google/generativeai/types/retriever_types.py [1625:1646]:
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        c_data = []
        if self.custom_metadata:
            for cm in self.custom_metadata:
                c_data.append(cm._to_proto())

        # When handling updates, use to the _to_proto result of the custom_metadata
        self.custom_metadata = c_data

        updates = flatten_update_paths(updates)
        # At this time, only `data` can be updated
        for item in updates:
            if item != "data.string_value":
                raise ValueError(
                    f"Invalid operation: Currently, only the 'data' attribute can be updated for a 'Chunk'. Attempted to update '{item}'."
                )
        field_mask = field_mask_pb2.FieldMask()

        for path in updates.keys():
            field_mask.paths.append(path)
        for path, value in updates.items():
            self._apply_update(path, value)
        request = protos.UpdateChunkRequest(chunk=self.to_dict(), update_mask=field_mask)
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google/generativeai/types/retriever_types.py [1665:1686]:
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        c_data = []
        if self.custom_metadata:
            for cm in self.custom_metadata:
                c_data.append(cm._to_proto())

        # When handling updates, use to the _to_proto result of the custom_metadata
        self.custom_metadata = c_data

        updates = flatten_update_paths(updates)
        # At this time, only `data` can be updated
        for item in updates:
            if item != "data.string_value":
                raise ValueError(
                    f"Invalid operation: Currently, only the 'data' attribute can be updated for a 'Chunk'. Attempted to update '{item}'."
                )
        field_mask = field_mask_pb2.FieldMask()

        for path in updates.keys():
            field_mask.paths.append(path)
        for path, value in updates.items():
            self._apply_update(path, value)
        request = protos.UpdateChunkRequest(chunk=self.to_dict(), update_mask=field_mask)
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