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Telegram AI chatbot with document-based answers using OpenAI and PGVector RAG

n8nn8n24 modulesv1.0
NotionAirtableOpenAIGoogle DriveDropboxTelegram

AI Q&A Chatbot Workflow – Build Your Own AI Agent Trained on Private Documents This powerful AI automation add-on upgrades your Telegram Bot Starter Template by integrating a fully functional AI chatbot and a context-aware AI agent that answers user questions using your internal documents. Unlike generic bots, this chatbot uses your own data to respond with deeply personalized, context-relevant information — perfect for support, onboarding, internal knowledge access, and client-facing interactio

At a glance

Telegram AI chatbot with document-based answers using OpenAI and PGVector RAG is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects Notion, Airtable, OpenAI, Google Drive. It's free to download. Follow the 5-step import below to go live in minutes.

Platform
n8n
Connects
Notion, Airtable, OpenAI, Google Drive, Dropbox, Telegram
Modules
24
Price
Free
Version
v1.0
Telegram AI chatbot with document-based answers using OpenAI and PGVector RAG workflow diagram

About this workflow

AI Q&A Chatbot Workflow – Build Your Own AI Agent Trained on Private Documents This powerful AI automation add-on upgrades your Telegram Bot Starter Template by integrating a fully functional AI chatbot and a context-aware AI agent that answers user questions using your internal documents. Unlike generic bots, this chatbot uses your own data to respond with deeply personalized, context-relevant information — perfect for support, onboarding, internal knowledge access, and client-facing interactions. It connects to any PostgreSQL database — including Neon.tech, Supabase, or a self-hosted Postgres setup — allowing you to build custom AI-powered FAQ assistants, internal support bots, or knowledge-based customer service tools. --- 🧠 Why It Works: Contextual Retrieval The secret is Contextual Retrieval — a powerful technique where your documents are stored in a way that preserves meaning and context. This allows the AI to fetch highly relevant, source-backed responses, eliminating hallucinations and guesswork. > Data is embedded, chunked, and saved in a vector database (Postgres + PGVector), enabling smart semantic search tailored to your needs. 📖 Learn more about this approach in this article by Anthropic → --- ✨ Key Features - Chat with your internal documents: Uses your content to answer questions with precision - Built-in document vectorization: Pre-configured Google Drive ingestion flow (Notion, Airtable, Dropbox available separately) - Contextual memory: Past chats stored in PostgreSQL for personalized conversations - Plug-and-play architecture: Connect Supabase, OpenAI, custom APIs via n8n’s interface --- 👤 Who Can Use This Workflow? - Entrepreneurs & startups building branded AI chatbots without code - Customer support teams automating answers using documentation - Ops teams creating internal FAQ bots for onboarding and training - No-code developers using n8n to build Telegram bots with AI features --- ⚙️ Setup Instructions You'll find step-by-step instructions inside the workflow. Quick Setup Overview: 1. Import the workflow into n8n (cloud or self-hosted) 2. Add your Telegram Bot credentials 3. Connect your PostgreSQL DB (Neon, Supabase, etc.) 4. Set up document ingestion from Google Drive 5. Activate the workflow and start chatting --- 🧩 Extensibility This workflow is modular and ready to expand. Build powerful assistants by connecting additional workflows: - Vectorization modules for Notion, Airtable, Dropbox, and others - Any vector DB: Neon.tech, Supabase, or self-hosted PGVector - ✍🏻 Telegram User Registration Module → - 💵 Telegram Payment, Invoicing & Refund Module → --- 🧠 More Smart AI Agents Explore more AI workflows and agents on my Gumroad → - 🌐 Agent: Find in the Internet — fetches live info from the web - 📁 Agent: Search Internal Docs — queries Notion, Google Drive, etc. - 📦 Agent: Check Order Status — reads status from Airtable or CRM - 💰 Agent: Calculate Cost or Quote — builds pricing logic from inputs 📨 Submit your idea here for a custom AI agent →

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How to import this n8n workflow

  1. 1

    Download the workflow JSON file after purchase.

  2. 2

    Open n8n → click the menu → Import from File.

  3. 3

    Select the downloaded JSON and import.

  4. 4

    Set up credentials for each node that requires them.

  5. 5

    Click Execute Workflow to test, then activate.

Setup guide

Setup guide included

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  • JSON blueprint — instant download
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