commit application files.

app.py

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+import gradio as gr
+import outlines
+import os, json
+from outlines.models import openai
+from outlines.generate import choice
+
+
+model_list = ["google/gemma-2b-it",
+            "Qwen/Qwen2.5-7B-Instruct-Turbo"]
+model = openai(
+    model_list[0],
+    api_key=os.getenv("TOGETHER_AI_KEY"),
+    base_url="https://api.together.xyz/v1"
+    )
+classifier = choice(model, ["Reservation", "Others"])
+
+def create_prompt_message(message: str) -> str:
+    return f"""
+        You are an agent that classifies restaurant-related user messages.
+
+        Your job is to classify the following message into one of two categories: "Reservation" or "Others".
+
+        You MUST respond EXACTLY with one of these two JSON objects:
+
+        {{"result": "Reservation"}} or {{"result": "Others"}}
+
+        Do not add any explanation or other content.
+
+        Message: {message}
+        """.strip()
+
+def create_prompt(message:str) -> str:
+    prompt = create_prompt_message(message)
+    try:
+        result = classifier(prompt)
+        return result
+    except Exception as e:
+        print(f"[Error] Failed to classify message: {e}")
+        return "Error"
+
+def inference(message:str)->str:
+    try:
+        result = create_prompt(message)
+        if result == 'Reservation':
+            result = "要訂位！"
+        elif result == 'Others':
+            result = "非訂位！"
+        else:
+            result = "不明意圖。"
+    except Exception as e:
+        print(f"[Error!]: {e}")
+        return "Error!"
+
+    return result
+
+
+iface = gr.Interface(
+    fn=inference,
+    inputs=gr.Textbox(lines=2, placeholder="請輸入顧客訊息...", label="輸入訊息"),
+    outputs=gr.Textbox(label="分類結果"),
+    title="訂位意圖分類器",
+    description="判斷輸入訊息是否與訂位有關"
+)
+
+iface.launch()
+

requirements.txt

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+gradio>=5.0.0
+outlines
+openai