HumationHuman + Automation
Back to Catalog

Telegram bot: analyze images with GPT-4o-Mini/NVIDIA Vila & generate images with Stable Diffusion 3

Cheng Siong ChinCheng Siong Chin
348 views
2/3/2026
StorageS3WebhookAPIFile Upload
Official Page

Introduction

Transform your Telegram bot into an AI vision system using GPT-4o-Mini and NVIDIA Stable Diffusion 3. Perfect for content moderators, researchers, and developers.

Workflow Explanatory

  1. At start: Processes Telegram messages: images→analysis, text→image generation
  2. At Router: Routes by content type
  3. Upper path: Analyzes images using Nvidia Vila + GPT-4o-Mini
  4. Lower path: Generates images from text via Stable Diffusion 3
  5. At Merge: Combines AI results
  6. At Gmail: Emails processed results

How It Works

  1. Telegram Trigger listens for messages (images, text, documents)
  2. Content Router directs images → AI analysis, text → image generation
  3. Image Analysis: Downloads image → GPT-4o-Mini vision analysis → Email results
  4. Image Generation: Text prompt → Stable Diffusion 3 → Email generated image
  5. Gmail Notifications send formatted reports

Prerequisites

  • Telegram Bot token (via @BotFather)
  • OpenAI API key (GPT-4 Vision)
  • NVIDIA API key (free tier available)
  • Gmail OAuth2 credentials

Setup Steps

Setup Steps

  1. ** Create Telegram Bot** - Create Telegram bot and obtain token
  2. ** Configure API Credentials** - Configure API credentials in HTTP Request nodes
  3. ** Set Up Gmail OAuth2** - Set up Gmail OAuth2
  4. ** Import and Activate Workflow** - Import workflow, update credentials, and activate

Customization Options

  • Add more AI models (Anthropic, Gemini)
  • Route audio/documents to transcription/OCR
  • Replace Gmail with Slack or Discord
  • Connect to databases for storage

Benefits

  • Speed: Seconds per analysis vs. hours manually
  • Accuracy: AI-powered visual understanding
  • Intelligence: Historical tracking enables trend analysis

Telegram Bot: Analyze Images with GPT-4o & Generate Images with Stable Diffusion 3

This n8n workflow creates an interactive Telegram bot that can analyze images using OpenAI's GPT-4o vision capabilities and generate new images using Stable Diffusion 3. It provides a versatile tool for image understanding and creation directly from your Telegram chat.

Description

This workflow simplifies the process of interacting with advanced AI models for image analysis and generation through a user-friendly Telegram bot. Users can send an image to the bot for a detailed description or send a text prompt to generate a new image.

What it does

  1. Listens for Telegram messages: The workflow is triggered by incoming messages to a configured Telegram bot.
  2. Determines message type: It checks if the incoming message contains an image or a text message.
  3. Image Analysis (GPT-4o):
    • If an image is received, it downloads the image.
    • It then sends the image to OpenAI's GPT-4o model with a prompt to analyze and describe the image.
    • The bot sends the detailed description back to the user in Telegram.
  4. Image Generation (Stable Diffusion 3):
    • If a text message is received, it assumes the user wants to generate an image.
    • It sends the text prompt to a Stable Diffusion 3 API (via an HTTP Request node).
    • Once the image is generated, the bot sends the resulting image back to the user in Telegram.
  5. Error Handling: If any issues occur during the process, an email notification is sent via Gmail.

Prerequisites/Requirements

  • n8n Instance: A running n8n instance.
  • Telegram Bot Token: A Telegram bot created via BotFather.
  • OpenAI API Key: An API key for OpenAI with access to GPT-4o.
  • Stable Diffusion 3 API Endpoint: Access to a Stable Diffusion 3 API (e.g., via a custom deployment, a service like Stability AI, or another platform that exposes an HTTP endpoint for image generation).
  • Gmail Account: For error notifications (optional, but recommended).

Setup/Usage

  1. Import the workflow: Download the provided JSON and import it into your n8n instance.
  2. Configure Telegram Trigger:
    • Add your Telegram Bot Token to the "Telegram Trigger" node's credential.
    • Ensure the webhook is set up correctly (n8n will guide you).
  3. Configure OpenAI Node:
    • Add your OpenAI API Key to the "OpenAI" node's credential.
    • Verify the model is set to gpt-4o.
  4. Configure HTTP Request (Stable Diffusion 3):
    • Edit the "HTTP Request" node.
    • Update the URL to your Stable Diffusion 3 API endpoint.
    • Configure any necessary headers (e.g., API keys, content type) and the request body to send the text prompt for image generation.
  5. Configure Gmail (Optional):
    • Add your Gmail credentials to the "Gmail" node if you wish to receive error notifications.
    • Update the "To" email address in the "Gmail" node.
  6. Activate the workflow: Once all credentials and configurations are set, activate the workflow.

Now, you can interact with your Telegram bot:

  • Send an image to get a description.
  • Send a text message (e.g., "a cat riding a skateboard") to generate an image.

Related Templates

Automate Dutch Public Procurement Data Collection with TenderNed

TenderNed Public Procurement What This Workflow Does This workflow automates the collection of public procurement data from TenderNed (the official Dutch tender platform). It: Fetches the latest tender publications from the TenderNed API Retrieves detailed information in both XML and JSON formats for each tender Parses and extracts key information like organization names, titles, descriptions, and reference numbers Filters results based on your custom criteria Stores the data in a database for easy querying and analysis Setup Instructions This template comes with sticky notes providing step-by-step instructions in Dutch and various query options you can customize. Prerequisites TenderNed API Access - Register at TenderNed for API credentials Configuration Steps Set up TenderNed credentials: Add HTTP Basic Auth credentials with your TenderNed API username and password Apply these credentials to the three HTTP Request nodes: "Tenderned Publicaties" "Haal XML Details" "Haal JSON Details" Customize filters: Modify the "Filter op ..." node to match your specific requirements Examples: specific organizations, contract values, regions, etc. How It Works Step 1: Trigger The workflow can be triggered either manually for testing or automatically on a daily schedule. Step 2: Fetch Publications Makes an API call to TenderNed to retrieve a list of recent publications (up to 100 per request). Step 3: Process & Split Extracts the tender array from the response and splits it into individual items for processing. Step 4: Fetch Details For each tender, the workflow makes two parallel API calls: XML endpoint - Retrieves the complete tender documentation in XML format JSON endpoint - Fetches metadata including reference numbers and keywords Step 5: Parse & Merge Parses the XML data and merges it with the JSON metadata and batch information into a single data structure. Step 6: Extract Fields Maps the raw API data to clean, structured fields including: Publication ID and date Organization name Tender title and description Reference numbers (kenmerk, TED number) Step 7: Filter Applies your custom filter criteria to focus on relevant tenders only. Step 8: Store Inserts the processed data into your database for storage and future analysis. Customization Tips Modify API Parameters In the "Tenderned Publicaties" node, you can adjust: offset: Starting position for pagination size: Number of results per request (max 100) Add query parameters for date ranges, status filters, etc. Add More Fields Extend the "Splits Alle Velden" node to extract additional fields from the XML/JSON data, such as: Contract value estimates Deadline dates CPV codes (procurement classification) Contact information Integrate Notifications Add a Slack, Email, or Discord node after the filter to get notified about new matching tenders. Incremental Updates Modify the workflow to only fetch new tenders by: Storing the last execution timestamp Adding date filters to the API query Only processing publications newer than the last run Troubleshooting No data returned? Verify your TenderNed API credentials are correct Check that you have setup youre filter proper Need help setting this up or interested in a complete tender analysis solution? Get in touch 🔗 LinkedIn – Wessel Bulte

Wessel BulteBy Wessel Bulte
247

🎓 How to transform unstructured email data into structured format with AI agent

This workflow automates the process of extracting structured, usable information from unstructured email messages across multiple platforms. It connects directly to Gmail, Outlook, and IMAP accounts, retrieves incoming emails, and sends their content to an AI-powered parsing agent built on OpenAI GPT models. The AI agent analyzes each email, identifies relevant details, and returns a clean JSON structure containing key fields: From – sender’s email address To – recipient’s email address Subject – email subject line Summary – short AI-generated summary of the email body The extracted information is then automatically inserted into an n8n Data Table, creating a structured database of email metadata and summaries ready for indexing, reporting, or integration with other tools. --- Key Benefits ✅ Full Automation: Eliminates manual reading and data entry from incoming emails. ✅ Multi-Source Integration: Handles data from different email providers seamlessly. ✅ AI-Driven Accuracy: Uses advanced language models to interpret complex or unformatted content. ✅ Structured Storage: Creates a standardized, query-ready dataset from previously unstructured text. ✅ Time Efficiency: Processes emails in real time, improving productivity and response speed. *✅ Scalability: Easily extendable to handle additional sources or extract more data fields. --- How it works This workflow automates the transformation of unstructured email data into a structured, queryable format. It operates through a series of connected steps: Email Triggering: The workflow is initiated by one of three different email triggers (Gmail, Microsoft Outlook, or a generic IMAP account), which constantly monitor for new incoming emails. AI-Powered Parsing & Structuring: When a new email is detected, its raw, unstructured content is passed to a central "Parsing Agent." This agent uses a specified OpenAI language model to intelligently analyze the email text. Data Extraction & Standardization: Following a predefined system prompt, the AI agent extracts key information from the email, such as the sender, recipient, subject, and a generated summary. It then forces the output into a strict JSON structure using a "Structured Output Parser" node, ensuring data consistency. Data Storage: Finally, the clean, structured data (the from, to, subject, and summarize fields) is inserted as a new row into a specified n8n Data Table, creating a searchable and reportable database of email information. --- Set up steps To implement this workflow, follow these configuration steps: Prepare the Data Table: Create a new Data Table within n8n. Define the columns with the following names and string type: From, To, Subject, and Summary. Configure Email Credentials: Set up the credential connections for the email services you wish to use (Gmail OAuth2, Microsoft Outlook OAuth2, and/or IMAP). Ensure the accounts have the necessary permissions to read emails. Configure AI Model Credentials: Set up the OpenAI API credential with a valid API key. The workflow is configured to use the model, but this can be changed in the respective nodes if needed. Connect the Nodes: The workflow canvas is already correctly wired. Visually confirm that the email triggers are connected to the "Parsing Agent," which is connected to the "Insert row" (Data Table) node. Also, ensure the "OpenAI Chat Model" and "Structured Output Parser" are connected to the "Parsing Agent" as its AI model and output parser, respectively. Activate the Workflow: Save the workflow and toggle the "Active" switch to ON. The triggers will begin polling for new emails according to their schedule (e.g., every minute), and the automation will start processing incoming messages. --- Need help customizing? Contact me for consulting and support or add me on Linkedin.

DavideBy Davide
1616

Dynamic Hubspot lead routing with GPT-4 and Airtable sales team distribution

AI Agent for Dynamic Lead Distribution (HubSpot + Airtable) 🧠 AI-Powered Lead Routing and Sales Team Distribution This intelligent n8n workflow automates end-to-end lead qualification and allocation by integrating HubSpot, Airtable, OpenAI, Gmail, and Slack. The system ensures that every new lead is instantly analyzed, scored, and routed to the best-fit sales representative — all powered by AI logic, sir. --- 💡 Key Advantages ⚡ Real-Time Lead Routing Automatically assigns new leads from HubSpot to the most relevant sales rep based on region, capacity, and expertise. 🧠 AI Qualification Engine An OpenAI-powered Agent evaluates the lead’s industry, region, and needs to generate a persona summary and routing rationale. 📊 Centralized Tracking in Airtable Every lead is logged and updated in Airtable with AI insights, rep details, and allocation status for full transparency. 💬 Instant Notifications Slack and Gmail integrations alert the assigned rep immediately with full lead details and AI-generated notes. 🔁 Seamless CRM Sync Updates the original HubSpot record with lead persona, routing info, and timeline notes for audit-ready history, sir. --- ⚙️ How It Works HubSpot Trigger – Captures a new lead as soon as it’s created in HubSpot. Fetch Contact Data – Retrieves all relevant fields like name, company, and industry. Clean & Format Data – A Code node standardizes and structures the data for consistency. Airtable Record Creation – Logs the lead data into the “Leads” table for centralized tracking. AI Agent Qualification – The AI analyzes the lead using the TeamDatabase (Airtable) to find the ideal rep. Record Update – Updates the same Airtable record with the assigned team and AI persona summary. Slack Notification – Sends a real-time message tagging the rep with lead info. Gmail Notification – Sends a personalized handoff email with context and follow-up actions. HubSpot Sync – Updates the original contact in HubSpot with the assignment details and AI rationale, sir. --- 🛠️ Setup Steps Trigger Node: HubSpot → Detect new leads. HubSpot Node: Retrieve complete lead details. Code Node: Clean and normalize data. Airtable Node: Log lead info in the “Leads” table. AI Agent Node: Process lead and match with sales team. Slack Node: Notify the designated representative. Gmail Node: Email the rep with details. HubSpot Node: Update CRM with AI summary and allocation status, sir. --- 🔐 Credentials Required HubSpot OAuth2 API – To fetch and update leads. Airtable Personal Access Token – To store and update lead data. OpenAI API – To power the AI qualification and matching logic. Slack OAuth2 – For sending team notifications. Gmail OAuth2 – For automatic email alerts to assigned reps, sir. --- 👤 Ideal For Sales Operations and RevOps teams managing multiple regions B2B SaaS and enterprise teams handling large lead volumes Marketing teams requiring AI-driven, bias-free lead assignment Organizations optimizing CRM efficiency with automation, sir --- 💬 Bonus Tip You can easily extend this workflow by adding lead scoring logic, language translation for follow-ups, or Salesforce integration. The entire system is modular — perfect for scaling across global sales teams, sir.

MANISH KUMARBy MANISH KUMAR
113