create_batch'. Only 'openai' is supported.".format(
|
|
custom_llm_provider
|
|
),
|
|
model="n/a",
|
|
llm_provider=custom_llm_provider,
|
|
response=httpx.Response(
|
|
status_code=400,
|
|
content="Unsupported provider",
|
|
request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"), # type: ignore
|
|
),
|
|
)
|
|
return response
|
|
except Exception as e:
|
|
raise e
|
|
|
|
|
|
async def acreate_batch(
|
|
completion_window: Literal["24h"],
|
|
endpoint: Literal["/v1/chat/completions", "/v1/embeddings", "/v1/completions"],
|
|
input_file_id: str,
|
|
custom_llm_provider: Literal["openai"] = "openai",
|
|
metadata: Optional[Dict[str, str]] = None,
|
|
extra_headers: Optional[Dict[str, str]] = None,
|
|
extra_body: Optional[Dict[str, str]] = None,
|
|
**kwargs,
|
|
) -> Coroutine[Any, Any, Batch]:
|
|
"""
|
|
Creates and executes a batch from an uploaded file of request
|
|
|
|
LiteLLM Equivalent of POST: https://api.openai.com/v1/batches
|
|
"""
|
|
try:
|
|
loop = asyncio.get_event_loop()
|
|
kwargs["acreate_batch"] = True
|
|
|
|
# Use a partial function to pass your keyword arguments
|
|
func = partial(
|
|
create_batch,
|
|
completion_window,
|
|
endpoint,
|
|
input_file_id,
|
|
custom_llm_provider,
|
|
metadata,
|
|
extra_headers,
|
|
extra_body,
|
|
**kwargs,
|
|
)
|
|
|
|
# Add the context to the function
|
|
ctx = contextvars.copy_context()
|
|
func_with_context = partial(ctx.run, func)
|
|
init_response = await loop.run_in_executor(None, func_with_context)
|
|
if asyncio.iscoroutine(init_response):
|
|
response = await init_response
|
|
else:
|
|
response = init_response # type: ignore
|
|
|
|
return response
|
|
except Exception as e:
|
|
raise e
|
|
|
|
|
|
def create_batch(
|
|
completion_window: Literal["24h"],
|
|
endpoint: Literal["/v1/chat/completions", "/v1/embeddings", "/v1/completions"],
|
|
input_file_id: str,
|
|
custom_llm_provider: Literal["openai"] = "openai",
|
|
metadata: Optional[Dict[str, str]] = None,
|
|
extra_headers: Optional[Dict[str, str]] = None,
|
|
extra_body: Optional[Dict[str, str]] = None,
|
|
**kwargs,
|
|
) -> Union[Batch, Coroutine[Any, Any, Batch]]:
|
|
"""
|
|
Creates and executes a batch from an uploaded file of request
|
|
|
|
LiteLLM Equivalent of POST: https://api.openai.com/v1/batches
|
|
"""
|
|
try:
|
|
optional_params = GenericLiteLLMParams(**kwargs)
|
|
if custom_llm_provider == "openai":
|
|
|
|
# for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there
|
|
api_base = (
|
|
optional_params.api_base
|
|
or litellm.api_base
|
|
or os.getenv("OPENAI_API_BASE")
|
|
or "https://api.openai.com/v1"
|
|
)
|
|
organization = (
|
|
optional_params.organization
|
|
or litellm.organization
|
|
or os.getenv("OPENAI_ORGANIZATION", None)
|
|
or None # default - https://github.com/openai/openai-python/blob/284c1799070c723c6a553337134148a7ab088dd8/openai/util.py#L105
|
|
)
|
|
# set API KEY
|
|
api_key = (
|
|
optional_params.api_key
|
|
or litellm.api_key # for deepinfra/perplexity/anyscale we check in get_llm_provider and pass in the api key from there
|
|
or litellm.openai_key
|
|
or os.getenv("OPENAI_API_KEY")
|
|
)
|
|
### TIMEOUT LOGIC ###
|
|
timeout = (
|
|
optional_params.timeout or kwargs.get("request_timeout", 600) or 600
|
|
)
|
|
# set timeout for 10 minutes by default
|
|
|
|
if (
|
|
timeout is not None
|
|
and isinstance(timeout, httpx.Timeout)
|
|
and supports_httpx_timeout(custom_llm_provider) == False
|
|
):
|
|
read_timeout = timeout.read or 600
|
|
timeout = read_timeout # default 10 min timeout
|
|
elif timeout is not None and not isinstance(timeout, httpx.Timeout):
|
|
timeout = float(timeout) # type: ignore
|
|
elif timeout is None:
|
|
timeout = 600.0
|
|
|
|
_is_async = kwargs.pop("acreate_batch", False) is True
|
|
|
|
_create_batch_request = CreateBatchRequest(
|
|
completion_window=completion_window,
|
|
endpoint=endpoint,
|
|
input_file_id=input_file_id,
|
|
metadata=metadata,
|
|
extra_headers=extra_headers,
|
|
extra_body=extra_body,
|
|
)
|
|
|
|
response = openai_batches_instance.create_batch(
|
|
api_base=api_base,
|
|
api_key=api_key,
|
|
organization=organization,
|
|
create_batch_data=_create_batch_request,
|
|
timeout=timeout,
|
|
max_retries=optional_params.max_retries,
|
|
_is_async=_is_async,
|
|
)
|
|
else:
|
|
raise litellm.exceptions.BadRequestError(
|
|
message="LiteLLM doesn't support {} for 'create_batch'. Only 'openai' is supported.".format(
|
|
custom_llm_provider
|
|
),
|
|
model="n/a",
|
|
llm_provider=custom_llm_provider,
|
|
response=httpx.Response(
|
|
status_code=400,
|
|
content="Unsupported provider",
|
|
request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"), # type: ignore
|
|
),
|
|
)
|
|
return response
|
|
except Exception as e:
|
|
raise e
|
|
|
|
|
|
def retrieve_batch(
|
|
batch_id: str,
|
|
custom_llm_provider: Literal["openai"] = "openai",
|
|
metadata: Optional[Dict[str, str]] = None,
|
|
extra_headers: Optional[Dict[str, str]] = None,
|
|
extra_body: Optional[Dict[str, str]] = None,
|
|
**kwargs,
|
|
):
|
|
"""
|
|
Retrieves a batch.
|
|
|
|
LiteLLM Equivalent of GET https://api.openai.com/v1/batches/{batch_id}
|
|
"""
|
|
try:
|
|
optional_params = GenericLiteLLMParams(**kwargs)
|
|
if custom_llm_provider == "openai":
|
|
|
|
# for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there
|
|
api_base = (
|
|
optional_params.api_base
|
|
or litellm.api_base
|
|
or os.getenv("OPENAI_API_BASE")
|
|
or "https://api.openai.com/v1"
|
|
)
|
|
organization = (
|
|
optional_params.organization
|
|
or litellm.organization
|
|
or os.getenv("OPENAI_ORGANIZATION", None)
|
|
or None # default - https://github.com/openai/openai-python/blob/284c1799070c723c6a553337134148a7ab088dd8/openai/util.py#L105
|
|
)
|
|
# set API KEY
|
|
api_key = (
|
|
optional_params.api_key
|
|
or litellm.api_key # for deepinfra/perplexity/anyscale we check in get_llm_provider and pass in the api key from there
|
|
or litellm.openai_key
|
|
or os.getenv("OPENAI_API_KEY")
|
|
)
|
|
### TIMEOUT LOGIC ###
|
|
timeout = (
|
|
optional_params.timeout or kwargs.get("request_timeout", 600) or 600
|
|
)
|
|
# set timeout for 10 minutes by default
|
|
|
|
if (
|
|
timeout is not None
|
|
and isinstance(timeout, httpx.Timeout)
|
|
and supports_httpx_timeout(custom_llm_provider) == False
|
|
):
|
|
read_timeout = timeout.read or 600
|
|
timeout = read_timeout # default 10 min timeout
|
|
elif timeout is not None and not isinstance(timeout, httpx.Timeout):
|
|
timeout = float(timeout) # type: ignore
|
|
elif timeout is None:
|
|
timeout = 600.0
|
|
|
|
_retrieve_batch_request = RetrieveBatchRequest(
|
|
batch_id=batch_id,
|
|
extra_headers=extra_headers,
|
|
extra_body=extra_body,
|
|
)
|
|
|
|
_is_async = kwargs.pop("aretrieve_batch", False) is True
|
|
|
|
response = openai_batches_instance.retrieve_batch(
|
|
_is_async=_is_async,
|
|
retrieve_batch_data=_retrieve_batch_request,
|
|
api_base=api_base,
|
|
api_key=api_key,
|
|
organization=organization,
|
|
timeout=timeout,
|
|
max_retries=optional_params.max_retries,
|
|
)
|
|
else:
|
|
raise litellm.exceptions.BadRequestError(
|
|
message="LiteLLM doesn't support {} for 'create_batch'. Only 'openai' is supported.".format(
|
|
custom_llm_provider
|
|
),
|
|
model="n/a",
|
|
llm_provider=custom_llm_provider,
|
|
response=httpx.Response(
|
|
status_code=400,
|
|
content="Unsupported provider",
|
|
request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"), # type: ignore
|
|
),
|
|
)
|
|
return response
|
|
except Exception as e:
|
|
raise e
|
|
|
|
|
|
def cancel_batch():
|
|
pass
|
|
|
|
|
|
def list_batch():
|
|
pass
|
|
|
|
|
|
async def aretrieve_batch():
|
|
pass
|
|
|
|
|
|
async def acancel_batch():
|
|
pass
|
|
|
|
|
|
async def alist_batch():
|
|
pass
|