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https://github.com/dograh-hq/dograh.git
synced 2026-06-13 08:15:21 +02:00
feat: allow recordings in tool transitions
This commit is contained in:
Abhishek Kumar
parent
3a272d3a44
commit
ffe9a99401
38 changed files with 1555 additions and 692 deletions
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@ -1,4 +1,4 @@
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"""Service for duplicating workflows including recordings."""
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"""Service for duplicating workflows."""
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import copy
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import posixpath
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@ -44,7 +44,9 @@ async def duplicate_workflow(
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organization_id: int,
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user_id: int,
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):
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"""Duplicate a workflow including its definition, config, recordings, and triggers.
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"""Duplicate a workflow including its definition, config, and triggers.
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Recordings are org-scoped and shared, so they are not duplicated.
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Args:
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workflow_id: The source workflow ID to duplicate
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@ -118,15 +120,7 @@ async def duplicate_workflow(
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organization_id=organization_id,
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)
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# 6. Copy recordings (recording_ids are preserved since they're scoped per workflow)
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await _duplicate_recordings(
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source_workflow_id=workflow_id,
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new_workflow_id=new_workflow.id,
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organization_id=organization_id,
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user_id=user_id,
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)
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# 7. Sync triggers for the new workflow
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# 6. Sync triggers for the new workflow
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if workflow_definition:
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trigger_paths = _extract_trigger_paths(workflow_definition)
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if trigger_paths:
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@ -139,66 +133,6 @@ async def duplicate_workflow(
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return new_workflow
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async def _duplicate_recordings(
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source_workflow_id: int,
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new_workflow_id: int,
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organization_id: int,
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user_id: int,
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) -> None:
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"""Duplicate all recordings for a workflow.
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Copies each recording file to a new storage path scoped under the new
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workflow ID. Recording IDs are preserved since they are unique per
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(org, workflow).
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"""
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recordings = await db_client.get_recordings(
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workflow_id=source_workflow_id,
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organization_id=organization_id,
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)
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if not recordings:
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return
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for rec in recordings:
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try:
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# Build new storage key: recordings/{org_id}/{new_workflow_id}/{recording_id}/{filename}
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filename = posixpath.basename(rec.storage_key)
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new_storage_key = (
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f"recordings/{organization_id}"
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f"/{new_workflow_id}/{rec.recording_id}"
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f"/{filename}"
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)
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copied = await _copy_storage_object(
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rec.storage_key, new_storage_key, rec.storage_backend
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)
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if not copied:
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logger.warning(
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f"Failed to copy recording file {rec.recording_id}, skipping"
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)
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continue
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await db_client.create_recording(
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recording_id=rec.recording_id,
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workflow_id=new_workflow_id,
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organization_id=organization_id,
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tts_provider=rec.tts_provider,
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tts_model=rec.tts_model,
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tts_voice_id=rec.tts_voice_id,
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transcript=rec.transcript,
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storage_key=new_storage_key,
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storage_backend=rec.storage_backend,
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created_by=user_id,
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metadata=copy.deepcopy(rec.recording_metadata),
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)
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logger.info(f"Duplicated recording {rec.recording_id}")
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except Exception as e:
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logger.error(f"Error duplicating recording {rec.recording_id}: {e}")
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continue
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async def _copy_storage_object(
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source_key: str, dest_key: str, storage_backend: str
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) -> bool:
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@ -1,6 +1,6 @@
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from typing import TYPE_CHECKING, Awaitable, Callable, Optional, Union
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from api.services.pipecat.recording_playback import queue_recording_audio
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from api.services.pipecat.audio_playback import play_audio
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from api.services.workflow.disposition_mapper import (
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apply_disposition_mapping,
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get_organization_id_from_workflow_run,
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@ -115,6 +115,10 @@ class PipecatEngine:
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# Audio configuration (set via set_audio_config from _run_pipeline)
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self._audio_config = None
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# Transport output processor for injecting audio directly into the
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# output, bypassing STT (set via set_transport_output from _run_pipeline)
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self._transport_output = None
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# Recording audio fetcher (set via set_fetch_recording_audio from _run_pipeline)
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self._fetch_recording_audio = None
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@ -221,16 +225,17 @@ class PipecatEngine:
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f"Playing transition audio: {transition_speech_recording_id}"
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)
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self._queued_speech_mute_state = "waiting"
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audio_data = await self._fetch_recording_audio(
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transition_speech_recording_id
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result = await self._fetch_recording_audio(
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recording_pk=int(transition_speech_recording_id)
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)
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if audio_data:
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await queue_recording_audio(
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audio_data,
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if result:
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await play_audio(
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result.audio,
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sample_rate=self._audio_config.pipeline_sample_rate
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if self._audio_config
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else 16000,
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queue_frame=self.task.queue_frame,
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queue_frame=self._transport_output.queue_frame,
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transcript=result.transcript,
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)
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else:
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logger.warning(
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@ -753,6 +758,14 @@ class PipecatEngine:
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"""Set the audio configuration for the pipeline."""
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self._audio_config = audio_config
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def set_transport_output(self, transport_output) -> None:
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"""Set the transport output processor for direct audio playback.
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Audio queued here bypasses STT and the rest of the pipeline,
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going straight to the caller.
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"""
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self._transport_output = transport_output
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def set_fetch_recording_audio(self, fetch_fn) -> None:
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"""Set the recording audio fetcher callback."""
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self._fetch_recording_audio = fetch_fn
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@ -168,7 +168,6 @@ def create_aggregation_correction_callback(engine: "PipecatEngine"):
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reference = engine._current_llm_generation_reference_text
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if not reference:
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logger.warning("No reference text available for aggregation correction")
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return corrupted
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# Apply the correction algorithm
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@ -16,7 +16,7 @@ from loguru import logger
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from api.db import db_client
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from api.enums import ToolCategory, WorkflowRunMode
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from api.services.pipecat.recording_playback import queue_recording_audio
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from api.services.pipecat.audio_playback import play_audio, play_audio_loop
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from api.services.telephony.call_transfer_manager import get_call_transfer_manager
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from api.services.telephony.factory import get_telephony_provider
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from api.services.telephony.transfer_event_protocol import TransferContext
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@ -28,7 +28,6 @@ from api.services.workflow.tools.custom_tool import (
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execute_http_tool,
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tool_to_function_schema,
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)
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from api.utils.hold_audio import play_hold_audio_loop
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from pipecat.adapters.schemas.function_schema import FunctionSchema
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from pipecat.frames.frames import (
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FunctionCallResultProperties,
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@ -88,20 +87,23 @@ class CustomToolManager:
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message_type = config.get("messageType", "none")
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if message_type == "audio":
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recording_id = config.get("audioRecordingId", "")
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if recording_id and self._engine._fetch_recording_audio:
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audio_data = await self._engine._fetch_recording_audio(recording_id)
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if audio_data:
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await queue_recording_audio(
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audio_data,
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recording_pk = config.get("audioRecordingId")
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if recording_pk and self._engine._fetch_recording_audio:
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result = await self._engine._fetch_recording_audio(
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recording_pk=int(recording_pk)
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)
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if result:
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await play_audio(
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result.audio,
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sample_rate=self._engine._audio_config.pipeline_sample_rate
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if self._engine._audio_config
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else 16000,
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queue_frame=self._engine.task.queue_frame,
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queue_frame=self._engine._transport_output.queue_frame,
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transcript=result.transcript,
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)
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return True
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else:
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logger.warning(f"Failed to fetch recording {recording_id}")
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logger.warning(f"Failed to fetch recording pk={recording_pk}")
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return False
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if message_type == "custom":
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@ -292,22 +294,23 @@ class CustomToolManager:
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custom_msg_type = config.get("customMessageType", "text")
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custom_message = config.get("customMessage", "")
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if custom_msg_type == "audio":
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recording_id = config.get("customMessageRecordingId", "")
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if recording_id and self._engine._fetch_recording_audio:
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recording_pk = config.get("customMessageRecordingId")
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if recording_pk and self._engine._fetch_recording_audio:
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logger.info(
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f"Playing audio message before HTTP tool: {recording_id}"
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f"Playing audio message before HTTP tool: pk={recording_pk}"
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)
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self._engine._queued_speech_mute_state = "waiting"
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audio_data = await self._engine._fetch_recording_audio(
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recording_id
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result = await self._engine._fetch_recording_audio(
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recording_pk=int(recording_pk)
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)
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if audio_data:
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await queue_recording_audio(
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audio_data,
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if result:
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await play_audio(
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result.audio,
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sample_rate=self._engine._audio_config.pipeline_sample_rate
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if self._engine._audio_config
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else 16000,
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queue_frame=self._engine.task.queue_frame,
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queue_frame=self._engine._transport_output.queue_frame,
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transcript=result.transcript,
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)
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elif custom_message:
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logger.info(
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@ -587,10 +590,10 @@ class CustomToolManager:
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# Start hold music as background task
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hold_music_task = asyncio.create_task(
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play_hold_audio_loop(
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self._engine.task,
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hold_music_stop_event,
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sample_rate,
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play_audio_loop(
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stop_event=hold_music_stop_event,
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sample_rate=sample_rate,
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queue_frame=self._engine._transport_output.queue_frame,
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)
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)
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