apunkt/dograh
1
0
Fork 0
mirror of https://github.com/dograh-hq/dograh.git synced 2026-06-07 07:55:16 +02:00
Code Issues Projects Releases Packages Wiki Activity

feat: simplify pipecat engine execution (#54)

Browse source
This commit is contained in:
Abhishek 2025-11-15 17:38:27 +05:30 • committed by GitHub
parent 99a768f291
commit 6ce25a589c
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
20 changed files with 52 additions and 1405 deletions
Download patch file Download diff file Expand all files Collapse all files

106
api/services/workflow/pipecat_engine_callbacks.py
View file

@ -14,6 +14,7 @@ import re
from typing import TYPE_CHECKING, Awaitable, Callable
from loguru import logger
from pipecat.frames.frames import (
LLMFullResponseEndFrame,
LLMFullResponseStartFrame,
@ -23,9 +24,8 @@ from pipecat.processors.filters.stt_mute_filter import STTMuteFilter
from pipecat.utils.enums import EndTaskReason
if TYPE_CHECKING:
from pipecat.processors.user_idle_processor import UserIdleProcessor
from api.services.workflow.pipecat_engine import PipecatEngine
from pipecat.processors.user_idle_processor import UserIdleProcessor
# ---------------------------------------------------------------------------
@ -114,23 +114,6 @@ def create_max_duration_callback(engine: "PipecatEngine"):
return handle_max_duration
# ---------------------------------------------------------------------------
# LLM-generated-text handling
# ---------------------------------------------------------------------------
def create_llm_generated_text_callback(engine: "PipecatEngine"):
"""Return a callback invoked when the LLM emits text (not only tool calls)."""
async def handle_llm_generated_text(): # noqa: D401
logger.debug(
"Generation has text content in current response - deferring context push from set_node"
)
engine._defer_context_push = True
return handle_llm_generated_text
# ---------------------------------------------------------------------------
# Generation-started handling
# ---------------------------------------------------------------------------
@ -140,96 +123,13 @@ def create_generation_started_callback(engine: "PipecatEngine"):
"""Return a callback that resets flags at the start of each LLM generation."""
async def handle_generation_started(): # noqa: D401
logger.debug("LLM generation started - resetting defer flags and tool counters")
engine._defer_context_push = False
engine._pending_function_calls = 0
engine._pending_generated_transition_after_context_push = None
logger.debug("LLM generation started in callback processor")
# Clear reference text from previous generation
engine._current_llm_reference_text = ""
return handle_generation_started
# ---------------------------------------------------------------------------
# User-stopped-speaking handling
# ---------------------------------------------------------------------------
def create_user_stopped_speaking_callback(engine: "PipecatEngine"):
"""Return a callback that handles when the user stops speaking.
According to simplified flow:
- For start nodes with wait_for_user_response=True:
- Cancel timeout task if still active
- Transition to next node with _queue_context_frame=False
"""
async def handle_user_stopped_speaking():
# Only handle if current node is a start node with wait_for_user_response
if (
engine._current_node
and engine._current_node.is_start
and engine._current_node.wait_for_user_response
and engine._current_node.out_edges
):
# Cancel timeout task if it's still active
if (
engine._user_response_timeout_task
and not engine._user_response_timeout_task.done()
):
logger.debug("Cancelling user response timeout - user responded")
engine._user_response_timeout_task.cancel()
engine._user_response_timeout_task = None
# Transition to next node
next_node_id = engine._current_node.out_edges[0].target
logger.debug(
f"User stopped speaking after wait_for_user_response - transitioning to: {next_node_id}"
)
# Set flag to not queue context frame since
# it will be pushed by user context aggregator
# we are just setting the context with next node's
# functions and prompts
engine._queue_context_frame = False
# Transition to next node
await engine.set_node(next_node_id)
return handle_user_stopped_speaking
# ---------------------------------------------------------------------------
# User-started-speaking handling
# ---------------------------------------------------------------------------
def create_user_started_speaking_callback(engine: "PipecatEngine"):
"""Return a callback that handles when the user starts speaking.
According to simplified flow:
- For start nodes with wait_for_user_response=True:
- Cancel the timeout timer if it exists (but don't set to None)
"""
async def handle_user_started_speaking():
# Only handle if current node is a start node with wait_for_user_response
if (
engine._current_node
and engine._current_node.is_start
and engine._current_node.wait_for_user_response
and engine._user_response_timeout_task
and not engine._user_response_timeout_task.done()
):
logger.debug(
"User started speaking during wait_for_user_response - cancelling timeout timer"
)
engine._user_response_timeout_task.cancel()
# Don't set to None here - let user_stopped_speaking handle the transition
return handle_user_started_speaking
def create_aggregation_correction_callback(engine: "PipecatEngine"):
"""Create a callback that uses engine's reference text to correct corrupted aggregation."""