Generate SQL queries from schema only - AI-powered — n8n Workflow

Hoch Komplexität Auslöser20 Knoten⚒️ Engineering👁 38,321 Aufrufevon Yulia

Übersicht

This workflow is a modification of the previous template on how to create an SQL agent with LangChain and SQLite.

The key difference – the agent has access only to the database schema, not to the actual data. To achieve this, SQL queries are made outside the AI Agent node, and the results are never passed back to the agent.

This approach allows the agent to generate SQL queries based on the structure of tables and their relationships, without having to access the actual data.

This makes the p

Verwendete Knoten

MySQLAI AgentOpenAI Chat ModelSimple Memory

Workflow-Vorschau

Run this part only once
This section:
* loads a list of all tables from the database hosted o
* extracts the database schema for each table and adds
Pre-workflow setup
Connect to a free MySQL server and import your database
*The Chinook data used in this
On every chat message:
* The workflow gets the data from the local schema file
* faster processing time as we d
LangChain AI Agent's system prompt is modifie
It uses only the database schema to generate SQL querie
SQL query extraction
Check if the agent's response contains an SQL query. If
The AI Agent remembers the schema, questions,
- The SQL node accesses the database and exec
- Both the chat response and the query result are displ
When the agent responds without an SQL query,
modelmemory
OpenAI Chat Model
Window Buffer Memory
N
No Operation, do nothing
List all tables in a dat…
Extract database schema
A
Add table name to output
C
Convert data to binary
S
Save file locally
E
Extract data from file
C
Chat Trigger
AI Agent
W
When clicking "Test work…
C
Combine schema data and …
L
Load the schema from the…
E
Extract SQL query
C
Check if query exists
F
Format query results
Run SQL query
P
Prepare final output
C
Combine query result and…
20 nodes19 edges

So funktioniert es

  1. 1

    Auslöser

    Der Workflow startet mit einem auslöser-Auslöser.

  2. 2

    Verarbeitung

    Die Daten fließen durch 20 Knoten, connecting agent, chattrigger, converttofile.

  3. 3

    Ausgabe

    Der Workflow schließt seine Automatisierung ab und liefert das Ergebnis an das konfigurierte Ziel.

Knotendetails (20)

MY

MySQL

mySql

#1
AI

AI Agent

n8n-nodes-langchain.agent

#2
OP

OpenAI Chat Model

n8n-nodes-langchain.lmChatOpenAi

#3
SI

Simple Memory

n8n-nodes-langchain.memoryBufferWindow

#4

So importieren Sie diesen Workflow

  1. 1Klicken Sie rechts auf die Schaltfläche JSON herunterladen, um die Workflow-Datei zu speichern.
  2. 2Öffnen Sie Ihre n8n-Instanz. Gehen Sie zu Workflows → Neu → Aus Datei importieren.
  3. 3Wählen Sie die heruntergeladene Datei generate-sql-queries-from-schema-only-ai-powered und klicken Sie auf Importieren.
  4. 4Richten Sie Anmeldedaten für jeden Dienstknoten ein (API-Schlüssel, OAuth usw.).
  5. 5Klicken Sie auf Workflow testen, um zu überprüfen, ob alles funktioniert, und aktivieren Sie es dann.

Oder direkt in n8n → Aus JSON importieren einfügen:

{ "name": "Generate SQL queries from schema only - AI-powered", "nodes": [...], ...}

Integrationen

agentchattriggerconverttofileextractfromfileiflmchatopenaimanualtriggermemorybufferwindowmergemysqlreadwritefileset

Diesen Workflow holen

Herunterladen und mit einem Klick importieren

JSON herunterladenAuf n8n.io ansehen
Knoten20
Komplexitäthigh
Auslösertrigger
Aufrufe38,321
KategorieEngineering

Erstellt von

Yulia

Yulia

@yulia

Tags

agentchattriggerconverttofileextractfromfileiflmchatopenaimanualtriggermemorybufferwindowmergemysql

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