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Pass base parameters to acompletion (#343)

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Kerem Yilmaz 2024-05-17 16:36:15 -07:00 • committed by GitHub
parent 9c19442fed
commit 6908ca5844
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2 changed files with 11 additions and 3 deletions
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8
skyvern/forge/sdk/api/llm/api_handler_factory.py
View file

@ -133,7 +133,7 @@ class LLMAPIHandlerFactory:
return llm_api_handler_with_router_and_fallback
@staticmethod
def get_llm_api_handler(llm_key: str) -> LLMAPIHandler:
def get_llm_api_handler(llm_key: str, base_parameters: dict[str, Any] | None = None) -> LLMAPIHandler:
llm_config = LLMConfigRegistry.get_config(llm_key)
if LLMConfigRegistry.is_router_config(llm_key):
@ -145,9 +145,12 @@ class LLMAPIHandlerFactory:
screenshots: list[bytes] | None = None,
parameters: dict[str, Any] | None = None,
) -> dict[str, Any]:
active_parameters = base_parameters or {}
if parameters is None:
parameters = LLMAPIHandlerFactory.get_api_parameters()
active_parameters.update(parameters)
if step:
await app.ARTIFACT_MANAGER.create_artifact(
step=step,
@ -174,6 +177,7 @@ class LLMAPIHandlerFactory:
{
"model": llm_config.model_name,
"messages": messages,
# we're not using active_parameters here because it may contain sensitive information
**parameters,
}
).encode("utf-8"),
@ -185,7 +189,7 @@ class LLMAPIHandlerFactory:
response = await litellm.acompletion(
model=llm_config.model_name,
messages=messages,
**parameters,
**active_parameters,
)
except openai.OpenAIError as e:
raise LLMProviderError(llm_key) from e

6
skyvern/forge/sdk/experimentation/providers.py
View file

@ -17,7 +17,11 @@ class BaseExperimentationProvider(ABC):
if feature_name not in self.result_map:
self.result_map[feature_name] = {}
if distinct_id not in self.result_map[feature_name]:
self.result_map[feature_name][distinct_id] = self.is_feature_enabled(feature_name, distinct_id, properties)
feature_flag_value = self.is_feature_enabled(feature_name, distinct_id, properties)
self.result_map[feature_name][distinct_id] = feature_flag_value
if feature_flag_value:
LOG.info("Feature flag is enabled", flag=feature_name, distinct_id=distinct_id)
return self.result_map[feature_name][distinct_id]