morpheus_llm.llm.services.nemo_llm_service.NeMoLLMClient
- class NeMoLLMClient(parent, *, model_name, **model_kwargs)[source]
Bases:
morpheus_llm.llm.services.llm_service.LLMClient
Client for interacting with a specific model in Nemo. This class should be constructed with the
NeMoLLMService.get_client
method.- Parameters
- parentNeMoLLMService
The parent service for this client.
- model_namestr
The name of the model to interact with.
- model_kwargsdict[str, typing.Any]
Additional keyword arguments to pass to the model when generating text.
Methods
generate
(**input_dict)Issue a request to generate a response based on a given prompt. generate_async
(**input_dict)Issue an asynchronous request to generate a response based on a given prompt. generate_batch
()Issue a request to generate a list of responses based on a list of prompts. generate_batch_async
()Issue an asynchronous request to generate a list of responses based on a list of prompts. get_input_names
()Returns the names of the inputs to the model. - generate(**input_dict)[source]
Issue a request to generate a response based on a given prompt.
- Parameters
- input_dictdict
Input containing prompt data.
- async generate_async(**input_dict)[source]
Issue an asynchronous request to generate a response based on a given prompt.
- Parameters
- input_dictdict
Input containing prompt data.
- generate_batch(inputs: dict[str, list], return_exceptions: Literal[True]) → list[str | BaseException][source]
- generate_batch(inputs: dict[str, list], return_exceptions: Literal[False]) → list[str]
- generate_batch(inputs: dict[str, list], return_exceptions: bool = False) → list[str] | list[str | BaseException]
Issue a request to generate a list of responses based on a list of prompts.
- Parameters
- inputsdict
Inputs containing prompt data.
- return_exceptionsbool
Whether to return exceptions in the output list or raise them immediately.
- async generate_batch_async(inputs: dict[str, list], return_exceptions: Literal[True]) → list[str | BaseException][source]
- async generate_batch_async(inputs: dict[str, list], return_exceptions: Literal[False]) → list[str]
- async generate_batch_async(inputs: dict[str, list], return_exceptions: bool = False) → list[str] | list[str | BaseException]
Issue an asynchronous request to generate a list of responses based on a list of prompts.
- Parameters
- inputsdict
Inputs containing prompt data.
- return_exceptionsbool
Whether to return exceptions in the output list or raise them immediately.
- get_input_names()[source]
Returns the names of the inputs to the model.
- Returns
- list[str]
List of input names.