Update app.py

app.py

@@ -1,8 +1,10 @@
 from flask import Flask, request, jsonify, render_template
 from flask_socketio import SocketIO, emit
 from langchain_google_genai import ChatGoogleGenerativeAI
-from langchain.agents import initialize_agent, AgentType
+# from langchain.agents import initialize_agent, AgentType 
+from langchain.agents import AgentExecutor, create_react_agent
 from langchain_community.agent_toolkits import create_sql_agent, SQLDatabaseToolkit
+from langchain_core.prompts import PromptTemplate
 from langchain_community.utilities import SQLDatabase
 from langchain.tools import Tool
 from langchain.memory import ConversationBufferMemory
@@ -168,14 +170,25 @@ def init_sql_agent_from_uri(sql_uri: str):
                 - Return code or tool names.
                 - Give wrong Answers.
                 '''
+        # agent = create_sql_agent(
+        #     llm=llm,
+        #     toolkit=toolkit,
+        #     verbose=True,
+        #     prefix=prefix,
+        #     agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
+        #     memory=memory,
+        #     agent_executor_kwargs={"handle_parsing_errors": True},
+        # )
         agent = create_sql_agent(
             llm=llm,
             toolkit=toolkit,
             verbose=True,
-            prefix=prefix,
-            agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
-            memory=memory,
-            agent_executor_kwargs={"handle_parsing_errors": True},
+            agent_type="openai-tools",   # modern default; or "zero-shot-react-description" as string
+            agent_executor_kwargs={
+                "handle_parsing_errors": True,
+                "memory": memory,
+            },
+            extra_tools=[],
         )
         agent_executor = agent
         db_mode = 'sql'
@@ -377,15 +390,49 @@ def init_mongo_agent_from_uri(mongo_uri: str, database_name: str = None):
                 # - User: "How many users registered this month?"
                 #   Assistant: Use AggregateGroupBy and summarize results in a clear sentence.
                 # """
-        agent = initialize_agent(
+        # agent = initialize_agent(
+        #     tools=tools,
+        #     llm=llm,
+        #     agent_type=AgentType.CONVERSATIONAL_REACT_DESCRIPTION,
+        #     memory=memory,
+        #     verbose=True,
+        #     prefix=prefix,
+        #     handle_parsing_errors=True
+        # )
+
+        from langchain_core.prompts import PromptTemplate
+
+        prompt_template = PromptTemplate.from_template(
+            prefix + """
+        You have access to the following tools:
+        {tools}
+        
+        Use the following format:
+        Question: the input question you must answer
+        Thought: you should always think about what to do
+        Action: the action to take, should be one of [{tool_names}]
+        Action Input: the input to the action
+        Observation: the result of the action
+        ... (this Thought/Action/Action Input/Observation can repeat N times)
+        Thought: I now know the final answer
+        Final Answer: the final answer to the original input question
+        
+        Previous conversation history:
+        {chat_history}
+        
+        Question: {input}
+        {agent_scratchpad}"""
+        )
+        
+        react_agent = create_react_agent(llm=llm, tools=tools, prompt=prompt_template)
+        agent = AgentExecutor(
+            agent=react_agent,
             tools=tools,
-            llm=llm,
-            agent_type=AgentType.CONVERSATIONAL_REACT_DESCRIPTION,
             memory=memory,
             verbose=True,
-            prefix=prefix,
-            handle_parsing_errors=True
+            handle_parsing_errors=True,
         )
+        
         agent_executor = agent
         db_mode = 'mongo'
         logger.info('Mongo agent initialized')