async def get_chat_completions(
        self, context: OpenAILLMContext, messages: List[ChatCompletionMessageParam]
    ) -> AsyncStream[ChatCompletionChunk]:
        """Create a streaming chat completion using Cerebras's API.

        Args:
        context (OpenAILLMContext): The context object containing tools configuration
            and other settings for the chat completion.
        messages (List[ChatCompletionMessageParam]): The list of messages comprising
            the conversation history and current request.

        Returns:
        AsyncStream[ChatCompletionChunk]: A streaming response of chat completion
            chunks that can be processed asynchronously.
        """
        params = {
            "model": self.model_name,
            "stream": True,
            "messages": messages,
            "tools": context.tools,
            "tool_choice": context.tool_choice,
            "stream_options": {"include_usage": True},
            "frequency_penalty": self._settings["frequency_penalty"],
            "presence_penalty": self._settings["presence_penalty"],
            "temperature": self._settings["temperature"],
            "top_p": self._settings["top_p"],
            "max_tokens": self._settings["max_tokens"],
        }

        params.update(self._settings["extra"])

        chunks = await self._client.chat.completions.create(**params)
        return chunks
Create a streaming chat completion using Cerebras's API.

        Args:
        context (OpenAILLMContext): The context object containing tools configuration
            and other settings for the chat completion.
        messages (List[ChatCompletionMessageParam]): The list of messages comprising
            the conversation history and current request.

        Returns:
        AsyncStream[ChatCompletionChunk]: A streaming response of chat completion
            chunks that can be processed asynchronously.
        
src/pipecat/services/deepseek/llm.py