Update GeminiLLMService to work with LLMContext and LLMContextAggregatorPair

This commit is contained in:
Paul Kompfner
2025-10-27 16:36:50 -04:00
parent 8b063116ab
commit f974c66e12
13 changed files with 328 additions and 87 deletions

View File

@@ -9,21 +9,21 @@ import os
from datetime import datetime
from dotenv import load_dotenv
from google.genai.types import HttpOptions
from loguru import logger
from pipecat.adapters.schemas.function_schema import FunctionSchema
from pipecat.adapters.schemas.tools_schema import AdapterType, ToolsSchema
from pipecat.adapters.schemas.tools_schema import ToolsSchema
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response import LLMAssistantAggregatorParams
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService
from pipecat.services.google.gemini_live.llm_vertex import GeminiLiveVertexLLMService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import BaseTransport, TransportParams
@@ -139,10 +139,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
llm.register_function("get_current_weather", fetch_weather_from_api)
llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
context = OpenAILLMContext(
[{"role": "user", "content": "Say hello."}],
context = LLMContext([{"role": "user", "content": "Say hello."}])
context_aggregator = LLMContextAggregatorPair(
context,
# `expect_stripped_words=False` needed when Gemini Live used with AUDIO
# modality (the default)
assistant_params=LLMAssistantAggregatorParams(expect_stripped_words=False),
)
context_aggregator = llm.create_context_aggregator(context)
pipeline = Pipeline(
[