Autonomous Data Analysis Agent with Dify

This Dify agent workflow connects to a SQL database, accepts natural language questions, writes and executes SQL queries, analyzes the results, generates visualizations, and outputs a formatted analysis report with actionable insights.

Workflow Diagram

Step-by-Step Guide

1. 1

   Database Connection

   In Dify, add a database tool connection. Provide your PostgreSQL/MySQL connection string. Configure read-only access to prevent accidental writes. Set a row limit of 10,000 to prevent memory issues.

2. 2

   Agent Configuration

   Create a new Agent app with ReAct (Reasoning + Acting) mode. Add the database tool and a code execution tool. Set the system prompt: 'You are a data analyst. When given a question, write SQL, execute it, analyze the results, and provide insights. Always explain your SQL logic before running it.'

3. 3

   Query Safety Layer

   Add a pre-processing Code node that validates the SQL query before execution. Block DROP, DELETE, UPDATE, INSERT statements. Add a timeout of 30 seconds per query. Log all queries for audit.

4. 4

   Visualization Generation

   After the agent gets query results, use a Code node to generate a chart using a JavaScript charting library (e.g., Chart.js). Convert the chart to a base64 image and embed it in the response.

5. 5

   Report Output

   Format the final output as a structured report: 1) Executive summary, 2) SQL query used, 3) Data table (top 20 rows), 4) Chart visualization, 5) Key insights (3-5 bullet points), 6) Recommended actions. Save to your knowledge base for future reference.

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