morpheus_llm.llm.services.llm_service.LLMClient
- class LLMClient[source]
Bases:
abc.ABCAbstract interface for clients which are able to interact with LLM models. Concrete implementations of this class will have an associated implementation of
LLMServicewhich is able to construct instances of this class.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. - abstract generate(**input_dict)[source]
Issue a request to generate a response based on a given prompt.
- Parameters
- input_dictdict
Input containing prompt data.
- Returns
- str
Generated response for prompt.
- abstract 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.
- Returns
- str
Generated async response for prompt.
- abstract generate_batch(inputs: dict[str, list], return_exceptions: Literal[True]) → list[str | BaseException][source]
- abstract generate_batch(inputs: dict[str, list], return_exceptions: Literal[False]) → list[str]
- abstract 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.
- Returns
- list[str] | list[str | BaseException]
List of responses or list of responses and exceptions.
- abstract async generate_batch_async(inputs: dict[str, list], return_exceptions: Literal[True]) → list[str | BaseException][source]
- abstract async generate_batch_async(inputs: dict[str, list], return_exceptions: Literal[False]) → list[str]
- abstract 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.
- Returns
- list[str] | list[str | BaseException]
List of responses or list of responses and exceptions.
- abstract get_input_names()[source]
Returns the names of the inputs to the model.
- Returns
- list[str]
List of input names.