mirror of
https://github.com/dograh-hq/dograh.git
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feat: simplify TesterPanel design
This commit is contained in:
Abhishek Kumar
parent
f929a332bb
commit
b243e97502
15 changed files with 2461 additions and 565 deletions
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@ -375,6 +375,103 @@ class TestStartGreeting:
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result = engine.get_start_greeting()
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assert result == ("text", "Hello Alice!")
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@pytest.mark.asyncio
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async def test_queue_node_opening_queues_text_greeting(
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self, text_workflow: WorkflowGraph
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):
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"""Fresh node entry with a greeting should queue TTS and skip LLM bootstrap."""
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llm = Mock()
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llm.queue_frame = AsyncMock()
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task = Mock()
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task.queue_frame = AsyncMock()
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engine = PipecatEngine(
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llm=llm,
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context=LLMContext(),
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workflow=text_workflow,
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call_context_vars={},
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workflow_run_id=1,
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)
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engine.set_task(task)
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result = await engine.queue_node_opening(
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node_id=text_workflow.start_node_id,
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previous_node_id=None,
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generate_if_no_greeting=True,
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)
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assert result == "greeting"
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llm.queue_frame.assert_not_awaited()
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queued_frame = task.queue_frame.await_args.args[0]
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assert isinstance(queued_frame, TTSSpeakFrame)
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assert queued_frame.text == TEXT_GREETING
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assert queued_frame.append_to_context is True
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@pytest.mark.asyncio
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async def test_queue_node_opening_falls_back_to_llm_without_greeting(self):
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"""When a node has no greeting, the engine should queue initial LLM generation."""
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dto = ReactFlowDTO(
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nodes=[
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StartCallRFNode(
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id="start",
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position=Position(x=0, y=0),
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data=StartCallNodeData(
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name="Start",
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prompt="Prompt",
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is_start=True,
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add_global_prompt=False,
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extraction_enabled=False,
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),
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),
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EndCallRFNode(
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id="end",
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position=Position(x=0, y=200),
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data=EndCallNodeData(
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name="End",
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prompt="End",
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is_end=True,
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add_global_prompt=False,
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extraction_enabled=False,
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),
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),
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],
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edges=[
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RFEdgeDTO(
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id="e",
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source="start",
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target="end",
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data=EdgeDataDTO(label="End", condition="End"),
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),
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],
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)
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workflow = WorkflowGraph(dto)
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context = LLMContext()
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llm = Mock()
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llm.queue_frame = AsyncMock()
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task = Mock()
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task.queue_frame = AsyncMock()
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engine = PipecatEngine(
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llm=llm,
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context=context,
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workflow=workflow,
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call_context_vars={},
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workflow_run_id=1,
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)
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engine.set_task(task)
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result = await engine.queue_node_opening(
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node_id=workflow.start_node_id,
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previous_node_id=None,
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generate_if_no_greeting=True,
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)
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assert result == "llm"
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task.queue_frame.assert_not_awaited()
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queued_frame = llm.queue_frame.await_args.args[0]
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assert isinstance(queued_frame, LLMContextFrame)
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assert queued_frame.context is context
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# ─── Tests: Transition Speech (Pipeline) ────────────────────────
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849
api/tests/test_workflow_text_chat.py
Normal file
849
api/tests/test_workflow_text_chat.py
Normal file
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@ -0,0 +1,849 @@
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from unittest.mock import AsyncMock, patch
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import pytest
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from pipecat.tests import MockLLMService
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from api.db.models import OrganizationModel, UserModel
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from api.schemas.user_configuration import UserConfiguration
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from api.tests.integrations._run_pipeline_helpers import USER_CONFIGURATION
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async def _create_user_and_workflow(
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db_session,
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async_session,
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*,
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workflow_definition: dict,
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suffix: str,
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):
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org = OrganizationModel(provider_id=f"textchat-org-{suffix}")
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async_session.add(org)
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await async_session.flush()
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user = UserModel(
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provider_id=f"textchat-user-{suffix}",
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selected_organization_id=org.id,
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)
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async_session.add(user)
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await async_session.flush()
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await db_session.update_user_configuration(
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user_id=user.id,
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configuration=UserConfiguration.model_validate(USER_CONFIGURATION),
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)
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workflow = await db_session.create_workflow(
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name=f"Text Chat Workflow {suffix}",
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workflow_definition=workflow_definition,
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user_id=user.id,
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organization_id=org.id,
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)
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return user, workflow
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@pytest.mark.asyncio
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async def test_text_chat_session_creation_executes_initial_assistant_turn(
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db_session,
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async_session,
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test_client_factory,
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):
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workflow_definition = {
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"nodes": [
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{
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"id": "start",
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"type": "startCall",
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"position": {"x": 0, "y": 0},
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"data": {
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"name": "Start",
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"prompt": "You are a helpful assistant.",
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"is_start": True,
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"allow_interrupt": False,
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"add_global_prompt": False,
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},
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},
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{
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"id": "end",
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"type": "endCall",
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"position": {"x": 0, "y": 200},
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"data": {
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"name": "End",
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"prompt": "Wrap up the conversation.",
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"is_end": True,
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"allow_interrupt": False,
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"add_global_prompt": False,
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},
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},
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],
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"edges": [
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{
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"id": "start-end",
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"source": "start",
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"target": "end",
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"data": {"label": "End Call", "condition": "When the task is done."},
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}
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],
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}
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user, workflow = await _create_user_and_workflow(
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db_session,
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async_session,
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workflow_definition=workflow_definition,
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suffix="bootstrap",
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)
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llm = MockLLMService(
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mock_steps=[MockLLMService.create_text_chunks("Hello from the workflow tester.")],
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chunk_delay=0.001,
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)
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async with test_client_factory(user) as client:
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with patch(
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"api.services.workflow.text_chat_runner.create_llm_service",
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return_value=llm,
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), patch(
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"api.services.workflow.text_chat_runner.db_client.has_active_recordings",
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new=AsyncMock(return_value=False),
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):
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create_response = await client.post(
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f"/api/v1/workflow/{workflow.id}/text-chat/sessions",
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json={},
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)
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assert create_response.status_code == 200
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created = create_response.json()
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turns = created["session_data"]["turns"]
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assert created["revision"] == 2
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assert created["session_data"]["status"] == "idle"
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assert len(turns) == 1
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assert turns[0]["status"] == "completed"
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assert turns[0]["user_message"] is None
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assert turns[0]["assistant_message"]["text"] == "Hello from the workflow tester."
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assert turns[0]["checkpoint_after_turn"]["current_node_id"] == "start"
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assert created["checkpoint"]["current_node_id"] == "start"
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assert created["state"] == "running"
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assert "Start" in (created["gathered_context"] or {}).get("nodes_visited", [])
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@pytest.mark.asyncio
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async def test_text_chat_message_executes_assistant_turn(
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db_session,
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async_session,
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test_client_factory,
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):
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workflow_definition = {
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"nodes": [
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{
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"id": "start",
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"type": "startCall",
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"position": {"x": 0, "y": 0},
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"data": {
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"name": "Start",
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"prompt": "You are a helpful assistant.",
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"is_start": True,
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"allow_interrupt": False,
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"add_global_prompt": False,
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"greeting_type": "text",
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"greeting": "Welcome to the workflow tester.",
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},
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},
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{
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"id": "end",
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"type": "endCall",
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"position": {"x": 0, "y": 200},
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"data": {
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"name": "End",
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"prompt": "Wrap up the conversation.",
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"is_end": True,
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"allow_interrupt": False,
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"add_global_prompt": False,
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},
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},
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],
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"edges": [
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{
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"id": "start-end",
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"source": "start",
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"target": "end",
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"data": {"label": "End Call", "condition": "When the task is done."},
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}
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],
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}
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user, workflow = await _create_user_and_workflow(
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db_session,
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async_session,
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workflow_definition=workflow_definition,
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suffix="basic",
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)
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llm_responses = [
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MockLLMService(mock_steps=[], chunk_delay=0.001),
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MockLLMService(
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mock_steps=[MockLLMService.create_text_chunks("Hello from the workflow tester.")],
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chunk_delay=0.001,
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),
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]
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async with test_client_factory(user) as client:
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with patch(
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"api.services.workflow.text_chat_runner.create_llm_service",
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side_effect=llm_responses,
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), patch(
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"api.services.workflow.text_chat_runner.db_client.has_active_recordings",
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new=AsyncMock(return_value=False),
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):
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create_response = await client.post(
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f"/api/v1/workflow/{workflow.id}/text-chat/sessions",
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json={},
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)
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assert create_response.status_code == 200
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created = create_response.json()
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message_response = await client.post(
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f"/api/v1/workflow/{workflow.id}/text-chat/sessions/{created['workflow_run_id']}/messages",
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json={
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"text": "Hi there",
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"expected_revision": created["revision"],
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},
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)
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assert message_response.status_code == 200
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payload = message_response.json()
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turns = payload["session_data"]["turns"]
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assert payload["revision"] == 4
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assert payload["session_data"]["status"] == "idle"
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assert len(turns) == 2
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assert turns[0]["user_message"] is None
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assert turns[0]["assistant_message"]["text"] == "Welcome to the workflow tester."
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assert turns[1]["status"] == "completed"
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assert turns[1]["user_message"]["text"] == "Hi there"
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assert turns[1]["assistant_message"]["text"] == "Hello from the workflow tester."
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assert turns[1]["checkpoint_after_turn"]["current_node_id"] == "start"
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assert payload["checkpoint"]["current_node_id"] == "start"
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assert payload["state"] == "running"
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assert "Start" in (payload["gathered_context"] or {}).get("nodes_visited", [])
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@pytest.mark.asyncio
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async def test_text_chat_executes_deferred_tool_calls_after_text_response(
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db_session,
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async_session,
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test_client_factory,
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):
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workflow_definition = {
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"nodes": [
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{
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"id": "start",
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"type": "startCall",
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"position": {"x": 0, "y": 0},
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"data": {
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"name": "Start",
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"prompt": "You are at the start node.",
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"is_start": True,
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"allow_interrupt": False,
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"add_global_prompt": False,
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"greeting_type": "text",
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"greeting": "Welcome to the workflow tester.",
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},
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},
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{
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"id": "agent1",
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"type": "agentNode",
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"position": {"x": 0, "y": 200},
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"data": {
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"name": "Agent One",
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"prompt": "You are in agent one.",
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"allow_interrupt": False,
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"add_global_prompt": False,
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},
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},
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],
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"edges": [
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{
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"id": "start-agent1",
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"source": "start",
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"target": "agent1",
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"data": {
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"label": "Go To Agent One",
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"condition": "Move to agent one.",
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},
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}
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],
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}
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user, workflow = await _create_user_and_workflow(
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db_session,
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async_session,
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workflow_definition=workflow_definition,
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suffix="mixed-tool-turn",
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)
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llm_responses = [
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MockLLMService(mock_steps=[], chunk_delay=0.001),
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MockLLMService(
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mock_steps=[
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MockLLMService.create_mixed_chunks(
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"Let me transfer you.",
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"go_to_agent_one",
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{},
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tool_call_id="call_agent_one",
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),
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MockLLMService.create_text_chunks("Agent one here."),
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],
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chunk_delay=0.001,
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),
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]
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async with test_client_factory(user) as client:
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with patch(
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"api.services.workflow.text_chat_runner.create_llm_service",
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side_effect=llm_responses,
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), patch(
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"api.services.workflow.text_chat_runner.db_client.has_active_recordings",
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new=AsyncMock(return_value=False),
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):
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create_response = await client.post(
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f"/api/v1/workflow/{workflow.id}/text-chat/sessions",
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json={},
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)
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assert create_response.status_code == 200
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session = create_response.json()
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message_response = await client.post(
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f"/api/v1/workflow/{workflow.id}/text-chat/sessions/{session['workflow_run_id']}/messages",
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json={
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"text": "Please transfer me",
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"expected_revision": session["revision"],
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},
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)
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assert message_response.status_code == 200
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payload = message_response.json()
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assistant_text = payload["session_data"]["turns"][1]["assistant_message"]["text"]
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assert "Let me transfer you." in assistant_text
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assert "Agent one here." in assistant_text
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assert payload["checkpoint"]["current_node_id"] == "agent1"
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assert any(
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event["type"] == "tool_call_started"
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and event["payload"]["function_name"] == "go_to_agent_one"
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for event in payload["session_data"]["turns"][1]["events"]
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)
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@pytest.mark.asyncio
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async def test_text_chat_chains_multiple_follow_up_completions_in_one_turn(
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db_session,
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async_session,
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test_client_factory,
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):
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workflow_definition = {
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"nodes": [
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{
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"id": "start",
|
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"type": "startCall",
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"position": {"x": 0, "y": 0},
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"data": {
|
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"name": "Start",
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"prompt": "You are at the start node.",
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"is_start": True,
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"allow_interrupt": False,
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"add_global_prompt": False,
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"greeting_type": "text",
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"greeting": "Welcome to the workflow tester.",
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},
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},
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{
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"id": "agent1",
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"type": "agentNode",
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"position": {"x": 0, "y": 200},
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"data": {
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"name": "Agent One",
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"prompt": "You are in agent one.",
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"allow_interrupt": False,
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"add_global_prompt": False,
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},
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},
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{
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"id": "agent2",
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"type": "agentNode",
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"position": {"x": 0, "y": 400},
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"data": {
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"name": "Agent Two",
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"prompt": "You are in agent two.",
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"allow_interrupt": False,
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"add_global_prompt": False,
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},
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},
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],
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"edges": [
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{
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"id": "start-agent1",
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"source": "start",
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"target": "agent1",
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"data": {
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"label": "Go To Agent One",
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"condition": "Move to agent one.",
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},
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},
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{
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"id": "agent1-agent2",
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"source": "agent1",
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"target": "agent2",
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"data": {
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"label": "Go To Agent Two",
|
||||
"condition": "Move to agent two.",
|
||||
},
|
||||
},
|
||||
],
|
||||
}
|
||||
|
||||
user, workflow = await _create_user_and_workflow(
|
||||
db_session,
|
||||
async_session,
|
||||
workflow_definition=workflow_definition,
|
||||
suffix="multi-hop-turn",
|
||||
)
|
||||
|
||||
llm_responses = [
|
||||
MockLLMService(mock_steps=[], chunk_delay=0.001),
|
||||
MockLLMService(
|
||||
mock_steps=[
|
||||
MockLLMService.create_mixed_chunks(
|
||||
"Moving to agent one.",
|
||||
"go_to_agent_one",
|
||||
{},
|
||||
tool_call_id="call_agent_one",
|
||||
),
|
||||
MockLLMService.create_mixed_chunks(
|
||||
"Moving to agent two.",
|
||||
"go_to_agent_two",
|
||||
{},
|
||||
tool_call_id="call_agent_two",
|
||||
),
|
||||
MockLLMService.create_text_chunks("Agent two here."),
|
||||
],
|
||||
chunk_delay=0.001,
|
||||
),
|
||||
]
|
||||
|
||||
async with test_client_factory(user) as client:
|
||||
with patch(
|
||||
"api.services.workflow.text_chat_runner.create_llm_service",
|
||||
side_effect=llm_responses,
|
||||
), patch(
|
||||
"api.services.workflow.text_chat_runner.db_client.has_active_recordings",
|
||||
new=AsyncMock(return_value=False),
|
||||
):
|
||||
create_response = await client.post(
|
||||
f"/api/v1/workflow/{workflow.id}/text-chat/sessions",
|
||||
json={},
|
||||
)
|
||||
assert create_response.status_code == 200
|
||||
session = create_response.json()
|
||||
|
||||
message_response = await client.post(
|
||||
f"/api/v1/workflow/{workflow.id}/text-chat/sessions/{session['workflow_run_id']}/messages",
|
||||
json={
|
||||
"text": "Please route me through the flow",
|
||||
"expected_revision": session["revision"],
|
||||
},
|
||||
)
|
||||
assert message_response.status_code == 200
|
||||
|
||||
payload = message_response.json()
|
||||
assistant_text = payload["session_data"]["turns"][1]["assistant_message"]["text"]
|
||||
|
||||
assert "Moving to agent one." in assistant_text
|
||||
assert "Moving to agent two." in assistant_text
|
||||
assert "Agent two here." in assistant_text
|
||||
assert payload["checkpoint"]["current_node_id"] == "agent2"
|
||||
assert sum(
|
||||
1
|
||||
for event in payload["session_data"]["turns"][1]["events"]
|
||||
if event["type"] == "tool_call_started"
|
||||
) == 2
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_text_chat_greeting_only_plays_on_fresh_node_entry(
|
||||
db_session,
|
||||
async_session,
|
||||
test_client_factory,
|
||||
):
|
||||
workflow_definition = {
|
||||
"nodes": [
|
||||
{
|
||||
"id": "start",
|
||||
"type": "startCall",
|
||||
"position": {"x": 0, "y": 0},
|
||||
"data": {
|
||||
"name": "Start",
|
||||
"prompt": "You are a helpful assistant.",
|
||||
"is_start": True,
|
||||
"allow_interrupt": False,
|
||||
"add_global_prompt": False,
|
||||
"greeting_type": "text",
|
||||
"greeting": "Welcome to the workflow tester.",
|
||||
},
|
||||
},
|
||||
{
|
||||
"id": "end",
|
||||
"type": "endCall",
|
||||
"position": {"x": 0, "y": 200},
|
||||
"data": {
|
||||
"name": "End",
|
||||
"prompt": "Wrap up the conversation.",
|
||||
"is_end": True,
|
||||
"allow_interrupt": False,
|
||||
"add_global_prompt": False,
|
||||
},
|
||||
},
|
||||
],
|
||||
"edges": [
|
||||
{
|
||||
"id": "start-end",
|
||||
"source": "start",
|
||||
"target": "end",
|
||||
"data": {"label": "End Call", "condition": "When the task is done."},
|
||||
}
|
||||
],
|
||||
}
|
||||
|
||||
user, workflow = await _create_user_and_workflow(
|
||||
db_session,
|
||||
async_session,
|
||||
workflow_definition=workflow_definition,
|
||||
suffix="greeting-once",
|
||||
)
|
||||
|
||||
llm_responses = [
|
||||
MockLLMService(mock_steps=[], chunk_delay=0.001),
|
||||
MockLLMService(
|
||||
mock_steps=[MockLLMService.create_text_chunks("First answer.")],
|
||||
chunk_delay=0.001,
|
||||
),
|
||||
MockLLMService(
|
||||
mock_steps=[MockLLMService.create_text_chunks("Second answer.")],
|
||||
chunk_delay=0.001,
|
||||
),
|
||||
]
|
||||
|
||||
async with test_client_factory(user) as client:
|
||||
with patch(
|
||||
"api.services.workflow.text_chat_runner.create_llm_service",
|
||||
side_effect=llm_responses,
|
||||
), patch(
|
||||
"api.services.workflow.text_chat_runner.db_client.has_active_recordings",
|
||||
new=AsyncMock(return_value=False),
|
||||
):
|
||||
create_response = await client.post(
|
||||
f"/api/v1/workflow/{workflow.id}/text-chat/sessions",
|
||||
json={},
|
||||
)
|
||||
assert create_response.status_code == 200
|
||||
session = create_response.json()
|
||||
opening_text = session["session_data"]["turns"][0]["assistant_message"]["text"]
|
||||
|
||||
first_message = await client.post(
|
||||
f"/api/v1/workflow/{workflow.id}/text-chat/sessions/{session['workflow_run_id']}/messages",
|
||||
json={
|
||||
"text": "First turn",
|
||||
"expected_revision": session["revision"],
|
||||
},
|
||||
)
|
||||
assert first_message.status_code == 200
|
||||
first_payload = first_message.json()
|
||||
|
||||
second_message = await client.post(
|
||||
f"/api/v1/workflow/{workflow.id}/text-chat/sessions/{session['workflow_run_id']}/messages",
|
||||
json={
|
||||
"text": "Second turn",
|
||||
"expected_revision": first_payload["revision"],
|
||||
},
|
||||
)
|
||||
assert second_message.status_code == 200
|
||||
|
||||
first_text = first_payload["session_data"]["turns"][1]["assistant_message"]["text"]
|
||||
second_text = second_message.json()["session_data"]["turns"][2]["assistant_message"][
|
||||
"text"
|
||||
]
|
||||
|
||||
assert opening_text == "Welcome to the workflow tester."
|
||||
assert "Welcome to the workflow tester." not in first_text
|
||||
assert "First answer." in first_text
|
||||
assert "Welcome to the workflow tester." not in second_text
|
||||
assert "Second answer." in second_text
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_text_chat_rewind_reuses_checkpoint_snapshot(
|
||||
db_session,
|
||||
async_session,
|
||||
test_client_factory,
|
||||
):
|
||||
workflow_definition = {
|
||||
"nodes": [
|
||||
{
|
||||
"id": "start",
|
||||
"type": "startCall",
|
||||
"position": {"x": 0, "y": 0},
|
||||
"data": {
|
||||
"name": "Start",
|
||||
"prompt": "You are at the start node.",
|
||||
"is_start": True,
|
||||
"allow_interrupt": False,
|
||||
"add_global_prompt": False,
|
||||
"greeting_type": "text",
|
||||
"greeting": "Welcome to the rewind test.",
|
||||
},
|
||||
},
|
||||
{
|
||||
"id": "agent1",
|
||||
"type": "agentNode",
|
||||
"position": {"x": 0, "y": 200},
|
||||
"data": {
|
||||
"name": "Agent One",
|
||||
"prompt": "You are in agent one.",
|
||||
"allow_interrupt": False,
|
||||
"add_global_prompt": False,
|
||||
},
|
||||
},
|
||||
{
|
||||
"id": "agent2",
|
||||
"type": "agentNode",
|
||||
"position": {"x": 0, "y": 400},
|
||||
"data": {
|
||||
"name": "Agent Two",
|
||||
"prompt": "You are in agent two.",
|
||||
"allow_interrupt": False,
|
||||
"add_global_prompt": False,
|
||||
},
|
||||
},
|
||||
{
|
||||
"id": "end",
|
||||
"type": "endCall",
|
||||
"position": {"x": 0, "y": 600},
|
||||
"data": {
|
||||
"name": "End",
|
||||
"prompt": "You are at the end node.",
|
||||
"is_end": True,
|
||||
"allow_interrupt": False,
|
||||
"add_global_prompt": False,
|
||||
},
|
||||
},
|
||||
],
|
||||
"edges": [
|
||||
{
|
||||
"id": "start-agent1",
|
||||
"source": "start",
|
||||
"target": "agent1",
|
||||
"data": {
|
||||
"label": "Go To Agent One",
|
||||
"condition": "Move to agent one.",
|
||||
},
|
||||
},
|
||||
{
|
||||
"id": "agent1-agent2",
|
||||
"source": "agent1",
|
||||
"target": "agent2",
|
||||
"data": {
|
||||
"label": "Go To Agent Two",
|
||||
"condition": "Move to agent two.",
|
||||
},
|
||||
},
|
||||
{
|
||||
"id": "agent2-end",
|
||||
"source": "agent2",
|
||||
"target": "end",
|
||||
"data": {"label": "Finish", "condition": "End the flow."},
|
||||
},
|
||||
],
|
||||
}
|
||||
|
||||
user, workflow = await _create_user_and_workflow(
|
||||
db_session,
|
||||
async_session,
|
||||
workflow_definition=workflow_definition,
|
||||
suffix="rewind",
|
||||
)
|
||||
|
||||
llm_responses = [
|
||||
MockLLMService(mock_steps=[], chunk_delay=0.001),
|
||||
MockLLMService(
|
||||
mock_steps=[
|
||||
MockLLMService.create_function_call_chunks(
|
||||
"go_to_agent_one",
|
||||
{},
|
||||
tool_call_id="call_agent_one",
|
||||
),
|
||||
MockLLMService.create_text_chunks("Agent one here."),
|
||||
],
|
||||
chunk_delay=0.001,
|
||||
),
|
||||
MockLLMService(
|
||||
mock_steps=[
|
||||
MockLLMService.create_function_call_chunks(
|
||||
"go_to_agent_two",
|
||||
{},
|
||||
tool_call_id="call_agent_two",
|
||||
),
|
||||
MockLLMService.create_text_chunks("Agent two here."),
|
||||
],
|
||||
chunk_delay=0.001,
|
||||
),
|
||||
MockLLMService(
|
||||
mock_steps=[MockLLMService.create_text_chunks("Back in agent one.")],
|
||||
chunk_delay=0.001,
|
||||
),
|
||||
]
|
||||
|
||||
async with test_client_factory(user) as client:
|
||||
with patch(
|
||||
"api.services.workflow.text_chat_runner.create_llm_service",
|
||||
side_effect=llm_responses,
|
||||
), patch(
|
||||
"api.services.workflow.text_chat_runner.db_client.has_active_recordings",
|
||||
new=AsyncMock(return_value=False),
|
||||
):
|
||||
create_response = await client.post(
|
||||
f"/api/v1/workflow/{workflow.id}/text-chat/sessions",
|
||||
json={},
|
||||
)
|
||||
assert create_response.status_code == 200
|
||||
session = create_response.json()
|
||||
|
||||
first_message = await client.post(
|
||||
f"/api/v1/workflow/{workflow.id}/text-chat/sessions/{session['workflow_run_id']}/messages",
|
||||
json={
|
||||
"text": "First turn",
|
||||
"expected_revision": session["revision"],
|
||||
},
|
||||
)
|
||||
assert first_message.status_code == 200
|
||||
first_payload = first_message.json()
|
||||
first_turn_id = first_payload["session_data"]["turns"][1]["id"]
|
||||
assert first_payload["checkpoint"]["current_node_id"] == "agent1"
|
||||
|
||||
second_message = await client.post(
|
||||
f"/api/v1/workflow/{workflow.id}/text-chat/sessions/{session['workflow_run_id']}/messages",
|
||||
json={
|
||||
"text": "Second turn",
|
||||
"expected_revision": first_payload["revision"],
|
||||
},
|
||||
)
|
||||
assert second_message.status_code == 200
|
||||
second_payload = second_message.json()
|
||||
assert second_payload["checkpoint"]["current_node_id"] == "agent2"
|
||||
|
||||
rewind_response = await client.post(
|
||||
f"/api/v1/workflow/{workflow.id}/text-chat/sessions/{session['workflow_run_id']}/rewind",
|
||||
json={
|
||||
"cursor_turn_id": first_turn_id,
|
||||
"expected_revision": second_payload["revision"],
|
||||
},
|
||||
)
|
||||
assert rewind_response.status_code == 200
|
||||
rewound = rewind_response.json()
|
||||
assert rewound["session_data"]["cursor_turn_id"] == first_turn_id
|
||||
|
||||
third_message = await client.post(
|
||||
f"/api/v1/workflow/{workflow.id}/text-chat/sessions/{session['workflow_run_id']}/messages",
|
||||
json={
|
||||
"text": "Third turn after rewind",
|
||||
"expected_revision": rewound["revision"],
|
||||
},
|
||||
)
|
||||
assert third_message.status_code == 200
|
||||
|
||||
payload = third_message.json()
|
||||
assert payload["checkpoint"]["current_node_id"] == "agent1"
|
||||
assert payload["session_data"]["discarded_future"]
|
||||
assert len(payload["session_data"]["turns"]) == 3
|
||||
assert payload["session_data"]["turns"][1]["id"] == first_turn_id
|
||||
assert (
|
||||
payload["session_data"]["turns"][2]["assistant_message"]["text"]
|
||||
== "Back in agent one."
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_text_chat_session_is_not_accessible_from_another_org(
|
||||
db_session,
|
||||
async_session,
|
||||
test_client_factory,
|
||||
):
|
||||
workflow_definition = {
|
||||
"nodes": [
|
||||
{
|
||||
"id": "start",
|
||||
"type": "startCall",
|
||||
"position": {"x": 0, "y": 0},
|
||||
"data": {
|
||||
"name": "Start",
|
||||
"prompt": "You are a helpful assistant.",
|
||||
"is_start": True,
|
||||
"allow_interrupt": False,
|
||||
"add_global_prompt": False,
|
||||
},
|
||||
},
|
||||
{
|
||||
"id": "end",
|
||||
"type": "endCall",
|
||||
"position": {"x": 0, "y": 200},
|
||||
"data": {
|
||||
"name": "End",
|
||||
"prompt": "Wrap up the conversation.",
|
||||
"is_end": True,
|
||||
"allow_interrupt": False,
|
||||
"add_global_prompt": False,
|
||||
},
|
||||
},
|
||||
],
|
||||
"edges": [
|
||||
{
|
||||
"id": "start-end",
|
||||
"source": "start",
|
||||
"target": "end",
|
||||
"data": {"label": "End Call", "condition": "When the task is done."},
|
||||
}
|
||||
],
|
||||
}
|
||||
|
||||
owner_user, workflow = await _create_user_and_workflow(
|
||||
db_session,
|
||||
async_session,
|
||||
workflow_definition=workflow_definition,
|
||||
suffix="owner",
|
||||
)
|
||||
other_user, _ = await _create_user_and_workflow(
|
||||
db_session,
|
||||
async_session,
|
||||
workflow_definition=workflow_definition,
|
||||
suffix="other",
|
||||
)
|
||||
|
||||
async with test_client_factory(owner_user) as owner_client:
|
||||
llm = MockLLMService(
|
||||
mock_steps=[MockLLMService.create_text_chunks("Hello from the workflow tester.")],
|
||||
chunk_delay=0.001,
|
||||
)
|
||||
with patch(
|
||||
"api.services.workflow.text_chat_runner.create_llm_service",
|
||||
return_value=llm,
|
||||
), patch(
|
||||
"api.services.workflow.text_chat_runner.db_client.has_active_recordings",
|
||||
new=AsyncMock(return_value=False),
|
||||
):
|
||||
create_response = await owner_client.post(
|
||||
f"/api/v1/workflow/{workflow.id}/text-chat/sessions",
|
||||
json={},
|
||||
)
|
||||
assert create_response.status_code == 200
|
||||
created = create_response.json()
|
||||
|
||||
async with test_client_factory(other_user) as other_client:
|
||||
get_response = await other_client.get(
|
||||
f"/api/v1/workflow/{workflow.id}/text-chat/sessions/{created['workflow_run_id']}"
|
||||
)
|
||||
assert get_response.status_code == 404
|
||||
Loading…
Add table
Add a link
Reference in a new issue