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feat: global client for sync + async calls (openai + Azure only)

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Krrish Dholakia 2023-11-16 14:44:06 -08:00
parent 5fd4376802
commit 51bf637656
4 changed files with 22 additions and 14 deletions
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12
litellm/llms/azure.py
View file

@ -105,8 +105,6 @@ 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:
@ -137,7 +135,7 @@ 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, model=model, api_key=api_key, api_version=api_version, azure_ad_token=azure_ad_token)
else:
azure_client = AzureOpenAI(api_key=api_key, api_version=api_version, azure_endpoint=api_base, azure_deployment=model, azure_ad_token=azure_ad_token)
azure_client = AzureOpenAI(api_key=api_key, api_version=api_version, azure_endpoint=api_base, azure_deployment=model, azure_ad_token=azure_ad_token, http_client=litellm.client_session)
response = azure_client.chat.completions.create(**data) # type: ignore
return convert_to_model_response_object(response_object=json.loads(response.model_dump_json()), model_response_object=model_response)
except AzureOpenAIError as e:
@ -155,7 +153,7 @@ class AzureChatCompletion(BaseLLM):
model_response: ModelResponse,
azure_ad_token: Optional[str]=None, ):
try:
azure_client = AsyncAzureOpenAI(api_key=api_key, api_version=api_version, azure_endpoint=api_base, azure_deployment=model, azure_ad_token=azure_ad_token)
azure_client = AsyncAzureOpenAI(api_key=api_key, api_version=api_version, azure_endpoint=api_base, azure_deployment=model, azure_ad_token=azure_ad_token, http_client=litellm.aclient_session)
response = await azure_client.chat.completions.create(**data)
return convert_to_model_response_object(response_object=json.loads(response.model_dump_json()), model_response_object=model_response)
except Exception as e:
@ -175,7 +173,7 @@ class AzureChatCompletion(BaseLLM):
model: str,
azure_ad_token: Optional[str]=None,
):
azure_client = AzureOpenAI(api_key=api_key, api_version=api_version, azure_endpoint=api_base, azure_deployment=model, azure_ad_token=azure_ad_token)
azure_client = AzureOpenAI(api_key=api_key, api_version=api_version, azure_endpoint=api_base, azure_deployment=model, azure_ad_token=azure_ad_token, http_client=litellm.client_session)
response = azure_client.chat.completions.create(**data)
streamwrapper = CustomStreamWrapper(completion_stream=response, model=model, custom_llm_provider="azure",logging_obj=logging_obj)
for transformed_chunk in streamwrapper:
@ -189,7 +187,7 @@ class AzureChatCompletion(BaseLLM):
data: dict,
model: str,
azure_ad_token: Optional[str]=None):
azure_client = AsyncAzureOpenAI(api_key=api_key, api_version=api_version, azure_endpoint=api_base, azure_deployment=model, azure_ad_token=azure_ad_token)
azure_client = AsyncAzureOpenAI(api_key=api_key, api_version=api_version, azure_endpoint=api_base, azure_deployment=model, azure_ad_token=azure_ad_token, http_client=litellm.aclient_session)
response = await azure_client.chat.completions.create(**data)
streamwrapper = CustomStreamWrapper(completion_stream=response, model=model, custom_llm_provider="azure",logging_obj=logging_obj)
async for transformed_chunk in streamwrapper:
@ -210,7 +208,7 @@ class AzureChatCompletion(BaseLLM):
if self._client_session is None:
self._client_session = self.create_client_session()
try:
azure_client = AzureOpenAI(api_key=api_key, api_version=api_version, azure_endpoint=api_base, azure_deployment=model, azure_ad_token=azure_ad_token)
azure_client = AzureOpenAI(api_key=api_key, api_version=api_version, azure_endpoint=api_base, azure_deployment=model, azure_ad_token=azure_ad_token, http_client=litellm.client_session)
data = {
"model": model,
"input": input,

10
litellm/llms/openai.py
View file

@ -203,7 +203,7 @@ class OpenAIChatCompletion(BaseLLM):
elif optional_params.get("stream", False):
return self.streaming(logging_obj=logging_obj, data=data, model=model, api_base=api_base, api_key=api_key)
else:
openai_client = OpenAI(api_key=api_key, base_url=api_base)
openai_client = OpenAI(api_key=api_key, base_url=api_base, http_client=litellm.client_session)
response = openai_client.chat.completions.create(**data) # type: ignore
return convert_to_model_response_object(response_object=json.loads(response.model_dump_json()), model_response_object=model_response)
except Exception as e:
@ -238,7 +238,7 @@ class OpenAIChatCompletion(BaseLLM):
api_base: Optional[str]=None):
response = None
try:
openai_aclient = AsyncOpenAI(api_key=api_key, base_url=api_base)
openai_aclient = AsyncOpenAI(api_key=api_key, base_url=api_base, http_client=litellm.aclient_session)
response = await openai_aclient.chat.completions.create(**data)
return convert_to_model_response_object(response_object=json.loads(response.model_dump_json()), model_response_object=model_response)
except Exception as e:
@ -254,7 +254,7 @@ class OpenAIChatCompletion(BaseLLM):
api_key: Optional[str]=None,
api_base: Optional[str]=None
):
openai_client = OpenAI(api_key=api_key, base_url=api_base)
openai_client = OpenAI(api_key=api_key, base_url=api_base, http_client=litellm.client_session)
response = openai_client.chat.completions.create(**data)
streamwrapper = CustomStreamWrapper(completion_stream=response, model=model, custom_llm_provider="openai",logging_obj=logging_obj)
for transformed_chunk in streamwrapper:
@ -266,7 +266,7 @@ class OpenAIChatCompletion(BaseLLM):
model: str,
api_key: Optional[str]=None,
api_base: Optional[str]=None):
openai_aclient = AsyncOpenAI(api_key=api_key, base_url=api_base)
openai_aclient = AsyncOpenAI(api_key=api_key, base_url=api_base, http_client=litellm.aclient_session)
response = await openai_aclient.chat.completions.create(**data)
streamwrapper = CustomStreamWrapper(completion_stream=response, model=model, custom_llm_provider="openai",logging_obj=logging_obj)
async for transformed_chunk in streamwrapper:
@ -283,7 +283,7 @@ class OpenAIChatCompletion(BaseLLM):
super().embedding()
exception_mapping_worked = False
try:
openai_client = OpenAI(api_key=api_key, base_url=api_base)
openai_client = OpenAI(api_key=api_key, base_url=api_base, http_client=litellm.client_session)
model = model
data = {
"model": model,

4
litellm/tests/test_async_fn.py
View file

@ -16,7 +16,7 @@ from litellm import completion, acompletion, acreate
litellm.num_retries = 3
def test_sync_response():
litellm.set_verbose = True
litellm.set_verbose = False
user_message = "Hello, how are you?"
messages = [{"content": user_message, "role": "user"}]
try:
@ -146,4 +146,4 @@ def test_get_response_non_openai_streaming():
return response
asyncio.run(test_async_call())
test_get_response_non_openai_streaming()
# test_get_response_non_openai_streaming()

10
litellm/utils.py
View file

@ -1054,6 +1054,16 @@ def client(original_function):
try:
global callback_list, add_breadcrumb, user_logger_fn, Logging
function_id = kwargs["id"] if "id" in kwargs else None
if litellm.client_session is None:
litellm.client_session = httpx.Client(
limits=httpx.Limits(max_connections=100, max_keepalive_connections=20),
timeout = httpx.Timeout(timeout=600.0, connect=5.0)
)
if litellm.aclient_session is None:
litellm.aclient_session = httpx.AsyncClient(
limits=httpx.Limits(max_connections=100, max_keepalive_connections=20),
timeout = httpx.Timeout(timeout=600.0, connect=5.0)
)
if litellm.use_client or ("use_client" in kwargs and kwargs["use_client"] == True):
print_verbose(f"litedebugger initialized")
if "lite_debugger" not in litellm.input_callback: