Merge pull request #3980 from pipecat-ai/aleix/move-google-vertex-openai
Move Google Vertex and OpenAI LLM modules to subpackages
This commit is contained in:
Aleix Conchillo Flaqué
1
changelog/3980.deprecated.md
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1
changelog/3980.deprecated.md
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@@ -0,0 +1 @@
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- Deprecated `pipecat.services.google.llm_vertex`, `pipecat.services.google.llm_openai`, and `pipecat.services.google.gemini_live.llm_vertex` modules. Use `pipecat.services.google.vertex.llm`, `pipecat.services.google.openai.llm`, and `pipecat.services.google.gemini_live.vertex.llm` instead. The old import paths still work but will emit a `DeprecationWarning`.
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@@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments
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from pipecat.runner.utils import create_transport
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from pipecat.services.deepgram.stt import DeepgramSTTService
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from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
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from pipecat.services.google.llm_openai import GoogleLLMOpenAIBetaService
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from pipecat.services.google.openai.llm import GoogleLLMOpenAIBetaService
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from pipecat.services.llm_service import FunctionCallParams
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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from pipecat.transports.daily.transport import DailyParams
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@@ -26,7 +26,7 @@ from pipecat.runner.types import RunnerArguments
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from pipecat.runner.utils import create_transport
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from pipecat.services.deepgram.stt import DeepgramSTTService
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from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
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from pipecat.services.google.llm_vertex import GoogleVertexLLMService
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from pipecat.services.google.vertex.llm import GoogleVertexLLMService
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from pipecat.services.llm_service import FunctionCallParams
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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from pipecat.transports.daily.transport import DailyParams
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@@ -26,7 +26,7 @@ from pipecat.processors.aggregators.llm_response_universal import (
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)
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from pipecat.runner.types import RunnerArguments
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from pipecat.runner.utils import create_transport
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from pipecat.services.google.gemini_live.llm_vertex import GeminiLiveVertexLLMService
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from pipecat.services.google.gemini_live.vertex.llm import GeminiLiveVertexLLMService
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from pipecat.services.llm_service import FunctionCallParams
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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from pipecat.transports.daily.transport import DailyParams
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@@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments
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from pipecat.runner.utils import create_transport
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from pipecat.services.cartesia.tts import CartesiaTTSService
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from pipecat.services.deepgram.stt import DeepgramSTTService
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from pipecat.services.google.llm_vertex import GoogleVertexLLMService
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from pipecat.services.google.vertex.llm import GoogleVertexLLMService
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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from pipecat.transports.daily.transport import DailyParams
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from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
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@@ -19,7 +19,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext
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from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
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from pipecat.runner.types import RunnerArguments
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from pipecat.runner.utils import create_transport
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from pipecat.services.google.gemini_live.llm_vertex import GeminiLiveVertexLLMService
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from pipecat.services.google.gemini_live.vertex.llm import GeminiLiveVertexLLMService
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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from pipecat.transports.daily.transport import DailyParams
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from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
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@@ -12,12 +12,12 @@ from .frames import *
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from .gemini_live import *
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from .image import *
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from .llm import *
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from .llm_openai import *
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from .llm_vertex import *
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from .openai import *
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from .rtvi import *
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from .stt import *
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from .tts import *
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from .vertex import *
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sys.modules[__name__] = DeprecatedModuleProxy(
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globals(), "google", "google.[frames,image,llm,llm_openai,llm_vertex,rtvi,stt,tts]"
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globals(), "google", "google.[frames,image,llm,openai,vertex,rtvi,stt,tts]"
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)
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@@ -1,6 +1,6 @@
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from .file_api import GeminiFileAPI
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from .llm import GeminiLiveLLMService
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from .llm_vertex import GeminiLiveVertexLLMService
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from .vertex.llm import GeminiLiveVertexLLMService
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__all__ = [
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"GeminiFileAPI",
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@@ -4,277 +4,15 @@
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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"""Service for accessing Gemini Live via Google Vertex AI.
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"""Deprecated: use ``pipecat.services.google.gemini_live.vertex.llm`` instead."""
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This module provides integration with Google's Gemini Live model via
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Vertex AI, supporting both text and audio modalities with voice transcription,
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streaming responses, and tool usage.
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"""
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import warnings
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import json
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from dataclasses import dataclass
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from typing import List, Optional, Union
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from loguru import logger
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from pipecat.adapters.schemas.tools_schema import ToolsSchema
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from pipecat.services.google.gemini_live.llm import (
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GeminiLiveLLMService,
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GeminiLiveLLMSettings,
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GeminiMediaResolution,
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GeminiModalities,
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HttpOptions,
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InputParams,
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language_to_gemini_language,
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warnings.warn(
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"Module `pipecat.services.google.gemini_live.llm_vertex` is deprecated, "
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"use `pipecat.services.google.gemini_live.vertex.llm` instead.",
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DeprecationWarning,
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stacklevel=2,
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)
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from pipecat.services.settings import _warn_deprecated_param
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try:
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from google.auth import default
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from google.auth.exceptions import GoogleAuthError
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from google.auth.transport.requests import Request
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from google.genai import Client
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from google.oauth2 import service_account
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except ModuleNotFoundError as e:
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logger.error(f"Exception: {e}")
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logger.error("In order to use Google Vertex AI, you need to `pip install pipecat-ai[google]`.")
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raise Exception(f"Missing module: {e}")
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@dataclass
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class GeminiLiveVertexLLMSettings(GeminiLiveLLMSettings):
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"""Settings for GeminiLiveVertexLLMService."""
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pass
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class GeminiLiveVertexLLMService(GeminiLiveLLMService):
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"""Provides access to Google's Gemini Live model via Vertex AI.
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This service enables real-time conversations with Gemini, supporting both
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text and audio modalities. It handles voice transcription, streaming audio
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responses, and tool usage.
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"""
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Settings = GeminiLiveVertexLLMSettings
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_settings: GeminiLiveVertexLLMSettings
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def __init__(
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self,
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*,
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credentials: Optional[str] = None,
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credentials_path: Optional[str] = None,
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location: str,
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project_id: str,
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model: Optional[str] = None,
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voice_id: str = "Charon",
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start_audio_paused: bool = False,
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start_video_paused: bool = False,
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system_instruction: Optional[str] = None,
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tools: Optional[Union[List[dict], ToolsSchema]] = None,
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params: Optional[InputParams] = None,
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settings: Optional[GeminiLiveVertexLLMSettings] = None,
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inference_on_context_initialization: bool = True,
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file_api_base_url: str = "https://generativelanguage.googleapis.com/v1beta/files",
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http_options: Optional[HttpOptions] = None,
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**kwargs,
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):
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"""Initialize the service for accessing Gemini Live via Google Vertex AI.
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Args:
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credentials: JSON string of service account credentials.
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credentials_path: Path to the service account JSON file.
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location: GCP region for Vertex AI endpoint (e.g., "us-east4").
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project_id: Google Cloud project ID.
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model: Model identifier to use.
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.. deprecated:: 0.0.105
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Use ``settings=GeminiLiveLLMSettings(model=...)`` instead.
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voice_id: TTS voice identifier. Defaults to "Charon".
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.. deprecated:: 0.0.105
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Use ``settings=GeminiLiveVertexLLMSettings(voice=...)`` instead.
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start_audio_paused: Whether to start with audio input paused. Defaults to False.
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start_video_paused: Whether to start with video input paused. Defaults to False.
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system_instruction: System prompt for the model. Defaults to None.
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tools: Tools/functions available to the model. Defaults to None.
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params: Configuration parameters for the model along with Vertex AI
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location and project ID.
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.. deprecated:: 0.0.105
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Use ``settings=GeminiLiveLLMSettings(...)`` instead.
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settings: Gemini Live LLM settings. If provided together with deprecated
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top-level parameters, the ``settings`` values take precedence.
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inference_on_context_initialization: Whether to generate a response when context
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is first set. Defaults to True.
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file_api_base_url: Base URL for the Gemini File API. Defaults to the official endpoint.
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http_options: HTTP options for the client.
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**kwargs: Additional arguments passed to parent GeminiLiveLLMService.
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"""
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# Check if user incorrectly passed api_key, which is used by parent
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# class but not here.
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if "api_key" in kwargs:
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logger.error(
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"GeminiLiveVertexLLMService does not accept 'api_key' parameter. "
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"Use 'credentials' or 'credentials_path' instead for Vertex AI authentication."
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)
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raise ValueError(
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"Invalid parameter 'api_key'. Use 'credentials' or 'credentials_path' for Vertex AI authentication."
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)
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# These need to be set before calling super().__init__() because
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# super().__init__() invokes create_client(), which needs these.
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self._credentials = self._get_credentials(credentials, credentials_path)
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self._project_id = project_id
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self._location = location
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# Build default_settings from deprecated args, then apply settings delta.
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# We pass settings= to super() instead of model=/params= to avoid
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# double deprecation warnings from the parent.
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# 1. Initialize default_settings with hardcoded defaults
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default_settings = GeminiLiveVertexLLMSettings(
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model="google/gemini-live-2.5-flash-native-audio",
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voice="Charon",
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frequency_penalty=None,
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max_tokens=4096,
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presence_penalty=None,
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temperature=None,
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top_k=None,
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top_p=None,
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seed=None,
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filter_incomplete_user_turns=False,
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user_turn_completion_config=None,
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modalities=GeminiModalities.AUDIO,
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language="en-US",
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media_resolution=GeminiMediaResolution.UNSPECIFIED,
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vad=None,
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context_window_compression={},
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thinking={},
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enable_affective_dialog=False,
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proactivity={},
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extra={},
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)
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# 2. Apply direct init arg overrides (deprecated)
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if model is not None:
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_warn_deprecated_param("model", GeminiLiveVertexLLMSettings, "model")
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default_settings.model = model
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if voice_id != "Charon":
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_warn_deprecated_param("voice_id", GeminiLiveVertexLLMSettings, "voice")
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default_settings.voice = voice_id
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# 3. Apply params overrides — only if settings not provided
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if params is not None:
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_warn_deprecated_param("params", GeminiLiveVertexLLMSettings)
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if not settings:
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default_settings.frequency_penalty = params.frequency_penalty
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default_settings.max_tokens = params.max_tokens
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default_settings.presence_penalty = params.presence_penalty
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default_settings.temperature = params.temperature
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default_settings.top_k = params.top_k
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default_settings.top_p = params.top_p
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default_settings.modalities = params.modalities
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default_settings.language = (
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language_to_gemini_language(params.language) if params.language else "en-US"
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)
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default_settings.media_resolution = params.media_resolution
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default_settings.vad = params.vad
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default_settings.context_window_compression = (
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params.context_window_compression.model_dump()
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if params.context_window_compression
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else {}
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)
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default_settings.thinking = params.thinking or {}
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default_settings.enable_affective_dialog = params.enable_affective_dialog or False
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default_settings.proactivity = params.proactivity or {}
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if isinstance(params.extra, dict):
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default_settings.extra = params.extra
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# 4. Apply settings delta (canonical API, always wins)
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if settings is not None:
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default_settings.apply_update(settings)
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# Call parent constructor with the obtained settings
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super().__init__(
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# api_key is required by parent class, but actually not used with
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# Vertex
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api_key="dummy",
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start_audio_paused=start_audio_paused,
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start_video_paused=start_video_paused,
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system_instruction=system_instruction,
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tools=tools,
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settings=default_settings,
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inference_on_context_initialization=inference_on_context_initialization,
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file_api_base_url=file_api_base_url,
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http_options=http_options,
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**kwargs,
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)
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def create_client(self):
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"""Create the Gemini client instance."""
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self._client = Client(
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vertexai=True,
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credentials=self._credentials,
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project=self._project_id,
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location=self._location,
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http_options=self._http_options,
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)
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@property
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def file_api(self):
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"""Gemini File API is not supported with Vertex AI."""
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raise NotImplementedError(
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"When using Vertex AI, the recommended approach is to use Google Cloud Storage for file handling. The Gemini File API is not directly supported in this context."
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)
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@staticmethod
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def _get_credentials(credentials: Optional[str], credentials_path: Optional[str]) -> str:
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"""Retrieve Credentials using Google service account credentials JSON.
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Supports multiple authentication methods:
|
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1. Direct JSON credentials string
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2. Path to service account JSON file
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3. Default application credentials (ADC)
|
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|
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Args:
|
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credentials: JSON string of service account credentials.
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credentials_path: Path to the service account JSON file.
|
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Returns:
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OAuth token for API authentication.
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Raises:
|
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ValueError: If no valid credentials are provided or found.
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"""
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creds: Optional[service_account.Credentials] = None
|
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|
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if credentials:
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# Parse and load credentials from JSON string
|
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creds = service_account.Credentials.from_service_account_info(
|
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json.loads(credentials),
|
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scopes=["https://www.googleapis.com/auth/cloud-platform"],
|
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)
|
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elif credentials_path:
|
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# Load credentials from JSON file
|
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creds = service_account.Credentials.from_service_account_file(
|
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credentials_path,
|
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scopes=["https://www.googleapis.com/auth/cloud-platform"],
|
||||
)
|
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else:
|
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try:
|
||||
creds, project_id = default(
|
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scopes=["https://www.googleapis.com/auth/cloud-platform"]
|
||||
)
|
||||
except GoogleAuthError:
|
||||
pass
|
||||
|
||||
if not creds:
|
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raise ValueError("No valid credentials provided.")
|
||||
|
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creds.refresh(Request()) # Ensure token is up-to-date, lifetime is 1 hour.
|
||||
|
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return creds
|
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from pipecat.services.google.gemini_live.vertex.llm import * # noqa: E402, F401, F403
|
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|
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@@ -0,0 +1,5 @@
|
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#
|
||||
# Copyright (c) 2024-2026, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
280
src/pipecat/services/google/gemini_live/vertex/llm.py
Normal file
280
src/pipecat/services/google/gemini_live/vertex/llm.py
Normal file
@@ -0,0 +1,280 @@
|
||||
#
|
||||
# Copyright (c) 2024-2026, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
"""Service for accessing Gemini Live via Google Vertex AI.
|
||||
|
||||
This module provides integration with Google's Gemini Live model via
|
||||
Vertex AI, supporting both text and audio modalities with voice transcription,
|
||||
streaming responses, and tool usage.
|
||||
"""
|
||||
|
||||
import json
|
||||
from dataclasses import dataclass
|
||||
from typing import List, Optional, Union
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.adapters.schemas.tools_schema import ToolsSchema
|
||||
from pipecat.services.google.gemini_live.llm import (
|
||||
GeminiLiveLLMService,
|
||||
GeminiLiveLLMSettings,
|
||||
GeminiMediaResolution,
|
||||
GeminiModalities,
|
||||
HttpOptions,
|
||||
InputParams,
|
||||
language_to_gemini_language,
|
||||
)
|
||||
from pipecat.services.settings import _warn_deprecated_param
|
||||
|
||||
try:
|
||||
from google.auth import default
|
||||
from google.auth.exceptions import GoogleAuthError
|
||||
from google.auth.transport.requests import Request
|
||||
from google.genai import Client
|
||||
from google.oauth2 import service_account
|
||||
|
||||
except ModuleNotFoundError as e:
|
||||
logger.error(f"Exception: {e}")
|
||||
logger.error("In order to use Google Vertex AI, you need to `pip install pipecat-ai[google]`.")
|
||||
raise Exception(f"Missing module: {e}")
|
||||
|
||||
|
||||
@dataclass
|
||||
class GeminiLiveVertexLLMSettings(GeminiLiveLLMSettings):
|
||||
"""Settings for GeminiLiveVertexLLMService."""
|
||||
|
||||
pass
|
||||
|
||||
|
||||
class GeminiLiveVertexLLMService(GeminiLiveLLMService):
|
||||
"""Provides access to Google's Gemini Live model via Vertex AI.
|
||||
|
||||
This service enables real-time conversations with Gemini, supporting both
|
||||
text and audio modalities. It handles voice transcription, streaming audio
|
||||
responses, and tool usage.
|
||||
"""
|
||||
|
||||
Settings = GeminiLiveVertexLLMSettings
|
||||
_settings: GeminiLiveVertexLLMSettings
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
credentials: Optional[str] = None,
|
||||
credentials_path: Optional[str] = None,
|
||||
location: str,
|
||||
project_id: str,
|
||||
model: Optional[str] = None,
|
||||
voice_id: str = "Charon",
|
||||
start_audio_paused: bool = False,
|
||||
start_video_paused: bool = False,
|
||||
system_instruction: Optional[str] = None,
|
||||
tools: Optional[Union[List[dict], ToolsSchema]] = None,
|
||||
params: Optional[InputParams] = None,
|
||||
settings: Optional[GeminiLiveVertexLLMSettings] = None,
|
||||
inference_on_context_initialization: bool = True,
|
||||
file_api_base_url: str = "https://generativelanguage.googleapis.com/v1beta/files",
|
||||
http_options: Optional[HttpOptions] = None,
|
||||
**kwargs,
|
||||
):
|
||||
"""Initialize the service for accessing Gemini Live via Google Vertex AI.
|
||||
|
||||
Args:
|
||||
credentials: JSON string of service account credentials.
|
||||
credentials_path: Path to the service account JSON file.
|
||||
location: GCP region for Vertex AI endpoint (e.g., "us-east4").
|
||||
project_id: Google Cloud project ID.
|
||||
model: Model identifier to use.
|
||||
|
||||
.. deprecated:: 0.0.105
|
||||
Use ``settings=GeminiLiveLLMSettings(model=...)`` instead.
|
||||
|
||||
voice_id: TTS voice identifier. Defaults to "Charon".
|
||||
|
||||
.. deprecated:: 0.0.105
|
||||
Use ``settings=GeminiLiveVertexLLMSettings(voice=...)`` instead.
|
||||
start_audio_paused: Whether to start with audio input paused. Defaults to False.
|
||||
start_video_paused: Whether to start with video input paused. Defaults to False.
|
||||
system_instruction: System prompt for the model. Defaults to None.
|
||||
tools: Tools/functions available to the model. Defaults to None.
|
||||
params: Configuration parameters for the model along with Vertex AI
|
||||
location and project ID.
|
||||
|
||||
.. deprecated:: 0.0.105
|
||||
Use ``settings=GeminiLiveLLMSettings(...)`` instead.
|
||||
|
||||
settings: Gemini Live LLM settings. If provided together with deprecated
|
||||
top-level parameters, the ``settings`` values take precedence.
|
||||
inference_on_context_initialization: Whether to generate a response when context
|
||||
is first set. Defaults to True.
|
||||
file_api_base_url: Base URL for the Gemini File API. Defaults to the official endpoint.
|
||||
http_options: HTTP options for the client.
|
||||
**kwargs: Additional arguments passed to parent GeminiLiveLLMService.
|
||||
"""
|
||||
# Check if user incorrectly passed api_key, which is used by parent
|
||||
# class but not here.
|
||||
if "api_key" in kwargs:
|
||||
logger.error(
|
||||
"GeminiLiveVertexLLMService does not accept 'api_key' parameter. "
|
||||
"Use 'credentials' or 'credentials_path' instead for Vertex AI authentication."
|
||||
)
|
||||
raise ValueError(
|
||||
"Invalid parameter 'api_key'. Use 'credentials' or 'credentials_path' for Vertex AI authentication."
|
||||
)
|
||||
|
||||
# These need to be set before calling super().__init__() because
|
||||
# super().__init__() invokes create_client(), which needs these.
|
||||
self._credentials = self._get_credentials(credentials, credentials_path)
|
||||
self._project_id = project_id
|
||||
self._location = location
|
||||
|
||||
# Build default_settings from deprecated args, then apply settings delta.
|
||||
# We pass settings= to super() instead of model=/params= to avoid
|
||||
# double deprecation warnings from the parent.
|
||||
|
||||
# 1. Initialize default_settings with hardcoded defaults
|
||||
default_settings = GeminiLiveVertexLLMSettings(
|
||||
model="google/gemini-live-2.5-flash-native-audio",
|
||||
voice="Charon",
|
||||
frequency_penalty=None,
|
||||
max_tokens=4096,
|
||||
presence_penalty=None,
|
||||
temperature=None,
|
||||
top_k=None,
|
||||
top_p=None,
|
||||
seed=None,
|
||||
filter_incomplete_user_turns=False,
|
||||
user_turn_completion_config=None,
|
||||
modalities=GeminiModalities.AUDIO,
|
||||
language="en-US",
|
||||
media_resolution=GeminiMediaResolution.UNSPECIFIED,
|
||||
vad=None,
|
||||
context_window_compression={},
|
||||
thinking={},
|
||||
enable_affective_dialog=False,
|
||||
proactivity={},
|
||||
extra={},
|
||||
)
|
||||
|
||||
# 2. Apply direct init arg overrides (deprecated)
|
||||
if model is not None:
|
||||
_warn_deprecated_param("model", GeminiLiveVertexLLMSettings, "model")
|
||||
default_settings.model = model
|
||||
if voice_id != "Charon":
|
||||
_warn_deprecated_param("voice_id", GeminiLiveVertexLLMSettings, "voice")
|
||||
default_settings.voice = voice_id
|
||||
|
||||
# 3. Apply params overrides — only if settings not provided
|
||||
if params is not None:
|
||||
_warn_deprecated_param("params", GeminiLiveVertexLLMSettings)
|
||||
if not settings:
|
||||
default_settings.frequency_penalty = params.frequency_penalty
|
||||
default_settings.max_tokens = params.max_tokens
|
||||
default_settings.presence_penalty = params.presence_penalty
|
||||
default_settings.temperature = params.temperature
|
||||
default_settings.top_k = params.top_k
|
||||
default_settings.top_p = params.top_p
|
||||
default_settings.modalities = params.modalities
|
||||
default_settings.language = (
|
||||
language_to_gemini_language(params.language) if params.language else "en-US"
|
||||
)
|
||||
default_settings.media_resolution = params.media_resolution
|
||||
default_settings.vad = params.vad
|
||||
default_settings.context_window_compression = (
|
||||
params.context_window_compression.model_dump()
|
||||
if params.context_window_compression
|
||||
else {}
|
||||
)
|
||||
default_settings.thinking = params.thinking or {}
|
||||
default_settings.enable_affective_dialog = params.enable_affective_dialog or False
|
||||
default_settings.proactivity = params.proactivity or {}
|
||||
if isinstance(params.extra, dict):
|
||||
default_settings.extra = params.extra
|
||||
|
||||
# 4. Apply settings delta (canonical API, always wins)
|
||||
if settings is not None:
|
||||
default_settings.apply_update(settings)
|
||||
|
||||
# Call parent constructor with the obtained settings
|
||||
super().__init__(
|
||||
# api_key is required by parent class, but actually not used with
|
||||
# Vertex
|
||||
api_key="dummy",
|
||||
start_audio_paused=start_audio_paused,
|
||||
start_video_paused=start_video_paused,
|
||||
system_instruction=system_instruction,
|
||||
tools=tools,
|
||||
settings=default_settings,
|
||||
inference_on_context_initialization=inference_on_context_initialization,
|
||||
file_api_base_url=file_api_base_url,
|
||||
http_options=http_options,
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
def create_client(self):
|
||||
"""Create the Gemini client instance."""
|
||||
self._client = Client(
|
||||
vertexai=True,
|
||||
credentials=self._credentials,
|
||||
project=self._project_id,
|
||||
location=self._location,
|
||||
http_options=self._http_options,
|
||||
)
|
||||
|
||||
@property
|
||||
def file_api(self):
|
||||
"""Gemini File API is not supported with Vertex AI."""
|
||||
raise NotImplementedError(
|
||||
"When using Vertex AI, the recommended approach is to use Google Cloud Storage for file handling. The Gemini File API is not directly supported in this context."
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _get_credentials(credentials: Optional[str], credentials_path: Optional[str]) -> str:
|
||||
"""Retrieve Credentials using Google service account credentials JSON.
|
||||
|
||||
Supports multiple authentication methods:
|
||||
1. Direct JSON credentials string
|
||||
2. Path to service account JSON file
|
||||
3. Default application credentials (ADC)
|
||||
|
||||
Args:
|
||||
credentials: JSON string of service account credentials.
|
||||
credentials_path: Path to the service account JSON file.
|
||||
|
||||
Returns:
|
||||
OAuth token for API authentication.
|
||||
|
||||
Raises:
|
||||
ValueError: If no valid credentials are provided or found.
|
||||
"""
|
||||
creds: Optional[service_account.Credentials] = None
|
||||
|
||||
if credentials:
|
||||
# Parse and load credentials from JSON string
|
||||
creds = service_account.Credentials.from_service_account_info(
|
||||
json.loads(credentials),
|
||||
scopes=["https://www.googleapis.com/auth/cloud-platform"],
|
||||
)
|
||||
elif credentials_path:
|
||||
# Load credentials from JSON file
|
||||
creds = service_account.Credentials.from_service_account_file(
|
||||
credentials_path,
|
||||
scopes=["https://www.googleapis.com/auth/cloud-platform"],
|
||||
)
|
||||
else:
|
||||
try:
|
||||
creds, project_id = default(
|
||||
scopes=["https://www.googleapis.com/auth/cloud-platform"]
|
||||
)
|
||||
except GoogleAuthError:
|
||||
pass
|
||||
|
||||
if not creds:
|
||||
raise ValueError("No valid credentials provided.")
|
||||
|
||||
creds.refresh(Request()) # Ensure token is up-to-date, lifetime is 1 hour.
|
||||
|
||||
return creds
|
||||
@@ -13,12 +13,12 @@ from pipecat.services import DeprecatedModuleProxy
|
||||
from .frames import *
|
||||
from .image import *
|
||||
from .llm import *
|
||||
from .llm_openai import *
|
||||
from .llm_vertex import *
|
||||
from .openai import *
|
||||
from .rtvi import *
|
||||
from .stt import *
|
||||
from .tts import *
|
||||
from .vertex import *
|
||||
|
||||
sys.modules[__name__] = DeprecatedModuleProxy(
|
||||
globals(), "google", "google.[frames,image,llm,llm_openai,llm_vertex,rtvi,stt,tts]"
|
||||
globals(), "google", "google.[frames,image,llm,openai,vertex,rtvi,stt,tts]"
|
||||
)
|
||||
|
||||
@@ -4,211 +4,15 @@
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
"""Google LLM service using OpenAI-compatible API format.
|
||||
"""Deprecated: use ``pipecat.services.google.openai.llm`` instead."""
|
||||
|
||||
This module provides integration with Google's AI LLM models using the OpenAI
|
||||
API format through Google's Gemini API OpenAI compatibility layer.
|
||||
"""
|
||||
import warnings
|
||||
|
||||
import json
|
||||
import os
|
||||
from dataclasses import dataclass
|
||||
from typing import Optional
|
||||
warnings.warn(
|
||||
"Module `pipecat.services.google.llm_openai` is deprecated, "
|
||||
"use `pipecat.services.google.openai.llm` instead.",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
|
||||
from openai import AsyncStream
|
||||
from openai.types.chat import ChatCompletionChunk
|
||||
|
||||
from pipecat.services.llm_service import FunctionCallFromLLM
|
||||
|
||||
# Suppress gRPC fork warnings
|
||||
os.environ["GRPC_ENABLE_FORK_SUPPORT"] = "false"
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.frames.frames import LLMTextFrame
|
||||
from pipecat.metrics.metrics import LLMTokenUsage
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.openai.base_llm import OpenAILLMSettings
|
||||
from pipecat.services.openai.llm import OpenAILLMService
|
||||
from pipecat.services.settings import _warn_deprecated_param
|
||||
|
||||
|
||||
@dataclass
|
||||
class GoogleOpenAILLMSettings(OpenAILLMSettings):
|
||||
"""Settings for GoogleLLMOpenAIBetaService."""
|
||||
|
||||
pass
|
||||
|
||||
|
||||
class GoogleLLMOpenAIBetaService(OpenAILLMService):
|
||||
"""Google LLM service using OpenAI-compatible API format.
|
||||
|
||||
This service provides access to Google's AI LLM models (like Gemini) through
|
||||
the OpenAI API format. It handles streaming responses, function calls, and
|
||||
tool usage while maintaining compatibility with OpenAI's interface.
|
||||
|
||||
Note: This service includes a workaround for a Google API bug where function
|
||||
call indices may be incorrectly set to None, resulting in empty function names.
|
||||
|
||||
.. deprecated:: 0.0.82
|
||||
GoogleLLMOpenAIBetaService is deprecated and will be removed in a future version.
|
||||
Use GoogleLLMService instead for better integration with Google's native API.
|
||||
|
||||
Reference:
|
||||
https://ai.google.dev/gemini-api/docs/openai
|
||||
"""
|
||||
|
||||
Settings = GoogleOpenAILLMSettings
|
||||
_settings: GoogleOpenAILLMSettings
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
api_key: str,
|
||||
base_url: str = "https://generativelanguage.googleapis.com/v1beta/openai/",
|
||||
model: Optional[str] = None,
|
||||
settings: Optional[GoogleOpenAILLMSettings] = None,
|
||||
**kwargs,
|
||||
):
|
||||
"""Initialize the Google LLM service.
|
||||
|
||||
Args:
|
||||
api_key: Google API key for authentication.
|
||||
base_url: Base URL for Google's OpenAI-compatible API.
|
||||
model: Google model name to use (e.g., "gemini-2.0-flash").
|
||||
|
||||
.. deprecated:: 0.0.105
|
||||
Use ``settings=OpenAILLMSettings(model=...)`` instead.
|
||||
|
||||
settings: Runtime-updatable settings. When provided alongside deprecated
|
||||
parameters, ``settings`` values take precedence.
|
||||
**kwargs: Additional arguments passed to the parent OpenAILLMService.
|
||||
"""
|
||||
import warnings
|
||||
|
||||
with warnings.catch_warnings():
|
||||
warnings.simplefilter("always")
|
||||
warnings.warn(
|
||||
"GoogleLLMOpenAIBetaService is deprecated and will be removed in a future version. "
|
||||
"Use GoogleLLMService instead for better integration with Google's native API.",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
|
||||
# 1. Initialize default_settings with hardcoded defaults
|
||||
default_settings = GoogleOpenAILLMSettings(model="gemini-2.0-flash")
|
||||
|
||||
# 2. Apply direct init arg overrides (deprecated)
|
||||
if model is not None:
|
||||
_warn_deprecated_param("model", GoogleOpenAILLMSettings, "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)
|
||||
|
||||
async def _process_context(self, context: OpenAILLMContext):
|
||||
functions_list = []
|
||||
arguments_list = []
|
||||
tool_id_list = []
|
||||
func_idx = 0
|
||||
function_name = ""
|
||||
arguments = ""
|
||||
tool_call_id = ""
|
||||
|
||||
await self.start_ttfb_metrics()
|
||||
|
||||
chunk_stream: AsyncStream[
|
||||
ChatCompletionChunk
|
||||
] = await self._stream_chat_completions_specific_context(context)
|
||||
|
||||
# Use context manager to ensure stream is closed on cancellation/exception.
|
||||
# Without this, CancelledError during iteration leaves the underlying socket open.
|
||||
async with chunk_stream:
|
||||
async for chunk in chunk_stream:
|
||||
if chunk.usage:
|
||||
tokens = LLMTokenUsage(
|
||||
prompt_tokens=chunk.usage.prompt_tokens or 0,
|
||||
completion_tokens=chunk.usage.completion_tokens or 0,
|
||||
total_tokens=chunk.usage.total_tokens or 0,
|
||||
)
|
||||
await self.start_llm_usage_metrics(tokens)
|
||||
|
||||
if chunk.choices is None or len(chunk.choices) == 0:
|
||||
continue
|
||||
|
||||
await self.stop_ttfb_metrics()
|
||||
|
||||
if not chunk.choices[0].delta:
|
||||
continue
|
||||
|
||||
if chunk.choices[0].delta.tool_calls:
|
||||
# We're streaming the LLM response to enable the fastest response times.
|
||||
# For text, we just yield each chunk as we receive it and count on consumers
|
||||
# to do whatever coalescing they need (eg. to pass full sentences to TTS)
|
||||
#
|
||||
# If the LLM is a function call, we'll do some coalescing here.
|
||||
# If the response contains a function name, we'll yield a frame to tell consumers
|
||||
# that they can start preparing to call the function with that name.
|
||||
# We accumulate all the arguments for the rest of the streamed response, then when
|
||||
# the response is done, we package up all the arguments and the function name and
|
||||
# yield a frame containing the function name and the arguments.
|
||||
logger.debug(f"Tool call: {chunk.choices[0].delta.tool_calls}")
|
||||
tool_call = chunk.choices[0].delta.tool_calls[0]
|
||||
if tool_call.index != func_idx:
|
||||
functions_list.append(function_name)
|
||||
arguments_list.append(arguments)
|
||||
tool_id_list.append(tool_call_id)
|
||||
function_name = ""
|
||||
arguments = ""
|
||||
tool_call_id = ""
|
||||
func_idx += 1
|
||||
if tool_call.function and tool_call.function.name:
|
||||
function_name += tool_call.function.name
|
||||
tool_call_id = tool_call.id
|
||||
if tool_call.function and tool_call.function.arguments:
|
||||
# Keep iterating through the response to collect all the argument fragments
|
||||
arguments += tool_call.function.arguments
|
||||
elif chunk.choices[0].delta.content:
|
||||
await self.push_frame(LLMTextFrame(chunk.choices[0].delta.content))
|
||||
|
||||
# if we got a function name and arguments, check to see if it's a function with
|
||||
# a registered handler. If so, run the registered callback, save the result to
|
||||
# the context, and re-prompt to get a chat answer. If we don't have a registered
|
||||
# handler, raise an exception.
|
||||
if function_name and arguments:
|
||||
# added to the list as last function name and arguments not added to the list
|
||||
functions_list.append(function_name)
|
||||
arguments_list.append(arguments)
|
||||
tool_id_list.append(tool_call_id)
|
||||
|
||||
logger.debug(
|
||||
f"Function list: {functions_list}, Arguments list: {arguments_list}, Tool ID list: {tool_id_list}"
|
||||
)
|
||||
|
||||
function_calls = []
|
||||
for function_name, arguments, tool_id in zip(
|
||||
functions_list, arguments_list, tool_id_list
|
||||
):
|
||||
if function_name == "":
|
||||
# TODO: Remove the _process_context method once Google resolves the bug
|
||||
# where the index is incorrectly set to None instead of returning the actual index,
|
||||
# which currently results in an empty function name('').
|
||||
continue
|
||||
|
||||
arguments = json.loads(arguments)
|
||||
|
||||
function_calls.append(
|
||||
FunctionCallFromLLM(
|
||||
context=context,
|
||||
tool_call_id=tool_id,
|
||||
function_name=function_name,
|
||||
arguments=arguments,
|
||||
)
|
||||
)
|
||||
|
||||
await self.run_function_calls(function_calls)
|
||||
from pipecat.services.google.openai.llm import * # noqa: E402, F401, F403
|
||||
|
||||
@@ -4,306 +4,15 @@
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
"""Google Vertex AI LLM service implementation.
|
||||
"""Deprecated: use ``pipecat.services.google.vertex.llm`` instead."""
|
||||
|
||||
This module provides integration with Google's AI models via Vertex AI,
|
||||
extending the GoogleLLMService with Vertex AI authentication.
|
||||
"""
|
||||
import warnings
|
||||
|
||||
import json
|
||||
import os
|
||||
from dataclasses import dataclass
|
||||
warnings.warn(
|
||||
"Module `pipecat.services.google.llm_vertex` is deprecated, "
|
||||
"use `pipecat.services.google.vertex.llm` instead.",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
|
||||
# Suppress gRPC fork warnings
|
||||
os.environ["GRPC_ENABLE_FORK_SUPPORT"] = "false"
|
||||
|
||||
from typing import Optional
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings
|
||||
from pipecat.services.settings import _warn_deprecated_param
|
||||
|
||||
try:
|
||||
from google.auth import default
|
||||
from google.auth.exceptions import GoogleAuthError
|
||||
from google.auth.transport.requests import Request
|
||||
from google.genai import Client
|
||||
from google.genai.types import HttpOptions
|
||||
from google.oauth2 import service_account
|
||||
|
||||
except ModuleNotFoundError as e:
|
||||
logger.error(f"Exception: {e}")
|
||||
logger.error(
|
||||
"In order to use Google AI, you need to `pip install pipecat-ai[google]`. Also, set `GOOGLE_APPLICATION_CREDENTIALS` environment variable."
|
||||
)
|
||||
raise Exception(f"Missing module: {e}")
|
||||
|
||||
|
||||
@dataclass
|
||||
class GoogleVertexLLMSettings(GoogleLLMSettings):
|
||||
"""Settings for GoogleVertexLLMService."""
|
||||
|
||||
pass
|
||||
|
||||
|
||||
class GoogleVertexLLMService(GoogleLLMService):
|
||||
"""Google Vertex AI LLM service extending GoogleLLMService.
|
||||
|
||||
Provides access to Google's AI models via Vertex AI while using the same
|
||||
Google AI client and message format as GoogleLLMService. Handles authentication
|
||||
using Google service account credentials and configures the client for
|
||||
Vertex AI endpoints.
|
||||
|
||||
Reference:
|
||||
https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference
|
||||
"""
|
||||
|
||||
Settings = GoogleVertexLLMSettings
|
||||
_settings: GoogleVertexLLMSettings
|
||||
|
||||
class InputParams(GoogleLLMService.InputParams):
|
||||
"""Input parameters specific to Vertex AI.
|
||||
|
||||
Parameters:
|
||||
location: GCP region for Vertex AI endpoint (e.g., "us-east4").
|
||||
|
||||
.. deprecated:: 0.0.90
|
||||
Use `location` as a direct argument to
|
||||
`GoogleVertexLLMService.__init__()` instead.
|
||||
|
||||
project_id: Google Cloud project ID.
|
||||
|
||||
.. deprecated:: 0.0.90
|
||||
Use `project_id` as a direct argument to
|
||||
`GoogleVertexLLMService.__init__()` instead.
|
||||
"""
|
||||
|
||||
# https://cloud.google.com/vertex-ai/generative-ai/docs/learn/locations
|
||||
location: Optional[str] = None
|
||||
project_id: Optional[str] = None
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
"""Initializes the InputParams."""
|
||||
import warnings
|
||||
|
||||
with warnings.catch_warnings():
|
||||
warnings.simplefilter("always")
|
||||
if "location" in kwargs and kwargs["location"] is not None:
|
||||
warnings.warn(
|
||||
"GoogleVertexLLMService.InputParams.location is deprecated. "
|
||||
"Please provide 'location' as a direct argument to GoogleVertexLLMService.__init__() instead.",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
|
||||
if "project_id" in kwargs and kwargs["project_id"] is not None:
|
||||
warnings.warn(
|
||||
"GoogleVertexLLMService.InputParams.project_id is deprecated. "
|
||||
"Please provide 'project_id' as a direct argument to GoogleVertexLLMService.__init__() instead.",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
super().__init__(**kwargs)
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
credentials: Optional[str] = None,
|
||||
credentials_path: Optional[str] = None,
|
||||
model: Optional[str] = None,
|
||||
location: Optional[str] = None,
|
||||
project_id: Optional[str] = None,
|
||||
params: Optional[GoogleLLMService.InputParams] = None,
|
||||
settings: Optional[GoogleVertexLLMSettings] = None,
|
||||
system_instruction: Optional[str] = None,
|
||||
tools: Optional[list] = None,
|
||||
tool_config: Optional[dict] = None,
|
||||
http_options: Optional[HttpOptions] = None,
|
||||
**kwargs,
|
||||
):
|
||||
"""Initializes the VertexLLMService.
|
||||
|
||||
Args:
|
||||
credentials: JSON string of service account credentials.
|
||||
credentials_path: Path to the service account JSON file.
|
||||
model: Model identifier (e.g., "gemini-2.5-flash").
|
||||
|
||||
.. deprecated:: 0.0.105
|
||||
Use ``settings=GoogleLLMSettings(model=...)`` instead.
|
||||
|
||||
location: GCP region for Vertex AI endpoint (e.g., "us-east4").
|
||||
project_id: Google Cloud project ID.
|
||||
params: Input parameters for the model.
|
||||
|
||||
.. deprecated:: 0.0.105
|
||||
Use ``settings=GoogleLLMSettings(...)`` instead.
|
||||
|
||||
settings: Runtime-updatable settings for this service. When both
|
||||
deprecated parameters and *settings* are provided, *settings*
|
||||
values take precedence.
|
||||
system_instruction: System instruction/prompt for the model.
|
||||
|
||||
.. deprecated:: 0.0.105
|
||||
Use ``settings=GoogleVertexLLMSettings(system_instruction=...)`` instead.
|
||||
tools: List of available tools/functions.
|
||||
tool_config: Configuration for tool usage.
|
||||
http_options: HTTP options for the client.
|
||||
**kwargs: Additional arguments passed to GoogleLLMService.
|
||||
"""
|
||||
# Check if user incorrectly passed api_key, which is used by parent
|
||||
# class but not here.
|
||||
if "api_key" in kwargs:
|
||||
logger.error(
|
||||
"GoogleVertexLLMService does not accept 'api_key' parameter. "
|
||||
"Use 'credentials' or 'credentials_path' instead for Vertex AI authentication."
|
||||
)
|
||||
raise ValueError(
|
||||
"Invalid parameter 'api_key'. Use 'credentials' or 'credentials_path' for Vertex AI authentication."
|
||||
)
|
||||
|
||||
# Handle deprecated InputParams fields (location/project_id extraction
|
||||
# must happen before validation, regardless of settings)
|
||||
if params and isinstance(params, GoogleVertexLLMService.InputParams):
|
||||
if project_id is None:
|
||||
project_id = params.project_id
|
||||
if location is None:
|
||||
location = params.location
|
||||
# Convert to base InputParams
|
||||
params = GoogleLLMService.InputParams(
|
||||
**params.model_dump(exclude={"location", "project_id"}, exclude_unset=True)
|
||||
)
|
||||
|
||||
# Validate project_id and location parameters
|
||||
# NOTE: once we remove Vertex-specific InputParams class, we can update
|
||||
# __init__() signature as follows:
|
||||
# - location: str = "us-east4",
|
||||
# - project_id: str,
|
||||
# But for now, we need them as-is to maintain proper backward
|
||||
# compatibility.
|
||||
if project_id is None:
|
||||
raise ValueError("project_id is required")
|
||||
if location is None:
|
||||
# If location is not provided, default to "us-east4".
|
||||
# Note: this is legacy behavior; ideally location would be
|
||||
# required.
|
||||
logger.warning("location is not provided. Defaulting to 'us-east4'.")
|
||||
location = "us-east4" # Default location if not provided
|
||||
|
||||
# These need to be set before calling super().__init__() because
|
||||
# super().__init__() invokes _create_client(), which needs these.
|
||||
self._credentials = self._get_credentials(credentials, credentials_path)
|
||||
self._project_id = project_id
|
||||
self._location = location
|
||||
|
||||
# 1. Initialize default_settings with hardcoded defaults
|
||||
default_settings = GoogleVertexLLMSettings(
|
||||
model="gemini-2.5-flash",
|
||||
system_instruction=None,
|
||||
max_tokens=4096,
|
||||
temperature=None,
|
||||
top_k=None,
|
||||
top_p=None,
|
||||
frequency_penalty=None,
|
||||
presence_penalty=None,
|
||||
seed=None,
|
||||
filter_incomplete_user_turns=False,
|
||||
user_turn_completion_config=None,
|
||||
thinking=None,
|
||||
extra={},
|
||||
)
|
||||
|
||||
# 2. Apply direct init arg overrides (deprecated)
|
||||
if model is not None:
|
||||
_warn_deprecated_param("model", GoogleVertexLLMSettings, "model")
|
||||
default_settings.model = model
|
||||
if system_instruction is not None:
|
||||
_warn_deprecated_param(
|
||||
"system_instruction", GoogleVertexLLMSettings, "system_instruction"
|
||||
)
|
||||
default_settings.system_instruction = system_instruction
|
||||
|
||||
# 3. Apply params overrides — only if settings not provided
|
||||
if params is not None:
|
||||
_warn_deprecated_param("params", GoogleVertexLLMSettings)
|
||||
if not settings:
|
||||
default_settings.max_tokens = params.max_tokens
|
||||
default_settings.temperature = params.temperature
|
||||
default_settings.top_k = params.top_k
|
||||
default_settings.top_p = params.top_p
|
||||
default_settings.thinking = params.thinking
|
||||
if isinstance(params.extra, dict):
|
||||
default_settings.extra = params.extra
|
||||
|
||||
# 4. Apply settings delta (canonical API, always wins)
|
||||
if settings is not None:
|
||||
default_settings.apply_update(settings)
|
||||
|
||||
# Call parent constructor with dummy api_key
|
||||
# (api_key is required by parent class, but not actually used with Vertex)
|
||||
super().__init__(
|
||||
api_key="dummy",
|
||||
settings=default_settings,
|
||||
tools=tools,
|
||||
tool_config=tool_config,
|
||||
http_options=http_options,
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
def create_client(self):
|
||||
"""Create the Gemini client instance configured for Vertex AI."""
|
||||
self._client = Client(
|
||||
vertexai=True,
|
||||
credentials=self._credentials,
|
||||
project=self._project_id,
|
||||
location=self._location,
|
||||
http_options=self._http_options,
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _get_credentials(credentials: Optional[str], credentials_path: Optional[str]):
|
||||
"""Retrieve Credentials using Google service account credentials.
|
||||
|
||||
Supports multiple authentication methods:
|
||||
1. Direct JSON credentials string
|
||||
2. Path to service account JSON file
|
||||
3. Default application credentials (ADC)
|
||||
|
||||
Args:
|
||||
credentials: JSON string of service account credentials.
|
||||
credentials_path: Path to the service account JSON file.
|
||||
|
||||
Returns:
|
||||
Google credentials object for API authentication.
|
||||
|
||||
Raises:
|
||||
ValueError: If no valid credentials are provided or found.
|
||||
"""
|
||||
creds: Optional[service_account.Credentials] = None
|
||||
|
||||
if credentials:
|
||||
# Parse and load credentials from JSON string
|
||||
creds = service_account.Credentials.from_service_account_info(
|
||||
json.loads(credentials),
|
||||
scopes=["https://www.googleapis.com/auth/cloud-platform"],
|
||||
)
|
||||
elif credentials_path:
|
||||
# Load credentials from JSON file
|
||||
creds = service_account.Credentials.from_service_account_file(
|
||||
credentials_path,
|
||||
scopes=["https://www.googleapis.com/auth/cloud-platform"],
|
||||
)
|
||||
else:
|
||||
try:
|
||||
creds, project_id = default(
|
||||
scopes=["https://www.googleapis.com/auth/cloud-platform"]
|
||||
)
|
||||
except GoogleAuthError:
|
||||
pass
|
||||
|
||||
if not creds:
|
||||
raise ValueError("No valid credentials provided.")
|
||||
|
||||
creds.refresh(Request()) # Ensure token is up-to-date, lifetime is 1 hour.
|
||||
|
||||
return creds
|
||||
from pipecat.services.google.vertex.llm import * # noqa: E402, F401, F403
|
||||
|
||||
5
src/pipecat/services/google/openai/__init__.py
Normal file
5
src/pipecat/services/google/openai/__init__.py
Normal file
@@ -0,0 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024-2026, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
214
src/pipecat/services/google/openai/llm.py
Normal file
214
src/pipecat/services/google/openai/llm.py
Normal file
@@ -0,0 +1,214 @@
|
||||
#
|
||||
# Copyright (c) 2024-2026, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
"""Google LLM service using OpenAI-compatible API format.
|
||||
|
||||
This module provides integration with Google's AI LLM models using the OpenAI
|
||||
API format through Google's Gemini API OpenAI compatibility layer.
|
||||
"""
|
||||
|
||||
import json
|
||||
import os
|
||||
from dataclasses import dataclass
|
||||
from typing import Optional
|
||||
|
||||
from openai import AsyncStream
|
||||
from openai.types.chat import ChatCompletionChunk
|
||||
|
||||
from pipecat.services.llm_service import FunctionCallFromLLM
|
||||
|
||||
# Suppress gRPC fork warnings
|
||||
os.environ["GRPC_ENABLE_FORK_SUPPORT"] = "false"
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.frames.frames import LLMTextFrame
|
||||
from pipecat.metrics.metrics import LLMTokenUsage
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.openai.base_llm import OpenAILLMSettings
|
||||
from pipecat.services.openai.llm import OpenAILLMService
|
||||
from pipecat.services.settings import _warn_deprecated_param
|
||||
|
||||
|
||||
@dataclass
|
||||
class GoogleOpenAILLMSettings(OpenAILLMSettings):
|
||||
"""Settings for GoogleLLMOpenAIBetaService."""
|
||||
|
||||
pass
|
||||
|
||||
|
||||
class GoogleLLMOpenAIBetaService(OpenAILLMService):
|
||||
"""Google LLM service using OpenAI-compatible API format.
|
||||
|
||||
This service provides access to Google's AI LLM models (like Gemini) through
|
||||
the OpenAI API format. It handles streaming responses, function calls, and
|
||||
tool usage while maintaining compatibility with OpenAI's interface.
|
||||
|
||||
Note: This service includes a workaround for a Google API bug where function
|
||||
call indices may be incorrectly set to None, resulting in empty function names.
|
||||
|
||||
.. deprecated:: 0.0.82
|
||||
GoogleLLMOpenAIBetaService is deprecated and will be removed in a future version.
|
||||
Use GoogleLLMService instead for better integration with Google's native API.
|
||||
|
||||
Reference:
|
||||
https://ai.google.dev/gemini-api/docs/openai
|
||||
"""
|
||||
|
||||
Settings = GoogleOpenAILLMSettings
|
||||
_settings: GoogleOpenAILLMSettings
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
api_key: str,
|
||||
base_url: str = "https://generativelanguage.googleapis.com/v1beta/openai/",
|
||||
model: Optional[str] = None,
|
||||
settings: Optional[GoogleOpenAILLMSettings] = None,
|
||||
**kwargs,
|
||||
):
|
||||
"""Initialize the Google LLM service.
|
||||
|
||||
Args:
|
||||
api_key: Google API key for authentication.
|
||||
base_url: Base URL for Google's OpenAI-compatible API.
|
||||
model: Google model name to use (e.g., "gemini-2.0-flash").
|
||||
|
||||
.. deprecated:: 0.0.105
|
||||
Use ``settings=OpenAILLMSettings(model=...)`` instead.
|
||||
|
||||
settings: Runtime-updatable settings. When provided alongside deprecated
|
||||
parameters, ``settings`` values take precedence.
|
||||
**kwargs: Additional arguments passed to the parent OpenAILLMService.
|
||||
"""
|
||||
import warnings
|
||||
|
||||
with warnings.catch_warnings():
|
||||
warnings.simplefilter("always")
|
||||
warnings.warn(
|
||||
"GoogleLLMOpenAIBetaService is deprecated and will be removed in a future version. "
|
||||
"Use GoogleLLMService instead for better integration with Google's native API.",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
|
||||
# 1. Initialize default_settings with hardcoded defaults
|
||||
default_settings = GoogleOpenAILLMSettings(model="gemini-2.0-flash")
|
||||
|
||||
# 2. Apply direct init arg overrides (deprecated)
|
||||
if model is not None:
|
||||
_warn_deprecated_param("model", GoogleOpenAILLMSettings, "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)
|
||||
|
||||
async def _process_context(self, context: OpenAILLMContext):
|
||||
functions_list = []
|
||||
arguments_list = []
|
||||
tool_id_list = []
|
||||
func_idx = 0
|
||||
function_name = ""
|
||||
arguments = ""
|
||||
tool_call_id = ""
|
||||
|
||||
await self.start_ttfb_metrics()
|
||||
|
||||
chunk_stream: AsyncStream[
|
||||
ChatCompletionChunk
|
||||
] = await self._stream_chat_completions_specific_context(context)
|
||||
|
||||
# Use context manager to ensure stream is closed on cancellation/exception.
|
||||
# Without this, CancelledError during iteration leaves the underlying socket open.
|
||||
async with chunk_stream:
|
||||
async for chunk in chunk_stream:
|
||||
if chunk.usage:
|
||||
tokens = LLMTokenUsage(
|
||||
prompt_tokens=chunk.usage.prompt_tokens or 0,
|
||||
completion_tokens=chunk.usage.completion_tokens or 0,
|
||||
total_tokens=chunk.usage.total_tokens or 0,
|
||||
)
|
||||
await self.start_llm_usage_metrics(tokens)
|
||||
|
||||
if chunk.choices is None or len(chunk.choices) == 0:
|
||||
continue
|
||||
|
||||
await self.stop_ttfb_metrics()
|
||||
|
||||
if not chunk.choices[0].delta:
|
||||
continue
|
||||
|
||||
if chunk.choices[0].delta.tool_calls:
|
||||
# We're streaming the LLM response to enable the fastest response times.
|
||||
# For text, we just yield each chunk as we receive it and count on consumers
|
||||
# to do whatever coalescing they need (eg. to pass full sentences to TTS)
|
||||
#
|
||||
# If the LLM is a function call, we'll do some coalescing here.
|
||||
# If the response contains a function name, we'll yield a frame to tell consumers
|
||||
# that they can start preparing to call the function with that name.
|
||||
# We accumulate all the arguments for the rest of the streamed response, then when
|
||||
# the response is done, we package up all the arguments and the function name and
|
||||
# yield a frame containing the function name and the arguments.
|
||||
logger.debug(f"Tool call: {chunk.choices[0].delta.tool_calls}")
|
||||
tool_call = chunk.choices[0].delta.tool_calls[0]
|
||||
if tool_call.index != func_idx:
|
||||
functions_list.append(function_name)
|
||||
arguments_list.append(arguments)
|
||||
tool_id_list.append(tool_call_id)
|
||||
function_name = ""
|
||||
arguments = ""
|
||||
tool_call_id = ""
|
||||
func_idx += 1
|
||||
if tool_call.function and tool_call.function.name:
|
||||
function_name += tool_call.function.name
|
||||
tool_call_id = tool_call.id
|
||||
if tool_call.function and tool_call.function.arguments:
|
||||
# Keep iterating through the response to collect all the argument fragments
|
||||
arguments += tool_call.function.arguments
|
||||
elif chunk.choices[0].delta.content:
|
||||
await self.push_frame(LLMTextFrame(chunk.choices[0].delta.content))
|
||||
|
||||
# if we got a function name and arguments, check to see if it's a function with
|
||||
# a registered handler. If so, run the registered callback, save the result to
|
||||
# the context, and re-prompt to get a chat answer. If we don't have a registered
|
||||
# handler, raise an exception.
|
||||
if function_name and arguments:
|
||||
# added to the list as last function name and arguments not added to the list
|
||||
functions_list.append(function_name)
|
||||
arguments_list.append(arguments)
|
||||
tool_id_list.append(tool_call_id)
|
||||
|
||||
logger.debug(
|
||||
f"Function list: {functions_list}, Arguments list: {arguments_list}, Tool ID list: {tool_id_list}"
|
||||
)
|
||||
|
||||
function_calls = []
|
||||
for function_name, arguments, tool_id in zip(
|
||||
functions_list, arguments_list, tool_id_list
|
||||
):
|
||||
if function_name == "":
|
||||
# TODO: Remove the _process_context method once Google resolves the bug
|
||||
# where the index is incorrectly set to None instead of returning the actual index,
|
||||
# which currently results in an empty function name('').
|
||||
continue
|
||||
|
||||
arguments = json.loads(arguments)
|
||||
|
||||
function_calls.append(
|
||||
FunctionCallFromLLM(
|
||||
context=context,
|
||||
tool_call_id=tool_id,
|
||||
function_name=function_name,
|
||||
arguments=arguments,
|
||||
)
|
||||
)
|
||||
|
||||
await self.run_function_calls(function_calls)
|
||||
5
src/pipecat/services/google/vertex/__init__.py
Normal file
5
src/pipecat/services/google/vertex/__init__.py
Normal file
@@ -0,0 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024-2026, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
309
src/pipecat/services/google/vertex/llm.py
Normal file
309
src/pipecat/services/google/vertex/llm.py
Normal file
@@ -0,0 +1,309 @@
|
||||
#
|
||||
# Copyright (c) 2024-2026, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
"""Google Vertex AI LLM service implementation.
|
||||
|
||||
This module provides integration with Google's AI models via Vertex AI,
|
||||
extending the GoogleLLMService with Vertex AI authentication.
|
||||
"""
|
||||
|
||||
import json
|
||||
import os
|
||||
from dataclasses import dataclass
|
||||
|
||||
# Suppress gRPC fork warnings
|
||||
os.environ["GRPC_ENABLE_FORK_SUPPORT"] = "false"
|
||||
|
||||
from typing import Optional
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings
|
||||
from pipecat.services.settings import _warn_deprecated_param
|
||||
|
||||
try:
|
||||
from google.auth import default
|
||||
from google.auth.exceptions import GoogleAuthError
|
||||
from google.auth.transport.requests import Request
|
||||
from google.genai import Client
|
||||
from google.genai.types import HttpOptions
|
||||
from google.oauth2 import service_account
|
||||
|
||||
except ModuleNotFoundError as e:
|
||||
logger.error(f"Exception: {e}")
|
||||
logger.error(
|
||||
"In order to use Google AI, you need to `pip install pipecat-ai[google]`. Also, set `GOOGLE_APPLICATION_CREDENTIALS` environment variable."
|
||||
)
|
||||
raise Exception(f"Missing module: {e}")
|
||||
|
||||
|
||||
@dataclass
|
||||
class GoogleVertexLLMSettings(GoogleLLMSettings):
|
||||
"""Settings for GoogleVertexLLMService."""
|
||||
|
||||
pass
|
||||
|
||||
|
||||
class GoogleVertexLLMService(GoogleLLMService):
|
||||
"""Google Vertex AI LLM service extending GoogleLLMService.
|
||||
|
||||
Provides access to Google's AI models via Vertex AI while using the same
|
||||
Google AI client and message format as GoogleLLMService. Handles authentication
|
||||
using Google service account credentials and configures the client for
|
||||
Vertex AI endpoints.
|
||||
|
||||
Reference:
|
||||
https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference
|
||||
"""
|
||||
|
||||
Settings = GoogleVertexLLMSettings
|
||||
_settings: GoogleVertexLLMSettings
|
||||
|
||||
class InputParams(GoogleLLMService.InputParams):
|
||||
"""Input parameters specific to Vertex AI.
|
||||
|
||||
Parameters:
|
||||
location: GCP region for Vertex AI endpoint (e.g., "us-east4").
|
||||
|
||||
.. deprecated:: 0.0.90
|
||||
Use `location` as a direct argument to
|
||||
`GoogleVertexLLMService.__init__()` instead.
|
||||
|
||||
project_id: Google Cloud project ID.
|
||||
|
||||
.. deprecated:: 0.0.90
|
||||
Use `project_id` as a direct argument to
|
||||
`GoogleVertexLLMService.__init__()` instead.
|
||||
"""
|
||||
|
||||
# https://cloud.google.com/vertex-ai/generative-ai/docs/learn/locations
|
||||
location: Optional[str] = None
|
||||
project_id: Optional[str] = None
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
"""Initializes the InputParams."""
|
||||
import warnings
|
||||
|
||||
with warnings.catch_warnings():
|
||||
warnings.simplefilter("always")
|
||||
if "location" in kwargs and kwargs["location"] is not None:
|
||||
warnings.warn(
|
||||
"GoogleVertexLLMService.InputParams.location is deprecated. "
|
||||
"Please provide 'location' as a direct argument to GoogleVertexLLMService.__init__() instead.",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
|
||||
if "project_id" in kwargs and kwargs["project_id"] is not None:
|
||||
warnings.warn(
|
||||
"GoogleVertexLLMService.InputParams.project_id is deprecated. "
|
||||
"Please provide 'project_id' as a direct argument to GoogleVertexLLMService.__init__() instead.",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
super().__init__(**kwargs)
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
credentials: Optional[str] = None,
|
||||
credentials_path: Optional[str] = None,
|
||||
model: Optional[str] = None,
|
||||
location: Optional[str] = None,
|
||||
project_id: Optional[str] = None,
|
||||
params: Optional[GoogleLLMService.InputParams] = None,
|
||||
settings: Optional[GoogleVertexLLMSettings] = None,
|
||||
system_instruction: Optional[str] = None,
|
||||
tools: Optional[list] = None,
|
||||
tool_config: Optional[dict] = None,
|
||||
http_options: Optional[HttpOptions] = None,
|
||||
**kwargs,
|
||||
):
|
||||
"""Initializes the VertexLLMService.
|
||||
|
||||
Args:
|
||||
credentials: JSON string of service account credentials.
|
||||
credentials_path: Path to the service account JSON file.
|
||||
model: Model identifier (e.g., "gemini-2.5-flash").
|
||||
|
||||
.. deprecated:: 0.0.105
|
||||
Use ``settings=GoogleLLMSettings(model=...)`` instead.
|
||||
|
||||
location: GCP region for Vertex AI endpoint (e.g., "us-east4").
|
||||
project_id: Google Cloud project ID.
|
||||
params: Input parameters for the model.
|
||||
|
||||
.. deprecated:: 0.0.105
|
||||
Use ``settings=GoogleLLMSettings(...)`` instead.
|
||||
|
||||
settings: Runtime-updatable settings for this service. When both
|
||||
deprecated parameters and *settings* are provided, *settings*
|
||||
values take precedence.
|
||||
system_instruction: System instruction/prompt for the model.
|
||||
|
||||
.. deprecated:: 0.0.105
|
||||
Use ``settings=GoogleVertexLLMSettings(system_instruction=...)`` instead.
|
||||
tools: List of available tools/functions.
|
||||
tool_config: Configuration for tool usage.
|
||||
http_options: HTTP options for the client.
|
||||
**kwargs: Additional arguments passed to GoogleLLMService.
|
||||
"""
|
||||
# Check if user incorrectly passed api_key, which is used by parent
|
||||
# class but not here.
|
||||
if "api_key" in kwargs:
|
||||
logger.error(
|
||||
"GoogleVertexLLMService does not accept 'api_key' parameter. "
|
||||
"Use 'credentials' or 'credentials_path' instead for Vertex AI authentication."
|
||||
)
|
||||
raise ValueError(
|
||||
"Invalid parameter 'api_key'. Use 'credentials' or 'credentials_path' for Vertex AI authentication."
|
||||
)
|
||||
|
||||
# Handle deprecated InputParams fields (location/project_id extraction
|
||||
# must happen before validation, regardless of settings)
|
||||
if params and isinstance(params, GoogleVertexLLMService.InputParams):
|
||||
if project_id is None:
|
||||
project_id = params.project_id
|
||||
if location is None:
|
||||
location = params.location
|
||||
# Convert to base InputParams
|
||||
params = GoogleLLMService.InputParams(
|
||||
**params.model_dump(exclude={"location", "project_id"}, exclude_unset=True)
|
||||
)
|
||||
|
||||
# Validate project_id and location parameters
|
||||
# NOTE: once we remove Vertex-specific InputParams class, we can update
|
||||
# __init__() signature as follows:
|
||||
# - location: str = "us-east4",
|
||||
# - project_id: str,
|
||||
# But for now, we need them as-is to maintain proper backward
|
||||
# compatibility.
|
||||
if project_id is None:
|
||||
raise ValueError("project_id is required")
|
||||
if location is None:
|
||||
# If location is not provided, default to "us-east4".
|
||||
# Note: this is legacy behavior; ideally location would be
|
||||
# required.
|
||||
logger.warning("location is not provided. Defaulting to 'us-east4'.")
|
||||
location = "us-east4" # Default location if not provided
|
||||
|
||||
# These need to be set before calling super().__init__() because
|
||||
# super().__init__() invokes _create_client(), which needs these.
|
||||
self._credentials = self._get_credentials(credentials, credentials_path)
|
||||
self._project_id = project_id
|
||||
self._location = location
|
||||
|
||||
# 1. Initialize default_settings with hardcoded defaults
|
||||
default_settings = GoogleVertexLLMSettings(
|
||||
model="gemini-2.5-flash",
|
||||
system_instruction=None,
|
||||
max_tokens=4096,
|
||||
temperature=None,
|
||||
top_k=None,
|
||||
top_p=None,
|
||||
frequency_penalty=None,
|
||||
presence_penalty=None,
|
||||
seed=None,
|
||||
filter_incomplete_user_turns=False,
|
||||
user_turn_completion_config=None,
|
||||
thinking=None,
|
||||
extra={},
|
||||
)
|
||||
|
||||
# 2. Apply direct init arg overrides (deprecated)
|
||||
if model is not None:
|
||||
_warn_deprecated_param("model", GoogleVertexLLMSettings, "model")
|
||||
default_settings.model = model
|
||||
if system_instruction is not None:
|
||||
_warn_deprecated_param(
|
||||
"system_instruction", GoogleVertexLLMSettings, "system_instruction"
|
||||
)
|
||||
default_settings.system_instruction = system_instruction
|
||||
|
||||
# 3. Apply params overrides — only if settings not provided
|
||||
if params is not None:
|
||||
_warn_deprecated_param("params", GoogleVertexLLMSettings)
|
||||
if not settings:
|
||||
default_settings.max_tokens = params.max_tokens
|
||||
default_settings.temperature = params.temperature
|
||||
default_settings.top_k = params.top_k
|
||||
default_settings.top_p = params.top_p
|
||||
default_settings.thinking = params.thinking
|
||||
if isinstance(params.extra, dict):
|
||||
default_settings.extra = params.extra
|
||||
|
||||
# 4. Apply settings delta (canonical API, always wins)
|
||||
if settings is not None:
|
||||
default_settings.apply_update(settings)
|
||||
|
||||
# Call parent constructor with dummy api_key
|
||||
# (api_key is required by parent class, but not actually used with Vertex)
|
||||
super().__init__(
|
||||
api_key="dummy",
|
||||
settings=default_settings,
|
||||
tools=tools,
|
||||
tool_config=tool_config,
|
||||
http_options=http_options,
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
def create_client(self):
|
||||
"""Create the Gemini client instance configured for Vertex AI."""
|
||||
self._client = Client(
|
||||
vertexai=True,
|
||||
credentials=self._credentials,
|
||||
project=self._project_id,
|
||||
location=self._location,
|
||||
http_options=self._http_options,
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _get_credentials(credentials: Optional[str], credentials_path: Optional[str]):
|
||||
"""Retrieve Credentials using Google service account credentials.
|
||||
|
||||
Supports multiple authentication methods:
|
||||
1. Direct JSON credentials string
|
||||
2. Path to service account JSON file
|
||||
3. Default application credentials (ADC)
|
||||
|
||||
Args:
|
||||
credentials: JSON string of service account credentials.
|
||||
credentials_path: Path to the service account JSON file.
|
||||
|
||||
Returns:
|
||||
Google credentials object for API authentication.
|
||||
|
||||
Raises:
|
||||
ValueError: If no valid credentials are provided or found.
|
||||
"""
|
||||
creds: Optional[service_account.Credentials] = None
|
||||
|
||||
if credentials:
|
||||
# Parse and load credentials from JSON string
|
||||
creds = service_account.Credentials.from_service_account_info(
|
||||
json.loads(credentials),
|
||||
scopes=["https://www.googleapis.com/auth/cloud-platform"],
|
||||
)
|
||||
elif credentials_path:
|
||||
# Load credentials from JSON file
|
||||
creds = service_account.Credentials.from_service_account_file(
|
||||
credentials_path,
|
||||
scopes=["https://www.googleapis.com/auth/cloud-platform"],
|
||||
)
|
||||
else:
|
||||
try:
|
||||
creds, project_id = default(
|
||||
scopes=["https://www.googleapis.com/auth/cloud-platform"]
|
||||
)
|
||||
except GoogleAuthError:
|
||||
pass
|
||||
|
||||
if not creds:
|
||||
raise ValueError("No valid credentials provided.")
|
||||
|
||||
creds.refresh(Request()) # Ensure token is up-to-date, lifetime is 1 hour.
|
||||
|
||||
return creds
|
||||
@@ -15,7 +15,7 @@ import pytest
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
|
||||
try:
|
||||
from pipecat.services.google.llm_openai import GoogleLLMOpenAIBetaService
|
||||
from pipecat.services.google.openai.llm import GoogleLLMOpenAIBetaService
|
||||
|
||||
google_available = True
|
||||
except Exception:
|
||||
|
||||
Reference in New Issue
Block a user