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)