Update app.py

app.py

@@ -4,7 +4,7 @@ from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
 from transformers import pipeline, set_seed
 
-# Tambahkan ini 👇
+# Direktori cache Hugging Face
 os.environ["TRANSFORMERS_CACHE"] = "/tmp/huggingface"
 
 app = FastAPI(title="StemdjaGPT", version="1.0")
@@ -25,14 +25,63 @@ set_seed(42)
 
 class PromptInput(BaseModel):
     prompt: str
-    max_length: int = 100
+    max_tokens: int = 256       # ganti nama parameter agar lebih jelas
     temperature: float = 0.8
 
 @app.post("/generate")
 def generate_text(item: PromptInput):
     result = generator(
         item.prompt,
-        max_length=item.max_length,
+        max_new_tokens=item.max_tokens,  # pakai max_new_tokens, bukan max_length
+        do_sample=True,
+        temperature=item.temperature,
+        top_p=0.9,
+        truncation=True
+    )[0]["generated_text"]
+
+    return {
+        "input": item.prompt,
+        "output": result.strip()
+    }
+
+@app.get("/")
+def home():
+    return {"message": "StemdjaGPT siap menghasilkan teks Bahasa Indonesia"}
+import os
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from transformers import pipeline, set_seed
+
+# Direktori cache Hugging Face
+os.environ["TRANSFORMERS_CACHE"] = "/tmp/huggingface"
+
+app = FastAPI(title="StemdjaGPT", version="1.0")
+
+# Middleware CORS
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+MODEL = "cahya/gpt2-small-indonesian-522M"
+generator = pipeline("text-generation", model=MODEL, tokenizer=MODEL)
+
+set_seed(42)
+
+class PromptInput(BaseModel):
+    prompt: str
+    max_tokens: int = 256       # ganti nama parameter agar lebih jelas
+    temperature: float = 0.8
+
+@app.post("/generate")
+def generate_text(item: PromptInput):
+    result = generator(
+        item.prompt,
+        max_new_tokens=item.max_tokens,  # pakai max_new_tokens, bukan max_length
         do_sample=True,
         temperature=item.temperature,
         top_p=0.9,