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# `langchain.model_laboratory`.ModelLaboratory

class langchain.model_laboratory.ModelLaboratory(chains: Sequence[Chain], names: Optional[List[str]] = None)

  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: Optional[List[str]] = None)

    Initialize with chains to experiment with.

    Parameters

      - chains (Sequence[Chain]) – list of chains to experiment with.

      - names (Optional[List[str]]) –

  compare(text: str) → None

    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: Optional[PromptTemplate] = None) → ModelLaboratory

    Initialize with LLMs to experiment with and optional prompt.

    Parameters

      - llms (List[BaseLLM]) – list of LLMs to experiment with

      - prompt (Optional[PromptTemplate]) – 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

      ModelLaboratory

# Examples using ModelLaboratory

- Map reduce example