Gmail Assistant with Full Gmail history RAG using OpenAI

Description

🧠 RAG with Full Gmail history + Real time email updates in RAG using OpenAI & Qdrant

> Summary:
> This workflow listens for new Gmail messages, extracts and cleans email content, generates embeddings via OpenAI, stores them in a Qdrant vector database, and then enables a Retrieval‑Augmented‑Generation (RAG) agent to answer user queries against those stored emails. It’s designed for teams or bots that need conversational access to past emails.

🧑‍🤝‍🧑 Who’s it for
Support teams** who want to surface past customer emails in chatbots or help‑desk portals
Sales ops** that need AI‑powered summaries and quick lookup of email histories
Developers** building RAG agents over email archives

⚙️ How it works / What it does
Trigger
Gmail Trigger polls every minute for new messages.
Fetch & Clean
Get Mail Data pulls full message metadata and body.
Code node normalizes the body (removes line breaks, collapses spaces).
Embed & Store
Embeddings OpenAI node computes vector embeddings.
Qdrant Vector Store inserts embeddings + metadata into the emails_history collection.
Batch Processing
SplitInBatches handles large inbox loads in chunks of 50.
RAG Interaction
When chat message received → RAG Agent → uses Qdrant Email Vector Store as a tool to retrieve relevant email snippets before responding.
Memory
Simple Memory buffer ensures the agent retains recent context.

🛠️ How to set up
n8n Instance
Deploy n8n (self‑hosted or via Coolify/Docker).
Credentials
Create an OAuth2 credential in n8n for Gmail (with Gmail API scopes).
Add your OpenAI API key in n8n credentials.
Qdrant
Stand up a Qdrant instance (self‑hosted or Qdrant Cloud).
Note your host, port, and API key (if any).
Import Workflow
In n8n, go to Workflows → Import → paste the JSON you provided.
Ensure each credential reference (Gmail & OpenAI) matches your n8n credential IDs.
Test
Click Execute Workflow or send a test email to your Gmail.
Monitor n8n logs: you should see new points in Qdrant and RAG responses.

📋 Requirements
n8n** (Self-hosted or Cloud)
Gmail API** enabled on a Google Cloud project
OpenAI API** access (with Embedding & Chat endpoints)
Qdrant** (hosted or cloud) with a collection named emails_history

🎨 How to customize the workflow
Change Collection Name**
Update the qdrantCollection.value in all Qdrant nodes if you prefer a different collection.
Adjust Polling Frequency**
In the Gmail Trigger node, switch from everyMinute to everyFiveMinutes or a webhook‑style trigger.
Metadata Tags**
In Enhanced Default Data Loader, tweak the metadataValues to tag by folder, label, or sender domain.
Batch Size**
In SplitInBatches, change batchSize to suit your inbox volume.
RAG Agent Prompt**
Customize the systemMessage in the RAG Agent node to set the assistant’s tone, instruct on date handling, or add additional tools.
Additional Tools**
Chain other n8n nodes (e.g., Slack, Discord) after the RAG Agent to broadcast AI answers to team channels.