wehub-resource-sync
48 lines
1.3 KiB
Python
48 lines
1.3 KiB
Python
import requests
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# __serve_example_begin__
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import starlette
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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from ray import serve
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@serve.deployment
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class Translator:
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def __init__(self):
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self.tokenizer = AutoTokenizer.from_pretrained("t5-small")
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self.model = AutoModelForSeq2SeqLM.from_pretrained("t5-small")
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def translate(self, text: str) -> str:
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input_ids = self.tokenizer(
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f"translate English to German: {text}", return_tensors="pt"
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).input_ids
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output_ids = self.model.generate(
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input_ids, num_beams=4, early_stopping=True, max_length=300
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)
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return self.tokenizer.decode(
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output_ids[0], skip_special_tokens=True, clean_up_tokenization_spaces=False
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)
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async def __call__(self, req: starlette.requests.Request):
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req = await req.json()
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return self.translate(req["text"])
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app = Translator.bind()
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# __serve_example_end__
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serve.run(app, name="app2", route_prefix="/translate")
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# __request_begin__
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text = "Hello, the weather is quite fine today!"
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resp = requests.post("http://localhost:8000/translate", json={"text": text})
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print(resp.text)
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# 'Hallo, das Wetter ist heute ziemlich gut!'
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# __request_end__
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assert resp.text == "Hallo, das Wetter ist heute ziemlich gut!"
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