Update app.py

app.py

@@ -1,15 +1,15 @@
 import gradio as gr
 from gradio import ChatMessage
+#from crewai.tools import tool, BaseTool
 from groq import Groq
 import requests
 import uvicorn
 import os
 import mysql.connector
+from qdrant_client import QdrantClient
 
 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
 
 # MySQLに接続
 conn = mysql.connector.connect(
@@ -94,32 +94,35 @@ async def autogen(qry: str):
     },
     )
 
+    client = QdrantClient(url="https://02cbe366-829e-43a6-adf5-3b712a886c21.us-west-1-0.aws.cloud.qdrant.io", api_key="eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJhY2Nlc3MiOiJtIn0.hWu5_qKaYHUhuMAjUScqw1R_1kkXiidv337wuGKcu9o")
     # Create user proxy agent RetrieveUserProxyAgent(
     ragproxyagent = RetrieveUserProxyAgent(
     name="ragproxyagent",
     human_input_mode="NEVER",
     max_consecutive_auto_reply=3,
-    retrieve_config={
+    retrieve_config = {
         "task": "qa",
         "docs_path": [
             "https://www.ryhintl.com/hunting.md"
         ],
         "chunk_token_size": 2000,
         "model": config_list[0]["model"],
-        "vector_db": "mongodb",  # MongoDB Atlas database
-        "collection_name": "scout_base",
-        "db_config": {
-            "connection_string": "mongodb+srv://richardhuh0629:VIPpOA51jOsiirVY@cluster0.yzn9dzx.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0",  # MongoDB Atlas connection string
-            "database_name": "human_database",  # MongoDB Atlas database
-            "index_name": "scout_index",
-            "wait_until_index_ready": 120.0,  # Setting to wait 120 seconds or until index is constructed before querying
-            "wait_until_document_ready": 120.0,  # Setting to wait 120 seconds or until document is properly indexed after insertion/update
-        },
+        "vector_db": "qdrant",  # Qdrant Cloud database
+        "collection_name": "scouter_base",
+        #"db_config": {
+            #"connection_string": "https://02cbe366-829e-43a6-adf5-3b712a886c21.us-west-1-0.aws.cloud.qdrant.io",  # Qdrant Cloud connection string
+            #"api_key": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJhY2Nlc3MiOiJtIn0.hWu5_qKaYHUhuMAjUScqw1R_1kkXiidv337wuGKcu9o",  # Qdrant Cloud API key
+            #"database_name": "human_database",  # Qdrant Cloud database (if applicable)
+            #"index_name": "scout_index",
+            #"wait_until_index_ready": 120.0,  # Setting to wait 120 seconds or until index is constructed before querying
+            #"wait_until_document_ready": 120.0,  # Setting to wait 120 seconds or until document is properly indexed after insertion/update
+        #},
+        "db_config": {"client": client},
         "get_or_create": True,  # set to False if you don't want to reuse an existing collection
         "overwrite": True,  # set to True if you want to overwrite an existing collection, each overwrite will force a index creation and reupload of documents
-    },
-    code_execution_config=False,  # set to False if you don't want to execute the code
-)
+        },
+        code_execution_config=False,  # set to False if you don't want to execute the code
+    )
 
 
     # Create a group chat between all agents
@@ -275,4 +278,4 @@ with gr.Blocks(js=js,title="人材スカウトのガイドライン") as llm:
         )
 
 if __name__ == "__main__":
-    llm.launch(share=True)
+    llm.launch()