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