Class VertexAI

libs/community/langchain_community/llms/vertexai.py:209–391

Google Vertex AI large language models.

    alternative_import="langchain_google_vertexai.VertexAI",
)
class VertexAI(_VertexAICommon, BaseLLM):
    """Google Vertex AI large language models."""

    model_name: str = "text-bison"
    "The name of the Vertex AI large language model."
    tuned_model_name: Optional[str] = None
    "The name of a tuned model. If provided, model_name is ignored."

    @classmethod
    def is_lc_serializable(self) -> bool:
        return True

    @classmethod
    def get_lc_namespace(cls) -> List[str]:
        """Get the namespace of the langchain object."""
        return ["langchain", "llms", "vertexai"]

    @root_validator()
    def validate_environment(cls, values: Dict) -> Dict:
        """Validate that the python package exists in environment."""
        tuned_model_name = values.get("tuned_model_name")
        model_name = values["model_name"]
        is_gemini = is_gemini_model(values["model_name"])
        cls._try_init_vertexai(values)
        try:
            from vertexai.language_models import (
                CodeGenerationModel,
                TextGenerationModel,
            )
            from vertexai.preview.language_models import (
                CodeGenerationModel as PreviewCodeGenerationModel,
            )
            from vertexai.preview.language_models import (
                TextGenerationModel as PreviewTextGenerationModel,
            )

            if is_gemini:
                from vertexai.preview.generative_models import (
                    GenerativeModel,
                )

            if is_codey_model(model_name):
                model_cls = CodeGenerationModel
                preview_model_cls = PreviewCodeGenerationModel
            elif is_gemini:
                model_cls = GenerativeModel
                preview_model_cls = GenerativeModel
            else:
                model_cls = TextGenerationModel
                preview_model_cls = PreviewTextGenerationModel

            if tuned_model_name:
                values["client"] = model_cls.get_tuned_model(tuned_model_name)
                values["client_preview"] = preview_model_cls.get_tuned_model(
                    tuned_model_name
                )
            else:
                if is_gemini: