Dualmind-Assistant
128 lines
3.3 KiB
Python
128 lines
3.3 KiB
Python
from pathlib import Path
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import json
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from typing import Any, Dict, List, Optional
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from fastapi import FastAPI, HTTPException
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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# --- Domain models ---
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class Answer(BaseModel):
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question_code: str
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value: Any
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class SessionCreate(BaseModel):
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language: str
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answers: List[Answer]
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class MtsPreparation(BaseModel):
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session_id: str
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proposed_presenting_flowchart: Optional[str] = None
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red_flag_indicators: List[str] = []
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suggested_priority_level: Optional[str] = None
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class QuestionOption(BaseModel):
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value: str
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label: str
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class Question(BaseModel):
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code: str
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type: str
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title: str
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options: Optional[List[QuestionOption]] = None
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min: Optional[int] = None
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max: Optional[int] = None
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class QuestionsResponse(BaseModel):
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language: str
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questions: List[Question]
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BASE_DIR = Path(__file__).resolve().parents[2]
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MTS_CONFIG_DIR = BASE_DIR / "mts-config"
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def load_questions(language: str) -> QuestionsResponse:
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"""Load questions configuration for the given language from mts-config.
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This keeps the triage logic data-driven and allows adding further
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languages by simply providing a new questions.<lang>.json file.
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"""
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file_path = MTS_CONFIG_DIR / f"questions.{language}.json"
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if not file_path.exists():
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raise HTTPException(status_code=404, detail=f"No question config for language '{language}'")
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with file_path.open("r", encoding="utf-8") as f:
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raw: Dict[str, Any] = json.load(f)
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return QuestionsResponse(**raw)
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app = FastAPI(title="Triage-Fragen API", version="0.2.0")
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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@app.get("/health")
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async def health() -> Dict[str, str]:
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return {"status": "ok"}
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@app.get("/questions/{language}", response_model=QuestionsResponse)
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async def get_questions(language: str) -> QuestionsResponse:
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"""Return the triage question configuration for the selected language."""
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return load_questions(language)
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@app.post("/sessions", response_model=MtsPreparation)
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async def create_session(payload: SessionCreate) -> MtsPreparation:
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"""Create a triage preparation proposal from the given answers.
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For now this implements a very small ruleset as a walking skeleton
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that we can refine step by step.
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"""
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session_id = "dummy-session-id"
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flowchart: Optional[str] = None
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red_flags: List[str] = []
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priority: Optional[str] = None
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for ans in payload.answers:
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if ans.question_code == "chief_complaint" and ans.value == "chest_pain":
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flowchart = "CHEST_PAIN"
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if ans.question_code == "breathlessness" and ans.value is True:
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red_flags.append("breathlessness")
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if (
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ans.question_code == "pain_intensity"
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and isinstance(ans.value, int)
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and ans.value >= 8
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):
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red_flags.append("severe_pain")
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if "breathlessness" in red_flags:
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priority = "RED_OR_ORANGE"
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return MtsPreparation(
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session_id=session_id,
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proposed_presenting_flowchart=flowchart,
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red_flag_indicators=red_flags,
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suggested_priority_level=priority,
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)
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