Spaces:
Runtime error
Runtime error
File size: 2,458 Bytes
6424126 |
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 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 |
import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore
import io
from fastapi import FastAPI, File, UploadFile
from werkzeug.utils import secure_filename
import speech_recognition as sr
import subprocess
import os
import requests
import random
import pandas as pd
from pydub import AudioSegment
from datetime import datetime
from datetime import date
import numpy as np
from sklearn.ensemble import RandomForestRegressor
import shutil
import json
# from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
from pydantic import BaseModel
from typing import Annotated
# from transformers import BertTokenizerFast, EncoderDecoderModel
import torch
import re
from transformers import AutoTokenizer, T5ForConditionalGeneration
from fastapi import Form
class Query(BaseModel):
text: str
WHITESPACE_HANDLER = lambda k: re.sub('\s+', ' ', re.sub('\n+', ' ', k.strip()))
model_name = "JulesBelveze/t5-small-headline-generator"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = T5ForConditionalGeneration.from_pretrained(model_name)
from fastapi import FastAPI, Request, Depends, UploadFile, File
from fastapi.exceptions import HTTPException
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
# now = datetime.now()
# UPLOAD_FOLDER = '/files'
# ALLOWED_EXTENSIONS = {'txt', 'pdf', 'png',
# 'jpg', 'jpeg', 'gif', 'ogg', 'mp3', 'wav'}
app = FastAPI()
app.add_middleware(
CORSMiddleware,
allow_origins=['*'],
allow_credentials=True,
allow_methods=['*'],
allow_headers=['*'],
)
# cred = credentials.Certificate('key.json')
# app1 = firebase_admin.initialize_app(cred)
# db = firestore.client()
# data_frame = pd.read_csv('data.csv')
@app.on_event("startup")
async def startup_event():
print("on startup")
@app.post("/")
async def get_answer(q: Query ):
long_text = q.text
input_ids = tokenizer(
[WHITESPACE_HANDLER(long_text)],
return_tensors="pt",
padding="max_length",
truncation=True,
max_length=384
)["input_ids"]
output_ids = model.generate(
input_ids=input_ids,
max_length=84,
no_repeat_ngram_size=2,
num_beams=4
)[0]
summary = tokenizer.decode(
output_ids,
skip_special_tokens=True,
clean_up_tokenization_spaces=False
)
return summary
return "hello"
|