Update app.py

app.py

@@ -2,47 +2,77 @@ import gradio as gr
 import os
 from openai import OpenAI
 
-OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
-openai_client = OpenAI(api_key=OPENAI_API_KEY)
-
+# 从环境变量读取两个 API Key
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_API_KEY")
-deepseek_client = OpenAI(api_key=DEEPSEEK_API_KEY, base_url="https://api.deepseek.com")
 
-def generate_response(prompt, model_provider, temperature, top_p, max_tokens, repetition_penalty):
-    models = {
-        "DeepSeek": ("deepseek-chat", deepseek_client),
-        "OpenAI": ("gpt-3.5-turbo", openai_client)
+# 初始化两个客户端
+openai_client = OpenAI(api_key=OPENAI_API_KEY)
+deepseek_client = OpenAI(
+    api_key=DEEPSEEK_API_KEY,
+    # 如果 DeepSeek 的 API 路径需要带 /v1，可以根据实际文档调整
+    base_url="https://api.deepseek.com/v1"
+)
+
+def generate_response(model_provider, prompt, temperature, top_p, max_tokens, repetition_penalty):
+    # 根据 model_provider 分发到对应 client 和 model 名称
+    clients = {
+        "DeepSeek": (deepseek_client, "deepseek-chat"),
+        "OpenAI":   (openai_client,   "gpt-3.5-turbo")
     }
-    model, client = models[model_provider]
+    client, model = clients[model_provider]
     
     try:
-        response = client.chat.completions.create(
+        resp = client.chat.completions.create(
             model=model,
             messages=[{"role": "user", "content": prompt}],
             temperature=temperature,
             top_p=top_p,
             max_tokens=max_tokens,
-            presence_penalty=repetition_penalty,
-            stream=False
+            # repetition_penalty 建议映射到 frequency_penalty 或 presence_penalty，根据需求选一个
+            frequency_penalty=repetition_penalty,
+            presence_penalty=0.0
         )
-        return response.choices[0].message.content.strip()
+        return resp.choices[0].message.content.strip()
     except Exception as e:
-        return f"{model_provider} API Error: {str(e)}"
+        return f"{model_provider} API Error: {e}"
 
-iface = gr.Interface(
-    fn=generate_response,
-    inputs=[
-        gr.Dropdown(choices=["DeepSeek", "OpenAI"], value="DeepSeek", label="Model Provider",interactive=False),
-        gr.Textbox(label="Prompt", lines=6, placeholder="Ask something..."),
-        gr.Slider(minimum=0.1, maximum=1.5, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(minimum=0.1, maximum=1.0, value=0.9, step=0.05, label="Top-p"),
-        gr.Slider(minimum=32, maximum=2048, value=512, step=32, label="Max New Tokens"),
-        gr.Slider(minimum=1.0, maximum=2.0, value=1.1, step=0.1, label="Repetition Penalty")
-    ],
-    outputs="text",
-    title="🧠 DeepSeek LLM Chat with Parameter Tuning",
-    theme=gr.themes.Soft()
-)
+with gr.Blocks(theme=gr.themes.Soft()) as iface:
+    gr.Markdown("## 🧠 DeepSeek / OpenAI 聊天演示（可调参）")
+    with gr.Row():
+        provider = gr.Dropdown(
+            choices=["DeepSeek", "OpenAI"],
+            value="DeepSeek",
+            label="模型供应商"
+        )
+        temperature = gr.Slider(
+            minimum=0.1, maximum=1.5, step=0.1, value=0.7,
+            label="Temperature"
+        )
+        top_p = gr.Slider(
+            minimum=0.1, maximum=1.0, step=0.05, value=0.9,
+            label="Top-p"
+        )
+    prompt = gr.Textbox(
+        label="Prompt",
+        lines=6,
+        placeholder="在这里输入你的问题……"
+    )
+    with gr.Row():
+        max_tokens = gr.Slider(
+            minimum=32, maximum=2048, step=32, value=512,
+            label="Max Tokens"
+        )
+        rep_penalty = gr.Slider(
+            minimum=0.0, maximum=2.0, step=0.1, value=1.1,
+            label="Frequency Penalty"
+        )
+    output = gr.Textbox(label="Response")
+    btn = gr.Button("生成回答")
+    btn.click(
+        fn=generate_response,
+        inputs=[provider, prompt, temperature, top_p, max_tokens, rep_penalty],
+        outputs=output
+    )
 
 iface.launch()
-