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import os |
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import pickle |
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import requests |
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from dotenv import load_dotenv |
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from flask import Flask, render_template, request |
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from pydantic import BaseModel, Field, PositiveFloat |
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app = Flask(__name__) |
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MODEL = pickle.load(open("model.sav", "rb")) |
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PRICE_BASE = 10**5 |
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load_dotenv(override=False) |
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API_HOST = os.environ.get("API_HOST", "localhost") |
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class FormQuery(BaseModel): |
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med_inc: PositiveFloat = Field(..., validation_alias="MedInc") |
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house_age: PositiveFloat = Field(..., validation_alias="HouseAge") |
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ave_rooms: PositiveFloat = Field(..., validation_alias="AveRooms") |
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ave_bedrms: PositiveFloat = Field(..., validation_alias="AveBedrms") |
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population: PositiveFloat = Field(..., validation_alias="Population") |
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ave_occup: PositiveFloat = Field(..., validation_alias="AveOccup") |
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latitude: float = Field(..., validation_alias="Latitude") |
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longitude: float = Field(..., validation_alias="Longitude") |
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@app.route("/", methods=["GET"]) |
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def california_index(): |
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return render_template("index.html") |
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@app.route("/predict/", methods=["POST"]) |
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def local_model_result(): |
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form_query = FormQuery(**request.form.to_dict(flat=True)) |
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reg = MODEL.predict( |
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[ |
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[ |
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form_query.med_inc, |
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form_query.house_age, |
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form_query.ave_rooms, |
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form_query.ave_bedrms, |
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form_query.population, |
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form_query.ave_occup, |
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form_query.latitude, |
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form_query.longitude, |
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] |
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] |
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)[0] |
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return render_template("prediction.html", price=reg * PRICE_BASE) |
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@app.route("/predict_from_api/", methods=["POST"]) |
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def api_result(): |
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model_list = requests.get(f"http://{API_HOST}:8000/model/list/").json() |
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if len(model_list) == 0: |
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raise Exception("No model could be retrieved from the model registry") |
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best_model = sorted(model_list, key=lambda d: d["rse"])[0] |
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app.logger.debug(f"Best model retrieved : {best_model}") |
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api_response = requests.post( |
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f"http://{API_HOST}:8000/model/predict/", |
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json={ |
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**{"train_id": best_model["train_id"]}, |
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**FormQuery(**request.form.to_dict(flat=True)).model_dump(), |
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}, |
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) |
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response = api_response.json() |
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app.logger.debug(response) |
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return render_template("prediction.html", price=response["reg"] * PRICE_BASE) |
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if __name__ == "__main__": |
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app.debug = True |
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app.run(host="0.0.0.0", port=5000, debug=True) |
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