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dS ) a� Initialize the ModelLaboratory with chains to experiment with.
Args:
chains (Sequence[Chain]): A sequence of chains to experiment with.
Each chain must have exactly one input and one output variable.
names (Optional[List[str]]): Optional list of names corresponding to each chain.
If provided, its length must match the number of chains.
Raises:
ValueError: If any chain is not an instance of `Chain`.
ValueError: If a chain does not have exactly one input variable.
ValueError: If a chain does not have exactly one output variable.
ValueError: If the length of `names` does not match the number of chains.
z�ModelLaboratory should now be initialized with Chains. If you want to initialize with LLMs, use the `from_llms` method instead (`ModelLaboratory.from_llms(...)`)� z;Currently only support chains with one input variable, got z<Currently only support chains with one output variable, got Nz0Length of chains does not match length of names.c S � g | ]}t |��qS � ��str)�.0�ir r �E/usr/local/lib/python3.10/dist-packages/langchain/model_laboratory.py�
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List[BaseLLM]�prompt�Optional[PromptTemplate]�returnc sB � du r t dgdd�� � fdd�|D �}dd� |D �}| ||d�S ) a� Initialize the ModelLaboratory with LLMs and an optional prompt.
Args:
llms (List[BaseLLM]): A list of LLMs to experiment with.
prompt (Optional[PromptTemplate]): An optional prompt to use with the LLMs.
If provided, the prompt must contain exactly one input variable.
Returns:
ModelLaboratory: An instance of `ModelLaboratory` initialized with LLMs.
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