Database Search Node

The Database Search node lets you query a connected SQL database using natural language or explicit search text. It returns a list of tables (and optional aliases) that match your criteria, which you can then use in downstream SQL actions or function calls.

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🔧 Configuration Panel

When you expand the node, you’ll see three main sections:

1. Model & Instruction
2. Search Text
3. Database & Table Selection

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⚙️ 1. Model & Instruction

• Header Bar: Shows the current LLM model (gpt-4) and the “Instruction” label.
• Usage: Click the pencil icon to add an optional system prompt that guides how the AI matches tables.

Model: gpt-4   Instruction: [edit…]

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⚙️ 2. Search Text

• Field: Search Text

• Type: Text input

• Purpose: A short phrase or keyword that describes the table(s) you want to find.

• Example:

  • user profile
  • transactions in the last 30 days
  • customer orders summary

Search Text: [ Enter your keywords… ]

The AI will use this text to rank and surface relevant tables from the selected database.

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⚙️ 3. Database Name

• Field: Database Name (required)
• Type: Dropdown
• Options: All databases you’ve connected (e.g. digisquaresmysql, Default: MySQL).
• Purpose: Choose which data source to search in.

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⚙️ 4. Table Name & Alias

Once you hit OK, the node will populate a table of matching results:

Table Name	Alias
customers	cust
orders	—
transaction_log	tx_log

• Table Name: The actual schema name in your database.
• Alias: (Optional) A shorthand you can assign to refer to this table in later SQL or function calls.

How to use aliases

• In subsequent SQL nodes, reference cust instead of customers for brevity:

  SELECT cust.name, cust.email FROM customers AS cust;

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🚀 Best Practices

• Be specific in your search text to avoid broad results (e.g. “monthly sales” rather than just “sales”).
• Choose the correct database if you have multiple connections.
• Assign aliases to avoid long table names in your code.
• Review results visually in preview mode before running queries.
• Combine with JSON Instruction or Function Calling to programmatically build full SQL statements using the tables you select.

Example flow:
1. Database Search → fetch “transactions” from `digisquaresmysql`
2. JSON Instruction → build JSON payload { "table": "transaction_log", "alias": "tx" }
3. Function Calling → run `queryDatabase` with this payload

By leveraging the Database Search node, you can quickly discover and reference the right tables without memorizing your schema.