#
# Copyright (c) 2024-2026, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
"""Cerebras LLM service implementation using OpenAI-compatible interface."""
from dataclasses import dataclass
from loguru import logger
from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams
from pipecat.services.openai.base_llm import BaseOpenAILLMService
from pipecat.services.openai.llm import OpenAILLMService
[docs]
@dataclass
class CerebrasLLMSettings(BaseOpenAILLMService.Settings):
"""Settings for CerebrasLLMService."""
pass
[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.
"""
# Cerebras doesn't support the "developer" message role.
# This value is used by BaseOpenAILLMService when calling the adapter.
supports_developer_role = False
Settings = CerebrasLLMSettings
_settings: Settings
[docs]
def __init__(
self,
*,
api_key: str,
base_url: str = "https://api.cerebras.ai/v1",
model: str | None = None,
settings: Settings | None = None,
**kwargs,
):
"""Initialize the Cerebras LLM service.
Args:
api_key: The API key for accessing Cerebras's API.
base_url: The base URL for Cerebras API. Defaults to "https://api.cerebras.ai/v1".
model: The model identifier to use. Defaults to "gpt-oss-120b".
.. deprecated:: 0.0.105
Use ``settings=CerebrasLLMService.Settings(model=...)`` instead.
settings: Runtime-updatable settings. When provided alongside deprecated
parameters, ``settings`` values take precedence.
**kwargs: Additional keyword arguments passed to OpenAILLMService.
"""
# 1. Initialize default_settings with hardcoded defaults
default_settings = self.Settings(model="gpt-oss-120b")
# 2. Apply direct init arg overrides (deprecated)
if model is not None:
self._warn_init_param_moved_to_settings("model", "model")
default_settings.model = model
# 3. (No step 3, as there's no params object to apply)
# 4. Apply settings delta (canonical API, always wins)
if settings is not None:
default_settings.apply_update(settings)
super().__init__(api_key=api_key, base_url=base_url, settings=default_settings, **kwargs)
[docs]
def create_client(self, api_key=None, base_url=None, **kwargs):
"""Create OpenAI-compatible client for Cerebras API endpoint.
Args:
api_key: The API key for authentication. If None, uses instance key.
base_url: The base URL for the API. If None, uses instance URL.
**kwargs: Additional arguments passed to the client constructor.
Returns:
An OpenAI-compatible client configured for Cerebras API.
"""
logger.debug(f"Creating Cerebras client with api {base_url}")
return super().create_client(api_key, base_url, **kwargs)
[docs]
def build_chat_completion_params(self, params_from_context: OpenAILLMInvocationParams) -> dict:
"""Build parameters for Cerebras chat completion request.
Cerebras supports a subset of OpenAI parameters, focusing on core
completion settings without advanced features like frequency/presence penalties.
Args:
params_from_context: Parameters, derived from the LLM context, to
use for the chat completion. Contains messages, tools, and tool
choice.
Returns:
Dictionary of parameters for the chat completion request.
"""
params = {
"model": self._settings.model,
"stream": True,
"seed": self._settings.seed,
"temperature": self._settings.temperature,
"top_p": self._settings.top_p,
"max_completion_tokens": self._settings.max_completion_tokens,
}
# Messages, tools, tool_choice
params.update(params_from_context)
params.update(self._settings.extra)
return params