Steps Explained: Connect LangChain with Databricks Unity Catalog
1. Install Required Packages
pip install langchain databricks-sql-connector
2. Configure Access to Databricks Unity Catalog
Use Databricks SQL Connector to connect to Unity Catalog tables.
from databricks import sql
conn = sql.connect(
server_hostname = "<your-databricks-workspace-url>", # e.g. "adb-1234567890123456.7.azuredatabricks.net"
http_path = "<sql-endpoint-http-path>", # From Databricks SQL Warehouse
access_token = "<your-personal-access-token>" # Or use Databricks secrets
)
cursor = conn.cursor()
cursor.execute("SELECT * FROM catalog_name.schema_name.table_name LIMIT 5")
result = cursor.fetchall()
for row in result:
print(row)
NOTE PS:This works for tables registered in Unity Catalog โ ensure the SQL Warehouse you're using has access to the correct catalog/schema/table.
3.Use with LangChain: SQLDatabaseChain
Now you can use LangChain's SQLDatabaseChain to query your Delta tables.
from langchain.chains import SQLDatabaseChain
from langchain.agents.agent_toolkits import SQLDatabaseToolkit
from langchain.sql_database import SQLDatabase
from langchain.chat_models import ChatOpenAI
db = SQLDatabase.from_databricks(
catalog="your_catalog",
schema="your_schema",
token="<your-access-token>",
host="adb-xxx.azuredatabricks.net",
http_path="<your-http-path>"
)
llm = ChatOpenAI(temperature=0)
db_chain = SQLDatabaseChain.from_llm(llm, db, verbose=True)
# Ask a question
db_chain.run("What is the average usage in the last 7 days?")
Databricks Solution Architect
