import sys
import logging
import gradio as gr
# from flask import Flask, jsonify, request
from similarity import LanguageModel, Similarity

# app = Flask(__name__)

PRE_TRAINED_MODEL_PATH = './model'

def init_logger():
    root_logger= logging.getLogger()
    root_logger.setLevel(logging.INFO)
    root_logger.addHandler(logging.StreamHandler(sys.stdout))
    logging.info("Logger initialized")

init_logger()

lm = LanguageModel(pre_trained_model_path=PRE_TRAINED_MODEL_PATH, max_len=1000)
similarity = Similarity(featurize_fn=lm.featurize)

# @app.route('/getSimilarity/', methods=['GET', 'POST'])
# def process_request():
#     text1 = request.values.get('text1')
#     text2 = request.values.get('text2')
#     score = similarity.get_score(text1, text2)

#     response = {'similarity score': score}
#     response = jsonify(response)
#     response.headers.add("Access-Control-Allow-Origin", "*")
#     return response

def process(text1, text2): #request: gr.Request
    # text1 = request.query_params.get("text1")
    # text2 = request.query_params.get("text2")
    score = similarity.get_score(text1, text2)
    response = {'similarity score': score}
    return response

demo = gr.Interface(
    fn=process,
    inputs=[
        gr.Textbox(lines=2),
        gr.Textbox(lines=2),
    ],
    outputs=gr.JSON(),
    allow_flagging="never"
)
    
if __name__ == "__main__":
    # app.run(host="0.0.0.0", port=7860)
    demo.launch(server_name="0.0.0.0", server_port=7860,)