更新
This commit is contained in:
Your Name
@@ -5,7 +5,7 @@ from __future__ import annotations
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import mimetypes
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import re
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import time
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from collections.abc import Mapping, Sequence
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from collections.abc import Mapping, Sequence
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from contextlib import suppress
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from datetime import date
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from io import BytesIO
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@@ -41,9 +41,21 @@ PRESCRIPTION_LIBRARY_PERMISSIONS: Final[dict[str, str]] = {
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"read": "wcf.prescription/read",
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"update": "wcf.prescription/edit",
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"delete": "wcf.prescription/delete",
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"ai_reports": "tcm.prescriptionLibrary/aiReports",
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"generate_ai_reports": "tcm.prescriptionLibrary/generateAiReports",
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"edit_ai_report": "tcm.prescriptionLibrary/editAiReport",
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}
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"""Canonical permissions used by the routed prescription-library view."""
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DIAGNOSIS_AI_PERMISSIONS: Final[dict[str, str]] = {
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"ai_reports": "tcm.diagnosis/aiReports",
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"generate_ai_reports": "tcm.diagnosis/generateAiReports",
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"edit_ai_report": "tcm.diagnosis/editAiReport",
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"analysis": "tcm.diagnosis/aiAnalysis",
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"assistant": "tcm.diagnosis/aiAssistant",
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}
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"""Canonical permissions used by reception and patient-profile AI reports."""
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PRESCRIPTION_PERMISSIONS: Final[dict[str, str]] = {
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"create": "cf.prescription/add",
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"read": "cf.prescription/read",
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@@ -140,6 +152,64 @@ class DoctorRepository(Protocol):
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def delete_prescription_template(self, template_id: int) -> Any:
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"""Delete a prescription-library record."""
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def list_prescription_template_ai_reports(self, template_id: int) -> dict[str, Any]:
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"""Return saved AI interpretation reports for one library template."""
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def generate_prescription_template_ai_reports(self, template_id: int) -> dict[str, Any]:
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"""Regenerate every model report for one library template."""
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def edit_prescription_template_ai_report(
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self,
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template_id: int,
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*,
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report_id: int,
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content: str,
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) -> dict[str, Any]:
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"""Save a manually edited AI report for one library template."""
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def list_diagnosis_ai_reports(self, diagnosis_id: int) -> dict[str, Any]:
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"""Return saved AI reports for one diagnosis / patient profile."""
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def generate_diagnosis_ai_reports(self, diagnosis_id: int) -> dict[str, Any]:
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"""Regenerate every model report for one diagnosis."""
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def edit_diagnosis_ai_report(
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self,
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diagnosis_id: int,
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*,
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report_id: int,
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content: str,
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) -> dict[str, Any]:
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"""Save a manually edited AI report for one diagnosis."""
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def analyze_diagnosis_ai(
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self,
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diagnosis_id: int,
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prompt: str,
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*,
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task: str = "custom",
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) -> dict[str, Any]:
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"""Ask the first-party diagnosis assistant; the server selects the model."""
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def get_diagnosis_ai_analysis(
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self,
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diagnosis_id: int,
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*,
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model: Literal["qwen", "openai"] = "qwen",
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) -> dict[str, Any]:
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"""Generate one model's structured reception analysis for a diagnosis."""
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def list_patient_ai_reports(self, patient_id: int) -> dict[str, Any]:
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"""Return every persisted AI diagnosis snapshot for one patient."""
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def generate_patient_ai_report(
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self,
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patient_id: int,
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*,
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model: Literal["qwen", "openai"],
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) -> dict[str, Any]:
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"""Append one model-specific AI diagnosis snapshot for one patient."""
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def get_prescription(self, prescription_id: int) -> Prescription:
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"""Return one issued prescription."""
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@@ -619,38 +689,38 @@ class DoctorRepository(Protocol):
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def end_call(self, diagnosis_id: int) -> Any:
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"""End the active diagnosis call."""
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def bind_call_room(self, diagnosis_id: int, room_id: str) -> Any:
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"""Bind a TRTC room to the active call."""
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def start_call_transcription(
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self,
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diagnosis_id: int,
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call_record_id: int | str,
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transcription_session_id: str,
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*,
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language: str = "zh-CN",
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) -> Any:
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"""Start a transcript stored on one exact call record."""
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def upsert_call_transcript_segments(
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self,
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diagnosis_id: int,
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call_record_id: int | str,
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transcription_session_id: str,
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segments: Sequence[Mapping[str, Any]],
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) -> Any:
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"""Idempotently persist completed transcript segments."""
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def finish_call_transcription(
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self,
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diagnosis_id: int,
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call_record_id: int | str,
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transcription_session_id: str,
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expected_segment_count: int,
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*,
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status: str = "completed",
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) -> Any:
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"""Finalize and materialize the transcript text on a call record."""
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def bind_call_room(self, diagnosis_id: int, room_id: str) -> Any:
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"""Bind a TRTC room to the active call."""
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def start_call_transcription(
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self,
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diagnosis_id: int,
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call_record_id: int | str,
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transcription_session_id: str,
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*,
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language: str = "zh-CN",
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) -> Any:
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"""Start a transcript stored on one exact call record."""
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def upsert_call_transcript_segments(
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self,
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diagnosis_id: int,
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call_record_id: int | str,
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transcription_session_id: str,
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segments: Sequence[Mapping[str, Any]],
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) -> Any:
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"""Idempotently persist completed transcript segments."""
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def finish_call_transcription(
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self,
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diagnosis_id: int,
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call_record_id: int | str,
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transcription_session_id: str,
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expected_segment_count: int,
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*,
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status: str = "completed",
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) -> Any:
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"""Finalize and materialize the transcript text on a call record."""
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def my_self(self) -> Session:
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"""Compatibility alias for :meth:`get_session`."""
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@@ -1165,7 +1235,191 @@ class RemoteDoctorRepository:
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return self.client.post("tcm.prescriptionLibrary/delete", {"id": template_id})
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def list_medicines(
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def list_prescription_template_ai_reports(self, template_id: int) -> dict[str, Any]:
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"""Read persisted AI reports without triggering model generation."""
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payload = _client_request(
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self.client,
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"get",
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"tcm.prescriptionLibrary/aiReports",
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{"id": template_id},
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timeout=30.0,
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)
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return dict(_require_mapping(payload, "tcm.prescriptionLibrary/aiReports"))
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def generate_prescription_template_ai_reports(self, template_id: int) -> dict[str, Any]:
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"""Regenerate the multi-model diagnosis report; not retried by the client."""
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payload = _client_request(
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self.client,
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"post",
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"tcm.prescriptionLibrary/generateAiReports",
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{"id": template_id},
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timeout=210.0,
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)
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return dict(_require_mapping(payload, "tcm.prescriptionLibrary/generateAiReports"))
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def edit_prescription_template_ai_report(
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self,
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template_id: int,
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*,
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report_id: int,
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content: str,
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) -> dict[str, Any]:
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"""Persist a manual edit of one saved model report."""
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payload = _client_request(
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self.client,
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"post",
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"tcm.prescriptionLibrary/editAiReport",
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{"id": template_id, "report_id": report_id, "content": content},
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timeout=30.0,
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)
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return dict(_require_mapping(payload, "tcm.prescriptionLibrary/editAiReport"))
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def list_diagnosis_ai_reports(self, diagnosis_id: int) -> dict[str, Any]:
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"""Read persisted diagnosis AI reports without triggering model generation."""
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payload = _client_request(
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self.client,
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"get",
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"tcm.diagnosis/aiReports",
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{"id": diagnosis_id},
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timeout=30.0,
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)
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return dict(_require_mapping(payload, "tcm.diagnosis/aiReports"))
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def generate_diagnosis_ai_reports(self, diagnosis_id: int) -> dict[str, Any]:
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"""Regenerate the multi-model diagnosis report; not retried by the client."""
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payload = _client_request(
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self.client,
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"post",
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"tcm.diagnosis/generateAiReports",
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{"id": diagnosis_id},
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timeout=210.0,
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)
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return dict(_require_mapping(payload, "tcm.diagnosis/generateAiReports"))
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def edit_diagnosis_ai_report(
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self,
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diagnosis_id: int,
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*,
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report_id: int,
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content: str,
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) -> dict[str, Any]:
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"""Persist a manual edit of one saved diagnosis report."""
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payload = _client_request(
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self.client,
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"post",
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"tcm.diagnosis/editAiReport",
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{"id": diagnosis_id, "report_id": report_id, "content": content},
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timeout=30.0,
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)
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return dict(_require_mapping(payload, "tcm.diagnosis/editAiReport"))
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def analyze_diagnosis_ai(
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self,
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diagnosis_id: int,
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prompt: str,
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*,
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task: str = "custom",
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) -> dict[str, Any]:
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"""Submit a diagnosis question to the first-party server assistant."""
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if diagnosis_id <= 0:
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raise ValueError("diagnosis_id must be positive")
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clean_prompt = prompt.strip()
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if not clean_prompt:
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raise ValueError("prompt is required")
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if len(clean_prompt) > 500:
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raise ValueError("prompt must not exceed 500 characters")
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clean_task = task.strip().lower() or "custom"
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if clean_task not in {
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"summary",
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"tcm_pattern",
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"prescription_review",
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"medication_review",
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"exam_review",
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"complication_risk",
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"guideline_review",
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"custom",
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}:
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raise ValueError("task is not supported")
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payload = _client_request(
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self.client,
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"post",
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"tcm.diagnosis/aiAssistant",
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{"id": diagnosis_id, "prompt": clean_prompt, "task": clean_task},
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# The upstream is allowed 90 seconds by server configuration. Keep a
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# small transport buffer so the desktop can receive the server's own
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# timeout response instead of racing it.
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timeout=105.0,
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)
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return dict(_require_mapping(payload, "tcm.diagnosis/aiAssistant"))
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def get_diagnosis_ai_analysis(
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self,
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diagnosis_id: int,
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*,
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model: Literal["qwen", "openai"] = "qwen",
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) -> dict[str, Any]:
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"""Generate one model's structured analysis via the first-party API."""
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if diagnosis_id <= 0:
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raise ValueError("diagnosis_id must be positive")
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clean_model = str(model).strip().lower()
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if clean_model not in {"qwen", "openai"}:
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raise ValueError("model must be qwen or openai")
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payload = _client_request(
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self.client,
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"post",
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"tcm.diagnosis/aiAnalysis",
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{"id": diagnosis_id, "model": clean_model},
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timeout=105.0,
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)
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return dict(_require_mapping(payload, "tcm.diagnosis/aiAnalysis"))
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def list_patient_ai_reports(self, patient_id: int) -> dict[str, Any]:
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"""Read patient-level snapshots without triggering model generation."""
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if patient_id <= 0:
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raise ValueError("patient_id must be positive")
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payload = _client_request(
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self.client,
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"get",
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"tcm.diagnosis/patientAiReports",
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{"patient_id": patient_id},
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timeout=30.0,
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)
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return dict(_require_mapping(payload, "tcm.diagnosis/patientAiReports"))
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def generate_patient_ai_report(
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self,
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patient_id: int,
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*,
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model: Literal["qwen", "openai"],
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) -> dict[str, Any]:
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"""Append one patient snapshot; the desktop never sends provider secrets."""
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if patient_id <= 0:
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raise ValueError("patient_id must be positive")
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clean_model = str(model).strip().lower()
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if clean_model not in {"qwen", "openai"}:
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raise ValueError("model must be qwen or openai")
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payload = _client_request(
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self.client,
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"post",
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"tcm.diagnosis/generatePatientAiReport",
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{"patient_id": patient_id, "model": clean_model},
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timeout=105.0,
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)
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return dict(
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_require_mapping(payload, "tcm.diagnosis/generatePatientAiReport")
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)
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def list_medicines(
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self,
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*,
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name: str = "",
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@@ -2201,157 +2455,157 @@ class RemoteDoctorRepository:
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ticket.diagnosis_id = diagnosis_id
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return ticket
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def start_call(self, diagnosis_id: int, patient_id: int, *, call_type: int = 2) -> Any:
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"""Create the server-side call record before ringing participants."""
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payload = self.client.post(
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"tcm.diagnosis/startCall",
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{
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"diagnosis_id": diagnosis_id,
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"patient_id": patient_id,
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"call_type": call_type,
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},
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)
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if not isinstance(payload, Mapping):
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raise ApiProtocolError(
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"tcm.diagnosis/startCall returned no valid call_record_id object", data=payload
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)
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raw_id = next(
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(
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payload[key]
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for key in ("call_record_id", "callRecordId", "id")
|
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if key in payload
|
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),
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None,
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)
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try:
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if isinstance(raw_id, bool):
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raise ValueError
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call_record_id = int(raw_id)
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except (TypeError, ValueError) as exc:
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raise ApiProtocolError(
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"tcm.diagnosis/startCall returned no valid call_record_id",
|
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data=dict(payload),
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) from exc
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if call_record_id <= 0:
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raise ApiProtocolError(
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"tcm.diagnosis/startCall returned no valid call_record_id",
|
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data=dict(payload),
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)
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return {"call_record_id": call_record_id}
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def start_call(self, diagnosis_id: int, patient_id: int, *, call_type: int = 2) -> Any:
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"""Create the server-side call record before ringing participants."""
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|
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payload = self.client.post(
|
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"tcm.diagnosis/startCall",
|
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{
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"diagnosis_id": diagnosis_id,
|
||||
"patient_id": patient_id,
|
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"call_type": call_type,
|
||||
},
|
||||
)
|
||||
if not isinstance(payload, Mapping):
|
||||
raise ApiProtocolError(
|
||||
"tcm.diagnosis/startCall returned no valid call_record_id object", data=payload
|
||||
)
|
||||
raw_id = next(
|
||||
(
|
||||
payload[key]
|
||||
for key in ("call_record_id", "callRecordId", "id")
|
||||
if key in payload
|
||||
),
|
||||
None,
|
||||
)
|
||||
try:
|
||||
if isinstance(raw_id, bool):
|
||||
raise ValueError
|
||||
call_record_id = int(raw_id)
|
||||
except (TypeError, ValueError) as exc:
|
||||
raise ApiProtocolError(
|
||||
"tcm.diagnosis/startCall returned no valid call_record_id",
|
||||
data=dict(payload),
|
||||
) from exc
|
||||
if call_record_id <= 0:
|
||||
raise ApiProtocolError(
|
||||
"tcm.diagnosis/startCall returned no valid call_record_id",
|
||||
data=dict(payload),
|
||||
)
|
||||
return {"call_record_id": call_record_id}
|
||||
|
||||
def end_call(self, diagnosis_id: int) -> Any:
|
||||
"""End the active call/recording associated with a diagnosis."""
|
||||
|
||||
return self.client.post("tcm.diagnosis/endCall", {"diagnosis_id": diagnosis_id})
|
||||
|
||||
def bind_call_room(self, diagnosis_id: int, room_id: str) -> Any:
|
||||
"""Bind the actual TRTC room to the active call record."""
|
||||
def bind_call_room(self, diagnosis_id: int, room_id: str) -> Any:
|
||||
"""Bind the actual TRTC room to the active call record."""
|
||||
|
||||
if not room_id.strip():
|
||||
raise ValueError("room_id is required")
|
||||
return self.client.post(
|
||||
"tcm.diagnosis/bindCallRoom",
|
||||
{"diagnosis_id": diagnosis_id, "room_id": room_id.strip()},
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _transcription_identity(
|
||||
diagnosis_id: int,
|
||||
call_record_id: int | str,
|
||||
transcription_session_id: str,
|
||||
) -> dict[str, Any]:
|
||||
if diagnosis_id <= 0:
|
||||
raise ValueError("diagnosis_id must be positive")
|
||||
if isinstance(call_record_id, bool) or not str(call_record_id).strip():
|
||||
raise ValueError("call_record_id is required")
|
||||
clean_session = transcription_session_id.strip()
|
||||
if not clean_session or len(clean_session) > 128:
|
||||
raise ValueError("transcription_session_id must contain 1 to 128 characters")
|
||||
return {
|
||||
"diagnosis_id": diagnosis_id,
|
||||
"call_record_id": call_record_id,
|
||||
"transcription_session_id": clean_session,
|
||||
}
|
||||
|
||||
def start_call_transcription(
|
||||
self,
|
||||
diagnosis_id: int,
|
||||
call_record_id: int | str,
|
||||
transcription_session_id: str,
|
||||
*,
|
||||
language: str = "zh-CN",
|
||||
) -> Any:
|
||||
"""Create the server transcript session for one call record."""
|
||||
|
||||
body = self._transcription_identity(
|
||||
diagnosis_id, call_record_id, transcription_session_id
|
||||
)
|
||||
body["language"] = language.strip()[:32] or "zh-CN"
|
||||
return self.client.post("tcm.diagnosis/startCallTranscription", body)
|
||||
|
||||
def upsert_call_transcript_segments(
|
||||
self,
|
||||
diagnosis_id: int,
|
||||
call_record_id: int | str,
|
||||
transcription_session_id: str,
|
||||
segments: Sequence[Mapping[str, Any]],
|
||||
) -> Any:
|
||||
"""Upsert a bounded batch using each segment_id as the idempotency key."""
|
||||
|
||||
body = self._transcription_identity(
|
||||
diagnosis_id, call_record_id, transcription_session_id
|
||||
)
|
||||
normalized: list[dict[str, Any]] = []
|
||||
if len(segments) > 50:
|
||||
raise ValueError("at most 50 transcript segments may be submitted at once")
|
||||
for segment in segments:
|
||||
segment_id = str(segment.get("segment_id") or "").strip()
|
||||
text = str(segment.get("text") or "").strip()
|
||||
if not segment_id or len(segment_id) > 160:
|
||||
raise ValueError("transcript segment_id is invalid")
|
||||
if not text or len(text) > 4_000:
|
||||
raise ValueError("transcript text is invalid")
|
||||
normalized.append(
|
||||
{
|
||||
"segment_id": segment_id,
|
||||
"speaker_user_id": str(segment.get("speaker_user_id") or "")[:160],
|
||||
"speaker_role": str(segment.get("speaker_role") or "unknown")[:20],
|
||||
"timestamp": max(int(segment.get("timestamp") or 0), 0),
|
||||
"text": text,
|
||||
}
|
||||
)
|
||||
if not normalized:
|
||||
raise ValueError("at least one transcript segment is required")
|
||||
body["segments"] = normalized
|
||||
return self.client.post("tcm.diagnosis/upsertCallTranscriptSegments", body)
|
||||
|
||||
def finish_call_transcription(
|
||||
self,
|
||||
diagnosis_id: int,
|
||||
call_record_id: int | str,
|
||||
transcription_session_id: str,
|
||||
expected_segment_count: int,
|
||||
*,
|
||||
status: str = "completed",
|
||||
) -> Any:
|
||||
"""Finalize a transcript; repeated requests use the same session identity."""
|
||||
|
||||
body = self._transcription_identity(
|
||||
diagnosis_id, call_record_id, transcription_session_id
|
||||
)
|
||||
clean_status = status.strip().lower()
|
||||
if clean_status not in {"completed", "partial", "failed"}:
|
||||
raise ValueError("transcription status is invalid")
|
||||
if expected_segment_count < 0:
|
||||
raise ValueError("expected_segment_count must not be negative")
|
||||
body.update(
|
||||
{
|
||||
"expected_segment_count": expected_segment_count,
|
||||
"status": clean_status,
|
||||
}
|
||||
)
|
||||
return self.client.post("tcm.diagnosis/finishCallTranscription", body)
|
||||
return self.client.post(
|
||||
"tcm.diagnosis/bindCallRoom",
|
||||
{"diagnosis_id": diagnosis_id, "room_id": room_id.strip()},
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _transcription_identity(
|
||||
diagnosis_id: int,
|
||||
call_record_id: int | str,
|
||||
transcription_session_id: str,
|
||||
) -> dict[str, Any]:
|
||||
if diagnosis_id <= 0:
|
||||
raise ValueError("diagnosis_id must be positive")
|
||||
if isinstance(call_record_id, bool) or not str(call_record_id).strip():
|
||||
raise ValueError("call_record_id is required")
|
||||
clean_session = transcription_session_id.strip()
|
||||
if not clean_session or len(clean_session) > 128:
|
||||
raise ValueError("transcription_session_id must contain 1 to 128 characters")
|
||||
return {
|
||||
"diagnosis_id": diagnosis_id,
|
||||
"call_record_id": call_record_id,
|
||||
"transcription_session_id": clean_session,
|
||||
}
|
||||
|
||||
def start_call_transcription(
|
||||
self,
|
||||
diagnosis_id: int,
|
||||
call_record_id: int | str,
|
||||
transcription_session_id: str,
|
||||
*,
|
||||
language: str = "zh-CN",
|
||||
) -> Any:
|
||||
"""Create the server transcript session for one call record."""
|
||||
|
||||
body = self._transcription_identity(
|
||||
diagnosis_id, call_record_id, transcription_session_id
|
||||
)
|
||||
body["language"] = language.strip()[:32] or "zh-CN"
|
||||
return self.client.post("tcm.diagnosis/startCallTranscription", body)
|
||||
|
||||
def upsert_call_transcript_segments(
|
||||
self,
|
||||
diagnosis_id: int,
|
||||
call_record_id: int | str,
|
||||
transcription_session_id: str,
|
||||
segments: Sequence[Mapping[str, Any]],
|
||||
) -> Any:
|
||||
"""Upsert a bounded batch using each segment_id as the idempotency key."""
|
||||
|
||||
body = self._transcription_identity(
|
||||
diagnosis_id, call_record_id, transcription_session_id
|
||||
)
|
||||
normalized: list[dict[str, Any]] = []
|
||||
if len(segments) > 50:
|
||||
raise ValueError("at most 50 transcript segments may be submitted at once")
|
||||
for segment in segments:
|
||||
segment_id = str(segment.get("segment_id") or "").strip()
|
||||
text = str(segment.get("text") or "").strip()
|
||||
if not segment_id or len(segment_id) > 160:
|
||||
raise ValueError("transcript segment_id is invalid")
|
||||
if not text or len(text) > 4_000:
|
||||
raise ValueError("transcript text is invalid")
|
||||
normalized.append(
|
||||
{
|
||||
"segment_id": segment_id,
|
||||
"speaker_user_id": str(segment.get("speaker_user_id") or "")[:160],
|
||||
"speaker_role": str(segment.get("speaker_role") or "unknown")[:20],
|
||||
"timestamp": max(int(segment.get("timestamp") or 0), 0),
|
||||
"text": text,
|
||||
}
|
||||
)
|
||||
if not normalized:
|
||||
raise ValueError("at least one transcript segment is required")
|
||||
body["segments"] = normalized
|
||||
return self.client.post("tcm.diagnosis/upsertCallTranscriptSegments", body)
|
||||
|
||||
def finish_call_transcription(
|
||||
self,
|
||||
diagnosis_id: int,
|
||||
call_record_id: int | str,
|
||||
transcription_session_id: str,
|
||||
expected_segment_count: int,
|
||||
*,
|
||||
status: str = "completed",
|
||||
) -> Any:
|
||||
"""Finalize a transcript; repeated requests use the same session identity."""
|
||||
|
||||
body = self._transcription_identity(
|
||||
diagnosis_id, call_record_id, transcription_session_id
|
||||
)
|
||||
clean_status = status.strip().lower()
|
||||
if clean_status not in {"completed", "partial", "failed"}:
|
||||
raise ValueError("transcription status is invalid")
|
||||
if expected_segment_count < 0:
|
||||
raise ValueError("expected_segment_count must not be negative")
|
||||
body.update(
|
||||
{
|
||||
"expected_segment_count": expected_segment_count,
|
||||
"status": clean_status,
|
||||
}
|
||||
)
|
||||
return self.client.post("tcm.diagnosis/finishCallTranscription", body)
|
||||
|
||||
# Compatibility aliases keep UI naming independent from endpoint history.
|
||||
def my_self(self) -> Session:
|
||||
@@ -2402,6 +2656,26 @@ def _require_mapping(value: object, endpoint: str) -> Mapping[str, Any]:
|
||||
return value
|
||||
|
||||
|
||||
def _client_request(
|
||||
client: Any,
|
||||
method: str,
|
||||
endpoint: str,
|
||||
payload: Mapping[str, Any] | None = None,
|
||||
*,
|
||||
timeout: float | None = None,
|
||||
) -> Any:
|
||||
"""Call get/post, ignoring timeout kwargs that test doubles do not accept."""
|
||||
|
||||
fn = getattr(client, method)
|
||||
params = dict(payload or {})
|
||||
try:
|
||||
if timeout is None:
|
||||
return fn(endpoint, params)
|
||||
return fn(endpoint, params, timeout=timeout)
|
||||
except TypeError:
|
||||
return fn(endpoint, params)
|
||||
|
||||
|
||||
def _material_kind(
|
||||
material_type: str,
|
||||
) -> Literal["image", "video", "file"]:
|
||||
|
||||
Reference in New Issue
Block a user