Add application file

Dockerfile

@@ -0,0 +1,16 @@
+# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.9
+
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+WORKDIR /app
+
+COPY --chown=user ./requirements.txt requirements.txt
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+COPY --chown=user . /app
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -5,6 +5,7 @@ colorFrom: pink
 colorTo: indigo
 sdk: docker
 pinned: false
+app_port: 7860
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+from fastapi import FastAPI
+from pydantic import BaseModel, Field
+from typing import Optional
+from transformers import MarianMTModel, MarianTokenizer
+import datetime
+import logging
+
+logger = logging.getLogger("translate")
+logger.setLevel(logging.INFO)
+
+app = FastAPI(title="翻译服务")
+
+# 加载翻译模型
+MODEL_NAME = "Helsinki-NLP/opus-mt-tc-bible-big-zhx-en"
+logger.info(f"{datetime.datetime.now()} Loading model {MODEL_NAME}...")
+tokenizer = MarianTokenizer.from_pretrained(MODEL_NAME)
+model = MarianMTModel.from_pretrained(MODEL_NAME)
+logger.info(f"{datetime.datetime.now()} Model loaded.")
+
+class TranslateRequest(BaseModel):
+    text: str = Field(..., description="待翻译的中文文本")
+
+class TranslateResponse(BaseModel):
+    translated_text: str
+    detected_lang: Optional[str] = None
+
+@app.post("/api/translate", response_model=TranslateResponse)
+async def translate(req: TranslateRequest):
+    # tokenizer 会处理编码
+    batch = tokenizer([req.text], return_tensors="pt", padding=True)
+    translated = model.generate(**batch)
+    output = tokenizer.decode(translated[0], skip_special_tokens=True)
+
+    return TranslateResponse(
+        translated_text=output,
+        detected_lang=None  # 简单翻译版暂不返回检测语言
+    )

requirements.txt

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+fastapi
+uvicorn[standard]
+transformers
+torch
+