Email Assistant: Convert Natural Language to SQL Queries with Phi4-mini and PostgreSQL

# Who is this for? **Humans** and **Robots** alike. This workflow can be used as a **Chat trigger**, as well as a **Workflow trigger**. It will take a natural language request, and then generate a `SQL` query. The resulting `query` parameter will contain the query, and a `sqloutput` parameter will contain the results of executing such a query. ## What's the use case? This template is most useful paired with other workflows that extract e-mail information and store it in a structured Postgres table, and use LLMs to understand inquiries about information contained in an e-mail inbox and formulate questions that need answering. Plus, the prompt can be easily adapted to formulate SQL queries over any kind of structured database. ## Privacy and Economics As an LLM provider, I'm using **Ollama** locally, as I consider my e-mail extremely sensitive information. As a model, [`phi4-mini`](https://ollama.com/library/phi4-mini) does an excellent job balancing quality and efficiency. ## Setup Upon running for the first time, this workflow will **automatically** trigger a sub-section to read all tables and extract their schema into a local file. Then, either by **chatting** with the workflow in n8n's interface or by using it as a **sub-workflow**, you will get a `query` and a `sqloutput` response. ## Customizations If you want to work with just one particular table yet keep edits at bay, append a condition to the `List all tables in a database` step, like so: ```sql WHERE table_schema=public AND table_name=my_emails_table_name ``` To repurpose this workflow to work with any other data corpus in a structured database, inspect the `AI Agent` **user** and **system** prompts and edit them accordingly.