Build an Interactive Q&A NotebookLM-Style Bot for Telegram

Overview

NotebookLM doesn’t yet provide a public API for live querying, but you can build a Telegram bot that behaves almost identically by combining:

  • Your NotebookLM source documents (stored in Google Drive)

  • Google Drive API

  • Gemini (Google AI Studio or Vertex AI)

  • Telegram Bot API

This gives you a mobile-friendly interface where users ask questions like:

“Summarize the latest research notes”
“What are the key themes across the last 10 documents?”
“Explain yesterday’s doc in simple terms.”

What You Will Build

A Telegram bot that:

  1. Receives a question.

  2. Pulls relevant content from your Google Drive folder (same sources used in NotebookLM).

  3. Sends that content + the question to a Gemini model for grounded reasoning.

  4. Produces an answer in Telegram.

This effectively becomes "NotebookLM in Telegram" using the same knowledge base.

Prerequisites

  • Telegram bot token

  • Google Cloud project

  • Gemini API (API key or service account)

  • Google Drive API access

  • Node.js or Python backend

  • NotebookLM sources stored in Google Drive

Step-by-Step Instructions

Step 1 — Prepare your NotebookLM sources

  1. Put all documents you want the bot to use into a folder, e.g.:
    NotebookLM Knowledge Base

  2. Use Docs, Sheets, PDFs, audio transcripts, etc.

  3. Grant your service account read access.

Step 2 — Create your Telegram bot

  1. Use @BotFather

  2. Run: /newbot

  3. Save the bot token.

Step 3 — Build the backend logic

3.1 Listen to messages

Your backend endpoint receives messages via Telegram’s webhook or long polling.

Example flow:

  • User sends: /ask summarize the last meeting

  • Your server gets:

    • chat_id

    • text

  • You parse the command.

3.2 Retrieve relevant documents

Using Google Drive API:

  • List files in your “NotebookLM Knowledge Base” folder

  • Fetch the content of:

    • The most recent docs

    • Docs matching a keyword

    • Or all docs (depending on your design)

3.3 Send content + question to Gemini

Format a prompt:

You are an assistant with access to the following source documents.

Sources:
{{doc_text_1}}
{{doc_text_2}}
...

User Question:
{{user_query}}

Provide a grounded, structured answer citing text where appropriate.

Call Gemini’s model (e.g. gemini-pro or gemini-1.5).

3.4 Send the answer back to Telegram

Use Telegram’s sendMessage API or replyMarkup capabilities for formatting.

Step 4 — Deploy your bot

Deploy to:

  • Google Cloud Run

  • Railway

  • Render

  • Heroku

  • Vercel (serverless)

Then set Telegram webhook:

https://api.telegram.org/bot<YOUR_BOT_TOKEN>/setWebhook?url=<YOUR_DEPLOYED_URL>

Step 5 — Test your assistant

In Telegram:

/ask summarize the Q1 planning doc

or

What were the customer pain points found in the last 5 files?

You should get a grounded answer derived from your NotebookLM source folder.

Done!

You now have a powerful interactive Telegram companion that replicates core NotebookLM behavior:

  • Summarization

  • Research assistance

  • Q&A

  • Document comparison

  • Custom prompts

Right inside Telegram.

NotebookLM, Notebook LM, TelegramFrancesca Tabor