#
# Copyright (c) 2024–2025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
from typing import List
from loguru import logger
from openai import AsyncStream
from openai.types.chat import ChatCompletionChunk, ChatCompletionMessageParam
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.openai.llm import OpenAILLMService
[docs]
class CerebrasLLMService(OpenAILLMService):
"""A service for interacting with Cerebras's API using the OpenAI-compatible interface.
This service extends OpenAILLMService to connect to Cerebras's API endpoint while
maintaining full compatibility with OpenAI's interface and functionality.
Args:
api_key (str): The API key for accessing Cerebras's API
base_url (str, optional): The base URL for Cerebras API. Defaults to "https://api.cerebras.ai/v1"
model (str, optional): The model identifier to use. Defaults to "llama-3.3-70b"
**kwargs: Additional keyword arguments passed to OpenAILLMService
"""
def __init__(
self,
*,
api_key: str,
base_url: str = "https://api.cerebras.ai/v1",
model: str = "llama-3.3-70b",
**kwargs,
):
super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs)
[docs]
def create_client(self, api_key=None, base_url=None, **kwargs):
"""Create OpenAI-compatible client for Cerebras API endpoint."""
logger.debug(f"Creating Cerebras client with api {base_url}")
return super().create_client(api_key, base_url, **kwargs)
[docs]
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,
"seed": self._settings["seed"],
"temperature": self._settings["temperature"],
"top_p": self._settings["top_p"],
"max_completion_tokens": self._settings["max_completion_tokens"],
}
params.update(self._settings["extra"])
chunks = await self._client.chat.completions.create(**params)
return chunks