This article provides a complete, practical walkthrough of the Http Telegram Automation 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:**
   Building AI-Powered Telegram Bots with n8n and NeurochainAI: A Complete Low-Code Workflow
   
   **Meta Description:**
   Learn how to create an intelligent Telegram bot using n8n and NeurochainAI's REST and image-generation APIs. This guide walks through a low-code workflow that handles text and image requests via Telegram, integrates with NeurochainAI models, and provides dynamic error handling.
   
   **Keywords:**
   n8n workflow, Telegram bot, NeurochainAI, AI image generation, AI chatbot, low-code automation, Meta-LLaMA model, text-to-image API, REST API integration, prompt engineering, Telegram automation
   
   ---
   
   **Building AI-Powered Telegram Bots with n8n and NeurochainAI: A Complete Low-Code Workflow**
   
   The growing accessibility of powerful AI models through APIs has opened up exciting possibilities for automation and bot creation — especially when integrated with messaging platforms like Telegram. By combining n8n (a low-code workflow automation tool) with NeurochainAI, anyone can build sophisticated AI-powered bots capable of generating text or images in response to user input.
   
   In this article, we break down a complete n8n workflow that integrates a Telegram bot with NeurochainAI’s REST and image synthesis APIs. Whether you're a developer looking to prototype generative applications or an automation enthusiast exploring AI chat integrations, this guide will show how the pieces come together.
   
   ---
   
   ### Overview of the Workflow
   
   This n8n workflow titled “NeurochainAI Basic API Integration” serves as a smart, two-in-one assistant deployed via Telegram. It listens to Telegram messages and routes them based on context — either for language model responses or AI-generated images — powered by NeurochainAI’s API.
   
   Key goals of this automation include:
   
   - Detect and handle messages sent to a Telegram bot.
   - Parse and sanitize user prompts.
   - Forward prompt data to the appropriate NeurochainAI endpoint (text or image generation).
   - Return results (text or image) directly in Telegram.
   - Handle errors gracefully with user-friendly messages and retry actions.
   
   ---
   
   ### Features and How It Works
   
   #### 🔹 1. Telegram Trigger & Message Routing
   It all starts with the Telegram Trigger node, which listens for all message types. The workflow uses a Switch node to route messages based on their content:
   
   - Messages starting with `/flux`: prompt for image generation.
   - Messages mentioning `@NCNAI_BOT`: text interaction.
   - Direct/private messages: general AI conversation.
   
   This flexible routing allows a single bot to serve multiple AI functionalities.
   
   #### 🔹 2. Prompt Parsing and Typing Feedback
   Before submitting to the API, the user's message is cleaned using a JavaScript Code node — for example, stripping out the `/flux` command prefix. Simultaneously, a “Typing…” action is sent via Telegram to indicate that the bot is processing the request, improving UX.
   
   #### 🔹 3. Connecting to NeurochainAI APIs
   
   Two unique HTTP Request nodes serve the AI integrations:
   
   - 📄 **Text Response (REST API)**: Sends sanitized user input to NeurochainAI’s `/tasks/message` endpoint using the Meta-LLaMA-3.1-8B-Instruct-Q6_K.gguf model.
     
     Configurable parameters such as max_tokens, temperature, top_p, and frequency_penalty adjust the nature of the AI's response.
   
   - 🖼️ **Image Generation (Flux API)**: Uses NeurochainAI’s `/tasks/tti` endpoint to generate an image from a prompt with optional model selections like “flux1-schnell-gguf”.
   
     The image URL returned by this endpoint is parsed using another Code node and fetched using a follow-up HTTP request.
   
   #### 🔹 4. Telegram Delivery
   
   Once a response (text or image) is received:
   
   - Text messages are sent directly using Telegram’s sendMessage command.
   - Images are sent using sendPhoto, with the original prompt shown in the caption.
   
   These final results are cleanly threaded as replies to the user’s original Telegram message.
   
   #### 🔹 5. Intelligent Error Handling
   
   The workflow includes multiple Switch nodes and conditional branches to gracefully handle various error states, such as:
   
   - Prompt too short.
   - Invalid prompt structure.
   - Worker timeout or API inactivity.
   
   Friendly Telegram messages guide users to correct the error — and where applicable, include inline buttons to “Retry” the operation.
   
   ---
   
   ### Step-by-Step Setup
   
   1. **Create a Telegram Bot:**  
      Use BotFather on Telegram to set up a bot, then obtain the token and add it to all Telegram-related nodes.
   
   2. **Get a NeurochainAI API Key:**  
      Sign up or log in to NeurochainAI, then generate an API key from the "Inference as a Service" dashboard. Insert this key into OAuth headers for both REST and Flux API nodes.
   
   3. **Choose Your Model:**  
      The REST API node allows you to specify the AI model. Available models include:
   
      - Meta-Llama-3.1-8B-Instruct-Q6_K.gguf
      - Mistral-7B-Instruct-v0.2-GPTQ
      - flux1-schnell-gguf (for images)
   
   4. **Test & Iterate:**  
      Activate the workflow and try sending `/flux A futuristic robot in neon lights` or messages like `@NCNAI_BOT What is the capital of Germany?`.
   
   ---
   
   ### Real-World Use Cases
   
   - 🤖 AI Chatbot Assistant: Answer user questions or simulate conversation using powerful language models.
   - 🎨 AI Design Tools: Generate inspirational visuals based on user prompts, turning conversations into creative outputs.
   - 📈 Customer Support: Automate repetitive questions and route requests to human support if needed.
   - 📷 Social Media Bots: Generate shareable, custom imagery directly from Telegram commands.
   
   ---
   
   ### Third-Party APIs Used
   
   - 🔗 **Telegram Bot API**  
     Used for interacting with the Telegram messaging platform — sending/receiving messages, photos, typing indicators, inline keyboard buttons.
   
   - 🔗 **NeurochainAI API**  
     - REST Endpoint: https://ncmb.neurochain.io/tasks/message  
     - Flux Image Generation Endpoint: https://ncmb.neurochain.io/tasks/tti  
     Used to generate AI text responses and text-to-image content.
   
   ---
   
   This powerful n8n automation symbolizes the next step in citizen development — where setting up conversational AI or creative agents doesn’t require writing thousands of lines of code. By bridging Telegram and NeurochainAI, you can offer engaging AI-driven user experiences with minimal effort.
   
   Ready to try it? Build, customize, and deploy your Telegram AI assistant today!
   
   --- 
   
   Need Help Getting Started?
   Explore more on the official [n8n Docs](https://docs.n8n.io/) and [NeurochainAI Dashboard](https://neurochain.io/).

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.