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import os
from flask import *
from routes.helpers import configFile
from routes import *
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
from random import randint
#initing
app = Flask(__name__)
VERSION = '1.0 build128'
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 notfound_handler(e): return render_template('notfound.html')
@app.errorhandler(405)
def methodnotallowed_handler(e): return render_template('methodnotallowed.html')
@app.errorhandler(500)
def internalservererror_handler(e): return render_template('intervalservererror.html')
@app.errorhandler(502)
def badgateway_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'])
@app.route('/jokes/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'])
@app.route('/jokes/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('/system/api/v1/info', 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)
###############
#JOKES API
@app.route('/jokes/api/v1/get', methods=['POST'])
def getJoke(): return jokes.getJoke(request)
@app.route('/jokes/api/v1/sources', methods=['POST'])
def getJokesSources(): return jokes.getSources(request)
###############
#HOLIDAYS API (dont wanna document it)
@app.route('/holidays/api/v1/get', methods=['POST'])
def getHolidays(): return holidays.getHolidays(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 = helpers.getFromRequest(request, "text")
if not 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 = helpers.getFromRequest(request, "text")
if not 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
##############
# GENERATE TEXT
generator = pipeline("text-generation", model="IlyaGusev/rugpt_large_turbo_instructed")
@app.route('/text/api/v1/generate', methods=['POST'])
def generateText():
try:
text = helpers.getFromRequest(request, "text")
if not text: return {"status": "error", "details": { "error_code": 101, "error_details": "No text provided" }} , 400
result = generator(text, min_length=512, max_length=1512, return_full_text=False, do_sample=bool(randint(0,1)), temperature=float(randint(5,15))/10.0, max_time=15)
return {"status": "pass", "result": result[0]["generated_text"]}
except Exception as e: return {"status": "error", "details": { "error_code": 123, "error_details": str(e).replace("\n", " | ") }} , 400
##############
# INIT APP
if __name__ == "__main__":
config = configFile()
with open(config['config-path'], "w", encoding="utf-8") as outfile:
config['buildVersion'] = VERSION
json.dump(config, outfile)
with open(config['openapi-yaml-path'], "r+", encoding="utf-8") 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)