AI Agents · Lesson

Schema Understanding and Injection

Extracting and formatting DB schema for LLM context: tables, columns, relations.

Why Schema Context Matters

The LLM knows SQL syntax but knows nothing about your database. Without schema context, it will hallucinate table and column names.

Schema injection means programmatically extracting your DB structure and including it in every prompt — making the LLM aware of your exact tables, columns, and types.

Querying INFORMATION_SCHEMA

All major relational databases expose metadata through INFORMATION_SCHEMA. You can query it to get every table, column name, and data type without touching application code.

This works in PostgreSQL, MySQL, SQL Server, and SQLite (with minor differences).

import psycopg2

def get_schema(conn):
    query = '''
        SELECT table_name, column_name, data_type
        FROM information_schema.columns
        WHERE table_schema = 'public'
        ORDER BY table_name, ordinal_position
    '''
    with conn.cursor() as cur:
        cur.execute(query)
        return cur.fetchall()

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