IDKHowToCodeFr/tinyml-backend

1import asyncio2from typing import AsyncGenerator3from simulator import PatientDataSimulator4from inference import evaluate5from schemas import PatientData6 7class TelemetryStreamer:8    """9    Deep Module for Telemetry Streaming.10    Encapsulates the simulator lifecycle, ML inference threading, and payload formatting.11    Provides a simple async generator interface.12    """13    def __init__(self, ensemble_model):14        self.ensemble_model = ensemble_model15        self.simulator = PatientDataSimulator()16 17    async def stream(self) -> AsyncGenerator[dict, None]:18        async for state in self.simulator.run():19            data = PatientData(**state)20            21            # Offload ML inference to thread pool to avoid blocking the event loop22            prediction_result = await asyncio.to_thread(evaluate, self.ensemble_model, data)23            24            front_pred = None25            if "error" not in prediction_result:26                front_pred = {27                    "is_at_risk": 1 if prediction_result.get("prediction") else 0,28                    "label": prediction_result.get("prediction_label"),29                    "confidence": prediction_result.get("probability"),30                    "disease_probs": prediction_result.get("disease_probs", {})31                }32            33            yield {34                "sensor_data": data.model_dump(),35                "prediction": front_pred36            }37