更新

app/src/doctor_workstation/services/repository.py

@@ -233,8 +233,29 @@ class DoctorRepository(Protocol):
     ) -> dict[str, Any]:
         """Append one model-specific AI diagnosis snapshot for one patient."""
 
-    def get_prescription(self, prescription_id: int) -> Prescription:
-        """Return one issued prescription."""
+    def get_prescription(self, prescription_id: int) -> Prescription:
+        """Return one issued prescription."""
+
+    def list_prescription_ai_statuses(self, ids: list[int]) -> dict[str, Any]:
+        """Read cached dual-model states for up to 100 prescriptions."""
+
+    def list_prescription_ai_reports(self, *, prescription_id: int = 0, diagnosis_id: int = 0, page_no: int = 1, page_size: int = 20) -> dict[str, Any]:
+        """Read immutable analysis batch history in the authorized scope."""
+
+    def get_prescription_ai_report(self, batch_id: int) -> dict[str, Any]:
+        """Read one analysis batch without starting model work."""
+
+    def regenerate_prescription_ai(self, prescription_id: int, reason: str) -> dict[str, Any]:
+        """Explicitly request a new analysis batch with a reason."""
+
+    def retry_prescription_ai(self, batch_id: int, model_key: str) -> dict[str, Any]:
+        """Retry only the requested failed model."""
+
+    def review_prescription_ai(self, batch_id: int, model_key: str, status: str, comment: str) -> dict[str, Any]:
+        """Save a doctor's review separately from immutable AI output."""
+
+    def prescription_ai_statistics(self, date_from: str, date_to: str, doctor_id: int | None = None) -> dict[str, Any]:
+        """Read baseline agreement statistics, never diagnostic accuracy."""
 
     def create_prescription(
         self,
@@ -1574,14 +1595,55 @@ class RemoteDoctorRepository:
             payload, Prescription.from_dict, page_no=page_no, page_size=page_size
         )
 
-    def get_prescription(self, prescription_id: int) -> Prescription:
-        """Load one issued prescription using ``tcm.prescription/detail``."""
+    def get_prescription(self, prescription_id: int) -> Prescription:
+        """Load one issued prescription using ``tcm.prescription/detail``."""
 
         result = _require_mapping(
             self.client.get("tcm.prescription/detail", {"id": prescription_id}),
             "tcm.prescription/detail",
         )
-        return Prescription.from_dict(result)
+        return Prescription.from_dict(result)
+
+    def _prescription_ai_request(self, action: str, params: dict[str, Any], *, mutation: bool = False) -> dict[str, Any]:
+        endpoint = f"tcm.prescriptionAi/{action}"
+        payload = _client_request(self.client, "post" if mutation else "get", endpoint, params, timeout=30.0)
+        return dict(_require_mapping(payload, endpoint))
+
+    def list_prescription_ai_statuses(self, ids: list[int]) -> dict[str, Any]:
+        if len(ids) > 100 or any(int(value) <= 0 for value in ids):
+            raise ValueError("statuses requires at most 100 positive prescription IDs")
+        return self._prescription_ai_request("statuses", {"ids": ",".join(str(int(value)) for value in dict.fromkeys(ids))})
+
+    def list_prescription_ai_reports(self, *, prescription_id: int = 0, diagnosis_id: int = 0, page_no: int = 1, page_size: int = 20) -> dict[str, Any]:
+        if bool(prescription_id) == bool(diagnosis_id):
+            raise ValueError("Exactly one prescription_id or diagnosis_id is required")
+        params = {"prescription_id": prescription_id} if prescription_id else {"diagnosis_id": diagnosis_id}
+        params.update(page_no=page_no, page_size=page_size)
+        return self._prescription_ai_request("reports", params)
+
+    def get_prescription_ai_report(self, batch_id: int) -> dict[str, Any]:
+        return self._prescription_ai_request("detail", {"batch_id": batch_id})
+
+    def regenerate_prescription_ai(self, prescription_id: int, reason: str) -> dict[str, Any]:
+        if not reason.strip():
+            raise ValueError("重新分析需要填写原因")
+        return self._prescription_ai_request("regenerate", {"prescription_id": prescription_id, "reason": reason.strip()}, mutation=True)
+
+    def retry_prescription_ai(self, batch_id: int, model_key: str) -> dict[str, Any]:
+        if model_key not in {"qwen", "openai"}:
+            raise ValueError("Unknown model_key")
+        return self._prescription_ai_request("retry", {"batch_id": batch_id, "model_key": model_key}, mutation=True)
+
+    def review_prescription_ai(self, batch_id: int, model_key: str, status: str, comment: str) -> dict[str, Any]:
+        if model_key not in {"qwen", "openai"} or status not in {"viewed", "needs_information", "not_adopted", "reviewed"}:
+            raise ValueError("Invalid review state")
+        return self._prescription_ai_request("review", {"batch_id": batch_id, "model_key": model_key, "status": status, "comment": comment}, mutation=True)
+
+    def prescription_ai_statistics(self, date_from: str, date_to: str, doctor_id: int | None = None) -> dict[str, Any]:
+        params: dict[str, Any] = {"date_from": date_from, "date_to": date_to}
+        if doctor_id is not None:
+            params["doctor_id"] = doctor_id
+        return self._prescription_ai_request("statistics", params)
 
     def create_prescription(
         self,