Files
api/tests/test_deep_agent.py

289 lines
9.1 KiB
Python

"""Unit tests for single-agent deep_agent flows with mocked tool results."""
from __future__ import annotations
from datetime import date, timedelta
from types import SimpleNamespace
from unittest.mock import patch
import pytest
from langchain_core.messages import AIMessage, ToolMessage
from app.core.deep_agent import (
_infer_floating_domain,
_normalize_tagged_list_lines,
run_floating,
run_floating_stream,
run_home,
)
class _FakeTool:
name = "list_tasks"
async def ainvoke(self, args):
return {"rows": [{"id": "task-1", "title": "Mock Task"}], "echo": args}
class _FakeLLM:
def __init__(self) -> None:
self.agent_calls = 0
def bind_tools(self, _tools):
return self
async def ainvoke(self, messages):
system_prompt = str(getattr(messages[0], "content", "")) if messages else ""
if "strict domain classifier" in system_prompt:
return AIMessage(content='{"type":"timeline","id":"tl-1","section":null}')
self.agent_calls += 1
if self.agent_calls == 1:
return AIMessage(
content="",
tool_calls=[
{
"id": "call-1",
"name": "list_tasks",
"args": {"project_id": "proj-1"},
}
],
)
tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
assert tool_messages, "Expected at least one tool message"
return AIMessage(content=f"Final answer from mocked tool: {tool_messages[-1].content}")
async def astream(self, _messages):
yield SimpleNamespace(content="stream-")
yield SimpleNamespace(content="ok")
@pytest.mark.asyncio
async def test_run_home_uses_mocked_tool_result():
fake_llm = _FakeLLM()
with patch("app.core.deep_agent.get_llm", return_value=fake_llm), patch(
"app.core.deep_agent._all_tools", return_value=[_FakeTool()]
):
out = await run_home("user-1", "list my tasks", {})
assert "Final answer from mocked tool" in out
assert "Mock Task" in out
@pytest.mark.asyncio
async def test_run_floating_stream_emits_domain_then_tokens_with_mocked_tool_result():
fake_llm = _FakeLLM()
with patch("app.core.deep_agent.get_llm", return_value=fake_llm), patch(
"app.core.deep_agent._all_tools", return_value=[_FakeTool()]
):
events = []
async for event in run_floating_stream(
"user-1",
"show me timeline updates",
{"scope": {"type": "timeline", "id": "tl-1"}},
):
events.append(event)
assert events[0] == (
"floating_domain",
{"type": "timeline", "id": "tl-1", "section": None},
)
assert ("token", "stream-") in events
assert ("token", "ok") in events
@pytest.mark.asyncio
async def test_infer_floating_domain_prefers_message_intent_over_scope_type():
class _ClassifierOnlyLLM:
async def ainvoke(self, _messages):
return AIMessage(
content='{"type":"project","id":"213213-312321-312312-421321","section":"task"}'
)
with patch("app.core.deep_agent.get_llm", return_value=_ClassifierOnlyLLM()):
domain = await _infer_floating_domain(
"Quali sono i miei task per il progetto X",
{
"scope": {"type": "timeline"},
"resolved_project_id": "213213-312321-312312-421321",
},
)
assert domain == {
"type": "project",
"id": "213213-312321-312312-421321",
"section": "task",
}
def test_normalize_tagged_list_lines_rewrites_mixed_task_lines_to_tag_only_lines():
raw = (
"Certo!\n\n"
"1. **Task A** — priorita high <task>[task-1]</task>\n"
"2. **Task B** — priorita medium <task>[task-2]</task>\n"
)
out = _normalize_tagged_list_lines(raw, "quali sono le prossime attivita?")
assert "<task>[task-1]</task>" in out
assert "<task>[task-2]</task>" in out
assert "Task A" not in out
assert "Task B" not in out
def test_normalize_tagged_list_lines_filters_upcoming_timeline_query_to_current_month_future_only():
today = date.today()
tomorrow = today + timedelta(days=1)
yesterday = today - timedelta(days=1)
next_month = (today.replace(day=28) + timedelta(days=5)).replace(day=1)
raw = "\n".join(
[
f"- Milestone old — {yesterday.strftime('%d/%m/%Y')} <timeline>[tl-old]</timeline>",
f"- Milestone next — {tomorrow.strftime('%d/%m/%Y')} <timeline>[tl-next]</timeline>",
f"- Milestone future — {next_month.strftime('%d/%m/%Y')} <timeline>[tl-future]</timeline>",
]
)
out = _normalize_tagged_list_lines(raw, "invece i miei eventi prossimi?")
assert "<timeline>[tl-next]</timeline>" in out
assert "<timeline>[tl-old]</timeline>" not in out
assert "<timeline>[tl-future]</timeline>" not in out
@pytest.mark.asyncio
async def test_run_floating_strips_xml_like_tags_from_final_text():
fake_llm = _FakeLLM()
async def _fake_run_single_agent(**_kwargs):
return (
"Hai 1 task:\\n"
"Mail barra in prod <task>[180faff3-507d-4d88-aba8-66f204eb59ef]</task>"
)
with patch("app.core.deep_agent.get_llm", return_value=fake_llm), patch(
"app.core.deep_agent._run_single_agent", side_effect=_fake_run_single_agent
):
text, _domain = await run_floating(
"user-1",
"quali task ho?",
{"scope": {"type": "task"}},
)
assert "<task>" not in text
assert "</task>" not in text
assert "[180faff3-507d-4d88-aba8-66f204eb59ef]" not in text
@pytest.mark.asyncio
async def test_run_floating_stream_strips_xml_like_tags_from_streamed_text():
fake_llm = _FakeLLM()
async def _fake_stream(**_kwargs):
yield "token", "Hai 1 task:\\n"
yield "token", "Mail barra in prod <task>[180faff3-507d-4d88-aba8-66f204eb59ef]</task>"
with patch("app.core.deep_agent.get_llm", return_value=fake_llm), patch(
"app.core.deep_agent._run_single_agent_stream", side_effect=_fake_stream
):
events = []
async for event in run_floating_stream(
"user-1",
"quali task ho?",
{"scope": {"type": "task"}},
):
events.append(event)
token_events = [str(data) for event_type, data in events if event_type == "token"]
combined = "".join(token_events)
assert "<task>" not in combined
assert "</task>" not in combined
assert "[180faff3-507d-4d88-aba8-66f204eb59ef]" not in combined
@pytest.mark.asyncio
async def test_run_floating_stream_falls_back_to_final_response_content_when_astream_is_empty():
class _NoChunkLLM:
def __init__(self) -> None:
self.calls = 0
def bind_tools(self, _tools):
return self
async def ainvoke(self, _messages):
self.calls += 1
if self.calls == 1:
return AIMessage(
content="",
tool_calls=[
{
"id": "call-1",
"name": "list_tasks",
"args": {},
}
],
)
return AIMessage(content="No notes found.")
async def astream(self, _messages):
if False:
yield None
with patch("app.core.deep_agent.get_llm", return_value=_NoChunkLLM()), patch(
"app.core.deep_agent._all_tools", return_value=[_FakeTool()]
):
events = []
async for event in run_floating_stream(
"user-1",
"quali sono le note?",
{"scope": {"type": "note"}},
):
events.append(event)
assert events[0][0] == "floating_domain"
assert ("token", "No notes found.") in events
@pytest.mark.asyncio
async def test_run_floating_returns_fallback_when_sanitization_would_empty_text():
fake_llm = _FakeLLM()
async def _fake_run_single_agent(**_kwargs):
return "<task>[180faff3-507d-4d88-aba8-66f204eb59ef]</task>"
with patch("app.core.deep_agent.get_llm", return_value=fake_llm), patch(
"app.core.deep_agent._run_single_agent", side_effect=_fake_run_single_agent
):
text, _domain = await run_floating(
"user-1",
"quali task ho?",
{"scope": {"type": "task"}},
)
assert text == "No results found."
@pytest.mark.asyncio
async def test_run_floating_stream_returns_fallback_when_sanitization_would_empty_text():
fake_llm = _FakeLLM()
async def _fake_stream(**_kwargs):
yield "token", "<task>[180faff3-507d-4d88-aba8-66f204eb59ef]</task>"
with patch("app.core.deep_agent.get_llm", return_value=fake_llm), patch(
"app.core.deep_agent._run_single_agent_stream", side_effect=_fake_stream
):
events = []
async for event in run_floating_stream(
"user-1",
"quali task ho?",
{"scope": {"type": "task"}},
):
events.append(event)
assert ("token", "No results found.") in events