Add LLMRunFrame to trigger an LLM response, replacing context_aggregator.user().get_context_frame()
This commit is contained in:
@@ -16,6 +16,7 @@ from loguru import logger
|
||||
from pipecat.adapters.schemas.function_schema import FunctionSchema
|
||||
from pipecat.adapters.schemas.tools_schema import ToolsSchema
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
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
|
||||
@@ -253,7 +254,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
async def on_client_connected(transport, client):
|
||||
logger.info(f"Client connected")
|
||||
# Kick off the conversation.
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
await task.queue_frames([LLMRunFrame()])
|
||||
# HACK: for now, we need this special way of triggering the first assistant response in AWS
|
||||
# Nova Sonic. Note that this trigger requires a special corresponding bit of text in the
|
||||
# system instruction. In the future, simply queueing the context frame should be sufficient.
|
||||
|
||||
Reference in New Issue
Block a user