modify app.py

app.py

@@ -10,22 +10,15 @@ os.system("python -m mindsearch.app --lang cn --model_format internlm_silicon &"
 PLANNER_HISTORY = []
 SEARCHER_HISTORY = []
 
-
 def rst_mem(history_planner: list, history_searcher: list):
-    '''
-    Reset the chatbot memory.
-    '''
     history_planner = []
     history_searcher = []
     if PLANNER_HISTORY:
         PLANNER_HISTORY.clear()
     return history_planner, history_searcher
 
-
 def format_response(gr_history, agent_return):
-    if agent_return['state'] in [
-            AgentStatusCode.STREAM_ING, AgentStatusCode.ANSWER_ING
-    ]:
+    if agent_return['state'] in [AgentStatusCode.STREAM_ING, AgentStatusCode.ANSWER_ING]:
         gr_history[-1][1] = agent_return['response']
     elif agent_return['state'] == AgentStatusCode.PLUGIN_START:
         thought = gr_history[-1][1].split('```')[0]
@@ -34,25 +27,17 @@ def format_response(gr_history, agent_return):
     elif agent_return['state'] == AgentStatusCode.PLUGIN_END:
         thought = gr_history[-1][1].split('```')[0]
         if isinstance(agent_return['response'], dict):
-            gr_history[-1][
-                1] = thought + '\n' + f'```json\n{json.dumps(agent_return["response"], ensure_ascii=False, indent=4)}\n```'  # noqa: E501
+            gr_history[-1][1] = thought + '\n' + f'```json\n{json.dumps(agent_return["response"], ensure_ascii=False, indent=4)}\n```'
     elif agent_return['state'] == AgentStatusCode.PLUGIN_RETURN:
         assert agent_return['inner_steps'][-1]['role'] == 'environment'
         item = agent_return['inner_steps'][-1]
-        gr_history.append([
-            None,
-            f"```json\n{json.dumps(item['content'], ensure_ascii=False, indent=4)}\n```"
-        ])
+        gr_history.append([None, f"```json\n{json.dumps(item['content'], ensure_ascii=False, indent=4)}\n```"])
         gr_history.append([None, ''])
     return
 
-
 def predict(history_planner, history_searcher):
-
     def streaming(raw_response):
-        for chunk in raw_response.iter_lines(chunk_size=8192,
-                                             decode_unicode=False,
-                                             delimiter=b'\n'):
+        for chunk in raw_response.iter_lines(chunk_size=8192, decode_unicode=False, delimiter=b'\n'):
             if chunk:
                 decoded = chunk.decode('utf-8')
                 if decoded == '\r':
@@ -71,11 +56,7 @@ def predict(history_planner, history_searcher):
     url = 'http://localhost:8002/solve'
     headers = {'Content-Type': 'application/json'}
     data = {'inputs': PLANNER_HISTORY}
-    raw_response = requests.post(url,
-                                 headers=headers,
-                                 data=json.dumps(data),
-                                 timeout=20,
-                                 stream=True)
+    raw_response = requests.post(url, headers=headers, data=json.dumps(data), timeout=20, stream=True)
 
     for resp in streaming(raw_response):
         agent_return, node_name = resp
@@ -98,57 +79,45 @@ def predict(history_planner, history_searcher):
             yield history_planner, history_searcher
     return history_planner, history_searcher
 
-
-with gr.Blocks() as demo:
-    gr.HTML("""<h1 align="center">MindSearch Gradio Demo</h1>""")
-    gr.HTML("""<p style="text-align: center; font-family: Arial, sans-serif;">MindSearch is an open-source AI Search Engine Framework with Perplexity.ai Pro performance. You can deploy your own Perplexity.ai-style search engine using either closed-source LLMs (GPT, Claude) or open-source LLMs (InternLM2.5-7b-chat).</p>""")
+with gr.Blocks(css="""
+    .block {margin-top: 20px; padding: 20px; border-radius: 10px; border: 1px solid #ddd;}
+    .centered-text {text-align: center; font-family: Arial, sans-serif; color: #333;}
+    .styled-button {background-color: #4A90E2; color: white; border: none; padding: 10px 20px; border-radius: 5px; cursor: pointer;}
+    .styled-button:hover {background-color: #357ABD;}
+    .input-textbox {border-radius: 5px; border: 1px solid #ccc; padding: 10px;}
+""") as demo:
+    gr.HTML("""<h1 class="centered-text">MindSearch Gradio Demo</h1>""")
+    gr.HTML("""<p class="centered-text">MindSearch is an open-source AI Search Engine Framework with Perplexity.ai Pro performance. Deploy your own search engine with either closed-source or open-source LLMs.</p>""")
+    
     gr.HTML("""
-    <div style="text-align: center; font-size: 16px;">
+    <div class="centered-text" style="font-size: 16px;">
         <a href="https://github.com/InternLM/MindSearch" style="margin-right: 15px; text-decoration: none; color: #4A90E2;">🔗 GitHub</a>
         <a href="https://arxiv.org/abs/2407.20183" style="margin-right: 15px; text-decoration: none; color: #4A90E2;">📄 Arxiv</a>
         <a href="https://huggingface.co/papers/2407.20183" style="margin-right: 15px; text-decoration: none; color: #4A90E2;">📚 Hugging Face Papers</a>
         <a href="https://huggingface.co/spaces/internlm/MindSearch" style="text-decoration: none; color: #4A90E2;">🤗 Hugging Face Demo</a>
     </div>
     """)
+
     with gr.Row():
         with gr.Column(scale=10):
             with gr.Row():
                 with gr.Column():
-                    planner = gr.Chatbot(label='planner',
-                                         height=700,
-                                         show_label=True,
-                                         show_copy_button=True,
-                                         bubble_full_width=False,
-                                         render_markdown=True)
+                    planner = gr.Chatbot(label='Planner', height=700, show_label=True, show_copy_button=True, bubble_full_width=False, render_markdown=True)
                 with gr.Column():
-                    searcher = gr.Chatbot(label='searcher',
-                                          height=700,
-                                          show_label=True,
-                                          show_copy_button=True,
-                                          bubble_full_width=False,
-                                          render_markdown=True)
+                    searcher = gr.Chatbot(label='Searcher', height=700, show_label=True, show_copy_button=True, bubble_full_width=False, render_markdown=True)
             with gr.Row():
-                user_input = gr.Textbox(show_label=False,
-                                        placeholder='帮我搜索一下 InternLM 开源体系',
-                                        lines=5,
-                                        container=False)
+                user_input = gr.Textbox(show_label=False, placeholder='帮我搜索一下 InternLM 开源体系', lines=5, container=False, elem_classes="input-textbox")
             with gr.Row():
                 with gr.Column(scale=2):
-                    submitBtn = gr.Button('Submit')
+                    submitBtn = gr.Button('Submit', elem_classes="styled-button")
                 with gr.Column(scale=1, min_width=20):
-                    emptyBtn = gr.Button('Clear History')
+                    emptyBtn = gr.Button('Clear History', elem_classes="styled-button")
 
     def user(query, history):
         return '', history + [[query, '']]
 
-    submitBtn.click(user, [user_input, planner], [user_input, planner],
-                    queue=False).then(predict, [planner, searcher],
-                                      [planner, searcher])
-    emptyBtn.click(rst_mem, [planner, searcher], [planner, searcher],
-                   queue=False)
+    submitBtn.click(user, [user_input, planner], [user_input, planner], queue=False).then(predict, [planner, searcher], [planner, searcher])
+    emptyBtn.click(rst_mem, [planner, searcher], [planner, searcher], queue=False)
 
 demo.queue()
-demo.launch(server_name='0.0.0.0',
-            server_port=7860,
-            inbrowser=True,
-            share=True)
+demo.launch(server_name='0.0.0.0', server_port=7860, inbrowser=True, share=True)