gjm
f7fa8f14d9
- checklist.py：系统提示加入结构化输出契约（只输出 {summary, issues[]}，
引用 handle 必须真实存在、不得编造）
- review.py：review_frame 返回 {summary, issues, raw}；仅在「不再请求工具」的回合
解析结论，中间工具回合的 content 永不解析；强制收口那次 chat 不传 tools
- report.py：删除 extract_issues 与 _EXTRACT_SYSTEM（不再需要第二次 LLM 调用）；
新增 format_finding（用 .get，顺带修复缺 frame 键 KeyError）；save_report 的
issues 省略时从 findings 拍平
- __main__.py：主流程改为 确定性检查 → review_frame → build_finding（合并+校验），
issues 由 flatten_issues 派生
顺带修复既有 gap：summarize 硬下标 KeyError、extract_issues 单行围栏解析失败。
246 lines
9.3 KiB
Python
246 lines
9.3 KiB
Python
"""`dwg_review.phases.review` 单元测试。"""
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import json
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from dwg_review.cad_tools import READ_ONLY_TOOLS
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from dwg_review.mcp_client import McpToolError
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from dwg_review.phases.review import (
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_run_readonly_tool,
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evidence_payload,
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review_frame,
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)
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from tests.fakes import (
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FakeLlmClient,
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FakeMcpClient,
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llm_calls,
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llm_text,
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make_ctx,
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make_evidence,
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ok_image,
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ok_mixed,
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ok_text,
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)
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# ---------------------------------------------------------------------------
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# evidence_payload
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# ---------------------------------------------------------------------------
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def test_evidence_payload_strips_image():
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ev = make_evidence(image_b64="QUJD", image_mime="image/png")
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payload = evidence_payload(ev)
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assert "image_b64" not in payload
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assert "image_mime" not in payload
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assert payload["frame_index"] == 1
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def test_evidence_payload_keeps_only_frame_metadata():
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ev = make_evidence()
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ev["frame"]["secret"] = "should-not-leak"
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payload = evidence_payload(ev)
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assert "secret" not in payload["frame"]
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assert set(payload["frame"]) == {"sheet_size", "kind", "layer", "bbox", "confidence"}
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def test_evidence_payload_carries_structured_data():
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ev = make_evidence(entities={"total": 9, "items": []}, texts={"total": 2})
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payload = evidence_payload(ev)
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assert payload["entities"] == {"total": 9, "items": []}
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assert payload["texts"] == {"total": 2}
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# ---------------------------------------------------------------------------
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# _run_readonly_tool
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# ---------------------------------------------------------------------------
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def test_readonly_rejects_non_whitelisted_tool():
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client = FakeMcpClient()
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ctx = make_ctx(client=client)
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content, budget = _run_readonly_tool(ctx, "get_some_unknown_tool", {}, [3])
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assert "不在只读取证白名单内" in content[0]["text"]
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assert client.calls == []
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assert budget == [3]
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def test_readonly_rejects_write_tool():
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client = FakeMcpClient()
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ctx = make_ctx(client=client)
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content, _ = _run_readonly_tool(ctx, "add_leader_annotation", {}, [3])
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assert "不在只读取证白名单内" in content[0]["text"]
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assert client.calls == []
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def test_readonly_whitelist_covers_expected_tools():
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assert {"query_entities", "get_entity_detail", "zoom_to_window"} <= READ_ONLY_TOOLS
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def test_readonly_handles_tool_error():
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client = FakeMcpClient(responses={"query_entities": McpToolError("炸了")})
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ctx = make_ctx(client=client)
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content, _ = _run_readonly_tool(ctx, "query_entities", {"window": {}}, [3])
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assert "执行失败" in content[0]["text"]
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def test_readonly_text_and_image_content():
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client = FakeMcpClient(
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responses={"query_entities": ok_mixed(["hi"], [("QUJD", "image/png")])}
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)
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ctx = make_ctx(client=client)
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content, budget = _run_readonly_tool(ctx, "query_entities", {}, [3])
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assert content[0] == {"type": "text", "text": "hi"}
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assert content[1]["type"] == "image_url"
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assert budget == [2]
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def test_readonly_image_budget_exhausted():
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client = FakeMcpClient(
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responses={"query_entities": ok_mixed(["t"], [("QUJD", "image/png")])}
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)
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ctx = make_ctx(client=client)
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content, budget = _run_readonly_tool(ctx, "query_entities", {}, [0])
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assert budget == [0]
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assert any("已省略" in c.get("text", "") for c in content)
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def test_readonly_empty_response_marker():
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empty = {"jsonrpc": "2.0", "id": 1, "result": {"content": []}}
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client = FakeMcpClient(responses={"query_entities": empty})
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ctx = make_ctx(client=client)
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content, _ = _run_readonly_tool(ctx, "query_entities", {}, [3])
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assert content == [{"type": "text", "text": "（无返回内容）"}]
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# ---------------------------------------------------------------------------
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# review_frame
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# ---------------------------------------------------------------------------
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def test_review_frame_returns_summary_when_no_tools():
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llm = FakeLlmClient(script=[llm_text("结论A")])
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ctx = make_ctx(client=FakeMcpClient(), llm=llm)
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out = review_frame(ctx, make_evidence(), "系统提示", log=lambda *a: None)
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assert out["summary"] == "结论A" # 非 JSON → 降级为纯文本 summary
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assert out["issues"] == []
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assert len(llm.calls) == 1
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assert llm.calls[0]["tools"] is not None # 传了只读工具 schema
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def test_review_frame_includes_image_block_when_present():
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llm = FakeLlmClient(script=[llm_text("ok")])
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ctx = make_ctx(client=FakeMcpClient(), llm=llm)
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ev = make_evidence(image_b64="QUJD", image_mime="image/png")
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review_frame(ctx, ev, "sys", log=lambda *a: None)
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user_content = llm.calls[0]["messages"][1]["content"]
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assert any(b.get("type") == "image_url" for b in user_content)
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def test_review_frame_omits_image_block_when_absent():
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llm = FakeLlmClient(script=[llm_text("ok")])
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ctx = make_ctx(client=FakeMcpClient(), llm=llm)
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review_frame(ctx, make_evidence(), "sys", log=lambda *a: None)
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user_content = llm.calls[0]["messages"][1]["content"]
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assert all(b.get("type") == "text" for b in user_content)
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def test_review_frame_runs_tool_then_concludes():
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llm = FakeLlmClient(
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script=[
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llm_calls([("query_entities", {"window": {}})]),
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llm_text("结论B"),
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]
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)
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client = FakeMcpClient(responses={"query_entities": ok_text({"total": 1})})
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ctx = make_ctx(client=client, llm=llm)
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out = review_frame(ctx, make_evidence(), "sys", log=lambda *a: None)
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assert out["summary"] == "结论B"
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assert len(llm.calls) == 2
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assert client.called_names() == ["query_entities"]
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def test_review_frame_feeds_observation_back_as_tool_message():
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llm = FakeLlmClient(script=[llm_calls([("query_entities", {})]), llm_text("done")])
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ctx = make_ctx(client=FakeMcpClient(), llm=llm)
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review_frame(ctx, make_evidence(), "sys", log=lambda *a: None)
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tool_msgs = [m for m in llm.calls[1]["messages"] if isinstance(m, dict) and m.get("role") == "tool"]
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assert tool_msgs and tool_msgs[0]["tool_call_id"] == "1"
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def test_review_frame_invalid_tool_arguments_become_empty():
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llm = FakeLlmClient(
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script=[llm_calls([("query_entities", "not-json")]), llm_text("done")]
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)
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client = FakeMcpClient()
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ctx = make_ctx(client=client, llm=llm)
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review_frame(ctx, make_evidence(), "sys", log=lambda *a: None)
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assert client.arguments_of("query_entities") == {}
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def test_review_frame_force_closes_at_iteration_limit():
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llm = FakeLlmClient(
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script=[
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llm_calls([("query_entities", {})]),
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llm_text("收口结论"),
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]
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)
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ctx = make_ctx(client=FakeMcpClient(), llm=llm, max_iters=1)
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out = review_frame(ctx, make_evidence(), "sys", log=lambda *a: None)
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assert out["summary"] == "收口结论"
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last_msg = llm.calls[-1]["messages"][-1]
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assert last_msg["role"] == "user"
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assert "上限" in last_msg["content"]
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def test_review_frame_with_zero_iters_forces_immediate_close():
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llm = FakeLlmClient(script=[llm_text("直接结论")])
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ctx = make_ctx(client=FakeMcpClient(), llm=llm, max_iters=0)
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out = review_frame(ctx, make_evidence(), "sys", log=lambda *a: None)
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assert out["summary"] == "直接结论"
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assert len(llm.calls) == 1
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def test_review_frame_logs_tool_usage():
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logs = []
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llm = FakeLlmClient(script=[llm_calls([("get_layers", {})]), llm_text("x")])
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ctx = make_ctx(client=FakeMcpClient(), llm=llm)
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review_frame(ctx, make_evidence(), "sys", log=logs.append)
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assert any("取证" in line and "get_layers" in line for line in logs)
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def test_review_frame_payload_is_json_serializable():
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llm = FakeLlmClient(script=[llm_text("ok")])
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ctx = make_ctx(client=FakeMcpClient(), llm=llm)
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review_frame(ctx, make_evidence(), "sys", log=lambda *a: None)
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text = llm.calls[0]["messages"][1]["content"][0]["text"]
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json.loads(text.split("：\n", 1)[1]) # 不抛异常即通过
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def test_review_frame_parses_structured_json_conclusion():
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text = (
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'{"summary": "整体尚可", "issues": ['
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'{"category": "几何", "severity": "medium", "message": "零长度", "handle": "A1"}]}'
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)
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llm = FakeLlmClient(script=[llm_text(text)])
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ctx = make_ctx(client=FakeMcpClient(), llm=llm)
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out = review_frame(ctx, make_evidence(), "sys", log=lambda *a: None)
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assert out["summary"] == "整体尚可"
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assert out["issues"] == [
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{"category": "几何", "severity": "medium", "message": "零长度", "handle": "A1"}
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]
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def test_review_frame_parses_fenced_json():
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llm = FakeLlmClient(script=[llm_text('```json\n{"summary": "s", "issues": []}\n```')])
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ctx = make_ctx(client=FakeMcpClient(), llm=llm)
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out = review_frame(ctx, make_evidence(), "sys", log=lambda *a: None)
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assert out["summary"] == "s"
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assert out["issues"] == []
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def test_review_frame_intermediate_tool_turn_json_not_parsed():
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# 中间工具回合的 content 里即使塞了 JSON，也不能被当成最终结论
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intermediate = '{"summary": "这不是最终结论", "issues": [{"message": "x"}]}'
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llm = FakeLlmClient(script=[
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llm_calls([("query_entities", {})], content=intermediate),
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llm_text('{"summary": "最终结论", "issues": []}'),
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])
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ctx = make_ctx(client=FakeMcpClient(), llm=llm)
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out = review_frame(ctx, make_evidence(), "sys", log=lambda *a: None)
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assert out["summary"] == "最终结论"
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assert out["issues"] == []
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