This article provides a complete, practical walkthrough of the Telegram Gmailtool Send Triggered n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   Build Your Own AI Personal Assistant with n8n, ChatGPT, Google, Gmail & Telegram
   
   Meta Description:  
   Discover how to create a fully automated AI personal assistant using n8n, Telegram, OpenAI GPT-4, Google Calendar, Gmail, and Baserow. Learn how Angie, the AI assistant, reads emails, checks your calendar, and responds to Telegram voice or text queries.
   
   Keywords:  
   n8n workflow, AI personal assistant, OpenAI GPT-4, Telegram bot, Gmail automation, Google Calendar API, Baserow, GPT-4o-mini, automate emails, voice-to-text automation, AI workflow automation, AI task assistant, OpenAI n8n integration, productivity automation
   
   Third-Party APIs and Services Used:
   
   1. OpenAI (ChatGPT, GPT-4, speech-to-text transcription)
   2. Telegram (Bot API for triggers and messaging)
   3. Google Calendar API (via Google OAuth)
   4. Gmail API (via Gmail OAuth)
   5. Baserow (Database service for tasks and contact management)
   
   Article:
   
   How to Build an AI Personal Assistant Using n8n, OpenAI, Google, Gmail, and Telegram
   
   In today's fast-paced digital world, juggling emails, calendar events, and countless to-do lists can feel overwhelming. But what if you had an AI assistant who could automatically summarize your unread emails, check your calendar, understand your tasks, and answer any question you ask—whether by text or voice—on Telegram? Thanks to a powerful no-code/low-code automation platform called n8n, you can now build just that. Meet Angie, the AI assistant.
   
   In this article, we’ll explore a sophisticated n8n workflow that seamlessly integrates OpenAI’s GPT-4, Google services, Gmail, Telegram, and Baserow to build your very own AI productivity assistant.
   
   💡 Getting Started: The Idea Behind Angie
   
   The cornerstone of this workflow is interaction. A user communicates with Angie via Telegram, either by typing or sending a voice message. Angie intelligently processes your request—whether it’s about today’s meetings, unread emails, or tasks—and replies with a summarized result tailored to your query.
   
   Let’s break down the functionality layer-by-layer.
   
   🎧 Step 1: Listening on Telegram
   
   The workflow begins with a Telegram Trigger node that listens for incoming events like messages or voice notes. Whether you type “What’s on my calendar today?” or send a spoken version of that query, Angie is ready to assist.
   
   The user's message is processed through a logic fork:
   
   - If the message is typed text, it proceeds directly.
   - If it's a voice message, it's routed through Telegram’s API to download the voice file, which is then transcribed to text using OpenAI's speech-to-text (Whisper) capability.
   
   🧠 Step 2: Memory and Context
   
   A memory buffer is maintained using LangChain’s Window Buffer Memory node, which stores the conversational context based on the Telegram user’s ID. This is important when a user wants to maintain a flowing conversation with the assistant, like asking follow-up questions.
   
   💬 Step 3: Language Understanding and AI Thinking
   
   All incoming messages (whether spoken or typed) are passed through OpenAI’s GPT-4o-mini via LangChain agents. Angie, powered by this model, understands the intent and context of your question. She uses the system message to apply logic and filters intelligently—for instance, if you ask about today’s schedule, she will only return today's calendar events and not future ones.
   
   🗓️ Step 4: Fetching Data from External Sources
   
   Depending on your request, the AI may need to pull in additional information from external APIs:
   
   - Google Calendar: Angie retrieves upcoming events from your calendar, filtered by the time window specified in the user's message. She uses $fromAI to extract date entities from the user's query naturally.
     
   - Gmail: Unread emails are fetched from your inbox, excluding promotional messages. Angie summarizes each message beautifully, giving a snapshot that includes sender, date, subject, and a concise message.
   
   - Baserow: This tool is used to access task and contact information from a custom database. If you ask, “What tasks are due today?” or “What’s John’s email address?” she knows where to look.
   
   🧠 Example System Message Guide for GPT-4:
   
   The AI’s effectiveness is powered by thoughtful instructions in the system prompt such as:
   
   - "Summarize emails including sender, date, and subject."
   - "If the user didn’t specify a date, assume today."
   - "Filter future calendar events more than a week away."
   
   These guidelines help Angie give you natural, concise, and contextually relevant replies.
   
   📩 Step 5: Delivering the Response
   
   Once Angie composes her response, it’s sent back to the originating Telegram user using Telegram’s Send Message node. The message includes markdown parsing for rich formatting and includes no attribution, keeping responses streamlined and elegant.
   
   A Smooth Voice-to-AI to Data to Message Pipeline
   
   This workflow showcases the true power of n8n in connecting multiple third-party APIs effortlessly. Whether it’s converting voice to text, tapping into your daily schedule, summarizing your inbox, or crawling a custom Baserow database, each task runs seamlessly and intelligently in the background.
   
   🌟 Bonus: Support for Voice Commands
   
   A defining feature is Angie’s support for audio messages. You no longer need to type. Just say, “What emails did I get today?” and let Angie transcribe, interpret, and answer—all within seconds.
   
   🔗 Want to Build It Yourself?
   
   This workflow is publicly inspired by a tutorial:  
   [📺 Watch: Build an AI Personal Assistant on YouTube](https://youtu.be/pXjowPc6V2s)
   
   📦 Tools in the Stack
   
   - n8n (Core automation platform)
   - OpenAI GPT-4o-mini (Language understanding, summarization, voice-to-text)
   - Telegram (Bot interface for user interaction)
   - Gmail API (Fetch unread messages)
   - Google Calendar API (Fetch events with date filters)
   - Baserow (Manage personal data like contacts and task lists)
   
   🎯 Final Thoughts
   
   Angie isn’t just a chatbot—it’s a context-aware AI assistant that proactively retrieves the right data, processes natural language, and helps you stay focused. Whether you’re managing a packed inbox, planning your day, or recalling your to-dos, this AI assistant will make your digital life more efficient.
   
   Thanks to n8n’s open-source and visual development environment, setting up your own version of Angie is not only achievable—it’s incredibly empowering.
   
   Work smarter, not harder—with your own AI assistant in your Telegram pocket.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.