Create app.py

app.py

@@ -0,0 +1,23 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from fastapi import FastAPI, Request
+import uvicorn
+
+model_name = "ibm-granite/granite-3.2-8b-instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+app = FastAPI()
+
+@app.post("/generate")
+async def generate_text(request: Request):
+    data = await request.json()
+    prompt = data.get("prompt", "")
+
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(**inputs, max_new_tokens=150)
+
+    response_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return {"output": response_text}
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7860)