scriptoriumadmin/litellm
1
0
Fork 0
mirror of https://github.com/BerriAI/litellm.git synced 2026-10-05 02:41:56 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions 49

Fix code qa

Browse source
This commit is contained in:
Sameer Kankute 2026-04-08 09:49:36 +05:30
parent 1ef7286996
commit 8795198107
No known key found for this signature in database
1 changed files with 63 additions and 59 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

122
litellm/llms/sap/chat/transformation.py
View file

@ -64,6 +64,50 @@ def validate_dict(data: dict, model) -> dict:
return model(**data).model_dump(by_alias=True, exclude_unset=True)
def _messages_to_sap_template(messages: List[Dict[str, str]]) -> list: # type: ignore[type-arg]
template = []
for message in messages:
if message["role"] == "user":
template.append(validate_dict(message, SAPUserMessage))
elif message["role"] == "assistant":
template.append(validate_dict(message, SAPAssistantMessage))
elif message["role"] == "tool":
template.append(validate_dict(message, SAPToolChatMessage))
else:
template.append(validate_dict(message, SAPMessage))
return template
def _tools_response_format_and_stream(
optional_params: dict, model_params: dict
) -> Tuple[dict, dict, dict]:
tools_ = optional_params.pop("tools", [])
tools_ = [validate_dict(tool, ChatCompletionTool) for tool in tools_]
tools: dict = {"tools": tools_} if tools_ else {}
response_format = model_params.pop("response_format", {})
resp_type = response_format.get("type", None)
if resp_type:
if resp_type == "json_schema":
response_format = validate_dict(
response_format, ResponseFormatJSONSchema
)
else:
response_format = validate_dict(response_format, ResponseFormat)
response_format = {"response_format": response_format}
model_params.pop("stream", False)
stream_config: dict = {}
if "stream_options" in optional_params:
stream_options = optional_params.pop("stream_options", {})
if "chunk_size" in stream_options:
stream_config["chunk_size"] = stream_options.get("chunk_size")
if "delimiters" in stream_options:
stream_config["delimiters"] = stream_options.get("delimiters")
return tools, response_format, stream_config
class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
frequency_penalty: Optional[int] = None
function_call: Optional[Union[str, dict]] = None
@ -292,57 +336,19 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
optional_params = dict(optional_params)
optional_params.pop("deployment_url", None)
template = messages
excluded_params = _SAP_MODEL_PARAMS_EXCLUDED_KEYS
model_params = {
k: v for k, v in optional_params.items() if k not in excluded_params
}
model_version = optional_params.pop("model_version", "latest")
template = []
for message in messages:
if message["role"] == "user":
template.append(validate_dict(message, SAPUserMessage))
elif message["role"] == "assistant":
template.append(validate_dict(message, SAPAssistantMessage))
elif message["role"] == "tool":
template.append(validate_dict(message, SAPToolChatMessage))
else:
template.append(validate_dict(message, SAPMessage))
template = _messages_to_sap_template(messages)
tools_ = optional_params.pop("tools", [])
tools_ = [validate_dict(tool, ChatCompletionTool) for tool in tools_]
if tools_ != []:
tools = {"tools": tools_}
else:
tools = {}
response_format = model_params.pop("response_format", {})
resp_type = response_format.get("type", None)
if resp_type:
if resp_type == "json_schema":
response_format = validate_dict(
response_format, ResponseFormatJSONSchema
)
else:
response_format = validate_dict(response_format, ResponseFormat)
response_format = {"response_format": response_format}
model_params.pop("stream", False)
stream_config = {}
if "stream_options" in optional_params:
stream_options = optional_params.pop("stream_options", {})
if "chunk_size" in stream_options:
stream_config["chunk_size"] = stream_options.get("chunk_size")
if "delimiters" in stream_options:
stream_config["delimiters"] = stream_options.get("delimiters")
tools, response_format, stream_config = _tools_response_format_and_stream(
optional_params, model_params
)
placeholder_values = optional_params.pop("placeholder_values", None)
placeholder_values = (
{"placeholder_values": placeholder_values}
if placeholder_values is not None
else {}
)
fallback_modules = optional_params.pop("fallback_sap_modules", [])
@ -373,26 +379,24 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
)
)
if fallback_modules:
modules_payload = modules
else:
modules_payload = modules[0] # type: ignore
request_body = {
"config": {
"modules": {
"prompt_templating": {
"prompt": {"template": template, **tools, **response_format},
"model": {
"name": model,
"params": model_params,
"version": model_version,
},
config_payload: Dict[str, Any] = {
"modules": {
"prompt_templating": {
"prompt": {"template": template, **tools, **response_format},
"model": {
"name": model,
"params": model_params,
"version": model_version,
},
},
"stream": stream_config,
}
},
}
if stream_config:
config_payload["stream"] = stream_config
request_body: Dict[str, Any] = {"config": config_payload}
if placeholder_values is not None:
request_body["placeholder_values"] = placeholder_values
body = validate_dict(request_body, OrchestrationRequest)