ModelLaboratory#
- class langchain.model_laboratory.ModelLaboratory(chains: Sequence[Chain], names: List[str] | None = None)[source]#
Experiment with different models.
Initialize with chains to experiment with.
- Parameters:
chains (Sequence[Chain]) – list of chains to experiment with.
names (Optional[List[str]])
Methods
__init__(chains[, names])Initialize with chains to experiment with.
compare(text)Compare model outputs on an input text.
from_llms(llms[, prompt])Initialize with LLMs to experiment with and optional prompt.
- __init__(chains: Sequence[Chain], names: List[str] | None = None)[source]#
Initialize with chains to experiment with.
- Parameters:
chains (Sequence[Chain]) – list of chains to experiment with.
names (List[str] | None)
- compare(text: str) None[source]#
Compare model outputs on an input text.
If a prompt was provided with starting the laboratory, then this text will be fed into the prompt. If no prompt was provided, then the input text is the entire prompt.
- Parameters:
text (str) – input text to run all models on.
- Return type:
None
- classmethod from_llms(llms: List[BaseLLM], prompt: PromptTemplate | None = None) ModelLaboratory[source]#
Initialize with LLMs to experiment with and optional prompt.
- Parameters:
llms (List[BaseLLM]) – list of LLMs to experiment with
prompt (PromptTemplate | None) – Optional prompt to use to prompt the LLMs. Defaults to None. If a prompt was provided, it should only have one input variable.
- Return type: