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 a Telegram-Powered Social Media Post Generator Using n8n, OpenAI, and Stable Diffusion
   
   Meta Description:
   Learn how to create an intelligent content generation bot using n8n that listens to Telegram messages, uses OpenAI for voice transcription and content writing, SerpAPI for real-time research, and generates visual prompts for image creation with Stable Diffusion.
   
   Keywords:
   n8n Telegram workflow, OpenAI Whisper, GPT-4o, Stable Diffusion image generation, Telegram bot automation, voice-to-text transcription, SerpAPI research automation, social media content AI, AI content generator, LangChain agent, automation with n8n
   
   —
   
   Article:
   
   Build a Telegram-Powered Social Media Content Generator with AI and n8n
   
   In our modern, fast-paced digital world, the demand for unique, engaging, and SEO-optimized social media content has never been higher. Whether you’re a solopreneur, digital marketer, or content creator, keeping up with content demands can be overwhelming. Imagine if you could just send a message—text or voice—on Telegram, and a fully-developed post along with a detailed image prompt is generated automatically, ready to be published.
   
   Thanks to the powerful automations possible with n8n, paired with AI services like OpenAI, SerpAPI, and the Stable Diffusion image generation model, that vision is now a reality. In this article, we’ll break down a robust and intelligent n8n workflow designed to convert Telegram messages into research-backed social media content—complete with photorealistic image prompts.
   
   Overview of the Workflow
   
   At the heart of this solution is n8n, an open-source workflow automation tool similar to Zapier but infinitely more customizable. Here’s what this multi-stage workflow does:
   
   1. Listens for incoming Telegram messages (either voice or text).
   2. Transcribes voice messages into text using OpenAI’s Whisper API.
   3. Determines whether the input is valid (voice or text); otherwise, gives an error.
   4. Sends the interpreted user request to an AI Agent built with LangChain and OpenAI.
   5. Uses SerpAPI to gather real-time research on the input topic.
   6. Generates a compelling, SEO-friendly social media post using GPT-4o.
   7. Crafts a hyper-detailed instruction for image generation using Stable Diffusion.
   8. Sends the image prompt to the Hugging Face API, which returns a generated image.
   9. Packages the text content and image together in a structured JSON output.
   
   Let’s explore each of these components in more detail.
   
   Step 1: Receiving Messages via Telegram
   
   The process begins with a Telegram Trigger node. This node listens for new messages sent to the connected bot. Users can send either a voice note or a text message, each of which is then filtered through a Switch node to determine the content type.
   
   Step 2: Voice Transcription Using OpenAI Whisper
   
   If the message is a voice note, it’s fetched via Telegram’s API using the file ID and transcribed into text using the OpenAI Whisper model. This automatic transcription eliminates the need for manual typing, perfect for capturing ideas on the go.
   
   Step 3: Preparing the Input for the AI Agent
   
   Once the workflow has a pure text input—whether via direct text or transcription—it routes it into a preparation step in which the necessary data fields are normalized and sent to the AI Agent node powered by LangChain.
   
   Step 4: Supercharging Content Creation with LangChain and OpenAI
   
   The LangChain AI Agent is configured with a detailed multi-part system prompt to guide its behavior. The agent performs three specific tasks:
   
   - Uses SerpAPI to research the user’s topic thoroughly.
   - Writes an 800–1000 character social media post that is engaging, factually accurate, and SEO-optimized.
   - Creates a highly descriptive, photorealistic prompt for an AI image generator, simulating how a platform like DALL·E or Stable Diffusion would interpret it.
   
   Step 5: Generating the Image Prompt and Sending to Stable Diffusion
   
   The image prompt generated by the AI Agent is then passed along to a Hugging Face-hosted Stable Diffusion 3.5 model. Using HTTP POST requests with predefined credentials, the workflow receives a generated image based on the prompt.
   
   The result? A stunning visual paired with a quality piece of social media content—output in formatted JSON like:
   
   {
     "content": "Boost your mood & health! 💪 Regular exercise reduces stress, improves sleep, and lowers disease risk. Get moving today! #exercise #healthylifestyle #fitness",
     "image": "[Base64 or URL of generated image]"
   }
   
   Step 6: Final Output Assembly
   
   A Set node formats the final response, which could be sent back to Telegram, stored in a database, or used in another system for scheduling and deployment to social platforms. All of this is achieved without writing a single line of traditional code.
   
   Why This Workflow Matters
   
   This workflow is more than just a novelty. It provides concrete benefits for busy creators:
   
   - ✅ Voice-based input makes ideation seamless on mobile.
   - ✅ Automated research ensures factual accuracy.
   - ✅ AI writing makes content creation scalable.
   - ✅ Image generation makes your posts eye-catching.
   - ✅ Fully customizable and open source.
   
   This is the future of AI-powered content pipelines—automated, intelligent, and efficient.
   
   List of Third-Party APIs Used:
   
   - Telegram API (for message listening and media fetching)
   - OpenAI Whisper (for voice-to-text transcription via the LanguageChain OpenAI Audio endpoint)
   - OpenAI GPT-4o (as the core language model for content generation)
   - SerpAPI (for topic research via real-time web search)
   - LangChain (for orchestration and agent logic)
   - Hugging Face Inference API (used to generate images via Stable Diffusion)
   
   Final Thoughts
   
   By combining powerful tools like n8n, Telegram, OpenAI, SerpAPI, and Hugging Face, we’ve automated a complex content creation workflow into a simple input system. Whether you're building this for a client, your own brand, or a productized SaaS offering, the possibilities are endless.
   
   Would you like to try this yourself or customize it even further? With n8n’s no-code environment, you can adjust every piece of the puzzle to fit your specific use case.
   
   Welcome to the future of AI-driven content automation. 🚀

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.