text: be used when connecting Databricks.**kwargs: Additional keyword arguments for the SQLDatabase.from_uri method.Examplesâ€‹# Connecting to Databricks with SQLDatabase wrapperfrom langchain import SQLDatabasedb = SQLDatabase.from_databricks(catalog="samples", schema="nyctaxi")# Creating a OpenAI Chat LLM wrapperfrom langchain.chat_models import ChatOpenAIllm = ChatOpenAI(temperature=0, model_name="gpt-4")SQL Chain exampleâ€‹This example demonstrates the use of the SQL Chain for answering a question over a Databricks database.from langchain import SQLDatabaseChaindb_chain = SQLDatabaseChain.from_llm(llm, db, verbose=True)db_chain.run(    "What is the average duration of taxi rides that start between midnight and 6am?")            > Entering new SQLDatabaseChain chain...    What is the average duration of taxi rides that start between midnight and 6am?    SQLQuery:SELECT AVG(UNIX_TIMESTAMP(tpep_dropoff_datetime) - UNIX_TIMESTAMP(tpep_pickup_datetime)) as avg_duration    FROM trips    WHERE HOUR(tpep_pickup_datetime) >= 0 AND HOUR(tpep_pickup_datetime) < 6    SQLResult: [(987.8122786304605,)]    Answer:The average duration of taxi rides that start between midnight and 6am is 987.81 seconds.    > Finished chain.    'The average duration of taxi rides that start between midnight and 6am is 987.81 seconds.'SQL Database Agent exampleâ€‹This example demonstrates the use of the SQL Database Agent for answering questions over a Databricks database.from langchain.agents import create_sql_agentfrom langchain.agents.agent_toolkits import