feat: update

app.py

@@ -5,14 +5,14 @@
 
 import os
 
-os.system("pip install transformers==4.43.2")
 
 # # # os.system("python -m mindsearch.app --lang en --model_format internlm_server")
-os.system("python -m mindsearch.app --lang en --model_format internlm_hf &")
+# os.system("python -m mindsearch.app --lang en --model_format internlm_server &")
 
 # os.system("bash install.sh")
 
 
+
 from flask import Flask, send_from_directory, request, jsonify
 
 import requests
@@ -28,25 +28,6 @@ def serve_index():
 def helloworld():
     return "Hello World"
 
-@app.route('/solve', methods=['GET', 'POST', 'PUT', 'DELETE'])
-def solve():
-    # 根据请求方法转发到本地 http://127.0.0.1:8002/solve
-    if request.method == 'GET':
-        response = requests.get('http://127.0.0.1:8002/solve')
-    elif request.method == 'POST':
-        data = request.get_json()
-        response = requests.post('http://127.0.0.1:8002/solve', json=data)
-    elif request.method == 'PUT':
-        data = request.get_json()
-        response = requests.put('http://127.0.0.1:8002/solve', json=data)
-    elif request.method == 'DELETE':
-        response = requests.delete('http://127.0.0.1:8002/solve')
-    
-    # 检查响应状态码
-    if response.status_code == 200:
-        return response.json()
-    else:
-        return jsonify({'error': 'Error calling local API'}), response.status_code
 
 @app.route('/<path:path>')
 def serve_file(path):
@@ -57,151 +38,3 @@ if __name__ == '__main__':
 
     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)
-
-
-# demo.queue()
-# demo.launch(server_name='0.0.0.0',
-#             server_port=7860,
-#             inbrowser=True,
-#             share=True)
-
-# pass

requirements.txt

@@ -1,14 +1,12 @@
 flask
-duckduckgo_search==5.3.1b1
-einops
-fastapi
-git+https://github.com/InternLM/lagent.git
-gradio
-janus
-pyvis
-sse-starlette
-termcolor
-uvicorn
-transformers==4.43.2
-sentencepiece
-accelerate
+# duckduckgo_search==5.3.1b1
+# einops
+# fastapi
+# git+https://github.com/InternLM/lagent.git
+# gradio
+# janus
+# lmdeploy==0.2.3
+# pyvis
+# sse-starlette
+# termcolor
+# uvicorn