Update app.py

app.py

@@ -103,35 +103,35 @@ def display_optimization_results(result_data):
         success = result["succeed"]
         prompt = result["prompt"]
 
-        with st.expander(f"Round {round_num} {':white_check_mark:' if success else ':x:'}"):
-            st.markdown("**Prompt:**")
+        with st.expander(f"轮次 {round_num} {':white_check_mark:' if success else ':x:'}"):
+            st.markdown("**提示词：**")
             st.code(prompt, language="text")
             st.markdown("<br>", unsafe_allow_html=True)
 
             col1, col2 = st.columns(2)
             with col1:
-                st.markdown(f"**Status:** {'Success ✅ ' if success else 'Failed ❌ '}")
+                st.markdown(f"**状态：** {'成功 ✅ ' if success else '失败 ❌ '}")
             with col2:
-                st.markdown(f"**Tokens:** {result['tokens']}")
+                st.markdown(f"**令牌数：** {result['tokens']}")
 
-            st.markdown("**Answers:**")
+            st.markdown("**回答：**")
             for idx, answer in enumerate(result["answers"]):
-                st.markdown(f"**Question {idx + 1}:**")
+                st.markdown(f"**问题 {idx + 1}：**")
                 st.text(answer["question"])
-                st.markdown("**Answer:**")
+                st.markdown("**答案：**")
                 st.text(answer["answer"])
                 st.markdown("---")
 
-    # Summary
+    # 总结
     success_count = sum(1 for r in result_data if r["succeed"])
     total_rounds = len(result_data)
 
-    st.markdown("### Summary")
+    st.markdown("### 总结")
     col1, col2 = st.columns(2)
     with col1:
-        st.metric("Total Rounds", total_rounds)
+        st.metric("总轮次", total_rounds)
     with col2:
-        st.metric("Successful Rounds", success_count)
+        st.metric("成功轮次", success_count)
 
 
 def main():
@@ -144,69 +144,68 @@ def main():
     """
     <div style="background-color: #f0f2f6; padding: 20px; border-radius: 10px; margin-bottom: 25px">
         <div style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 10px">
-            <h1 style="margin: 0;">SPO | Self-Supervised Prompt Optimization 🤖</h1>
+            <h1 style="margin: 0;">SPO | 自监督提示词优化 🤖</h1>
         </div>
         <div style="display: flex; gap: 20px; align-items: center">
             <a href="https://arxiv.org/pdf/2502.06855" target="_blank" style="text-decoration: none;">
-                <img src="https://img.shields.io/badge/Paper-PDF-red.svg" alt="Paper">
+                <img src="https://img.shields.io/badge/论文-PDF-red.svg" alt="论文">
             </a>
             <a href="https://github.com/geekan/MetaGPT/blob/main/examples/spo/README.md" target="_blank" style="text-decoration: none;">
-                <img src="https://img.shields.io/badge/GitHub-Repository-blue.svg" alt="GitHub">
+                <img src="https://img.shields.io/badge/GitHub-仓库-blue.svg" alt="GitHub">
             </a>
-            <span style="color: #666;">A framework for self-supervised prompt optimization</span>
+            <span style="color: #666;">一个自监督提示词优化框架</span>
         </div>
     </div>
     """,
     unsafe_allow_html=True
     )
 
-    # Sidebar for configurations
+    # 侧边栏配置
     with st.sidebar:
-        st.header("Configuration")
+        st.header("配置")
 
-        # Template Selection/Creation
+        # 模板选择/创建
         settings_path = Path("metagpt/ext/spo/settings")
         existing_templates = [f.stem for f in settings_path.glob("*.yaml")]
-
-        template_mode = st.radio("Template Mode", ["Use Existing", "Create New"])
+        template_mode = st.radio("模板模式", ["使用现有", "创建新模板"])
 
         existing_templates = get_all_templates()
 
-        if template_mode == "Use Existing":
-            template_name = st.selectbox("Select Template", existing_templates)
+        if template_mode == "使用现有":
+            template_name = st.selectbox("选择模板", existing_templates)
             is_new_template = False
         else:
-            template_name = st.text_input("New Template Name")
+            template_name = st.text_input("新模板名称")
             is_new_template = True
 
-        # LLM Settings
-        st.subheader("LLM Settings")
+        # LLM 设置
+        st.subheader("LLM 设置")
 
-        base_url = st.text_input("Base URL", value="https://api.example.com")
-        api_key = st.text_input("API Key", type="password")
+        base_url = st.text_input("基础 URL", value="https://api.example.com")
+        api_key = st.text_input("API 密钥", type="password")
 
         opt_model = st.selectbox(
-            "Optimization Model", ["gpt-4o-mini", "gpt-4o", "deepseek-chat", "claude-3-5-sonnet-20240620"], index=0
+            "优化模型", ["gpt-4o-mini", "gpt-4o", "deepseek-chat", "claude-3-5-sonnet-20240620"], index=0
         )
-        opt_temp = st.slider("Optimization Temperature", 0.0, 1.0, 0.7)
+        opt_temp = st.slider("优化温度", 0.0, 1.0, 0.7)
 
         eval_model = st.selectbox(
-            "Evaluation Model", ["gpt-4o-mini", "gpt-4o", "deepseek-chat", "claude-3-5-sonnet-20240620"], index=0
+            "评估模型", ["gpt-4o-mini", "gpt-4o", "deepseek-chat", "claude-3-5-sonnet-20240620"], index=0
         )
-        eval_temp = st.slider("Evaluation Temperature", 0.0, 1.0, 0.3)
+        eval_temp = st.slider("评估温度", 0.0, 1.0, 0.3)
 
         exec_model = st.selectbox(
-            "Execution Model", ["gpt-4o-mini", "gpt-4o", "deepseek-chat", "claude-3-5-sonnet-20240620"], index=0
+            "执行模型", ["gpt-4o-mini", "gpt-4o", "deepseek-chat", "claude-3-5-sonnet-20240620"], index=0
         )
-        exec_temp = st.slider("Execution Temperature", 0.0, 1.0, 0.0)
+        exec_temp = st.slider("执行温度", 0.0, 1.0, 0.0)
 
-        # Optimizer Settings
-        st.subheader("Optimizer Settings")
-        initial_round = st.number_input("Initial Round", 1, 100, 1)
-        max_rounds = st.number_input("Maximum Rounds", 1, 100, 10)
+        # 优化器设置
+        st.subheader("优化器设置")
+        initial_round = st.number_input("初始轮次", 1, 100, 1)
+        max_rounds = st.number_input("最大轮次", 1, 100, 10)
 
-    # Main content area
-    st.header("Template Configuration")
+    # 主要内容区域
+    st.header("模板配置")
 
     if template_name:
         template_real_name = get_template_path(template_name, is_new_template)
@@ -220,30 +219,30 @@ def main():
             st.session_state.current_template = template_name
             st.session_state.qas = template_data.get("qa", [])
 
-        # Edit template sections
-        prompt = st.text_area("Prompt", template_data.get("prompt", ""), height=100)
-        requirements = st.text_area("Requirements", template_data.get("requirements", ""), height=100)
+        # 编辑模板部分
+        prompt = st.text_area("提示词", template_data.get("prompt", ""), height=100)
+        requirements = st.text_area("要求", template_data.get("requirements", ""), height=100)
 
-        # qa section
-        st.subheader("Q&A Examples")
+        # 问答部分
+        st.subheader("问答示例")
 
-        # Add new qa button
-        if st.button("Add New Q&A"):
+        # 添加新问答按钮
+        if st.button("添加新问答"):
             st.session_state.qas.append({"question": "", "answer": ""})
 
-        # Edit qas
+        # 编辑问答
         new_qas = []
         for i in range(len(st.session_state.qas)):
-            st.markdown(f"**QA #{i + 1}**")
+            st.markdown(f"**问答 #{i + 1}**")
             col1, col2, col3 = st.columns([45, 45, 10])
 
             with col1:
                 question = st.text_area(
-                    f"Question {i + 1}", st.session_state.qas[i].get("question", ""), key=f"q_{i}", height=100
+                    f"问题 {i + 1}", st.session_state.qas[i].get("question", ""), key=f"q_{i}", height=100
                 )
             with col2:
                 answer = st.text_area(
-                    f"Answer {i + 1}", st.session_state.qas[i].get("answer", ""), key=f"a_{i}", height=100
+                    f"答案 {i + 1}", st.session_state.qas[i].get("answer", ""), key=f"a_{i}", height=100
                 )
             with col3:
                 if st.button("🗑️", key=f"delete_{i}"):
@@ -252,20 +251,20 @@ def main():
 
             new_qas.append({"question": question, "answer": answer})
 
-        # Save template button
-        if st.button("Save Template"):
+        # 保存模板按钮
+        if st.button("保存模板"):
             new_template_data = {"prompt": prompt, "requirements": requirements, "count": None, "qa": new_qas}
 
             save_yaml_template(template_path, new_template_data, is_new_template)
 
             st.session_state.qas = new_qas
-            st.success(f"Template saved to {template_path}")
+            st.success(f"模板已保存到 {template_path}")
 
-        st.subheader("Current Template Preview")
+        st.subheader("当前模板预览")
         preview_data = {"qa": new_qas, "requirements": requirements, "prompt": prompt}
         st.code(yaml.dump(preview_data, allow_unicode=True), language="yaml")
 
-        st.subheader("Optimization Logs")
+        st.subheader("优化日志")
         log_container = st.empty()
 
         class StreamlitSink:
@@ -289,8 +288,8 @@ def main():
         )
         _logger.add(METAGPT_ROOT / "logs/{time:YYYYMMDD}.txt", level="DEBUG")
 
-        # Start optimization button
-        if st.button("Start Optimization"):
+        # 开始优化按钮
+        if st.button("开始优化"):
             try:
                 # Initialize LLM
                 SPO_LLM.initialize(
@@ -315,37 +314,35 @@ def main():
                 with st.spinner("Optimizing prompts..."):
                     optimizer.optimize()
 
-                st.success("Optimization completed!")
-
-                st.header("Optimization Results")
-
+                st.success("优化完成！")
+                st.header("优化结果")
                 prompt_path = optimizer.root_path / "prompts"
                 result_data = optimizer.data_utils.load_results(prompt_path)
 
                 st.session_state.optimization_results = result_data
 
             except Exception as e:
-                st.error(f"An error occurred: {str(e)}")
-                _logger.error(f"Error during optimization: {str(e)}")
+                st.error(f"发生错误：{str(e)}")
+                _logger.error(f"优化过程中出错：{str(e)}")
 
         if st.session_state.optimization_results:
-            st.header("Optimization Results")
+            st.header("优化结果")
             display_optimization_results(st.session_state.optimization_results)
 
         st.markdown("---")
-        st.subheader("Test Optimized Prompt")
+        st.subheader("测试优化后的提示词")
         col1, col2 = st.columns(2)
 
         with col1:
-            test_prompt = st.text_area("Optimized Prompt", value="", height=200, key="test_prompt")
+            test_prompt = st.text_area("优化后的提示词", value="", height=200, key="test_prompt")
 
         with col2:
-            test_question = st.text_area("Your Question", value="", height=200, key="test_question")
+            test_question = st.text_area("你的问题", value="", height=200, key="test_question")
 
-        if st.button("Test Prompt"):
+        if st.button("测试提示词"):
             if test_prompt and test_question:
                 try:
-                    with st.spinner("Generating response..."):
+                    with st.spinner("正在生成回答..."):
                         SPO_LLM.initialize(
                             optimize_kwargs={"model": opt_model, "temperature": opt_temp, "base_url": base_url,
                                              "api_key": api_key},
@@ -368,13 +365,13 @@ def main():
                         finally:
                             loop.close()
 
-                        st.subheader("Response:")
+                        st.subheader("回答：")
                         st.markdown(response)
 
                 except Exception as e:
-                    st.error(f"Error generating response: {str(e)}")
+                    st.error(f"生成回答时出错：{str(e)}")
             else:
-                st.warning("Please enter both prompt and question.")
+                st.warning("请输入提示词和问题。")
 
 
 if __name__ == "__main__":