Update GeminiLLMService to work with LLMContext and LLMContextAggregatorPair

examples/foundational/26c-gemini-live-video.py

@@ -17,7 +17,9 @@ 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,
@@ -65,7 +67,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         # inference_on_context_initialization=False,
     )
 
-    context = OpenAILLMContext(
+    context = LLMContext(
         [
             {
                 "role": "user",
@@ -73,7 +75,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             },
         ],
     )
-    context_aggregator = llm.create_context_aggregator(context)
+    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),
+    )
 
     pipeline = Pipeline(
         [