#
# Copyright (c) 2024-2026, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
"""Fireworks AI 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 FireworksLLMSettings(BaseOpenAILLMService.Settings):
"""Settings for FireworksLLMService."""
pass
[docs]
class FireworksLLMService(OpenAILLMService):
"""A service for interacting with Fireworks AI using the OpenAI-compatible interface.
This service extends OpenAILLMService to connect to Fireworks' API endpoint while
maintaining full compatibility with OpenAI's interface and functionality.
"""
Settings = FireworksLLMSettings
_settings: Settings
[docs]
def __init__(
self,
*,
api_key: str,
model: str | None = None,
base_url: str = "https://api.fireworks.ai/inference/v1",
settings: Settings | None = None,
**kwargs,
):
"""Initialize the Fireworks LLM service.
Args:
api_key: The API key for accessing Fireworks AI.
model: The model identifier to use. Defaults to "accounts/fireworks/models/firefunction-v2".
.. deprecated:: 0.0.105
Use ``settings=FireworksLLMService.Settings(model=...)`` instead.
base_url: The base URL for Fireworks API. Defaults to "https://api.fireworks.ai/inference/v1".
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="accounts/fireworks/models/firefunction-v2")
# 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 Fireworks API endpoint.
Args:
api_key: API key for authentication. If None, uses instance default.
base_url: Base URL for the API. If None, uses instance default.
**kwargs: Additional arguments passed to the client constructor.
Returns:
Configured OpenAI client instance for Fireworks API.
"""
logger.debug(f"Creating Fireworks 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 Fireworks chat completion request.
Fireworks doesn't support some OpenAI parameters like seed, max_completion_tokens,
and stream_options.
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,
"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,
}
# Messages, tools, tool_choice
params.update(params_from_context)
params.update(self._settings.extra)
return params