Multi-AI Agent Database Query and Chart Generation

Target Audience

• Data Analysts: Those who need to extract insights from databases and visualize them quickly.
• Business Intelligence Professionals: Users who require automated reporting and chart generation for decision-making.
• Developers: Individuals looking to integrate AI capabilities into their applications for database interactions and data visualization.
• Researchers: Those needing to analyze large datasets and present findings in a clear, visual format.
• Educators: Teachers and trainers who want to utilize data in their curriculum and demonstrate data analysis techniques.

Problem Solved

This workflow addresses the challenge of efficiently querying databases and visualizing the results without requiring extensive coding knowledge. It automates the process of generating SQL queries based on user prompts and creating dynamic charts using QuickChart, thereby saving time and reducing the complexity of data analysis tasks.

Workflow Steps

1. Trigger: The workflow is initiated when a chat message is received from a user, allowing for a manual start.
2. User Input Processing: The primary AI agent captures the user's prompt and determines the action required (querying the database or generating a chart).
3. Database Query Execution: If the user requests data, the workflow executes an SQL query against a PostgreSQL database using the Execute SQL Query tool, returning the relevant records.
4. Chart Generation: If the user requests a chart, the workflow processes the database records and user prompt through the generate_chart_tool, which utilizes AI to create a Chart.js configuration object.
5. URL Construction: The workflow constructs a URL for QuickChart using the generated chart configuration, facilitating the creation of the chart image.
6. Final Output: The results of the database query and the chart URL are returned to the user in the chat, providing immediate insights and visualizations.