# PostgreSQL Database Chain Example

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

1. **Database Setup**: 
   - Creates two tables: `foo` and `foo1`.
   - Populates `foo` with 100 rows and `foo1` with 200 rows of sample data.

2. **LangChain Integration**:
   - Initializes an OpenAI language model.
   - Sets up a SQL database chain using the PostgreSQL database.

3. **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

1. Ensure you have a PostgreSQL database set up and accessible.
2. Set the `LANGCHAINGO_POSTGRESQL` environment variable with your database connection string.
3. Make sure you have an OpenAI API key set up (the example uses default configuration).
4. 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.
