Email Query Automation Workflow

This workflow is designed for:

• Data Analysts: Who need to generate SQL queries from natural language requests related to email metadata.
• Database Administrators: Who want to automate the process of querying email databases and retrieving relevant information efficiently.
• Developers: Looking to integrate natural language processing with SQL databases for improved user interaction and data retrieval.
• Business Intelligence Professionals: Who require quick access to email data for reporting and analysis without needing extensive SQL knowledge.

This workflow addresses the challenge of translating natural language queries about emails into SQL queries that can be executed against a PostgreSQL database. It simplifies the process for users who may not be familiar with SQL syntax, allowing them to retrieve relevant email data quickly and accurately based on their requests.

1. Trigger the Workflow: The workflow can be manually initiated or triggered via a chat interface.
2. Load Database Schema: It checks for existing schema files or retrieves the schema from the database, ensuring the latest structure is used.
3. Extract User Input: The workflow captures the user's natural language query and combines it with the schema data.
4. AI Query Generation: An AI agent generates an appropriate SQL query based on the provided input while adhering to strict schema rules.
5. Query Execution: The generated SQL query is executed against the PostgreSQL database, and the results are formatted for output.
6. Results Presentation: The results are combined with the original chat input for seamless user feedback, ensuring clarity and relevance.