Spaces:
Runtime error
Runtime error
File size: 4,177 Bytes
08b7f89 |
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 |
import requests
# from flask_cors import CORS
from groq import Groq
# CORS()
# GROQ_API_URL = "https://api.groq.com/translate" # استبدل هذا بعنوان API الخاص بـ Groq
GROQ_API_KEY = "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" # ضع هنا مفتاح API الخاص بك
client = Groq(api_key=GROQ_API_KEY)
def translate_texts_groq(texts, target_language="ar"):
"""
Translates a list of texts to the target language using Groq.
:param texts: List of texts to translate
:param target_language: Target language code
:return: List of translated texts
"""
# headers = {
# "Authorization": f"Bearer {GROQ_API_KEY}",
# "Content-Type": "application/json"
# }
translated_texts = []
# for text in texts:
# payload = {
# "source_language": "en", # تأكد من ضبط لغة المصدر
# "target_language": target_language,
# "text": text
# }
# response = requests.post(GROQ_API_URL, json=payload, headers=headers)
# if response.status_code == 200:
# translated_text = response.json().get("translated_text")
# translated_texts.append(translated_text)
# else:
# # في حالة حدوث خطأ، يمكنك التعامل معه هنا
# translated_texts.append(text) # احتفظ بالنص الأصلي في حال فشل الترجمة
chat_completion = client.chat.completions.create(
messages=[
{
"role": "user",
"content": f"Translate the text fllowing into Arabic language:{texts}",
}
],
model="llama3-8b-8192",
)
translated_texts.append(chat_completion.choices[0].message.content)
return translated_texts
def translate_content(content, target_language):
"""
Translates the content of a markdown file, preserving non-translatable parts.
:param content: Markdown content
:param target_language: Target language code
:return: Translated content
"""
translatable_texts = extract_translatable_text(content)
translated_texts = translate_texts_groq(translatable_texts, target_language)
# Reconstruct the content with translated texts
for original, translated in zip(translatable_texts, translated_texts):
content = content.replace(original, translated)
return content
# from transformers import MarianMTModel, MarianTokenizer
# # Initialize the model and tokenizer
# model_name = 'Helsinki-NLP/opus-mt-en-<target_language>' # Replace <target_language> with the target language code
# model = MarianMTModel.from_pretrained(model_name)
# tokenizer = MarianTokenizer.from_pretrained(model_name)
# def translate_texts(texts, target_language):
# """
# Translates a list of texts to the target language.
# :param texts: List of texts to translate
# :param target_language: Target language code
# :return: List of translated texts
# """
# translated_texts = []
# for text in texts:
# inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
# translated = model.generate(**inputs)
# translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
# translated_texts.append(translated_text)
# return translated_texts
# def translate_content(content, target_language):
# """
# Translates the content of a markdown file, preserving non-translatable parts.
# :param content: Markdown content
# :param target_language: Target language code
# :return: Translated content
# """
# translatable_texts = extract_translatable_text(content)
# translated_texts = translate_texts(translatable_texts, target_language)
# # Reconstruct the content with translated texts
# for original, translated in zip(translatable_texts, translated_texts):
# content = content.replace(original, translated)
# return content
|