Create app.py

app.py

@@ -0,0 +1,36 @@
+from fastapi import FastAPI
+from pydantic import BaseModel
+from transformers import PegasusTokenizer, PegasusForConditionalGeneration
+import torch
+
+app = FastAPI()
+
+# Load mô hình
+model_name = "google/pegasus-cnn_dailymail"
+tokenizer = PegasusTokenizer.from_pretrained(model_name)
+model = PegasusForConditionalGeneration.from_pretrained(model_name)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model = model.to(device)
+
+# Schema input
+class InputText(BaseModel):
+    text: str
+
+# Hàm tóm tắt
+def summarize(text: str) -> str:
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=1024)
+    inputs = {k: v.to(device) for k, v in inputs.items()}
+    summary_ids = model.generate(
+        inputs["input_ids"],
+        max_length=150,
+        min_length=60,
+        num_beams=4,
+        no_repeat_ngram_size=3,
+        early_stopping=True
+    )
+    return tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+
+# Route API
+@app.post("/summarize")
+def summarize_api(input: InputText):
+    return {"summary": summarize(input.text)}