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import requests
from PIL import Image
import io
import base64
# FILTER
import re
def clean_string(input_string):
# Lowercase the string and remove non-alphabetic characters
cleaned_string = re.sub(r'[^a-z]', '', input_string.lower())
return cleaned_string
with open("invalid_searches.txt", 'r') as f:
invalid = f.readlines()
invalid = [clean_string(i) for i in invalid]
invalid = [i for i in invalid if i != ""]
invalid.append("")
def check_invalid(word):
word = clean_string(word)
return word in invalid
# GETTING THE KEYS
# from keys import *
import os
HF_TOKEN = os.environ.get('HF_TOKEN')
DICTIONARY_API_KEY = os.environ.get('DICTIONARY_API_KEY')
def get_definition(word):
url = 'https://siwar.ksaa.gov.sa/api/alriyadh/exact-search'
headers = {
'accept': 'application/json',
'apikey': DICTIONARY_API_KEY
}
params = {'query': word}
response = requests.get(url, params=params, headers=headers)
print(response)
# word not found
define = response.json()
if len(define) == 0:
return "", "", []
define = define[0]
word = define['lemma']['formRepresentations'][0]['form']
english = None
meanings_examples = []
for i, sense in enumerate(define['senses']):
meaning = sense['definition']['textRepresentations'][0]['form']
example = None
for ex in sense['examples']:
if ex['form'] != "":
example = ex['form']
for ex in sense['translations']:
if ex['form'] != "" and not english:
english = ex['form']
meanings_examples.append({
"i": i+1,
"meaning": meaning,
"example": example
})
return word, english, meanings_examples
def get_translation(word):
if word == "":
return ""
API_URL = "https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-ar-en"
headers = {"Authorization": f"Bearer {HF_TOKEN}"}
response = requests.post(API_URL, headers=headers, json={
"inputs": word,
})
print(response)
response = response.json()
print(response)
# error in response
if type(response) == dict:
return ""
return response[0]['translation_text']
def get_image(word):
print(word)
if check_invalid(word):
return None
# blank image
return "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII="
API_URL = "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5"
headers = {"Authorization": f"Bearer {HF_TOKEN}"}
response = requests.post(API_URL, headers=headers, json={
"inputs": word,
})
print(response)
image_bytes = response.content
image = Image.open(io.BytesIO(image_bytes))
# Convert image to base64
image_base64 = ""
with io.BytesIO() as buffer:
image.save(buffer, format="JPEG") # You can change the format if your image is in a different format
image_base64 = base64.b64encode(buffer.getvalue()).decode('utf-8')
return image_base64
if __name__ == "__main__":
pass
# word, meanings_examples = get_definition('fsdf')
# print(word, meanings_examples)