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adding telemetry to litellm

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Krrish Dholakia 2023-08-02 12:34:47 -07:00
parent 851f681156
commit 03ac0277d1
8 changed files with 90 additions and 43 deletions
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63
litellm/main.py
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@ -252,35 +252,40 @@ def completion(
@client
@timeout(60) ## set timeouts, in case calls hang (e.g. Azure) - default is 60s, override with `force_timeout`
def embedding(model, input=[], azure=False, force_timeout=60, logger_fn=None):
response = None
if azure == True:
# azure configs
openai.api_type = "azure"
openai.api_base = os.environ.get("AZURE_API_BASE")
openai.api_version = os.environ.get("AZURE_API_VERSION")
openai.api_key = os.environ.get("AZURE_API_KEY")
## LOGGING
logging(model=model, input=input, azure=azure, logger_fn=logger_fn)
## EMBEDDING CALL
response = openai.Embedding.create(input=input, engine=model)
print_verbose(f"response_value: {str(response)[:50]}")
elif model in litellm.open_ai_embedding_models:
openai.api_type = "openai"
openai.api_base = "https://api.openai.com/v1"
openai.api_version = None
openai.api_key = os.environ.get("OPENAI_API_KEY")
## LOGGING
logging(model=model, input=input, azure=azure, logger_fn=logger_fn)
## EMBEDDING CALL
response = openai.Embedding.create(input=input, model=model)
print_verbose(f"response_value: {str(response)[:50]}")
else:
logging(model=model, input=input, azure=azure, logger_fn=logger_fn)
args = locals()
raise ValueError(f"No valid embedding model args passed in - {args}")
return response
try:
response = None
if azure == True:
# azure configs
openai.api_type = "azure"
openai.api_base = os.environ.get("AZURE_API_BASE")
openai.api_version = os.environ.get("AZURE_API_VERSION")
openai.api_key = os.environ.get("AZURE_API_KEY")
## LOGGING
logging(model=model, input=input, azure=azure, logger_fn=logger_fn)
## EMBEDDING CALL
response = openai.Embedding.create(input=input, engine=model)
print_verbose(f"response_value: {str(response)[:50]}")
elif model in litellm.open_ai_embedding_models:
openai.api_type = "openai"
openai.api_base = "https://api.openai.com/v1"
openai.api_version = None
openai.api_key = os.environ.get("OPENAI_API_KEY")
## LOGGING
logging(model=model, input=input, azure=azure, logger_fn=logger_fn)
## EMBEDDING CALL
response = openai.Embedding.create(input=input, model=model)
print_verbose(f"response_value: {str(response)[:50]}")
else:
logging(model=model, input=input, azure=azure, logger_fn=logger_fn)
args = locals()
raise ValueError(f"No valid embedding model args passed in - {args}")
return response
except Exception as e:
# log the original exception
logging(model=model, input=input, azure=azure, logger_fn=logger_fn, exception=e)
## Map to OpenAI Exception
raise exception_type(model=model, original_exception=e)
####### HELPER FUNCTIONS ################
## Set verbose to true -> ```litellm.set_verbose = True```
def print_verbose(print_statement):