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# from fastapi import FastAPI, File, UploadFile
# from transformers import MarianMTModel, MarianTokenizer
# app = FastAPI()
# # Load the translation model and tokenizer
# model_name = "Helsinki-NLP/opus-mt-de-en"
# model = MarianMTModel.from_pretrained(model_name)
# tokenizer = MarianTokenizer.from_pretrained(model_name)
# @app.get("/")
# def read_root():
# return {"message": "Welcome to the German to English Translation API!"}
# @app.post("/translate/")
# async def translate_text(text: str):
# # Perform translation
# input_text = f"translate German to English: {text}"
# # Tokenize input text
# input_ids = tokenizer.encode(input_text, return_tensors="pt")
# # Generate translation
# with torch.no_grad():
# output_ids = model.generate(input_ids)
# # Decode the output
# translated_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
# return {"translated_text": translated_text}
from fastapi import FastAPI
from transformers import MarianMTModel, MarianTokenizer
import torch
app = FastAPI()
# Load the translation model and tokenizer
model_name = "Helsinki-NLP/opus-mt-de-en"
model = MarianMTModel.from_pretrained(model_name)
tokenizer = MarianTokenizer.from_pretrained(model_name)
@app.get("/")
def read_root():
return {"message": "Welcome to the German to English Translation API!"}
@app.post("/translate/")
async def translate_text(input_text: dict):
# Extract the input text from the JSON payload
text = input_text.get("text", "")
# Perform translation
input_text = f"translate German to English: {text}"
# Tokenize input text
input_ids = tokenizer.encode(input_text, return_tensors="pt")
# Generate translation
with torch.no_grad():
output_ids = model.generate(input_ids)
# Decode the output
translated_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
return {"translated_text": translated_text}
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