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(router) re use client across requests

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ishaan-jaff 2023-11-28 16:21:16 -08:00
parent f4a7760ea1
commit 4d06c296e3
1 changed files with 20 additions and 7 deletions
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27
litellm/router.py
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@ -232,9 +232,9 @@ class Router:
data["model"] = original_model_string[:index_of_model_id]
else:
data["model"] = original_model_string
model_client = deployment["client"]
model_client = deployment["async_client"]
self.total_calls[original_model_string] +=1
response = await litellm.acompletion(**{**data, "messages": messages, "caching": self.cache_responses, "azure_client": model_client, **kwargs})
response = await litellm.acompletion(**{**data, "messages": messages, "caching": self.cache_responses, "client": model_client, **kwargs})
self.success_calls[original_model_string] +=1
return response
except Exception as e:
@ -801,15 +801,28 @@ class Router:
self.model_list = model_list
# we add api_base/api_key each model so load balancing between azure/gpt on api_base1 and api_base2 works
for model in self.model_list:
if "azure" in model["litellm_params"]["model"]:
model["async_client"] = openai.AsyncAzureOpenAI(
api_key= model["litellm_params"]["api_key"],
azure_endpoint = model["litellm_params"]["api_base"]
)
model["client"] = openai.AzureOpenAI(
api_key= model["litellm_params"]["api_key"],
azure_endpoint = model["litellm_params"]["api_base"]
)
elif model["litellm_params"]["model"] in litellm.open_ai_chat_completion_models:
model["async_client"] = openai.AsyncOpenAI(
api_key= model["litellm_params"]["api_key"],
base_ur = model["litellm_params"]["api_base"]
)
model["client"] = openai.OpenAI(
api_key= model["litellm_params"]["api_key"],
base_url = model["litellm_params"]["api_base"]
)
model_id = ""
for key in model["litellm_params"]:
model_id+= str(model["litellm_params"][key])
model["litellm_params"]["model"] += "-ModelID-" + model_id
model["client"] = openai.AsyncAzureOpenAI(
api_key= model["litellm_params"]["api_key"],
azure_endpoint = model["litellm_params"]["api_base"]
)
self.model_names = [m["model_name"] for m in model_list]
def get_model_names(self):