from fastapi import FastAPI
from pydantic import BaseModel
from model.model import predict_pipeline
from model.model import __version__ as model_version

from transformers import AutoTokenizer, AutoModelForSequenceClassification
from transformers import TextClassificationPipeline

import requests

app = FastAPI()


class TextIn(BaseModel):
    text: str


class PredictionOut(BaseModel):
    language: str

class TopicClassificationOut(BaseModel):
    result: str


@app.get("/")
def home():
    return {"health_check": "OK", "model_version": model_version}


@app.post("/predict", response_model=PredictionOut)
def predict(payload: TextIn):
    language = predict_pipeline(payload.text)
    return {"language": language}

@app.post("/TopicClassification", response_model=TopicClassificationOut)
def TopicClassification(payload: TextIn):
    model_name = 'lincoln/flaubert-mlsum-topic-classification'
    
    loaded_tokenizer = AutoTokenizer.from_pretrained(model_name)
    loaded_model = AutoModelForSequenceClassification.from_pretrained(model_name)
    
    nlp = TextClassificationPipeline(model=loaded_model, tokenizer=loaded_tokenizer)

    # print(payload.text)
    # text = re.sub(r'[!@#$(),\n"%^*?\:;~`0-9]', " ", payload.text)
    text = "Le Bayern Munich prend la grenadine."
    text = re.sub(r"[[]]", " ", text)
    text = text.lower()
    
    result = nlp(text, truncation=True)
    return {"result": result}

# https://hinacortus-api-knowyouraudience.hf.space/whichsocial/myspace
# https://hinacortus-api-knowyouraudience.hf.space/whichsocial/www.reddit.com
@app.get("/whichsocial/{request}")
def whichsocial(request):
    socialnetwork = "not found"
    if ('http' in request or 'https' in request or 'www' in request or '.com' in request or '.fr' in request):
        website = "ok"
        listsocialnetwork = ['facebook', 'youtube', 'myspace', 'linkedin', 'twitter', 'instagram', 'github',
                            'reddit', 'picterest', 'discord', '']
        for partsplit in request.split('/'):
            for part in partsplit.split('.'):
                for sn in listsocialnetwork:
                    if sn == part:
                        print('found part ', sn)
                        socialnetwork = sn
    else:
        website = "it's not a website link !"
    userprofile = 'me'
    return {"request": request, "website":website, "social_network": socialnetwork, "user_profile": userprofile}

# https://hinacortus-api-knowyouraudience.hf.space/content/https://www.20minutes.fr/auto/4039741-20230604-vente-encheres-citroen-2cv-bois-unique-monde-adjugee-210-000-euros
@app.get("/content/{request}")
def analyzecontent(request):
    content = requests.get(request.text)
    len_content = len(content.split(' '))
    return {"number_of_word":len_content}