Create app.py

app.py

@@ -0,0 +1,42 @@
+from fastapi import FastAPI, Request
+from transformers import MarianMTModel, MarianTokenizer
+import torch
+
+app = FastAPI()
+
+MODEL_MAP = {
+    "fr": "Helsinki-NLP/opus-mt-en-fr",
+    "de": "Helsinki-NLP/opus-mt-en-de"
+}
+
+MODEL_CACHE = {}
+
+def load_model(model_id):
+    if model_id not in MODEL_CACHE:
+        tokenizer = MarianTokenizer.from_pretrained(model_id)
+        model = MarianMTModel.from_pretrained(model_id).to("cpu")
+        MODEL_CACHE[model_id] = (tokenizer, model)
+    return MODEL_CACHE[model_id]
+
+@app.post("/translate")
+async def translate(request: Request):
+    data = await request.json()
+    text = data.get("text")
+    target_lang = data.get("target_lang")
+
+    if not text or not target_lang:
+        return {"error": "Missing text or target_lang"}
+
+    model_id = MODEL_MAP.get(target_lang)
+    if not model_id:
+        return {"error": f"No model for '{target_lang}'"}
+
+    tokenizer, model = load_model(model_id)
+    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True).to(model.device)
+    outputs = model.generate(**inputs)
+    return {"translation": tokenizer.decode(outputs[0], skip_special_tokens=True)}
+
+# Required for FastAPI to run on HF Spaces
+import uvicorn
+if __name__ == "__main__":
+    uvicorn.run("app:app", host="0.0.0.0", port=7860)