44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
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# -*-coding:utf-8-*-
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import os
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os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
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import json
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from flask import Flask, request, make_response
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from logzero import logger
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current_path = os.path.dirname(os.path.abspath(__file__)) # for local
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# current_path = "/app" # for docker
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logger.info(f"{current_path}")
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from models.lgb_predict import load_config, load_history_data, load_lgb_model, predict
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lgb_model = load_lgb_model(model_path=f"{current_path}/model_files/hour_best_model.txt")
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object_cols = load_config(f"{current_path}/config/object_cols.json")
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history_data = load_history_data(data_path=f"{current_path}/data/data_sample.csv")
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emission_factors = load_config(f"{current_path}/config/emission_factor.json")
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app = Flask(__name__)
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@app.route('/emission/', methods=["POST"])
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def run_case_check():
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resp_info = dict()
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if request.method == "POST":
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data = request.json.get('data')
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logger.info(data)
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if data is not None and len(data) != 0:
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rst = predict(history_data, data, lgb_model, object_cols, emission_factors)
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resp_info["code"] = 200
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resp_info["data"] = rst
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else:
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resp_info["msg"] = "Input is None, please check !"
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resp_info["code"] = 406
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resp = make_response(json.dumps(resp_info))
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resp.status_code = 200
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return resp
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if __name__ == '__main__':
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app.run(host='0.0.0.0', port=8788, debug=False)
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