Spaces:
Runtime error
Runtime error
File size: 2,347 Bytes
ad78747 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
import uvicorn
from fastapi import FastAPI, Form, Request
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates
from inference import inferenceAPI
# from transformers import RobertaTokenizerFast, EncoderDecoderModel
# ------- MODELE HUGGING FACE QUI MARCHE BIEN ------------------------------------
# device = 'cuda' if torch.cuda.is_available() else 'cpu'
# ckpt = 'mrm8488/camembert2camembert_shared-finetuned-french-summarization'
# tokenizer = RobertaTokenizerFast.from_pretrained(ckpt)
# model = EncoderDecoderModel.from_pretrained(ckpt).to(device)
# def generate_summary(text):
# inputs = tokenizer([text], padding="max_length", truncation=True, max_length=512, return_tensors="pt")
# input_ids = inputs.input_ids.to(device)
# attention_mask = inputs.attention_mask.to(device)
# output = model.generate(input_ids, attention_mask=attention_mask)
# return tokenizer.decode(output[0], skip_special_tokens=True)
# ----------------------------------------------------------------------------------
# ------ NOTRE MODELE --------------------------------------------------------------
# appel de la fonction inférence, adaptée pour une entrée txt
def summarize(text: str):
return " ".join(inferenceAPI(text))
# ----------------------------------------------------------------------------------
# -------- API ---------------------------------------------------------------------
app = FastAPI()
# static pour tout ce qui est css
templates = Jinja2Templates(directory="templates")
app.mount("/static", StaticFiles(directory="static"), name="static")
app.mount("/templates", StaticFiles(directory="templates"), name="templates")
@app.get("/")
async def index(request: Request):
return templates.TemplateResponse("index.html.jinja", {"request": request})
# pour donner les predictions
@app.post("/")
async def prediction(request: Request, text: str = Form(...)):
summary = summarize(text)
return templates.TemplateResponse(
"index.html.jinja", {"request": request, "text": text, "summary": summary}
)
# ------------------------------------------------------------------------------------
# pour lancer le serveur et le reload à chaque changement sauvegardé dans le repo
if __name__ == "__main__":
uvicorn.run("api:app", port=8000, reload=True)
|