feat: add api endpoint

app.py

@@ -14,8 +14,8 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 classifier = pipeline("text-classification", model="saiteki-kai/QA-DeBERTa-v3-large")
 
-@spaces.GPU(duration=60)
-def generate(prompts):
+@spaces.GPU()
+def generate(prompts: list[str]) -> tuple[list[str], list[dict[str, float]]]:
     messages = [[{"role": "user", "content": message}] for message in prompts]
 
     texts = tokenizer.apply_chat_template(
@@ -37,6 +37,8 @@ def generate(prompts):
 
     return responses, classifier([text + "[SEP]" + response for text, response in zip(texts, responses)])
 
+with gr.Blocks() as demo:
+    gr.Markdown("Welcome")
+    gr.api(generate, api_name="predict")
 
-demo = gr.Interface(fn=generate, inputs=gr.Text(), outputs=gr.Text())
 demo.launch()