def create_context_aggregator(
        self,
        context: OpenAILLMContext,
        *,
        user_params: LLMUserAggregatorParams = LLMUserAggregatorParams(),
        assistant_params: LLMAssistantAggregatorParams = LLMAssistantAggregatorParams(),
    ) -> AWSBedrockContextAggregatorPair:
        """Create an instance of AWSBedrockContextAggregatorPair from an
        OpenAILLMContext. Constructor keyword arguments for both the user and
        assistant aggregators can be provided.

        Args:
            context (OpenAILLMContext): The LLM context.
            user_params (LLMUserAggregatorParams, optional): User aggregator
                parameters.
            assistant_params (LLMAssistantAggregatorParams, optional): User
                aggregator parameters.

        Returns:
            AWSBedrockContextAggregatorPair: A pair of context aggregators, one
            for the user and one for the assistant, encapsulated in an
            AWSBedrockContextAggregatorPair.
        """
        context.set_llm_adapter(self.get_llm_adapter())

        if isinstance(context, OpenAILLMContext):
            context = AWSBedrockLLMContext.from_openai_context(context)

        user = AWSBedrockUserContextAggregator(context, params=user_params)
        assistant = AWSBedrockAssistantContextAggregator(context, params=assistant_params)
        return AWSBedrockContextAggregatorPair(_user=user, _assistant=assistant)
Create an instance of AWSBedrockContextAggregatorPair from an
        OpenAILLMContext. Constructor keyword arguments for both the user and
        assistant aggregators can be provided.

        Args:
            context (OpenAILLMContext): The LLM context.
            user_params (LLMUserAggregatorParams, optional): User aggregator
                parameters.
            assistant_params (LLMAssistantAggregatorParams, optional): User
                aggregator parameters.

        Returns:
            AWSBedrockContextAggregatorPair: A pair of context aggregators, one
            for the user and one for the assistant, encapsulated in an
            AWSBedrockContextAggregatorPair.
        
src/pipecat/services/aws/llm.py