This example demonstrates how to use the LangChain Go library to interact with a PostgreSQL database using natural language queries. It showcases the power of combining language models with database operations.
What This Example Does
Database Setup:
Creates two tables: foo and foo1.
Populates foo with 100 rows and foo1 with 200 rows of sample data.
LangChain Integration:
Initializes an OpenAI language model.
Sets up a SQL database chain using the PostgreSQL database.
Natural Language Queries:
Executes three different queries using natural language:
a. Retrieves rows from the foo table where the ID is less than 23.
b. Repeats the first query but specifies the table name explicitly.
c. Compares the data volume in foo and foo1 tables.
Key Features
Natural Language to SQL: Converts human-readable questions into SQL queries.
Database Interaction: Executes SQL queries and returns results.
Flexible Querying: Demonstrates querying with and without specifying table names.
Data Comparison: Shows the ability to analyze and compare data across tables.
How to Run
Ensure you have a PostgreSQL database set up and accessible.
Set the LANGCHAINGO_POSTGRESQL environment variable with your database connection string.
Make sure you have an OpenAI API key set up (the example uses default configuration).
Run the example using go run postgresql_database_chain.go.
This example is perfect for developers looking to integrate natural language processing with database operations, enabling more intuitive data querying and analysis.