更新

app/scripts/check_ai_context.py

@@ -0,0 +1,315 @@
+"""Smoke test for the AI context builder helpers in ai_consult.py.
+
+This avoids importing PySide6-bound modules by extracting only the pure
+helper functions we want to verify.
+"""
+
+from __future__ import annotations
+
+import ast
+import os
+import sys
+
+
+AI_CONSULT_PATH = os.path.join(
+    os.path.dirname(__file__), "..", "src", "doctor_workstation", "ui", "dialogs",
+    "ai_consult.py",
+)
+
+
+def _make_helpers() -> dict[str, object]:
+    """Pull the pure helpers out of ai_consult.py without importing PySide6."""
+
+    with open(AI_CONSULT_PATH, encoding="utf-8") as stream:
+        source = stream.read()
+    tree = ast.parse(source)
+    wanted_names = {
+        "AI_CONTEXT_MAX_CHARS",
+        "AI_PROMPT_LIMIT",
+        "AI_CONTEXT_SEPARATOR",
+        "_truncate_for_context",
+        "_patient_context_blood_sugar",
+        "_patient_context_tongue",
+        "_patient_context_reports",
+        "_patient_context_prescriptions",
+        "_patient_context_videos",
+        "build_patient_ai_context",
+        "_compose_ai_prompt",
+    }
+    selected: list[ast.stmt] = []
+    for node in tree.body:
+        if isinstance(node, ast.FunctionDef) and node.name in wanted_names:
+            selected.append(node)
+            continue
+        if isinstance(node, ast.Assign):
+            for target in node.targets:
+                if isinstance(target, ast.Name) and target.id in wanted_names:
+                    selected.append(node)
+                    break
+
+    namespace: dict[str, object] = {}
+
+    def _as_mapping(value: object) -> dict[str, object]:
+        if isinstance(value, dict):
+            return dict(value)
+        raw = getattr(value, "raw", None)
+        return dict(raw) if isinstance(raw, dict) else {}
+
+    def first_value(value: object, *keys: str, default: object = None) -> object:
+        """Return the first present, non-empty value from ``keys``.
+
+        Mirrors ``widgets.first_value``:
+        ``first_value(mapping, "k1", "k2", default=...)``.
+        """
+
+        for key in keys:
+            if not isinstance(value, dict):
+                break
+            if key in value and value[key] not in (None, "", "—"):
+                return value[key]
+        return default
+
+    def get_value(source: object, key: str, default: object = None) -> object:
+        if isinstance(source, dict) and key in source:
+            return source[key]
+        return default
+
+    def _human_value(value: object, *, empty: str = "未记录") -> str:
+        if value in (None, "", "—"):
+            return empty
+        if isinstance(value, str):
+            return value.strip() or empty
+        if isinstance(value, bool):
+            return "是" if value else "否"
+        if isinstance(value, dict):
+            parts = []
+            for key, nested in value.items():
+                rendered = _human_value(nested, empty="")
+                if rendered:
+                    parts.append(f"{key}：{rendered}")
+            return "；".join(parts) or empty
+        if isinstance(value, list):
+            parts = [_human_value(item, empty="") for item in value]
+            return "、".join(part for part in parts if part) or empty
+        return str(value).strip() or empty
+
+    def display_text(value: object, *, default: str = "") -> str:
+        if value in (None, "", "—"):
+            return default
+        return str(value).strip() or default
+
+    def _exact_positive_id(value: object, expected: int) -> bool:
+        if value in (None, ""):
+            return False
+        try:
+            return int(value) == expected
+        except (TypeError, ValueError):
+            return False
+
+    # Provide fallback names for ``collections.abc`` symbols referenced by
+    # the helpers without forcing the real module imports on this stub box.
+    import collections.abc as _abc
+    Sequence = _abc.Sequence  # type: ignore[attr-defined]
+    Mapping = _abc.Mapping  # type: ignore[attr-defined]
+    Any = object  # type: ignore[assignment]
+
+    namespace.update(
+        {
+            "_as_mapping": _as_mapping,
+            "first_value": first_value,
+            "get_value": get_value,
+            "_human_value": _human_value,
+            "display_text": display_text,
+            "_exact_positive_id": _exact_positive_id,
+            "Sequence": Sequence,
+            "Mapping": Mapping,
+            "Any": Any,
+        }
+    )
+
+    module_ast = ast.Module(body=selected, type_ignores=[])
+    ast.fix_missing_locations(module_ast)
+    exec(compile(module_ast, AI_CONSULT_PATH, "exec"), namespace)
+    return namespace
+
+
+def main() -> None:
+    helpers = _make_helpers()
+    AI_CONTEXT_MAX_CHARS = helpers["AI_CONTEXT_MAX_CHARS"]
+    AI_PROMPT_LIMIT = helpers["AI_PROMPT_LIMIT"]
+    _truncate_for_context = helpers["_truncate_for_context"]
+    _patient_context_blood_sugar = helpers["_patient_context_blood_sugar"]
+    _patient_context_tongue = helpers["_patient_context_tongue"]
+    _patient_context_reports = helpers["_patient_context_reports"]
+    _patient_context_videos = helpers["_patient_context_videos"]
+    build_patient_ai_context = helpers["build_patient_ai_context"]
+    _compose_ai_prompt = helpers["_compose_ai_prompt"]
+
+    def fail(message: str) -> None:
+        raise AssertionError(message)
+
+    def assertEqual(actual: object, expected: object, message: str) -> None:
+        if actual != expected:
+            fail(f"{message}: expected {expected!r}, got {actual!r}")
+
+    def assertContains(container: object, needle: str, message: str) -> None:
+        if not isinstance(container, str) or needle not in container:
+            fail(f"{message}: {needle!r} missing in output")
+
+    # 1. _truncate_for_context
+    short = _truncate_for_context("hello", max_chars=10)
+    assertEqual(short, "hello", "short text should pass through unchanged")
+
+    long_text = _truncate_for_context(
+        "诊断：血糖偏高，建议调整饮食结构，配合运动每周三次以上。",
+        max_chars=12,
+    )
+    assertContains(long_text, "…", "long text should end with ellipsis")
+    assertEqual(len(long_text), 12, "truncated text should respect max_chars")
+
+    # 2. _patient_context_tongue
+    tongue = _patient_context_tongue(
+        {
+            "diagnosis": {
+                "tongue": "舌红苔黄腻",
+                "tongue_coating": "黄腻",
+                "pulse": "弦滑",
+                "tongue_images": ["url1", "url2", "url3"],
+            }
+        }
+    )
+    assertContains(tongue, "舌红苔黄腻", "tongue text missing")
+    assertContains(tongue, "弦滑", "pulse text missing")
+    assertContains(tongue, "舌苔图片 3 张", "tongue image count missing")
+
+    # 3. _patient_context_blood_sugar
+    blood_sugar = _patient_context_blood_sugar(
+        {"diagnosis": {"fasting_blood_sugar": "7.8"}},
+        {
+            "blood_sugar": {
+                "entries": [
+                    {"date": "2026-08-15", "value": "6.2", "period": "空腹"},
+                    {"date": "2026-08-14", "value": "9.1", "period": "餐后"},
+                ]
+            }
+        },
+    )
+    assertContains(blood_sugar, "7.8", "fasting reading missing")
+    assertContains(blood_sugar, "每日血糖", "tracking summary missing")
+
+    # 4. _patient_context_videos: filters by current diagnosis id.
+    videos = _patient_context_videos(
+        [
+            {
+                "diagnosis_id": 99,
+                "transcript_text": "其他诊单",
+                "start_time_text": "今天",
+            },
+            {
+                "diagnosis_id": 501,
+                "transcript_text": "医生：请问您最近睡眠如何；患者：经常失眠。",
+                "start_time_text": "2026-08-15 10:30",
+            },
+        ],
+        diagnosis_id=501,
+    )
+    assertContains(videos, "医生", "transcript text missing")
+    assertContains(videos, "2026-08-15", "transcript timestamp missing")
+
+    # 5. _patient_context_reports
+    reports = _patient_context_reports(
+        {
+            "summary": "近期血糖偏高",
+            "diagnosis_advice": "建议控制饮食",
+            "risk_assessment": ["心血管风险升高", "肾功负担加重"],
+        }
+    )
+    assertContains(reports, "既往AI摘要", "summary missing")
+    assertContains(reports, "诊断建议", "advice missing")
+    assertContains(reports, "心血管风险", "risk bullet missing")
+
+    # 6. build_patient_ai_context: full envelope assembly.
+    detail = {
+        "diagnosis": {
+            "tongue": "舌淡苔白",
+            "pulse": "细弱",
+            "fasting_blood_sugar": "8.0",
+        },
+        "tongue_images": ["a", "b"],
+    }
+    tracking = {
+        "blood_sugar": {
+            "entries": [
+                {"date": "2026-08-19", "value": "6.1", "period": "空腹"},
+            ]
+        }
+    }
+    analysis = {
+        "summary": "控制尚可",
+        "diagnosis_advice": "调整饮食",
+        "risk_assessment": ["肾功"],
+    }
+    prescriptions = [
+        {"prescription_name": "六味地黄丸", "prescription_remark": "调理方"},
+    ]
+    call_records = [
+        {
+            "diagnosis_id": 501,
+            "transcript_text": "对话内容：患者表述近期乏力。",
+            "start_time_text": "2026-08-18 14:00",
+        }
+    ]
+    context_text, present = build_patient_ai_context(
+        detail=detail,
+        tracking=tracking,
+        analysis=analysis,
+        prescriptions=prescriptions,
+        call_records=call_records,
+        diagnosis_id=501,
+    )
+    for label in (
+        "每日血糖",
+        "舌苔/脉象",
+        "视频问诊文字",
+        "历史AI报告",
+        "处方记录",
+    ):
+        assertContains(context_text, label, f"section {label} missing in envelope")
+        if label not in present:
+            fail(f"label {label} not in present labels")
+    if len(context_text) > AI_CONTEXT_MAX_CHARS + 12:
+        fail(f"context exceeds {AI_CONTEXT_MAX_CHARS} chars: {len(context_text)}")
+
+    # 7. _compose_ai_prompt: short answer stays untouched.
+    short_prompt = _compose_ai_prompt("血糖如何？", context_text)
+    assertContains(short_prompt, context_text, "short prompt loses context")
+    assertContains(short_prompt, "血糖如何？", "short prompt loses question")
+    if len(short_prompt) > AI_PROMPT_LIMIT:
+        fail("short prompt exceeds limit")
+
+    # 8. Long answer is truncated with ellipsis.
+    long_question = (
+        "请结合患者既往糖尿病史、家族史以及服用的多种药物，给出一份详尽的"
+        "个性化治疗方案，并解释每一步的理由，最终输出一份结构化报告，"
+        "包括风险评估、用药合理性、并发症筛查和分级随访计划。"
+    ) * 6
+    long_prompt = _compose_ai_prompt(long_question, context_text)
+    if len(long_prompt) > AI_PROMPT_LIMIT:
+        fail(f"long prompt exceeds limit: {len(long_prompt)}")
+    if context_text not in long_prompt:
+        fail("long prompt loses context")
+    assertContains(long_prompt, "…", "long prompt should end with ellipsis")
+
+    # 9. Empty context returns bare question.
+    bare = _compose_ai_prompt("血糖？", "")
+    assertEqual(bare, "血糖？", "empty context should drop the envelope entirely")
+
+    # 10. Empty question returns empty string.
+    empty = _compose_ai_prompt("", context_text)
+    assertEqual(empty, "", "empty question returns empty string")
+
+    print("OK: all AI context helper assertions passed")
+
+
+if __name__ == "__main__":
+    main()