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test: set request timeout at request level

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This commit is contained in:
Krrish Dholakia 2023-11-15 17:41:04 -08:00
parent eda4401c71
commit 9fd7c5b343
6 changed files with 63 additions and 38 deletions
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2
litellm/__init__.py
View file

@ -19,7 +19,7 @@ telemetry = True
max_tokens = 256 # OpenAI Defaults
drop_params = False
retry = True
request_timeout: Optional[float] = None
request_timeout: Optional[float] = 600
api_key: Optional[str] = None
openai_key: Optional[str] = None
azure_key: Optional[str] = None

40
litellm/llms/azure.py
View file

@ -4,6 +4,7 @@ from .base import BaseLLM
from litellm.utils import ModelResponse, Choices, Message, CustomStreamWrapper, convert_to_model_response_object
from typing import Callable, Optional
from litellm import OpenAIConfig
import litellm
import httpx
class AzureOpenAIError(Exception):
@ -105,6 +106,8 @@ class AzureChatCompletion(BaseLLM):
acompletion: bool = False,
headers: Optional[dict]=None):
super().completion()
if self._client_session is None:
self._client_session = self.create_client_session()
exception_mapping_worked = False
try:
if headers is None:
@ -140,10 +143,11 @@ class AzureChatCompletion(BaseLLM):
elif "stream" in optional_params and optional_params["stream"] == True:
return self.streaming(logging_obj=logging_obj, api_base=api_base, data=data, headers=headers, model_response=model_response, model=model)
else:
response = httpx.post(
response = self._client_session.post(
url=api_base,
json=data,
headers=headers,
timeout=litellm.request_timeout
)
if response.status_code != 200:
raise AzureOpenAIError(status_code=response.status_code, message=response.text)
@ -157,15 +161,17 @@ class AzureChatCompletion(BaseLLM):
raise e
async def acompletion(self, api_base: str, data: dict, headers: dict, model_response: ModelResponse):
if self._aclient_session is None:
self._aclient_session = self.create_aclient_session()
client = self._aclient_session
try:
async with httpx.AsyncClient() as client:
response = await client.post(api_base, json=data, headers=headers)
response_json = response.json()
if response.status_code != 200:
raise AzureOpenAIError(status_code=response.status_code, message=response.text, request=response.request, response=response)
## RESPONSE OBJECT
return convert_to_model_response_object(response_object=response_json, model_response_object=model_response)
response = await client.post(api_base, json=data, headers=headers, timeout=litellm.request_timeout)
response_json = response.json()
if response.status_code != 200:
raise AzureOpenAIError(status_code=response.status_code, message=response.text, request=response.request, response=response)
## RESPONSE OBJECT
return convert_to_model_response_object(response_object=response_json, model_response_object=model_response)
except Exception as e:
if isinstance(e,httpx.TimeoutException):
raise AzureOpenAIError(status_code=500, message="Request Timeout Error")
@ -182,11 +188,14 @@ class AzureChatCompletion(BaseLLM):
model_response: ModelResponse,
model: str
):
with httpx.stream(
if self._client_session is None:
self._client_session = self.create_client_session()
with self._client_session.stream(
url=f"{api_base}",
json=data,
headers=headers,
method="POST"
method="POST",
timeout=litellm.request_timeout
) as response:
if response.status_code != 200:
raise AzureOpenAIError(status_code=response.status_code, message="An error occurred while streaming")
@ -203,12 +212,15 @@ class AzureChatCompletion(BaseLLM):
headers: dict,
model_response: ModelResponse,
model: str):
client = httpx.AsyncClient()
if self._aclient_session is None:
self._aclient_session = self.create_aclient_session()
client = self._aclient_session
async with client.stream(
url=f"{api_base}",
json=data,
headers=headers,
method="POST"
method="POST",
timeout=litellm.request_timeout
) as response:
if response.status_code != 200:
raise AzureOpenAIError(status_code=response.status_code, message=response.text)
@ -253,7 +265,7 @@ class AzureChatCompletion(BaseLLM):
)
## COMPLETION CALL
response = self._client_session.post(
api_base, headers=headers, json=data
api_base, headers=headers, json=data, timeout=litellm.request_timeout
)
## LOGGING
logging_obj.post_call(

4
litellm/llms/base.py
View file

@ -9,7 +9,7 @@ class BaseLLM:
if litellm.client_session:
_client_session = litellm.client_session
else:
_client_session = httpx.Client(timeout=litellm.request_timeout)
_client_session = httpx.Client()
return _client_session
@ -17,7 +17,7 @@ class BaseLLM:
if litellm.aclient_session:
_aclient_session = litellm.aclient_session
else:
_aclient_session = httpx.AsyncClient(timeout=litellm.request_timeout)
_aclient_session = httpx.AsyncClient()
return _aclient_session

49
litellm/llms/openai.py
View file

@ -5,6 +5,7 @@ from .base import BaseLLM
from litellm.utils import ModelResponse, Choices, Message, CustomStreamWrapper, convert_to_model_response_object, Usage
from typing import Callable, Optional
import aiohttp
import litellm
class OpenAIError(Exception):
def __init__(self, status_code, message, request: Optional[httpx.Request]=None, response: Optional[httpx.Response]=None):
@ -223,10 +224,11 @@ class OpenAIChatCompletion(BaseLLM):
elif optional_params.get("stream", False):
return self.streaming(logging_obj=logging_obj, api_base=api_base, data=data, headers=headers, model_response=model_response, model=model)
else:
response = httpx.post(
response = self._client_session.post(
url=api_base,
json=data,
headers=headers,
timeout=litellm.request_timeout
)
if response.status_code != 200:
raise OpenAIError(status_code=response.status_code, message=response.text, request=response.request, response=response)
@ -262,15 +264,18 @@ class OpenAIChatCompletion(BaseLLM):
api_base: str,
data: dict, headers: dict,
model_response: ModelResponse):
kwargs = locals()
if self._aclient_session is None:
self._aclient_session = self.create_aclient_session()
client = self._aclient_session
try:
async with httpx.AsyncClient() as client:
response = await client.post(api_base, json=data, headers=headers)
response_json = response.json()
if response.status_code != 200:
raise OpenAIError(status_code=response.status_code, message=response.text, request=response.request, response=response)
## RESPONSE OBJECT
return convert_to_model_response_object(response_object=response_json, model_response_object=model_response)
response = await client.post(api_base, json=data, headers=headers, timeout=litellm.request_timeout)
response_json = response.json()
if response.status_code != 200:
raise OpenAIError(status_code=response.status_code, message=response.text, request=response.request, response=response)
## RESPONSE OBJECT
return convert_to_model_response_object(response_object=response_json, model_response_object=model_response)
except Exception as e:
if isinstance(e, httpx.TimeoutException):
raise OpenAIError(status_code=500, message="Request Timeout Error")
@ -287,11 +292,14 @@ class OpenAIChatCompletion(BaseLLM):
model_response: ModelResponse,
model: str
):
with httpx.stream(
if self._client_session is None:
self._client_session = self.create_client_session()
with self._client_session.stream(
url=f"{api_base}", # type: ignore
json=data,
headers=headers,
method="POST"
method="POST",
timeout=litellm.request_timeout
) as response:
if response.status_code != 200:
raise OpenAIError(status_code=response.status_code, message=response.text()) # type: ignore
@ -308,12 +316,14 @@ class OpenAIChatCompletion(BaseLLM):
headers: dict,
model_response: ModelResponse,
model: str):
client = httpx.AsyncClient()
async with client.stream(
if self._aclient_session is None:
self._aclient_session = self.create_aclient_session()
async with self._aclient_session.stream(
url=f"{api_base}",
json=data,
headers=headers,
method="POST"
method="POST",
timeout=litellm.request_timeout
) as response:
if response.status_code != 200:
raise OpenAIError(status_code=response.status_code, message=response.text()) # type: ignore
@ -352,7 +362,7 @@ class OpenAIChatCompletion(BaseLLM):
)
## COMPLETION CALL
response = self._client_session.post(
api_base, headers=headers, json=data
api_base, headers=headers, json=data, timeout=litellm.request_timeout
)
## LOGGING
logging_obj.post_call(
@ -483,6 +493,7 @@ class OpenAITextCompletion(BaseLLM):
url=f"{api_base}",
json=data,
headers=headers,
timeout=litellm.request_timeout
)
if response.status_code != 200:
raise OpenAIError(status_code=response.status_code, message=response.text)
@ -513,7 +524,7 @@ class OpenAITextCompletion(BaseLLM):
api_key: str,
model: str):
async with httpx.AsyncClient() as client:
response = await client.post(api_base, json=data, headers=headers)
response = await client.post(api_base, json=data, headers=headers, timeout=litellm.request_timeout)
response_json = response.json()
if response.status_code != 200:
raise OpenAIError(status_code=response.status_code, message=response.text)
@ -544,7 +555,8 @@ class OpenAITextCompletion(BaseLLM):
url=f"{api_base}",
json=data,
headers=headers,
method="POST"
method="POST",
timeout=litellm.request_timeout
) as response:
if response.status_code != 200:
raise OpenAIError(status_code=response.status_code, message=response.text)
@ -565,7 +577,8 @@ class OpenAITextCompletion(BaseLLM):
url=f"{api_base}",
json=data,
headers=headers,
method="POST"
method="POST",
timeout=litellm.request_timeout
) as response:
if response.status_code != 200:
raise OpenAIError(status_code=response.status_code, message=response.text)

2
litellm/tests/test_completion.py
View file

@ -419,7 +419,7 @@ def test_completion_openai():
pass
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# test_completion_openai()
test_completion_openai()
def test_completion_text_openai():
try:

4
litellm/utils.py
View file

@ -1188,7 +1188,7 @@ def client(original_function):
litellm.cache.add_cache(result, *args, **kwargs)
# LOG SUCCESS - handle streaming success logging in the _next_ object, remove `handle_success` once it's deprecated
logging_obj.success_handler(result, start_time, end_time)
threading.Thread(target=logging_obj.success_handler, args=(result, start_time, end_time)).start()
# threading.Thread(target=logging_obj.success_handler, args=(result, start_time, end_time)).start()
my_thread = threading.Thread(
target=handle_success, args=(args, kwargs, result, start_time, end_time)
@ -1292,7 +1292,7 @@ def client(original_function):
litellm.cache.add_cache(result, *args, **kwargs)
# LOG SUCCESS - handle streaming success logging in the _next_ object, remove `handle_success` once it's deprecated
logging_obj.success_handler(result, start_time, end_time)
threading.Thread(target=logging_obj.success_handler, args=(result, start_time, end_time)).start()
# RETURN RESULT
return result
except Exception as e: