Multi-Modal Telegram AI Agent (n8n Workflow Automation)
I built a production-ready, multi-modal Telegram AI Agent utilizing n8n to automate complex conversation routing and media processing. The system dynamically intercepts text, voice notes, and images, routing them through specialized pipelines for real-time contextual analysis.
Key Features & Architecture:
Smart Conditional Routing: Implemented intelligent switch routers that automatically separate user intent based on incoming media types (Chat, Voice, or Image).
Voice-to-Text Pipeline: Integrated automated voice note retrieval coupled with OpenAI Whisper transcription models to convert spoken audio into structural prompt data.
Advanced Vision Analytics: Developed an image processing route that extracts, analyzes, and interprets visual uploads using OpenAI Vision capabilities.
Custom Engine Extensions: Embedded custom JavaScript code nodes to run custom data transformations, variable styling, and cleaner payload processing.
Dynamic Audio Generation: Configured text-to-speech feedback loops allowing the agent to respond automatically back to Telegram with freshly synthesized voice messages or contextual alerts.
0
76