feat: Localize UI and add project description

app.py

@@ -3,13 +3,13 @@ from comp import generate_response
 import re
 
 # --- Constants ---
-WORKFLOW_SYSTEM_PROMPT = """You are an expert in analyzing conversations and extracting user workflows.
-Based on the provided chat history, identify the user's main goal or intent.
-Then, break down the conversation into a series of actionable steps that represent the workflow to achieve that goal.
-The output should be in two parts, clearly separated:
-**Intent**: [A concise description of the user's goal]
-**Steps**:
-[A numbered list of steps]
+WORKFLOW_SYSTEM_PROMPT = """你是一位分析对话和提取用户工作流的专家。
+根据提供的聊天记录，识别用户的核心目标或意图。
+然后，将对话分解为一系列可执行的步骤，以实现该目标。
+输出应分为两部分，并明确分隔：
+**意图**: [用户目标的简洁描述]
+**步骤**:
+[步骤的编号列表]
 """
 
 # --- Helper Functions ---
@@ -17,35 +17,36 @@ def parse_workflow_response(response):
     intent_match = re.search(r"\*\*Intent\*\*:\s*(.*)", response, re.IGNORECASE)
     steps_match = re.search(r"\*\*Steps\*\*:\s*(.*)", response, re.DOTALL | re.IGNORECASE)
 
-    intent = intent_match.group(1).strip() if intent_match else "Could not determine intent."
-    steps = steps_match.group(1).strip() if steps_match else "Could not determine steps."
+    intent = intent_match.group(1).strip() if intent_match else "未能识别意图。"
+    steps = steps_match.group(1).strip() if steps_match else "未能识别步骤。"
     
     return intent, steps
 
 # --- Gradio UI ---
 
 with gr.Blocks() as demo:
-    gr.Markdown("# Ling Playground")
+    gr.Markdown("# Ling 灵动工作台")
+    gr.Markdown("这是一个对 Zero GPU 使用 Ring-mini-2.0 模型能力的验证项目。它会和用户聊天，并实时提取其中潜在有用的工作流。在合适的时机，它会告知用户，并提醒这些工作流未来可以被复用。")
 
     with gr.Row():
         with gr.Column(scale=2):
-            gr.Markdown("## Chat")
-            chat_chatbot = gr.Chatbot(label="Chat", bubble_full_width=False)
+            gr.Markdown("## 聊天")
+            chat_chatbot = gr.Chatbot(label="聊天", bubble_full_width=False)
             with gr.Row():
                 chat_msg = gr.Textbox(
-                    label="Your Message",
+                    label="请输入你的消息",
                     scale=4,
                 )
-                send_btn = gr.Button("Send", scale=1)
+                send_btn = gr.Button("发送", scale=1)
             
         with gr.Column(scale=1):
-            gr.Markdown("## Workflow Extraction")
-            intent_textbox = gr.Textbox(label="Task Intent", interactive=False)
+            gr.Markdown("## 工作流提取")
+            intent_textbox = gr.Textbox(label="任务意图", interactive=False)
             steps_textbox = gr.Textbox(
-                label="Extracted Steps", interactive=False, lines=15
+                label="提取步骤", interactive=False, lines=15
             )
     
-    chat_clear = gr.ClearButton([chat_msg, chat_chatbot, intent_textbox, steps_textbox])
+    chat_clear = gr.ClearButton([chat_msg, chat_chatbot, intent_textbox, steps_textbox], value="清除")
 
     def user(user_message, history):
         return "", history + [[user_message, None]]