Update app.py

app.py

@@ -1,8 +1,7 @@
 import gradio as gr
 from gradio import ChatMessage
-from crewai.tools import tool, BaseTool
-from crewai_tools import CodeInterpreterTool
-from groq import Groq
+#from crewai.tools import tool, BaseTool
+#om groq import Groq
 import requests
 import uvicorn
 #from fastapi.middleware.cors import CORSMiddleware
@@ -14,8 +13,8 @@ import mysql.connector
 
 from autogen import AssistantAgent, UserProxyAgent, GroupChat, GroupChatManager
 from autogen.agentchat.contrib.retrieve_user_proxy_agent import RetrieveUserProxyAgent
-from pathlib import Path
-from typing import Annotated
+#from pathlib import Path
+#from typing import Annotated
 
 # MySQLに接続
 conn = mysql.connector.connect(
@@ -78,8 +77,8 @@ function createGradioAnimation() {
 async def autogen(qry: str):
     # Prompts
     userPrompt=qry
-    basicAssistantAgentPrompt="あなたはヘッドハンティング会社のアナリストです。"
-    professionalAssistantAgentPrompt="あなたは高度な知識を持つヘッドハンティング会社の上席コンサルタントです。Basic_Assistant_Agent による応答を分析し、詳細情報を提供します。"
+    assistant="あなたはヘッドハンティング会社のアナリストです。"
+    ragproxyagent="あなたは高度な知識を持つヘッドハンティング会社の上席コンサルタントです。assistantによる応答を分析し、詳細情報を提供します。"
 
     # Cohere config
     config_list = [
@@ -130,7 +129,6 @@ async def autogen(qry: str):
 
     # Create a group chat between all agents
     groupChat = GroupChat(
-        #agents=[ragproxyagent, atlas_assistant_agent, basic_assistant_agent, professional_assistant_agent],
         agents=[assistant, ragproxyagent],
         messages=[],
         max_round=3,
@@ -146,17 +144,26 @@ async def autogen(qry: str):
         #groupChatManager,
         #message=userPrompt
     #)
-    chat_result = ragproxyagent.initiate_chat(assistant, message=userPrompt)
+    chat_result = ragproxyagent.initiate_chat(assistant, message=ragproxyagent.message_generator, problem=userPrompt)
+    #user_contents = [entry['content'] for entry in chat_result['chat_history'] if entry['role'] == 'user']
+    
+    #chat_result = ragproxyagent.initiate_chat(assistant, message=userPrompt)
+    #print(chat_result)
 
     chat_result_dict = vars(chat_result)
     user_contents = [entry['content'] for entry in chat_result_dict['chat_history'] if entry['role'] == 'user']
-    #print(chat_result_dict)
-    print(user_contents[0])
-    return user_contents[0]
+    #print("user_contents")
+    #print(user_contents)
+    #print("\n\n")
+    
+    #print(user_contents[0])
+    #return user_contents[0]
 
-    #basic_content = [entry["content"] for entry in chat_result_dict["chat_history"] if entry["name"] == "assistant"]
+    basic_content = [entry["content"] for entry in chat_result_dict["chat_history"] if entry["role"] == "assistant"]
+    #print("basic_content")
     #print(basic_content)
     #return basic_content
+    return user_contents[0]+"\n\n"+basic_content[0]
 
     
     #user_contents = [entry['content'] for entry in chat_result['chat_history'] if entry['role'] == 'user']
@@ -272,5 +279,5 @@ with gr.Blocks(js=js,title="人材スカウトのガイドライン") as llm:
             outputs=[auto_output]
         )
 
-    if __name__ == "__main__":
-        llm.launch()
+if __name__ == "__main__":
+    llm.launch()