google/generativeai/types/retriever_types.py [787:811]:
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        c_data = []
        if custom_metadata:
            for cm in custom_metadata:
                c_data.append(cm._to_proto())

        if name is not None:
            if valid_name(name):
                chunk_name = f"{self.name}/chunks/{name}"
            else:
                raise ValueError(NAME_ERROR_MSG.format(length=len(name), name=name))
        else:
            chunk_name = name

        if isinstance(data, str):
            chunk = protos.Chunk(
                name=chunk_name, data={"string_value": data}, custom_metadata=c_data
            )
        else:
            chunk = protos.Chunk(
                name=chunk_name,
                data={"string_value": data.string_value},
                custom_metadata=c_data,
            )

        request = protos.CreateChunkRequest(parent=self.name, chunk=chunk)
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google/generativeai/types/retriever_types.py [831:855]:
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        c_data = []
        if custom_metadata:
            for cm in custom_metadata:
                c_data.append(cm._to_proto())

        if name is not None:
            if valid_name(name):
                chunk_name = f"{self.name}/chunks/{name}"
            else:
                raise ValueError(NAME_ERROR_MSG.format(length=len(name), name=name))
        else:
            chunk_name = name

        if isinstance(data, str):
            chunk = protos.Chunk(
                name=chunk_name, data={"string_value": data}, custom_metadata=c_data
            )
        else:
            chunk = protos.Chunk(
                name=chunk_name,
                data={"string_value": data.string_value},
                custom_metadata=c_data,
            )

        request = protos.CreateChunkRequest(parent=self.name, chunk=chunk)
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