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Merge branch 'main' into litellm_add_semantic_cache

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Ishaan Jaff 2024-02-06 11:18:43 -08:00 • committed by GitHub
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25 changed files with 1499 additions and 342 deletions
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76
litellm/utils.py
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@ -980,12 +980,9 @@ class Logging:
self.model_call_details["log_event_type"] = "post_api_call"
# User Logging -> if you pass in a custom logging function
verbose_logger.debug(
print_verbose(
f"RAW RESPONSE:\n{self.model_call_details.get('original_response', self.model_call_details)}\n\n"
)
verbose_logger.debug(
f"Logging Details Post-API Call: LiteLLM Params: {self.model_call_details}"
)
if self.logger_fn and callable(self.logger_fn):
try:
self.logger_fn(
@ -1636,34 +1633,6 @@ class Logging:
end_time=end_time,
print_verbose=print_verbose,
)
if callback == "langfuse":
global langFuseLogger
print_verbose("reaches Async langfuse for logging!")
kwargs = {}
for k, v in self.model_call_details.items():
if (
k != "original_response"
): # copy.deepcopy raises errors as this could be a coroutine
kwargs[k] = v
# this only logs streaming once, complete_streaming_response exists i.e when stream ends
if self.stream:
if "complete_streaming_response" not in kwargs:
return
else:
print_verbose(
"reaches Async langfuse for streaming logging!"
)
result = kwargs["complete_streaming_response"]
if langFuseLogger is None:
langFuseLogger = LangFuseLogger()
await langFuseLogger._async_log_event(
kwargs=kwargs,
response_obj=result,
start_time=start_time,
end_time=end_time,
user_id=kwargs.get("user", None),
print_verbose=print_verbose,
)
except:
print_verbose(
f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while success logging {traceback.format_exc()}"
@ -1788,9 +1757,37 @@ class Logging:
response_obj=result,
kwargs=self.model_call_details,
)
elif callback == "langfuse":
global langFuseLogger
verbose_logger.debug("reaches langfuse for logging!")
kwargs = {}
for k, v in self.model_call_details.items():
if (
k != "original_response"
): # copy.deepcopy raises errors as this could be a coroutine
kwargs[k] = v
# this only logs streaming once, complete_streaming_response exists i.e when stream ends
if langFuseLogger is None or (
self.langfuse_public_key != langFuseLogger.public_key
and self.langfuse_secret != langFuseLogger.secret_key
):
langFuseLogger = LangFuseLogger(
langfuse_public_key=self.langfuse_public_key,
langfuse_secret=self.langfuse_secret,
)
langFuseLogger.log_event(
start_time=start_time,
end_time=end_time,
response_obj=None,
user_id=kwargs.get("user", None),
print_verbose=print_verbose,
status_message=str(exception),
level="ERROR",
kwargs=self.model_call_details,
)
except Exception as e:
print_verbose(
f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while failure logging with integrations {traceback.format_exc()}"
f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while failure logging with integrations {str(e)}"
)
print_verbose(
f"LiteLLM.Logging: is sentry capture exception initialized {capture_exception}"
@ -3860,6 +3857,8 @@ def get_optional_params(
and custom_llm_provider != "text-completion-openai"
and custom_llm_provider != "azure"
and custom_llm_provider != "vertex_ai"
and custom_llm_provider != "anyscale"
and custom_llm_provider != "together_ai"
):
if custom_llm_provider == "ollama" or custom_llm_provider == "ollama_chat":
# ollama actually supports json output
@ -3878,11 +3877,6 @@ def get_optional_params(
optional_params[
"functions_unsupported_model"
] = non_default_params.pop("functions")
elif (
custom_llm_provider == "anyscale"
and model == "mistralai/Mistral-7B-Instruct-v0.1"
): # anyscale just supports function calling with mistral
pass
elif (
litellm.add_function_to_prompt
): # if user opts to add it to prompt instead
@ -4095,6 +4089,8 @@ def get_optional_params(
"top_p",
"stop",
"frequency_penalty",
"tools",
"tool_choice",
]
_check_valid_arg(supported_params=supported_params)
@ -4112,6 +4108,10 @@ def get_optional_params(
] = frequency_penalty # https://docs.together.ai/reference/inference
if stop is not None:
optional_params["stop"] = stop
if tools is not None:
optional_params["tools"] = tools
if tool_choice is not None:
optional_params["tool_choice"] = tool_choice
elif custom_llm_provider == "ai21":
## check if unsupported param passed in
supported_params = [