class_docstr: This is a MindsDB integration for the LangChain library, which provides a unified interface for interacting with
  various large language models (LLMs).
  
  Currently, this integration supports exposing OpenAI and Anthrophic's LLMs with normal text completion support. They are then
  wrapped in a zero shot react description agent that offers a few third party tools out of the box, with support
  for additional ones if an API key is provided. Ongoing memory is also provided.
  
  Full tool support list:
      - wikipedia
      - python_repl
      - serper.dev search
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docstr: This completion will be used to answer based on information passed by any MindsDB DB or API engine.
docstr_tok: ["This","completion","will","be","used","to","answer","based","on","information","passed","by","any","MindsDB","DB","or","API","engine","."]
code: def sql_agent_completion(self, df, args=None, pred_args=None):
      """This completion will be used to answer based on information passed by any MindsDB DB or API engine."""
      db = MindsDBSQL(
          engine=args["executor"],
          metadata=args["executor"].session.integration_controller,
      )
      model_name = args.get("model_name", self.default_model)
      llm = (
          OpenAI(temperature=0)
          if model_name not in OPEN_AI_CHAT_MODELS
          else self._create_chat_model(args, pred_args)
      )  # noqa
      toolkit = SQLDatabaseToolkit(db=db, llm=llm)
      agent = create_sql_agent(
          llm=llm,
          toolkit=toolkit,
          verbose=pred_args.get("verbose", args.get("verbose", False)),
      )
      return agent, df
  
imports: import re
  import os
  from typing import Optional, Dict
  from concurrent.futures import as_completed, TimeoutError
  import numpy
  import pandas
  from langchain.schema import SystemMessage
  from langchain.agents import AgentType
  from langchain.llms import OpenAI
  from langchain.chat_models import ChatAnthropic, ChatOpenAI
  from langchain.agents import initialize_agent, create_sql_agent
  from langchain.prompts import PromptTemplate
  from langchain.agents.agent_toolkits import SQLDatabaseToolkit
  from langchain.chains.conversation.memory import ConversationSummaryBufferMemory
  from mindsdb.integrations.handlers.openai_handler.constants import CHAT_MODELS
  from mindsdb.integrations.handlers.langchain_handler.mindsdb_database_agent import MindsDBSQL
  from mindsdb.integrations.handlers.langchain_handler.tools import setup_tools
  from mindsdb.integrations.libs.base import BaseMLEngine
  from mindsdb.integrations.utilities.handler_utils import get_api_key
  from mindsdb.utilities import log
  from mindsdb.utilities.context_executor import ContextThreadPoolExecutor
label_desc: Use image node_id 13 for calling the LangChainHandler obj's underlying member method code with example usage: obj.sql_agent_completion(df, args, pred_args) and returns: agent,  df