feat: update

app.py

@@ -5,7 +5,7 @@ import sys
 
 # # os.system("python -m mindsearch.app --lang en --model_format internlm_server")
 
-
+os.system("apt install nodejs npm && cd frontend/React && npm install && npm run start")
 
 
 # from flask import Flask, send_from_directory
@@ -28,151 +28,151 @@ import sys
 #     app.run(debug=False, port=7860, host="0.0.0.0")
 
 
-import json
-
-import gradio as gr
-import requests
-from lagent.schema import AgentStatusCode
-
-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
-    ]:
-        gr_history[-1][1] = agent_return['response']
-    elif agent_return['state'] == AgentStatusCode.PLUGIN_START:
-        thought = gr_history[-1][1].split('```')[0]
-        if agent_return['response'].startswith('```'):
-            gr_history[-1][1] = thought + '\n' + agent_return['response']
-    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
-    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, ''])
-    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'):
-            if chunk:
-                decoded = chunk.decode('utf-8')
-                if decoded == '\r':
-                    continue
-                if decoded[:6] == 'data: ':
-                    decoded = decoded[6:]
-                elif decoded.startswith(': ping - '):
-                    continue
-                response = json.loads(decoded)
-                yield (response['response'], response['current_node'])
-
-    global PLANNER_HISTORY
-    PLANNER_HISTORY.append(dict(role='user', content=history_planner[-1][0]))
-    new_search_turn = True
-
-    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)
-
-    for resp in streaming(raw_response):
-        agent_return, node_name = resp
-        if node_name:
-            if node_name in ['root', 'response']:
-                continue
-            agent_return = agent_return['nodes'][node_name]['detail']
-            if new_search_turn:
-                history_searcher.append([agent_return['content'], ''])
-                new_search_turn = False
-            format_response(history_searcher, agent_return)
-            if agent_return['state'] == AgentStatusCode.END:
-                new_search_turn = True
-            yield history_planner, history_searcher
-        else:
-            new_search_turn = True
-            format_response(history_planner, agent_return)
-            if agent_return['state'] == AgentStatusCode.END:
-                PLANNER_HISTORY = agent_return['inner_steps']
-            yield history_planner, history_searcher
-    return history_planner, history_searcher
-
-
-with gr.Blocks() as demo:
-    gr.HTML("""<h1 align="center">WebAgent Gradio Simple Demo</h1>""")
-    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)
-                with gr.Column():
-                    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='inputs...',
-                                        lines=5,
-                                        container=False)
-            with gr.Row():
-                with gr.Column(scale=2):
-                    submitBtn = gr.Button('Submit')
-                with gr.Column(scale=1, min_width=20):
-                    emptyBtn = gr.Button('Clear History')
-
-    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)
-
-# subprocess.Popen(["python", "-m", "mindsearch.app", "--lang", "en", "--model_format", "internlm_server"], shell=True, stdout=sys.stdout, stderr=sys.stderr)
+# import json
+
+# import gradio as gr
+# import requests
+# from lagent.schema import AgentStatusCode
+
+# 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
+#     ]:
+#         gr_history[-1][1] = agent_return['response']
+#     elif agent_return['state'] == AgentStatusCode.PLUGIN_START:
+#         thought = gr_history[-1][1].split('```')[0]
+#         if agent_return['response'].startswith('```'):
+#             gr_history[-1][1] = thought + '\n' + agent_return['response']
+#     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
+#     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, ''])
+#     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'):
+#             if chunk:
+#                 decoded = chunk.decode('utf-8')
+#                 if decoded == '\r':
+#                     continue
+#                 if decoded[:6] == 'data: ':
+#                     decoded = decoded[6:]
+#                 elif decoded.startswith(': ping - '):
+#                     continue
+#                 response = json.loads(decoded)
+#                 yield (response['response'], response['current_node'])
+
+#     global PLANNER_HISTORY
+#     PLANNER_HISTORY.append(dict(role='user', content=history_planner[-1][0]))
+#     new_search_turn = True
+
+#     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)
+
+#     for resp in streaming(raw_response):
+#         agent_return, node_name = resp
+#         if node_name:
+#             if node_name in ['root', 'response']:
+#                 continue
+#             agent_return = agent_return['nodes'][node_name]['detail']
+#             if new_search_turn:
+#                 history_searcher.append([agent_return['content'], ''])
+#                 new_search_turn = False
+#             format_response(history_searcher, agent_return)
+#             if agent_return['state'] == AgentStatusCode.END:
+#                 new_search_turn = True
+#             yield history_planner, history_searcher
+#         else:
+#             new_search_turn = True
+#             format_response(history_planner, agent_return)
+#             if agent_return['state'] == AgentStatusCode.END:
+#                 PLANNER_HISTORY = agent_return['inner_steps']
+#             yield history_planner, history_searcher
+#     return history_planner, history_searcher
+
+
+# with gr.Blocks() as demo:
+#     gr.HTML("""<h1 align="center">WebAgent Gradio Simple Demo</h1>""")
+#     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)
+#                 with gr.Column():
+#                     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='inputs...',
+#                                         lines=5,
+#                                         container=False)
+#             with gr.Row():
+#                 with gr.Column(scale=2):
+#                     submitBtn = gr.Button('Submit')
+#                 with gr.Column(scale=1, min_width=20):
+#                     emptyBtn = gr.Button('Clear History')
+
+#     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)
+
+# # subprocess.Popen(["python", "-m", "mindsearch.app", "--lang", "en", "--model_format", "internlm_server"], shell=True, stdout=sys.stdout, stderr=sys.stderr)
 
 os.system("python -m mindsearch.app --lang en --model_format internlm_server &")
 
-demo.queue()
-demo.launch(server_name='0.0.0.0',
-            server_port=7860,
-            inbrowser=True,
-            share=True)
+# demo.queue()
+# demo.launch(server_name='0.0.0.0',
+#             server_port=7860,
+#             inbrowser=True,
+#             share=True)
 
-pass
+# pass

frontend/React/vite.config.ts

@@ -51,7 +51,7 @@ export default defineConfig({
     },
   },
   server: {
-    port: 8080,
+    port: 7860,
     proxy: {
       // "/solve": {
       //   target: "...",