Update app.py

app.py

@@ -2,10 +2,71 @@ import os
 import gradio as gr
 from openai import OpenAI
 
-# 初始化 OpenAI 客戶端
-client = OpenAI(api_key=os.getenv('OPENAI_API_KEY'))
+# 安裝並導入 Groq
+try:
+    from groq import Groq
+except ImportError:
+    os.system('pip install groq')
+    from groq import Groq
 
-def evaluate_essay(message, additional_prompt):
+# 初始化 API clients
+openai_client = OpenAI(api_key=os.getenv('OPENAI_API_KEY'))
+groq_client = Groq(api_key=os.getenv('groq_key'))
+
+# 模型設定
+MODEL_CONFIGS = {
+    "openai": {
+        "gpt-3.5-turbo": {
+            "max_tokens": 4096,
+            "temperature": 0.7
+        },
+        "gpt-4": {
+            "max_tokens": 8192,
+            "temperature": 0.7
+        },
+        "gpt-4-turbo": {
+            "max_tokens": 4096,
+            "temperature": 0.7
+        }
+    },
+    "groq": {
+        "llama3-8b-8192": {
+            "max_tokens": 4090,
+            "temperature": 0.7
+        },
+        "gemma2-9b-it": {
+            "max_tokens": 1024,
+            "temperature": 0.7
+        }
+    }
+}
+
+def get_llm_response(prompt, provider, model):
+    if provider == "openai":
+        response = openai_client.chat.completions.create(
+            model=model,
+            messages=[
+                {"role": "system", "content": "你是一位資深的國文作文評閱委員，請依據提供的評分規準進行評分。"},
+                {"role": "user", "content": prompt}
+            ],
+            **MODEL_CONFIGS["openai"][model]
+        )
+        return response.choices[0].message.content
+    else:  # groq
+        completion = groq_client.chat.completions.create(
+            model=model,
+            messages=[
+                {"role": "system", "content": "你是一位資深的國文作文評閱委員，請依據提供的評分規準進行評分。"},
+                {"role": "user", "content": prompt}
+            ],
+            **MODEL_CONFIGS["groq"][model],
+            stream=False,
+            top_p=1,
+            stop=None
+        )
+        return completion.choices[0].message.content
+
+def evaluate_essay(message, additional_prompt, provider, model):
     if not message.strip():
         return [], gr.Markdown("### 請輸入作文內容進行評分")
     
@@ -27,7 +88,7 @@ def evaluate_essay(message, additional_prompt):
         history = []
         total_score = 0
         history.append(("作文內容：", message))
-        history.append(("", "正在進行評分分析..."))
+        history.append(("", f"正在使用 {provider} ({model}) 進行評分分析..."))
         
         all_feedback = {}
         
@@ -46,16 +107,7 @@ def evaluate_essay(message, additional_prompt):
 等第：
 評語："""
 
-            response = client.chat.completions.create(
-                model="gpt-3.5-turbo",
-                messages=[
-                    {"role": "system", "content": "你是一位資深的國文作文評閱委員，請依據提供的評分規準進行評分。"},
-                    {"role": "user", "content": prompt}
-                ],
-                temperature=0.7
-            )
-            
-            result = response.choices[0].message.content
+            result = get_llm_response(prompt, provider, model)
             lines = result.lower().split('\n')
             grade = '0'
             comment = ""
@@ -78,13 +130,12 @@ def evaluate_essay(message, additional_prompt):
             
             all_feedback[criterion] = feedback
 
-        # 分別顯示每個面向的評分
         for criterion in criteria:
             history.append(("", all_feedback[criterion]))
         
-        # 最後顯示總分
         total_score_display = f"""
 # 總評分結果
+## 使用模型：{provider} ({model})
 ## 總分：{total_score:.1f}/100
 """
         
@@ -93,6 +144,9 @@ def evaluate_essay(message, additional_prompt):
     except Exception as e:
         return [("", f"評分過程發生錯誤：{str(e)}")], gr.Markdown("### ❌ 評分失敗")
 
+def update_model_choices(provider):
+    return gr.Dropdown(choices=list(MODEL_CONFIGS[provider].keys()))
+
 # 建立 Gradio 介面
 with gr.Blocks(title="國文作文自動評分系統") as demo:
     gr.Markdown("""
@@ -119,35 +173,11 @@ with gr.Blocks(title="國文作文自動評分系統") as demo:
         lines=2
     )
     
-    # 按鈕區
+    # 模型選擇
     with gr.Row():
-        submit = gr.Button("開始評分", variant="primary", size="lg")
-        clear = gr.Button("清除內容", size="lg")
-    
-    # 顯示區塊
-    with gr.Row():
-        # 左側顯示評分詳情
-        with gr.Column(scale=2):
-            chatbot = gr.Chatbot(
-                show_copy_button=True,
-                render_markdown=True,
-                height=600,
-                label="評分詳情"
-            )
-        # 右側顯示總分
-        with gr.Column(scale=1):
-            score_display = gr.Markdown("### 等待評分...")
-    
-    # 事件處理
-    submit.click(
-        evaluate_essay,
-        inputs=[msg, additional_prompt],
-        outputs=[chatbot, score_display]
-    )
-    clear.click(
-        lambda: [None, None, [], gr.Markdown("### 等待評分...")],
-        outputs=[msg, additional_prompt, chatbot, score_display]
-    )
-
-# 啟動應用
-demo.launch()
+        provider = gr.Radio(
+            choices=["openai", "groq"],
+            label="選擇服務提供者",
+            value="openai"
+        )
+        model = gr.D