🧠 RAG with Full Gmail history + Real time email updates in RAG using OpenAI & Qdrant
🧠 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. An n8n automation workflow template by Zain Ali.
Zain Ali
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