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import requests
from transformers import pipeline
import nltk
from nltk import sent_tokenize
from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
from transformers import pipeline
# nltk.download('punkt') # Run only once
tokenizer = MBart50TokenizerFast.from_pretrained("SnypzZz/Llama2-13b-Language-translate", src_lang="en_XX")
#pipe = pipeline("text2text-generation", model="SnypzZz/Llama2-13b-Language-translate", tokenizer=tokenizer)
model = None
model_loaded = False
api_token_header = ""
with open('./secret.py', 'r') as f:
api_token_header = f.read()
def load_model():
global model, model_loaded
model = MBartForConditionalGeneration.from_pretrained("SnypzZz/Llama2-13b-Language-translate")
model_loaded =True
return model
def translation(text,dest_lang,dest_lang_code, src_lang_code):
if(dest_lang_code == src_lang_code):
return "Please select different languages to translate between."
# headers = {"Authorization": f"Bearer {secrets_sih.api_token_header}"}
headers = {"Authorization": f"Bearer {api_token_header}"}
# Bengali Done
if(dest_lang == "Bengali" and src_lang_code == "en_XX"):
API_URL = "https://api-inference.huggingface.co/models/csebuetnlp/banglat5_nmt_en_bn"
def query(payload):
response = requests.post(API_URL, headers=headers, json=payload)
return response.json()
output = query({
"inputs": text,
})
print(output)
return output[0]['translation_text']
else:
global model
if model:
pass
else:
model = load_model()
loaded_model = model
tokenizer = MBart50TokenizerFast.from_pretrained("SnypzZz/Llama2-13b-Language-translate", src_lang=src_lang_code)
#model_inputs = tokenizer(text, return_tensors="pt")
loaded_model_inputs = tokenizer(text, return_tensors="pt")
# translate
generated_tokens = loaded_model.generate(
**loaded_model_inputs,
forced_bos_token_id=tokenizer.lang_code_to_id[dest_lang_code]
)
output = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
print(output)
return output[0]
def main_translation(text,dest_lang_code,src_lang_code):
codes = {"en_XX":"English","bn_IN":"Bengali", "en_GB":"English","gu_IN":"Gujarati","hi_IN":"Hindi","ta_IN":"Tamil","te_IN":"Telugu","mr_IN":"Marathi"}
dest_lang = codes[dest_lang_code]
src_lang = codes[src_lang_code]
sentences = sent_tokenize(text)
output = ""
for line in sentences:
output += translation(line,dest_lang,dest_lang_code, src_lang_code)
return {"output":output}
print(main_translation("hello world", "hi_IN", "en_XX")) |