mirror of
https://github.com/dograh-hq/dograh.git
synced 2026-06-10 08:05:22 +02:00
754 lines
32 KiB
Python
754 lines
32 KiB
Python
"""Custom tool management for PipecatEngine.
|
|
|
|
This module handles fetching, registering, and executing user-defined tools
|
|
during workflow execution.
|
|
"""
|
|
|
|
from __future__ import annotations
|
|
|
|
import asyncio
|
|
import re
|
|
from typing import TYPE_CHECKING, Any, Optional
|
|
|
|
import aiohttp
|
|
import httpx
|
|
from loguru import logger
|
|
|
|
from api.db import db_client
|
|
from api.enums import ToolCategory
|
|
from api.services.workflow.disposition_mapper import (
|
|
get_organization_id_from_workflow_run,
|
|
)
|
|
from api.services.workflow.pipecat_engine_utils import get_function_schema
|
|
from api.services.workflow.tools.custom_tool import (
|
|
execute_http_tool,
|
|
tool_to_function_schema,
|
|
)
|
|
from pipecat.adapters.schemas.function_schema import FunctionSchema
|
|
from pipecat.frames.frames import (
|
|
FunctionCallResultProperties,
|
|
TTSSpeakFrame,
|
|
OutputAudioRawFrame,
|
|
)
|
|
from pipecat.services.llm_service import FunctionCallParams
|
|
from pipecat.utils.enums import EndTaskReason
|
|
from pipecat.transports.websocket.fastapi import FastAPIWebsocketClient
|
|
|
|
from api.utils.hold_audio import load_hold_audio
|
|
from api.services.telephony.call_transfer_manager import get_call_transfer_manager
|
|
from api.services.telephony.transfer_event_protocol import (
|
|
TransferEvent,
|
|
TransferContext,
|
|
TransferEventType,
|
|
)
|
|
|
|
from dograh.api.utils.common import get_backend_endpoints
|
|
|
|
if TYPE_CHECKING:
|
|
from api.services.workflow.pipecat_engine import PipecatEngine
|
|
|
|
|
|
class CustomToolManager:
|
|
"""Manager for custom tool registration and execution.
|
|
|
|
This class handles:
|
|
1. Fetching tools from the database based on tool UUIDs
|
|
2. Converting tools to LLM function schemas
|
|
3. Registering tool execution handlers with the LLM
|
|
4. Executing tools when invoked by the LLM
|
|
"""
|
|
|
|
def __init__(self, engine: "PipecatEngine") -> None:
|
|
self._engine = engine
|
|
self._organization_id: Optional[int] = None
|
|
|
|
async def get_organization_id(self) -> Optional[int]:
|
|
"""Get and cache the organization ID from workflow run."""
|
|
if self._organization_id is None:
|
|
self._organization_id = await get_organization_id_from_workflow_run(
|
|
self._engine._workflow_run_id
|
|
)
|
|
return self._organization_id
|
|
|
|
async def get_tool_schemas(self, tool_uuids: list[str]) -> list[FunctionSchema]:
|
|
"""Fetch custom tools and convert them to function schemas.
|
|
|
|
Args:
|
|
tool_uuids: List of tool UUIDs to fetch
|
|
|
|
Returns:
|
|
List of FunctionSchema objects for LLM
|
|
"""
|
|
organization_id = await self.get_organization_id()
|
|
if not organization_id:
|
|
logger.warning("Cannot fetch custom tools: organization_id not available")
|
|
return []
|
|
|
|
try:
|
|
tools = await db_client.get_tools_by_uuids(tool_uuids, organization_id)
|
|
|
|
schemas: list[FunctionSchema] = []
|
|
for tool in tools:
|
|
raw_schema = tool_to_function_schema(tool)
|
|
function_name = raw_schema["function"]["name"]
|
|
|
|
# Convert to FunctionSchema object for compatibility with update_llm_context
|
|
func_schema = get_function_schema(
|
|
function_name,
|
|
raw_schema["function"]["description"],
|
|
properties=raw_schema["function"]["parameters"].get(
|
|
"properties", {}
|
|
),
|
|
required=raw_schema["function"]["parameters"].get("required", []),
|
|
)
|
|
schemas.append(func_schema)
|
|
|
|
logger.debug(
|
|
f"Loaded {len(schemas)} custom tools for node: "
|
|
f"{[s.name for s in schemas]}"
|
|
)
|
|
return schemas
|
|
|
|
except Exception as e:
|
|
logger.error(f"Failed to fetch custom tools: {e}")
|
|
return []
|
|
|
|
async def register_handlers(self, tool_uuids: list[str]) -> None:
|
|
"""Register custom tool execution handlers with the LLM.
|
|
|
|
Args:
|
|
tool_uuids: List of tool UUIDs to register handlers for
|
|
"""
|
|
organization_id = await self.get_organization_id()
|
|
if not organization_id:
|
|
logger.warning(
|
|
"Cannot register custom tool handlers: organization_id not available"
|
|
)
|
|
return
|
|
|
|
try:
|
|
tools = await db_client.get_tools_by_uuids(tool_uuids, organization_id)
|
|
|
|
for tool in tools:
|
|
schema = tool_to_function_schema(tool)
|
|
function_name = schema["function"]["name"]
|
|
|
|
# Create and register the handler
|
|
handler = self._create_handler(tool, function_name)
|
|
self._engine.llm.register_function(function_name, handler)
|
|
|
|
logger.debug(
|
|
f"Registered custom tool handler: {function_name} "
|
|
f"(tool_uuid: {tool.tool_uuid})"
|
|
)
|
|
|
|
except Exception as e:
|
|
logger.error(f"Failed to register custom tool handlers: {e}")
|
|
|
|
def _create_handler(self, tool: Any, function_name: str):
|
|
"""Create a handler function for a tool based on its category.
|
|
|
|
Args:
|
|
tool: The ToolModel instance
|
|
function_name: The function name used by the LLM
|
|
|
|
Returns:
|
|
Async handler function for the tool
|
|
"""
|
|
if tool.category == ToolCategory.END_CALL.value:
|
|
return self._create_end_call_handler(tool, function_name)
|
|
elif tool.category == ToolCategory.TRANSFER_CALL.value:
|
|
return self._create_transfer_call_handler(tool, function_name)
|
|
|
|
return self._create_http_tool_handler(tool, function_name)
|
|
|
|
def _create_http_tool_handler(self, tool: Any, function_name: str):
|
|
"""Create a handler function for an HTTP API tool.
|
|
|
|
Args:
|
|
tool: The ToolModel instance
|
|
function_name: The function name used by the LLM
|
|
|
|
Returns:
|
|
Async handler function for the HTTP API tool
|
|
"""
|
|
|
|
async def http_tool_handler(
|
|
function_call_params: FunctionCallParams,
|
|
) -> None:
|
|
logger.info(f"HTTP Tool EXECUTED: {function_name}")
|
|
logger.info(f"Arguments: {function_call_params.arguments}")
|
|
|
|
try:
|
|
result = await execute_http_tool(
|
|
tool=tool,
|
|
arguments=function_call_params.arguments,
|
|
call_context_vars=self._engine._call_context_vars,
|
|
organization_id=self._organization_id,
|
|
)
|
|
|
|
await function_call_params.result_callback(result)
|
|
|
|
except Exception as e:
|
|
logger.error(f"HTTP tool '{function_name}' execution failed: {e}")
|
|
await function_call_params.result_callback(
|
|
{"status": "error", "error": str(e)}
|
|
)
|
|
|
|
return http_tool_handler
|
|
|
|
def _create_end_call_handler(self, tool: Any, function_name: str):
|
|
"""Create a handler function for an end call tool.
|
|
|
|
Args:
|
|
tool: The ToolModel instance
|
|
function_name: The function name used by the LLM
|
|
|
|
Returns:
|
|
Async handler function for the end call tool
|
|
"""
|
|
# Don't run LLM after end call - we're terminating
|
|
properties = FunctionCallResultProperties(run_llm=False)
|
|
|
|
async def end_call_handler(
|
|
function_call_params: FunctionCallParams,
|
|
) -> None:
|
|
logger.info(f"End Call Tool EXECUTED: {function_name}")
|
|
|
|
try:
|
|
# Get the end call configuration
|
|
config = tool.definition.get("config", {})
|
|
message_type = config.get("messageType", "none")
|
|
custom_message = config.get("customMessage", "")
|
|
|
|
# Send result callback first
|
|
await function_call_params.result_callback(
|
|
{"status": "success", "action": "ending_call"},
|
|
properties=properties,
|
|
)
|
|
|
|
if message_type == "custom" and custom_message:
|
|
# Queue the custom message to be spoken
|
|
logger.info(f"Playing custom goodbye message: {custom_message}")
|
|
await self._engine.task.queue_frame(TTSSpeakFrame(custom_message))
|
|
# End the call after the message (not immediately)
|
|
await self._engine.end_call_with_reason(
|
|
EndTaskReason.END_CALL_TOOL_REASON.value,
|
|
abort_immediately=False,
|
|
)
|
|
else:
|
|
# No message - end call immediately
|
|
logger.info("Ending call immediately (no goodbye message)")
|
|
await self._engine.end_call_with_reason(
|
|
EndTaskReason.END_CALL_TOOL_REASON.value, abort_immediately=True
|
|
)
|
|
|
|
except Exception as e:
|
|
logger.error(f"End call tool '{function_name}' execution failed: {e}")
|
|
# Still try to end the call even if there's an error
|
|
await self._engine.end_call_with_reason(
|
|
EndTaskReason.UNEXPECTED_ERROR.value, abort_immediately=True
|
|
)
|
|
|
|
return end_call_handler
|
|
|
|
def _create_transfer_call_handler(self, tool: Any, function_name: str):
|
|
"""Create a handler function for a transfer call tool.
|
|
|
|
Args:
|
|
tool: The ToolModel instance
|
|
function_name: The function name used by the LLM
|
|
|
|
Returns:
|
|
Async handler function for the transfer call tool
|
|
"""
|
|
# Don't run LLM after starting transfer - we're handling async response
|
|
properties = FunctionCallResultProperties(run_llm=False)
|
|
|
|
async def transfer_call_handler(
|
|
function_call_params: FunctionCallParams,
|
|
) -> None:
|
|
logger.info(f"Transfer Call Tool EXECUTED: {function_name}")
|
|
logger.info(f"Arguments: {function_call_params.arguments}")
|
|
|
|
try:
|
|
# Get the transfer call configuration
|
|
config = tool.definition.get("config", {})
|
|
destination = config.get("destination", "")
|
|
message_type = config.get("messageType", "none")
|
|
custom_message = config.get("customMessage", "")
|
|
timeout_seconds = config.get(
|
|
"timeout", 30
|
|
) # Default 30 seconds if not configured
|
|
|
|
# Validate destination phone number
|
|
if not destination or not destination.strip():
|
|
validation_error_result = {
|
|
"status": "failed",
|
|
"message": "I'm sorry, but I don't have a phone number configured for the transfer. Please contact support to set up call transfer.",
|
|
"action": "transfer_failed",
|
|
"reason": "no_destination",
|
|
"end_call": True,
|
|
}
|
|
await self._handle_transfer_result(
|
|
validation_error_result, function_call_params, properties
|
|
)
|
|
return
|
|
|
|
# Validate E.164 format
|
|
e164_pattern = r"^\+[1-9]\d{1,14}$"
|
|
if not re.match(e164_pattern, destination):
|
|
validation_error_result = {
|
|
"status": "failed",
|
|
"message": "I'm sorry, but the transfer phone number appears to be invalid. Please contact support to verify the transfer settings.",
|
|
"action": "transfer_failed",
|
|
"reason": "invalid_destination",
|
|
"end_call": True,
|
|
}
|
|
await self._handle_transfer_result(
|
|
validation_error_result, function_call_params, properties
|
|
)
|
|
return
|
|
|
|
# Provider validation handled by telephony endpoint
|
|
|
|
# Note: User muting and hold music are handled automatically by
|
|
|
|
# Play pre-transfer message if configured
|
|
if message_type == "custom" and custom_message:
|
|
logger.info(f"Playing pre-transfer message: {custom_message}")
|
|
await self._engine.task.queue_frame(TTSSpeakFrame(custom_message))
|
|
|
|
# Get original call information from Pipecat context
|
|
from pipecat.utils.run_context import get_current_call_sid
|
|
|
|
original_call_sid = get_current_call_sid()
|
|
caller_number = None # Skip caller number for now as requested
|
|
|
|
logger.info(f"Found original call context: call_id={original_call_sid}")
|
|
|
|
# Get organization ID for provider configuration
|
|
organization_id = await self.get_organization_id()
|
|
if not organization_id:
|
|
validation_error_result = {
|
|
"status": "failed",
|
|
"message": "I'm sorry, but I can't determine which organization this call belongs to. Please contact support.",
|
|
"action": "transfer_failed",
|
|
"reason": "no_organization_id",
|
|
"end_call": False,
|
|
}
|
|
await self._handle_transfer_result(
|
|
validation_error_result, function_call_params, properties
|
|
)
|
|
return
|
|
|
|
# Prepare transfer request data
|
|
transfer_data = {
|
|
"destination": destination,
|
|
"organization_id": organization_id, # Required for provider configuration
|
|
"tool_call_id": function_call_params.tool_call_id, # Use LLM's tool call ID for pipeline coordination
|
|
"tool_uuid": tool.tool_uuid, # Add tool UUID for tracing and validation
|
|
"original_call_sid": original_call_sid, # Original caller's call SID
|
|
"caller_number": caller_number, # Original caller's phone number
|
|
}
|
|
|
|
# Initialize Redis-based transfer coordination
|
|
import time
|
|
|
|
# Get backend endpoint URL
|
|
backend_url, _ = await get_backend_endpoints()
|
|
|
|
# Get transfer coordinator for Redis-based coordination
|
|
call_transfer_manager = await get_call_transfer_manager()
|
|
|
|
# Now initiate the transfer call
|
|
transfer_url = f"{backend_url}/api/v1/telephony/call-transfer"
|
|
|
|
async with httpx.AsyncClient(timeout=30.0) as client:
|
|
response = await client.post(
|
|
transfer_url,
|
|
json=transfer_data,
|
|
headers={"Content-Type": "application/json"},
|
|
# Authentication headers added by provider if needed
|
|
)
|
|
|
|
if response.status_code == 200:
|
|
result_data = response.json()
|
|
logger.info(f"Transfer initiated successfully: {result_data}")
|
|
|
|
# Wait for webhook completion using standard Pipecat async pattern
|
|
logger.info(
|
|
f"Transfer call initiated for {destination}, waiting for webhook completion..."
|
|
)
|
|
|
|
# Start hold music during transfer waiting period
|
|
hold_music_stop_event = asyncio.Event()
|
|
hold_music_task = None
|
|
|
|
try:
|
|
# Mute the pipeline to prevent further LLM generations during transfer
|
|
logger.info("Muting pipeline during transfer call")
|
|
self._engine.set_mute_pipeline(True)
|
|
|
|
# Determine sample rate from transport (default to 8000Hz for Twilio)
|
|
sample_rate = 8000
|
|
if hasattr(self._engine.transport, "output") and hasattr(
|
|
self._engine.transport.output(), "sample_rate"
|
|
):
|
|
sample_rate = getattr(
|
|
self._engine.transport.output(), "sample_rate", 8000
|
|
)
|
|
|
|
logger.info(
|
|
f"Starting hold music at {sample_rate}Hz while waiting for transfer"
|
|
)
|
|
|
|
# Start hold music as background task
|
|
hold_music_task = asyncio.create_task(
|
|
self.play_hold_music_loop(
|
|
hold_music_stop_event, sample_rate
|
|
)
|
|
)
|
|
|
|
# Wait for transfer completion using Redis pub/sub
|
|
logger.info(
|
|
"Waiting for transfer completion via Redis pub/sub..."
|
|
)
|
|
transfer_event = (
|
|
await call_transfer_manager.wait_for_transfer_completion(
|
|
transfer_data["tool_call_id"], timeout_seconds
|
|
)
|
|
)
|
|
|
|
# Stop hold music and unmute pipeline
|
|
logger.info(
|
|
"Transfer completed, stopping hold music and unmuting pipeline"
|
|
)
|
|
hold_music_stop_event.set()
|
|
if hold_music_task:
|
|
await hold_music_task
|
|
self._engine.set_mute_pipeline(False)
|
|
|
|
if transfer_event:
|
|
# Get result from transfer event
|
|
final_result = transfer_event.to_result_dict()
|
|
|
|
# Get transfer context for caller number
|
|
transfer_context = (
|
|
await call_transfer_manager.get_transfer_context(
|
|
transfer_data["tool_call_id"]
|
|
)
|
|
)
|
|
if transfer_context and transfer_context.caller_number:
|
|
final_result["caller_number"] = (
|
|
transfer_context.caller_number
|
|
)
|
|
|
|
# Handle the transfer result and inform user appropriately
|
|
await self._handle_transfer_result(
|
|
final_result, function_call_params, properties
|
|
)
|
|
else:
|
|
# Handle timeout case
|
|
logger.error(
|
|
f"Transfer call timed out after {timeout_seconds} seconds"
|
|
)
|
|
|
|
# Create timeout result and handle it through the same flow
|
|
timeout_result = {
|
|
"status": "failed",
|
|
"message": "I'm sorry, but the call is taking longer than expected to connect. The person might not be available right now. Please try calling back later.",
|
|
"action": "transfer_failed",
|
|
"reason": "timeout",
|
|
"end_call": True,
|
|
}
|
|
await self._handle_transfer_result(
|
|
timeout_result, function_call_params, properties
|
|
)
|
|
|
|
except Exception as e:
|
|
logger.error(f"Error during transfer wait: {e}")
|
|
|
|
# Stop hold music and unmute pipeline on error
|
|
logger.info(
|
|
"Transfer error, stopping hold music and unmuting pipeline"
|
|
)
|
|
hold_music_stop_event.set()
|
|
if hold_music_task:
|
|
await hold_music_task
|
|
self._engine.set_mute_pipeline(False)
|
|
|
|
# Handle error case
|
|
error_result = {
|
|
"status": "failed",
|
|
"message": "I'm sorry, but there was an issue processing the transfer. Please try again.",
|
|
"action": "transfer_failed",
|
|
"reason": "system_error",
|
|
"end_call": True,
|
|
}
|
|
await self._handle_transfer_result(
|
|
error_result, function_call_params, properties
|
|
)
|
|
|
|
else:
|
|
error_data = (
|
|
response.json()
|
|
if response.content
|
|
else {"error": "Unknown error"}
|
|
)
|
|
logger.error(
|
|
f"Transfer initiation failed: {response.status_code} - {error_data}"
|
|
)
|
|
|
|
# No cleanup needed for Redis-based coordination
|
|
|
|
# Handle initiation failure with user-friendly message
|
|
initiation_failure_result = {
|
|
"status": "failed",
|
|
"message": "I'm sorry, but I'm having trouble setting up the call transfer right now. There might be a technical issue. Please try again later or contact support.",
|
|
"action": "transfer_failed",
|
|
"reason": "initiation_failed",
|
|
"end_call": True,
|
|
}
|
|
|
|
await self._handle_transfer_result(
|
|
initiation_failure_result, function_call_params, properties
|
|
)
|
|
|
|
except httpx.TimeoutException:
|
|
logger.error(f"Transfer call '{function_name}' HTTP request timed out")
|
|
|
|
# No cleanup needed for Redis-based coordination
|
|
|
|
# Handle HTTP timeout with user-friendly message
|
|
http_timeout_result = {
|
|
"status": "failed",
|
|
"message": "I'm sorry, but there seems to be a network issue preventing me from setting up the call transfer. Please try again in a moment.",
|
|
"action": "transfer_failed",
|
|
"reason": "network_timeout",
|
|
"end_call": True,
|
|
}
|
|
|
|
await self._handle_transfer_result(
|
|
http_timeout_result, function_call_params, properties
|
|
)
|
|
|
|
except Exception as e:
|
|
logger.error(
|
|
f"Transfer call tool '{function_name}' execution failed: {e}"
|
|
)
|
|
|
|
# No cleanup needed for Redis-based coordination
|
|
|
|
# Handle generic exception with user-friendly message
|
|
exception_result = {
|
|
"status": "failed",
|
|
"message": "I'm sorry, but something went wrong while trying to transfer your call. Please try again later or contact support if the problem persists.",
|
|
"action": "transfer_failed",
|
|
"reason": "execution_error",
|
|
"end_call": True,
|
|
}
|
|
|
|
await self._handle_transfer_result(
|
|
exception_result, function_call_params, properties
|
|
)
|
|
|
|
return transfer_call_handler
|
|
|
|
async def _handle_transfer_result(
|
|
self, result: dict, function_call_params, properties
|
|
):
|
|
"""Handle different transfer call outcomes and take appropriate action."""
|
|
action = result.get("action", "")
|
|
status = result.get("status", "")
|
|
message = result.get("message", "")
|
|
should_end_call = result.get("end_call", False)
|
|
|
|
logger.info(f"Handling transfer result: action={action}, status={status}")
|
|
|
|
if action == "transfer_success":
|
|
# Successful transfer - add original caller to conference and end pipeline
|
|
conference_id = result.get("conference_id")
|
|
original_call_sid = result.get("original_call_sid")
|
|
transfer_call_sid = result.get("transfer_call_sid")
|
|
|
|
logger.info(
|
|
f"Transfer successful! Conference: {conference_id}, Original: {original_call_sid}, Transfer: {transfer_call_sid}"
|
|
)
|
|
|
|
# First inform LLM of success (but don't continue call)
|
|
response_properties = FunctionCallResultProperties(
|
|
run_llm=False
|
|
) # We'll handle the transfer ourselves
|
|
await function_call_params.result_callback(
|
|
{
|
|
"status": "transfer_success",
|
|
"message": "Transfer successful - connecting to conference",
|
|
"conference_id": conference_id,
|
|
},
|
|
properties=response_properties,
|
|
)
|
|
|
|
await self._engine.end_call_with_reason(
|
|
EndTaskReason.TRANSFER_CALL.value, abort_immediately=False
|
|
)
|
|
|
|
elif action == "transfer_failed":
|
|
# Transfer failed - inform user via LLM and then end the call
|
|
reason = result.get("reason", "unknown")
|
|
logger.info(f"Transfer failed ({reason}), informing user and ending call")
|
|
|
|
# Use system message pattern to direct LLM response for transfer failure
|
|
# This is more reliable than function call results
|
|
from pipecat.frames.frames import LLMMessagesAppendFrame
|
|
|
|
# Create system message with clear instructions for transfer failure
|
|
failure_instruction = {
|
|
"role": "system",
|
|
"content": f"IMPORTANT: The transfer call has FAILED. Reason: {reason}. You must inform the customer about this failure using this message: '{message}' Then immediately say goodbye and end the conversation. Do NOT ask if they need anything else or continue the conversation. Do NOT continue with transfer language.",
|
|
}
|
|
|
|
# Push the system message to LLM context
|
|
await self._engine.task.queue_frame(
|
|
LLMMessagesAppendFrame([failure_instruction], run_llm=True)
|
|
)
|
|
|
|
# Also send the function call result for consistency
|
|
response_properties = FunctionCallResultProperties(
|
|
run_llm=False
|
|
) # LLM will be triggered by system message
|
|
await function_call_params.result_callback(
|
|
{"status": "transfer_failed", "reason": reason, "message": message},
|
|
properties=response_properties,
|
|
)
|
|
|
|
# Set appropriate disposition for analytics
|
|
disposition_map = {
|
|
"no_answer": "transfer_no_answer",
|
|
"busy": "transfer_busy",
|
|
"call_failed": "transfer_failed",
|
|
"timeout": "transfer_timeout",
|
|
"no_destination": "transfer_config_error",
|
|
"invalid_destination": "transfer_config_error",
|
|
"initiation_failed": "transfer_system_error",
|
|
"network_timeout": "transfer_system_error",
|
|
"execution_error": "transfer_system_error",
|
|
}
|
|
|
|
disposition = disposition_map.get(reason, "transfer_failed")
|
|
logger.info(
|
|
f"Setting disposition: {disposition} for transfer failure reason: {reason}"
|
|
)
|
|
|
|
# Give the LLM time to speak the message, then end the call with disposition
|
|
# We'll schedule the end call after a brief delay to allow TTS
|
|
logger.info("Scheduling call end after LLM delivers failure message")
|
|
|
|
# Import here to avoid circular dependencies
|
|
import asyncio
|
|
|
|
# Schedule call end after 3 seconds to allow LLM to speak
|
|
async def delayed_end_call():
|
|
import asyncio
|
|
|
|
await asyncio.sleep(3)
|
|
await self._engine.end_call_with_reason(
|
|
f"transfer_failed_{reason}", # Include specific reason in end reason
|
|
abort_immediately=False, # Allow any queued speech to complete
|
|
)
|
|
|
|
# Create task to end call asynchronously
|
|
asyncio.create_task(delayed_end_call())
|
|
|
|
elif action == "transfer_completed":
|
|
# This should no longer happen since we ignore "completed" status in webhook
|
|
# to avoid overriding successful transfers
|
|
logger.warning(
|
|
"Received unexpected 'transfer_completed' action - this should be ignored by webhook now"
|
|
)
|
|
logger.warning(
|
|
"If you see this message, there might be an issue with the webhook status filtering"
|
|
)
|
|
|
|
# For safety, treat it as a generic result without ending the call
|
|
await function_call_params.result_callback(result, properties=properties)
|
|
|
|
else:
|
|
# Unknown action, treat as generic success
|
|
logger.warning(f"Unknown transfer action: {action}, treating as success")
|
|
await function_call_params.result_callback(result, properties=properties)
|
|
|
|
async def play_hold_music_loop(
|
|
self, stop_event: asyncio.Event, sample_rate: int = 8000
|
|
):
|
|
"""Play hold music in a loop until stop event is triggered.
|
|
|
|
Args:
|
|
stop_event: Event to stop the hold music loop
|
|
sample_rate: Sample rate for the hold music (default 8000Hz for Twilio)
|
|
"""
|
|
try:
|
|
import os
|
|
|
|
# Path to hold music file based on sample rate
|
|
assets_dir = os.path.join(
|
|
os.path.dirname(os.path.dirname(os.path.dirname(__file__))), "assets"
|
|
)
|
|
|
|
# Select appropriate hold music file
|
|
if sample_rate == 16000:
|
|
hold_music_file = os.path.join(
|
|
assets_dir, "transfer_hold_ring_16000.wav"
|
|
)
|
|
else: # Default to 8000Hz for Twilio
|
|
hold_music_file = os.path.join(
|
|
assets_dir, "transfer_hold_ring_8000.wav"
|
|
)
|
|
|
|
logger.info(f"Starting hold music loop with file: {hold_music_file}")
|
|
|
|
# Load hold music audio data
|
|
hold_audio_data = load_hold_audio(hold_music_file, sample_rate)
|
|
if not hold_audio_data:
|
|
logger.error("Failed to load hold music data")
|
|
return
|
|
|
|
# Convert bytes to audio frames - each frame should be about 20ms worth of audio
|
|
# For 8000Hz: 20ms = 160 samples = 320 bytes (16-bit)
|
|
# For 16000Hz: 20ms = 320 samples = 640 bytes (16-bit)
|
|
frame_size = 320 if sample_rate == 8000 else 640
|
|
|
|
audio_data = hold_audio_data
|
|
total_length = len(audio_data)
|
|
position = 0
|
|
|
|
logger.info(
|
|
f"Hold music loaded: {total_length} bytes, frame size: {frame_size}"
|
|
)
|
|
|
|
while not stop_event.is_set():
|
|
# Extract audio chunk
|
|
if position + frame_size > total_length:
|
|
# Reached end of audio, loop back to beginning
|
|
position = 0
|
|
|
|
audio_chunk = audio_data[position : position + frame_size]
|
|
position += frame_size
|
|
|
|
# Create audio frame
|
|
audio_frame = OutputAudioRawFrame(
|
|
audio=audio_chunk,
|
|
sample_rate=sample_rate,
|
|
num_channels=1,
|
|
)
|
|
|
|
# Queue the frame
|
|
await self._engine.task.queue_frame(audio_frame)
|
|
|
|
# Sleep for frame duration (20ms)
|
|
await asyncio.sleep(0.02)
|
|
|
|
logger.info("Hold music loop stopped")
|
|
|
|
except Exception as e:
|
|
logger.error(f"Error in hold music loop: {e}")
|