Files
hyungi_document_server/tests/api/test_search_ask_react_endpoint.py
T
hyungi 51c3f6df10 feat(search): /ask/react endpoint with Qwen native tool calling ReAct loop
PR-DocSrv-Ask-ToolCalling-ReAct-1 — Qwen3.6-27B-8bit 의 native tool calling
으로 ReAct loop 도입. 기존 /api/search/ask 무수정. 트랙 B (frontend /ask SSE)
와 파일 단위 충돌 0 (search.py 의 ask() 함수 line diff = 0, 순수 추가).

핵심 invariant:
- 별 endpoint /api/search/ask/react (qwen-macbook only, implicit opt-in)
- MacBook unavailable 시 HTTP 503 + error_reason=macbook_unavailable.
  Gemma 자동 fallback X (정정 4 의 연장)

G0 (구현 전 hard gate, plan b-velvety-hare.md):
- G0-1 fixture (tests/fixtures/qwen_tool_call_response.json): 실제 mlx-vlm
  응답 박제. shape = OpenAI 표준 호환 (choices[0].message.tool_calls +
  function.arguments JSON string). generate_with_tools() 가 본 shape 기준 구현.
- G0-2 counter semantics: max_tool_rounds=2 + max_llm_calls=3 + search_exec_max=2.
  마지막 LLM 호출은 tool_choice="none" + system instruction 으로 final 강제.
- G0-3 trace exposure: default response 의 debug_trace=null. debug=true 시만
  채움. server log 에는 항상 round 기록.

backends.py (193 → 261줄):
- QwenMacBookBackend.generate_with_tools(messages, tools, tool_choice)
  신규 method. 기존 generate() 무수정. BackendUnavailable 처리 동일.

react_loop.py 신규 (275줄):
- agentic_ask_loop(session, query, *, backend, max_tool_rounds, debug)
- tool round 안에서 run_search 호출, results dedup by id, final round 강제,
  partial=True 조건 (final content 빈 경우)

search.py (+82줄):
- POST /api/search/ask/react + AskReactRequest/Response schema
- BackendUnavailable → JSONResponse(503, error_reason=macbook_unavailable)

config.yaml + config.py:
- search.ask.react: { enabled, max_tool_rounds=2, search_tool_limit=5,
  search_tool_mode=hybrid }

tests (566줄, 18 신규 + 23 회귀 모두 PASS):
- test_react_loop.py 13건: G0-1 fixture shape / G0-2 counter cap / G0-3 trace
  exposure / BackendUnavailable propagation / sources dedup
- test_search_ask_react_endpoint.py 5건: 503 + run_search 호출 0 / 정상 200 /
  debug=true trace 노출 / max rounds partial
- 회귀 (test_ask_eval_auth 9 + test_search_ask_macbook_503 5 +
  test_backend_dispatcher 9) 모두 PASS

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-22 13:43:47 +00:00

219 lines
7.3 KiB
Python

"""PR-DocSrv-Ask-ToolCalling-ReAct-1: /api/search/ask/react endpoint integration.
검증 항목 (G0-3 trace exposure + 정정 4 invariant):
- backend unavailable → HTTP 503 + error_reason=macbook_unavailable
+ ★ `run_search` mock 호출 횟수 == 0 (search 단계 진입 자체 차단)
- 정상 응답 → 200 + final_answer + sources + debug_trace=null (default)
- debug=true → debug_trace 채워짐
- max rounds 도달 → iterations=2 + partial=false (final content 정상)
endpoint 함수 (`api.search.ask_react`) 를 직접 호출하는 lightweight 패턴.
TestClient 없이 FastAPI deps 를 MagicMock 으로 우회. (priority_gate / backend_dispatcher
test 와 동일 service-layer 패턴.)
"""
from __future__ import annotations
import asyncio
import json
import os
import sys
from unittest.mock import AsyncMock, MagicMock
import pytest
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "..", "app"))
# ── helpers ────────────────────────────────────────────────────────────────
def _msg_with_tool_call(q: str, tc_id: str = "tc-1") -> dict:
return {
"role": "assistant",
"content": None,
"tool_calls": [
{
"id": tc_id,
"type": "function",
"function": {
"name": "search",
"arguments": json.dumps({"q": q}, ensure_ascii=False),
},
}
],
}
def _msg_with_content(text: str) -> dict:
return {"role": "assistant", "content": text, "tool_calls": None}
def _fake_chunk(chunk_id: int, doc_id: int = 100):
m = MagicMock()
m.id = chunk_id
m.chunk_id = chunk_id
m.doc_id = doc_id
m.title = f"doc {doc_id}"
m.score = 0.9
m.snippet = f"snippet {chunk_id}"
m.text = None
return m
def _fake_pr(chunks: list):
pr = MagicMock()
pr.results = chunks
return pr
@pytest.fixture
def patched_backend_and_search(monkeypatch):
"""get_backend + run_search 둘 다 mock. backend 의 generate_with_tools 는
각 테스트가 side_effect 설정.
Returns: (backend_mock, run_search_mock, set_backend_unavailable_fn).
"""
from services.llm.backends import BackendUnavailable, QwenMacBookBackend
from services.llm import backends as backends_mod
from services.search import react_loop
backend = MagicMock(spec=QwenMacBookBackend)
backend.name = "qwen-macbook"
backend.generate_with_tools = AsyncMock()
def _fake_get_backend(name):
# endpoint 가 qwen-macbook 만 호출하므로 단일 backend 반환
return backend
monkeypatch.setattr(backends_mod, "get_backend", _fake_get_backend)
# search.py 의 ask_react 안에서 `from services.llm.backends import ... get_backend`
# 로 import 하므로 module-level patch 만으로 충분 (지연 import 라 매번 fresh).
run_search_mock = AsyncMock(return_value=_fake_pr([_fake_chunk(1)]))
monkeypatch.setattr(react_loop, "run_search", run_search_mock)
def _make_unavailable():
backend.generate_with_tools.side_effect = BackendUnavailable(
"qwen-macbook", "ConnectError"
)
return backend, run_search_mock, _make_unavailable
def _call_endpoint(payload):
"""ask_react 를 직접 호출. user/session 은 MagicMock 으로 우회."""
from api.search import ask_react
user = MagicMock()
session = MagicMock()
return asyncio.run(ask_react(payload, user=user, session=session))
# ── ★ 정정 4 invariant: backend unavailable → 503 + run_search 호출 0 ──────
def test_qwen_unavailable_returns_503(patched_backend_and_search):
"""backend BackendUnavailable → HTTP 503 + error_reason=macbook_unavailable."""
from api.search import AskReactRequest
backend, run_search_mock, make_unavailable = patched_backend_and_search
make_unavailable()
response = _call_endpoint(AskReactRequest(query="Q"))
# JSONResponse instance
assert response.status_code == 503
body = json.loads(response.body)
assert body["error_reason"] == "macbook_unavailable"
assert body["backend_used"] is None
assert body["backend_requested"] == "qwen-macbook"
# ★ run_search 호출 0 (search 진입 자체 차단)
assert run_search_mock.call_count == 0
# ── 정상 200 + G0-3 default debug_trace=null ──────────────────────────────
def test_successful_response_default_no_debug_trace(patched_backend_and_search):
"""debug 미지정 (default false) → 200 + debug_trace == null."""
from api.search import AskReactRequest, AskReactResponse
backend, run_search_mock, _ = patched_backend_and_search
backend.generate_with_tools.side_effect = [
_msg_with_tool_call("q1"),
_msg_with_content("최종 답입니다"),
]
response = _call_endpoint(AskReactRequest(query="Q"))
# Pydantic instance (FastAPI response_model 적용 전 raw return)
assert isinstance(response, AskReactResponse)
assert response.final_answer == "최종 답입니다"
assert response.iterations == 2
assert response.partial is False
assert response.debug_trace is None # ★ G0-3
assert len(response.sources) == 1
# ── G0-3: debug=true → debug_trace 채워짐 ──────────────────────────────────
def test_debug_true_populates_trace(patched_backend_and_search):
from api.search import AskReactRequest
backend, run_search_mock, _ = patched_backend_and_search
backend.generate_with_tools.side_effect = [
_msg_with_content("바로 답"),
]
response = _call_endpoint(AskReactRequest(query="Q", debug=True))
assert response.debug_trace is not None
assert isinstance(response.debug_trace, list)
assert len(response.debug_trace) >= 1
# ── max rounds → final content 정상 → partial=false ──────────────────────
def test_max_rounds_with_final_content(patched_backend_and_search):
from api.search import AskReactRequest
backend, run_search_mock, _ = patched_backend_and_search
backend.generate_with_tools.side_effect = [
_msg_with_tool_call("q1"),
_msg_with_tool_call("q2", tc_id="tc-2"),
_msg_with_content("정리된 최종 답"),
]
response = _call_endpoint(AskReactRequest(query="Q"))
assert response.iterations == 2
assert response.partial is False
assert response.final_answer == "정리된 최종 답"
# LLM 호출 3회, search 2회 (G0-2 cap)
assert backend.generate_with_tools.call_count == 3
assert run_search_mock.call_count == 2
# ── max rounds + final content 빈 string → partial=true ──────────────────
def test_max_rounds_with_empty_final_partial(patched_backend_and_search):
from api.search import AskReactRequest
backend, run_search_mock, _ = patched_backend_and_search
backend.generate_with_tools.side_effect = [
_msg_with_tool_call("q1"),
_msg_with_tool_call("q2", tc_id="tc-2"),
_msg_with_content(""),
]
response = _call_endpoint(AskReactRequest(query="Q"))
assert response.iterations == 2
assert response.partial is True
assert response.final_answer == ""