This article provides a complete, practical walkthrough of the Http Telegram Create Webhook 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 an AI-Powered Telegram Bot with Long-Term Memory Using n8n, Supabase & OpenAI
   
   Meta Description:  
   Learn how to create a conversational AI Telegram bot using n8n, Supabase, and OpenAI's Assistants API. This no-code workflow enables persistent user memory for smarter, more contextual interactions.
   
   Keywords:  
   n8n Telegram bot, OpenAI assistant, Supabase memory, no-code chatbot, Telegram AI bot, OpenAI chat bot, contextual conversations, store Telegram user data, GPT-4o, OpenAI API integration, AI chatbot with memory
   
   Third-Party APIs Used:
   
   1. Telegram Bot API  
   2. OpenAI API (Assistants v2)  
   3. Supabase API  
   
   ---
   
   # Build an AI Telegram Bot with Long-Term Memory Using n8n, Supabase, and OpenAI
   
   In today's AI landscape, conversational bots are everywhere—but most of them lack context beyond the current session. Imagine being able to chat with a bot that remembers you and your past questions. This article walks you through setting up an AI-powered Telegram bot that integrates real-time OpenAI responses while retaining user memory through Supabase, all orchestrated by the no-code workflow automation tool, n8n.
   
   ### What You'll Build
   
   You’ll create an AI Telegram bot that:
   - Responds intelligently using OpenAI GPT models via the Assistants v2 API
   - Stores and retrieves user sessions using Supabase
   - Remembers users and continues conversations where they left off
   - Uses n8n to stitch everything together without needing to write complex code
   
   This solution is ideal for virtual assistants, customer support bots, or any application where continuity of conversation is essential.
   
   ---
   
   ## How the Workflow Works
   
   Here’s how the automation flows—from the moment a user sends a message to receiving a smart AI reply:
   
   ### Step 1: Trigger – Receive Messages via Telegram
   
   The `Telegram Trigger` node listens for incoming messages from users. This node requires a bot token created via the BotFather bot on Telegram.
   
   Whenever a user sends a message (e.g., “Hello, how are you?”), this node passes it down the chain.
   
   ### Step 2: Check for Existing User Data in Supabase
   
   The `Find User` node queries your Supabase database to check if the Telegram user already exists.
   
   - If a match is found, it continues with the stored `openai_thread_id`.
   - If not, the workflow proceeds to create a new thread.
   
   ### Step 3: On First-Time Contact – Create OpenAI Thread & Store User Info
   
   For new users:
   - A new thread is generated via the `OPENAI - Create thread` node using the OpenAI Assistants API.
   - The `Create User` node writes the Telegram user ID and the newly created thread ID into a `telegram_users` Supabase table:
     ```sql
     create table public.telegram_users (
       id uuid not null default gen_random_uuid (),
       date_created timestamp with time zone not null default now(),
       telegram_id bigint,
       openai_thread_id text,
       primary key (id)
     );
     ```
   
   This ensures future messages are tied to the same conversation thread, enabling context retention.
   
   ### Step 4: Merge Data for Next Steps
   
   Using the `Merge` node, the workflow consolidates the OpenAI thread ID and user message data needed downstream.
   
   ### Step 5: Send the User’s Message to OpenAI Assistant
   
   The bot sends the user’s message to the OpenAI Assistants API through the `OPENAI - Send message` node. The message is labeled with the "user" role to help the assistant interpret it correctly.
   
   ### Step 6: Trigger the Assistant Logic
   
   Next, the `OPENAI - Run assistant` node runs your preconfigured assistant (identified by the `assistant_id`) to generate a response. You can create and customize your assistant in the [OpenAI Assistants Dashboard](https://platform.openai.com/assistants).
   
   This assistant could be tailored to act as a language tutor, shopping assistant, customer service rep, or anything else you imagine.
   
   ### Step 7: Retrieve the Assistant’s Response
   
   Once processed, the `OPENAI - Get messages` node pulls messages from the associated OpenAI thread. The assistant’s latest response is extracted.
   
   ### Step 8: Respond to the User on Telegram
   
   The AI-generated message is finally sent back to the Telegram user using the `Send Message to User` node.
   
   The response includes full context, creating an engaging and intelligent user experience:
   > "Hello! I'm just a program, but I'm here and ready to help you. How can I assist you today?"
   
   ---
   
   ## Why Use Supabase?
   
   Supabase acts as the memory layer in this architecture. Unlike stateless bots that forget every past interaction, this bot uses Supabase to store a unique `openai_thread_id` per Telegram user.
   
   This thread is used to fetch and send messages, preserving conversational continuity.
   
   ## Technologies Behind the Scenes
   
   Here's a breakdown of the third-party services used:
   
   | Service      | Role                                           |
   |--------------|------------------------------------------------|
   | Telegram API | Enables message exchange with users            |
   | Supabase     | Stores user sessions and OpenAI thread IDs     |
   | OpenAI API   | Provides the Assistant engine (GPT-4o, etc.)   |
   
   ## Setup Checklist
   
   To build this yourself, follow these steps:
   
   1. 🧠 **Create a Telegram Bot**  
      Use [BotFather](https://t.me/botfather) to obtain your `telegram_token`.
   
   2. 🗃️ **Set Up Supabase Project**  
      - Use the provided SQL to create a `telegram_users` table.
      - Grab your `SUPABASE_URL` and `SUPABASE_KEY`.
   
   3. 🤖 **Configure OpenAI Assistant**  
      - Create an assistant in OpenAI's dashboard.
      - Copy the `assistant_id`.
   
   4. 🔧 **Set Up n8n Workflow**  
      - Configure three credentials: Telegram, Supabase, and OpenAI.
      - Set up the workflow nodes as shown in the example.
      - Start the workflow and talk to your bot!
   
   ---
   
   ## Final Thoughts
   
   This chatbot is more than just a clever gimmick; it’s a powerful template showing how you can build persistent, context-aware AI experiences using no-code tools. Thanks to n8n's visual automation engine, Supabase’s scalable backend, and OpenAI's cutting-edge models, you can deliver highly engaging interactions—no code required.
   
   Want to set it up yourself in under 5 minutes?  
   👉 Watch the video tutorial here: [YouTube Setup Video](https://www.youtube.com/watch?v=kS41gut8l0g)
   
   —
   
   Made by [Mark Shcherbakov](https://www.linkedin.com/in/marklowcoding/) for the [5minAI Community](https://www.skool.com/5minai-2861) 💡
   
   Now your AI bots can remember you. Welcome to the future of conversations.

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.