Prompt object to use.
param resolver_llm: Optional[langchain.schema.language_model.BaseLanguageModel] = None¶
LLM to use in resolve step. If None given, ‘llm’ will be used.
param return_intermediate_steps: bool = False¶
Whether to return ideas and critique, in addition to resolution.
param tags: Optional[List[str]] = None¶
Optional list of tags associated with the chain. Defaults to None.
These tags will be associated with each call to this chain,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a chain with its use case.
param verbose: bool [Optional]¶
Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to the console. Defaults to langchain.verbose value.
class SmartLLMChainHistory[source]¶
Bases: object
critique_prompt_inputs() → Dict[str, Any][source]¶
ideation_prompt_inputs() → Dict[str, Any][source]¶
resolve_prompt_inputs() → Dict[str, Any][source]¶
critique: str = ''¶
ideas: List[str] = []¶
property n_ideas: int¶
question: str = ''¶
__call__(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, run_name: Optional[str] = None, include_run_info: bool = False) → Dict[str, Any]¶
Execute the chain.
Parameters
inputs – Dictionary of inputs, or single input if chain expects
only one param. Should contain all inputs specified in