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feat: telephony call transfer (#155)

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* transfer call

* fix: ignore completed call status

* chore: refactor telephony

* chore: refactor pipecat engine custom tools and other telephony services

* chore: code refactor

* chore: put back office ambient sound files

* chore: remove transport from engine

* fix: fix alembic revision

* chore: remove set_transferring_call from engine

* fix: send OutputAudio frame and let transport chunk it

* fix: reinstate docker compose

* chore: remove unused transfer-twmil route for caller

* chore: update pipecat submodule

---------

Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
This commit is contained in:
Sabiha Khan 2026-02-16 14:33:33 +05:30 • committed by GitHub
parent 5d14d17ceb
commit c711920165
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30 changed files with 1965 additions and 128 deletions
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45
api/services/workflow/pipecat_engine.py
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@ -15,7 +15,6 @@ from pipecat.frames.frames import (
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import BaseTransport
from pipecat.utils.enums import EndTaskReason
if TYPE_CHECKING:
@ -61,7 +60,6 @@ class PipecatEngine:
task: Optional[PipelineTask] = None,
llm: Optional["LLMService"] = None,
context: Optional[LLMContext] = None,
transport: Optional[BaseTransport] = None,
workflow: WorkflowGraph,
call_context_vars: dict,
workflow_run_id: Optional[int] = None,
@ -75,7 +73,6 @@ class PipecatEngine:
self.task = task
self.llm = llm
self.context = context
self.transport = transport
self.workflow = workflow
self._call_context_vars = call_context_vars
self._workflow_run_id = workflow_run_id
@ -113,6 +110,9 @@ class PipecatEngine:
self._embeddings_model: Optional[str] = embeddings_model
self._embeddings_base_url: Optional[str] = embeddings_base_url
# Audio configuration (set via set_audio_config from _run_pipeline)
self._audio_config = None
async def _get_organization_id(self) -> Optional[int]:
"""Get and cache the organization ID from workflow run."""
if self._custom_tool_manager:
@ -207,14 +207,14 @@ class PipecatEngine:
)
logger.info(f"Arguments: {function_call_params.arguments}")
# Perform variable extraction before transitioning to new node
await self._perform_variable_extraction_if_needed(self._current_node)
# Set context for the new node, so that when the function call result
# frame is received by LLMContextAggregator and an LLM generation
# is done, we have updated context and functions
await self.set_node(transition_to_node)
try:
# Perform variable extraction before transitioning to new node
await self._perform_variable_extraction_if_needed(self._current_node)
# Set context for the new node, so that when the function call result
# frame is received by LLMContextAggregator and an LLM generation
# is done, we have updated context and functions
await self.set_node(transition_to_node)
async def on_context_updated() -> None:
"""
@ -245,6 +245,7 @@ class PipecatEngine:
await function_call_params.result_callback(
result, properties=properties
)
except Exception as e:
logger.error(f"Error in transition function {name}: {str(e)}")
error_result = {"status": "error", "error": str(e)}
@ -277,6 +278,7 @@ class PipecatEngine:
async def calculate_func(function_call_params: FunctionCallParams) -> None:
logger.info(f"LLM Function Call EXECUTED: safe_calculator")
logger.info(f"Arguments: {function_call_params.arguments}")
try:
expr = function_call_params.arguments.get("expression", "")
result = safe_calculator(expr)
@ -292,6 +294,7 @@ class PipecatEngine:
) -> None:
logger.info(f"LLM Function Call EXECUTED: get_current_time")
logger.info(f"Arguments: {function_call_params.arguments}")
try:
timezone = function_call_params.arguments.get("timezone", "UTC")
result = get_current_time(timezone)
@ -302,6 +305,7 @@ class PipecatEngine:
async def convert_time_func(function_call_params: FunctionCallParams) -> None:
logger.info(f"LLM Function Call EXECUTED: convert_time")
logger.info(f"Arguments: {function_call_params.arguments}")
try:
result = convert_time(
function_call_params.arguments.get("source_timezone"),
@ -332,6 +336,7 @@ class PipecatEngine:
async def retrieve_kb_func(function_call_params: FunctionCallParams) -> None:
logger.info("LLM Function Call EXECUTED: retrieve_from_knowledge_base")
logger.info(f"Arguments: {function_call_params.arguments}")
try:
query = function_call_params.arguments.get("query", "")
organization_id = await self._get_organization_id()
@ -532,7 +537,9 @@ class PipecatEngine:
self._current_node, run_in_background=False
)
frame_to_push = CancelFrame() if abort_immediately else EndFrame()
frame_to_push = (
CancelFrame(reason=reason) if abort_immediately else EndFrame(reason=reason)
)
# Apply disposition mapping - first try call_disposition if it is,
# extracted from the call conversation then fall back to reason
@ -705,6 +712,22 @@ class PipecatEngine:
f"Stasis connection set for immediate transfers: {connection.channel_id}"
)
def set_audio_config(self, audio_config) -> None:
"""Set the audio configuration for the pipeline."""
self._audio_config = audio_config
def set_mute_pipeline(self, mute: bool) -> None:
"""Set the pipeline mute state.
This controls whether user input should be muted via the CallbackUserMuteStrategy.
When muted, the user's audio input will be blocked.
Args:
mute: True to mute user input, False to allow input
"""
logger.debug(f"Setting pipeline mute state to: {mute}")
self._mute_pipeline = mute
async def handle_llm_text_frame(self, text: str):
"""Accumulate LLM text frames to build reference text."""
self._current_llm_generation_reference_text += text