Update app.py

app.py

@@ -1,38 +1,32 @@
 from transformers import AutoModelForCausalLM, AutoTokenizer
-from fastapi import FastAPI
 
-app = FastAPI()
+model_name = "Qwen/QwQ-32B-Preview"
 
-@app.get("/")
-def greet_json():
-    model_name = "Qwen/QwQ-32B-Preview"
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
 
-    model = AutoModelForCausalLM.from_pretrained(
-        model_name,
-        torch_dtype="auto",
-        device_map="auto"
-    )
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
+prompt = "How many r in strawberry."
+messages = [
+    {"role": "system", "content": "You are a helpful and harmless assistant. You are Qwen developed by Alibaba. You should think step-by-step."},
+    {"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
 
-    prompt = "How many r in strawberry."
-    messages = [
-        {"role": "system", "content": "You are a helpful and harmless assistant. You are Qwen developed by Alibaba. You should think step-by-step."},
-        {"role": "user", "content": prompt}
-    ]
-    text = tokenizer.apply_chat_template(
-        messages,
-        tokenize=False,
-        add_generation_prompt=True
-    )
-    model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+generated_ids = model.generate(
+    **model_inputs,
+    max_new_tokens=512
+)
+generated_ids = [
+    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
 
-    generated_ids = model.generate(
-        **model_inputs,
-        max_new_tokens=512
-    )
-    generated_ids = [
-        output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
-    ]
-
-    response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
-    return response
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]