Querying SQLite using LangChain

langchain_sql1.py

"""
This demo program outputs raw SQL query by analyzing table, which is run by agent executer, via SQL adapter.
"""

import os
import sqlite3
from langchain.agents import *
from langchain.sql_database import SQLDatabase
from langchain.chains import create_sql_query_chain
from langchain_community.llms import OpenAI
from langchain_openai import ChatOpenAI


# os.environ['OPENAI_API_KEY'] = "your_openai_api_key"
llm = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0)

db = SQLDatabase.from_uri(f"sqlite:///urls.db")

chain = create_sql_query_chain(llm, db)
response = chain.invoke({"question": "What are the top most popular 3 URLs in table `urls`?"})
print(response)

langchain_sql2.py

"""
This demo program outputs result of a SQL query, which is run by agent executer, via SQL adapter.
"""

import os
import sqlite3
from langchain.agents import *
from langchain.sql_database import SQLDatabase
from langchain_community.agent_toolkits.sql.toolkit import SQLDatabaseToolkit
from langchain_community.agent_toolkits import create_sql_agent
from langchain_openai import ChatOpenAI


db = SQLDatabase.from_uri(f"sqlite:///urls.db")
print(db.dialect)
print(db.get_usable_table_names())

# os.environ['OPENAI_API_KEY'] = "your_openai_api_key"
llm = ChatOpenAI(model_name="gpt-3.5-turbo")

agent_executor = create_sql_agent(llm, db=db, agent_type="openai-tools", verbose=True)

# agent_executor.run("Describe the `urls` table")
agent_executor.run("What are the top most popular 3 URLs in table `urls`?")

pypi_install.sh

pip install langchain-core
pip install -U langchain-community
pip install openai

Additional references

• https://python.langchain.com/docs/use_cases/sql/quickstart/
• Chat With a MySQL Database Using Python and LangChain
• https://medium.com/dataherald/how-to-langchain-sqlchain-c7342dd41614