🧠 Email real time RAG Assistant with Gmail, OpenAI & PGVector
📌 Who’s it for
This workflow is ideal for:
- Professionals
- Project managers
- Sales and support teams
- Anyone managing high volumes of Gmail messages
It enables fast and intelligent search through your email inbox using natural language queries.
⚙️ How it works / What it does
- Continuously monitors your Gmail inbox for new emails.
- Extracts email content and metadata (subject, body, sender, date).
- Converts email content into vector embeddings using OpenAI.
- Stores embeddings in a PostgreSQL database with PGVector.
- A conversational AI agent performs semantic search on your stored email history.
- Supports time-sensitive and context-aware responses via OpenAI Chat model.
🚀 How to set up
- Connect your Gmail account to the Gmail Trigger node (with API access enabled).
- Configure OpenAI credentials for the Embedding and Chat nodes.
- Set up a PostgreSQL database with the PGVector extension enabled.
- Import the workflow into your n8n instance (Cloud or Self-hosted).
- Customize parameters like polling frequency, embedding settings, or vector query depth.
📋 Requirements
- ✅ n8n instance (Self-hosted or Cloud)
- ✅ Gmail account with API access
- ✅ OpenAI API Key
- ✅ PostgreSQL database with PGVector extension installed
🛠️ How to customize the workflow
- Email Filtering : Change filters in the Gmail Trigger to watch specific labels or senders.
- Text Splitting Granularity : Adjust chunkSizeandchunkOverlapin the text splitter node.
- Query Depth : Modify topKin the vector search node to retrieve more or fewer similar results.
- Prompt Tuning : Customize the system message or agent instructions in the RAG node.
- Workflow Extensions : Add notifications, error logging, Slack/Telegram alerts, or data exports.