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add call transfer skeleton

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This commit is contained in:
Abhishek Kumar 2026-02-05 17:50:54 +05:30
parent e8005042e2
commit c990af2a16
8 changed files with 450 additions and 25 deletions
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20
api/tests/conftest.py
View file

@ -113,6 +113,7 @@ class MockToolModel:
name: str
description: str
definition: Dict[str, Any]
category: str = "http_api"
@pytest.fixture
@ -144,6 +145,25 @@ def mock_user_config():
return MockUserConfig()
@pytest.fixture
def transfer_call_tool():
"""Create a mock transfer call tool for testing."""
return MockToolModel(
tool_uuid="transfer-uuid-001",
name="Transfer to Support",
description="Transfer the call to a support representative",
category="transfer_call",
definition={
"schema_version": 1,
"type": "transfer_call",
"config": {
"transferNumber": "+15551234567",
"transferMessage": "Please hold while I transfer you to a support representative.",
},
},
)
@pytest.fixture
def sample_tools():
"""Create sample mock tools for testing."""

119
api/tests/test_pipecat_engine_tool_calls.py
View file

@ -5,14 +5,15 @@ using PipecatEngine's actual function registration and execution logic.
"""
import asyncio
from typing import Any, Dict, List
from typing import Any, Callable, Coroutine, Dict, List, Optional
from unittest.mock import AsyncMock, patch
import pytest
from api.services.workflow.pipecat_engine import PipecatEngine
from api.services.workflow.transfer_event_protocol import send_transfer_signal
from api.services.workflow.workflow import WorkflowGraph
from api.tests.conftest import END_CALL_SYSTEM_PROMPT
from api.tests.conftest import END_CALL_SYSTEM_PROMPT, MockToolModel
from pipecat.frames.frames import LLMContextFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
@ -32,7 +33,11 @@ async def run_pipeline_with_tool_calls(
functions: List[Dict[str, Any]],
text: str | None = None,
num_text_steps: int = 1,
) -> tuple[MockLLMService, LLMContext]:
mock_tools: Optional[List[MockToolModel]] = None,
on_engine_ready: Optional[
Callable[[PipecatEngine], Coroutine[Any, Any, None]]
] = None,
) -> tuple[MockLLMService, LLMContext, PipecatEngine]:
"""Run a pipeline with mock tool calls and return the LLM for assertions.
Args:
@ -40,9 +45,12 @@ async def run_pipeline_with_tool_calls(
functions: List of function call definitions with name, arguments, and tool_call_id.
text: Text to add to the first step (streamed before the tool calls).
num_text_steps: Number of text response steps after the tool calls.
mock_tools: Optional list of mock tools to be returned by db_client.get_tools_by_uuids.
on_engine_ready: Optional async callback called after engine is initialized.
Useful for sending signals or performing actions during pipeline execution.
Returns:
The MockLLMService instance for making assertions.
Tuple of (MockLLMService, LLMContext, PipecatEngine) for making assertions.
"""
# Create first step chunks
if text:
@ -118,25 +126,43 @@ async def run_pipeline_with_tool_calls(
return_value=1,
):
with patch(
"api.services.workflow.pipecat_engine.apply_disposition_mapping",
"api.services.workflow.pipecat_engine_custom_tools.get_organization_id_from_workflow_run",
new_callable=AsyncMock,
return_value="completed",
return_value=1,
):
runner = PipelineRunner()
with patch(
"api.services.workflow.pipecat_engine.apply_disposition_mapping",
new_callable=AsyncMock,
return_value="completed",
):
with patch(
"api.services.workflow.pipecat_engine_custom_tools.db_client.get_tools_by_uuids",
new_callable=AsyncMock,
return_value=mock_tools or [],
):
runner = PipelineRunner()
async def run_pipeline():
await runner.run(task)
async def run_pipeline():
await runner.run(task)
async def initialize_engine():
# Small delay to let runner start
await asyncio.sleep(0.01)
await engine.initialize()
await engine.llm.queue_frame(LLMContextFrame(engine.context))
async def initialize_engine():
# Small delay to let runner start
await asyncio.sleep(0.01)
await engine.initialize()
await engine.llm.queue_frame(LLMContextFrame(engine.context))
# Run both concurrently
await asyncio.gather(run_pipeline(), initialize_engine())
async def run_callback():
if on_engine_ready:
# Wait for engine to process tool calls
await asyncio.sleep(0.1)
await on_engine_ready(engine)
return llm, context
# Run all concurrently
await asyncio.gather(
run_pipeline(), initialize_engine(), run_callback()
)
return llm, context, engine
class TestPipecatEngineToolCalls:
@ -172,7 +198,7 @@ class TestPipecatEngineToolCalls:
},
]
llm, context = await run_pipeline_with_tool_calls(
llm, context, _ = await run_pipeline_with_tool_calls(
workflow=simple_workflow,
functions=functions,
num_text_steps=2,
@ -218,7 +244,7 @@ class TestPipecatEngineToolCalls:
},
]
llm, context = await run_pipeline_with_tool_calls(
llm, context, _ = await run_pipeline_with_tool_calls(
workflow=simple_workflow,
functions=functions,
num_text_steps=2,
@ -265,7 +291,7 @@ class TestPipecatEngineToolCalls:
},
]
llm, context = await run_pipeline_with_tool_calls(
llm, context, _ = await run_pipeline_with_tool_calls(
workflow=simple_workflow,
functions=functions,
text="Hello There!",
@ -302,7 +328,7 @@ class TestPipecatEngineToolCalls:
},
]
llm, context = await run_pipeline_with_tool_calls(
llm, context, _ = await run_pipeline_with_tool_calls(
workflow=simple_workflow,
functions=functions,
num_text_steps=1,
@ -316,3 +342,54 @@ class TestPipecatEngineToolCalls:
# Assert that the context was updated with END_CALL_SYSTEM_PROMPT
assert context.messages[0]["content"] == END_CALL_SYSTEM_PROMPT
@pytest.mark.asyncio
async def test_transfer_call_tool_execution(
self, simple_workflow: WorkflowGraph, transfer_call_tool: MockToolModel
):
"""Test transfer call tool execution through PipecatEngine.
This test verifies that when the LLM calls the transfer_to_support tool:
1. The transfer call handler is invoked
2. The handler waits for a transfer signal via Redis pub/sub
3. When the signal is sent, the handler proceeds
4. The gathered_context is updated with transfer_requested=True
5. The gathered_context contains the transfer_number
"""
# Add the transfer tool to the start node at runtime
simple_workflow.nodes["start"].tool_uuids = [transfer_call_tool.tool_uuid]
simple_workflow.nodes["start"].extraction_enabled = False
# The function name is derived from the tool name (snake_case)
functions = [
{
"name": "transfer_to_support",
"arguments": {},
"tool_call_id": "call_transfer",
},
]
# Callback to send transfer signal while handler is waiting
async def send_signal(engine: PipecatEngine):
# Send the transfer signal to unblock the waiting handler
await send_transfer_signal(
workflow_run_id=engine._workflow_run_id,
)
_, _, engine = await run_pipeline_with_tool_calls(
workflow=simple_workflow,
functions=functions,
num_text_steps=1,
mock_tools=[transfer_call_tool],
on_engine_ready=send_signal,
)
# Verify the gathered context was updated with transfer information
gathered_context = await engine.get_gathered_context()
assert gathered_context.get("transfer_requested") is True, (
"transfer_requested should be True in gathered_context"
)
assert gathered_context.get("transfer_number") == "+15551234567", (
"transfer_number should match the configured number"
)