import os
from flask import *

from routes.helpers import configFile
from routes import *

from transformers import AutoTokenizer, AutoModelForSequenceClassification

#initing
app = Flask(__name__)
VERSION = '1.0 build120'
app.config['JSON_AS_ASCII'] = False

#error pages
@app.errorhandler(429)
def ratelimit_handler(e): return render_template('ratelimit.html')
@app.errorhandler(403)
def forbidden_handler(e): return render_template('forbidden.html')
@app.errorhandler(404)
def ratelimit_handler(e): return render_template('notfound.html')
@app.errorhandler(500)
def ratelimit_handler(e): return render_template('intervalservererror.html')
@app.errorhandler(502)
def ratelimit_handler(e): return render_template('badgateway.html')

#empty routes
@app.route('/yt/api/v1', methods=['POST'])
@app.route('/recognize/api/v1', methods=['POST'])
@app.route('/osu/api/v1', methods=['POST'])
def emptyPath(): return {} 

@app.route('/yt/api/v1/<path:path>', methods=['POST'])
@app.route('/recognize/api/v1/<path:path>', methods=['POST'])
@app.route('/osu/api/v1/<path:path>', methods=['POST'])
def emptyApiWA(path):  return {"status": "error", "error_code": 100, "error_details": "No method like that found"}
    
#icon
@app.route('/favicon.ico')

def favicon(): return send_from_directory(os.path.join(app.root_path, 'static'), 'favicon.ico', mimetype='image/vnd.microsoft.icon')

###############
#SITE ROUTES
@app.route('/')
def index(): return render_template('index.html') 
@app.route('/signatures/api/v1/get', methods=['POST'])
def systemInfo(): return siteRoutes.systemInfo()

###############
#YT SOUND API
@app.route('/yt/api/v1/search', methods=['POST'])
def search(): return ytApi.search(request)
@app.route('/yt/api/v1/get-full', methods=['POST'])
def getFull(): return ytApi.getFull(request)
@app.route('/yt/api/v1/get-preview', methods=['POST'])
def getPreview(): return ytApi.getPreview(request)

###############
#OSU API
@app.route('/osu/api/v1/find-song', methods=['POST'])
def findSong(): return osuApi.findSong(request)
@app.route('/osu/api/v1/get-beatmap', methods=['POST'])
def getBeatmap(): return osuApi.getBeatmap(request)
@app.route('/osu/api/v1/get-preview', methods=['POST'])
def getBMPreview(): return osuApi.getPreview(request)
@app.route('/osu/api/v1/get-full', methods=['POST'])
def getBMFull(): return osuApi.getFull(request)

###############
# LOAD MODELS
sa_t, sa_m = AutoTokenizer.from_pretrained("cardiffnlp/twitter-xlm-roberta-base-sentiment"), AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-xlm-roberta-base-sentiment")
tc_t, tc_m = AutoTokenizer.from_pretrained("EIStakovskii/xlm_roberta_base_multilingual_toxicity_classifier_plus"), AutoModelForSequenceClassification.from_pretrained("EIStakovskii/xlm_roberta_base_multilingual_toxicity_classifier_plus")

##############
# ANALYZE DATA API
# to understand which text is negative, positive or neutral
@app.route('/analyzeText/api/v1/sentiment', methods=['POST'])
def sentimentAnalys():
    try:
        text = request.form.get('text') or request.args.get('text') or request.values.get('text') or ""
        if text == "": 
            try: text = request.json.get('text') or ""
            except: pass
                
        if text == "": return {"status": "error", "details": { "error_code": 101, "error_details": "No text provided" }}
        
        inputs = sa_t(text, return_tensors="pt")

        outputs = sa_m(**inputs)
        logits = outputs.logits
        predicted_sentiment_index = logits.argmax(dim=1).item()
        predicted_sentiment = sa_m.config.id2label[predicted_sentiment_index]
    
        return {"status": "pass", "predicted_sentiment": predicted_sentiment}
    except Exception as e: return {"status": "error", "details": { "error_code": 123, "error_details": str(e).replace("\n", " | ") }}
@app.route('/analyzeText/api/v1/toxicity', methods=['POST'])
def toxicityAnalys():
    try:
        text = request.form.get('text') or request.args.get('text') or request.values.get('text') or ""
        if text == "": 
            try: text = request.json.get('text') or ""
            except: pass
                
        if text == "": return {"status": "error", "details": { "error_code": 101, "error_details": "No text provided" }} , 400

        inputs = tc_t(text, return_tensors="pt")
        
        outputs = tc_m(**inputs)
        logits = outputs.logits
        predicted_class = logits.argmax(dim=1).item()
        predicted_sentiment = True if str(tc_m.config.id2label[predicted_class]) == "LABEL_1" else False
    
        return {"status": "pass", "toxicity": predicted_sentiment}
    except Exception as e: return {"status": "error", "details": { "error_code": 123, "error_details": str(e).replace("\n", " | ") }} , 400

if __name__ == "__main__":
    config = configFile()
    with open(config['config-path'], "w") as outfile:
        config['buildVersion'] = VERSION
        json.dump(config, outfile)
    with open(config['openapi-yaml-path'], "r+") as outfile:
        info = outfile.read()
        outfile.seek(0)
        outfile.write(info.replace('$VERSION_VARIABLE$', VERSION))
        outfile.truncate()
    
    app.run(host="0.0.0.0", port=7860)