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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) | |