Telegram bot that listens for image prompts, chats with the user, generates stunning visuals with DALL·E 3, and sends them back instantly all without writing a single line of code! ‎ ‎ Features: ‎- Chat prompt handling with OpenAI ‎- Context memory for better responses ‎- Image generation via DALL·E 3 ‎- Telegram integration for instant delivery ‎ ‎💡 Imagine offering this as a service to creatives, marketers, or even content creators! ‎ ‎Automation is changing the game — and I’m here for it 🔥 ‎ ‎#n8n #OpenAI #Dalle3 #AutomationBuilder #TelegramBot #NoCode #AIintegration

🚀 Just built an AI-powered virtual assistant using n8n + OpenAI + Gmail + Google Sheets it can: ✅ Understand messages ✅ Access memory ✅ Fetch contact data ✅ Send emails ✅ Trigger actions in external tools like Atlassian All fully automated through chat! #AI #Automation #n8n #VirtualAssistant #OpenAI #NoCode

‎ ‎Just built this cool workflow in n8n that listens for a chat message, runs it through OpenAI, stores the context with memory, and automatically sends it to Slackthen waits for a response! ‎ ‎💡 How this helps: ‎ ‎- 📥 Instantly reply to messages or requests using AI ‎- 🧠 Keep conversation memory for smart follow-ups ‎- 📊 Great for support teams, community managers, or internal ops ‎- ⏱ Saves hours of manual back-and-forth in Slack ‎ ‎You can easily modify it to route different messages to specific team channels or add automation triggers based on user replies. ‎ ‎

‎ ‎Just finished building a Meeting Availability Agent using n8n that: ‎ ‎1. Checks Google Calendar availability ‎2. Uses OpenAI to suggest ideal meeting times ‎3. Formats a personalized message with available slots ‎4. Sends the message for human review/approval ‎5. Then delivers it via Gmail ‎ ‎This setup is perfect for busy professionals who want to automate scheduling without fully removing the human touch. ‎ ‎ Ideal for client calls, sales teams, or service providers who want smart automation + control. ‎ ‎Let me know if you wish to get one for your business or workflows. ‎

‎ ‎Just built this smart chat agent for a client using Ollama’s Chat Model, and it’s been super effective for handling dynamic conversations. ‎ ‎ ‎Here’s what it does: ‎- Triggers when a chat message is received ‎- Uses a Window Buffer Memory to retain context from previous chats ‎- Fetches relevant info from Google Docs to answer with accuracy ‎- The AI Agent responds based on both memory and the retrieved document ‎ ‎ ‎It’s perfect for customer support, onboarding flows, or any use case where quick, context-aware replies are essential.