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feat(llama_guard.py): add llama guard support for content moderation + new async_moderation_hook endpoint

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Krrish Dholakia 2024-02-16 18:45:25 -08:00
parent 5e7dda4f88
commit 2a4a6995ac
12 changed files with 163 additions and 132 deletions
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10
litellm/utils.py
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@ -1141,7 +1141,7 @@ class Logging:
if (
litellm.max_budget
and self.stream
and self.stream == False
and result is not None
and "content" in result
):
@ -1668,7 +1668,9 @@ class Logging:
end_time=end_time,
)
if callable(callback): # custom logger functions
print_verbose(f"Making async function logging call")
print_verbose(
f"Making async function logging call - {self.model_call_details}"
)
if self.stream:
if "complete_streaming_response" in self.model_call_details:
await customLogger.async_log_event(
@ -3451,7 +3453,7 @@ def cost_per_token(
return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar
else:
# if model is not in model_prices_and_context_window.json. Raise an exception-let users know
error_str = f"Model not in model_prices_and_context_window.json. You passed model={model}\n"
error_str = f"Model not in model_prices_and_context_window.json. You passed model={model}. Register pricing for model - https://docs.litellm.ai/docs/proxy/custom_pricing\n"
raise litellm.exceptions.NotFoundError( # type: ignore
message=error_str,
model=model,
@ -3913,6 +3915,8 @@ def get_optional_params(
custom_llm_provider != "bedrock" and custom_llm_provider != "sagemaker"
): # allow dynamically setting boto3 init logic
continue
elif k == "hf_model_name" and custom_llm_provider != "sagemaker":
continue
elif (
k.startswith("vertex_") and custom_llm_provider != "vertex_ai"
): # allow dynamically setting vertex ai init logic