Convert LLM Output to Rich Telegram Messages — Auto-Media & Smart Chunking
Transforms long LLM outputs with text and media links into Telegram-friendly messages, automatically sending photos, audio, video, and smartly chunking oversized text.
This n8n workflow converts raw LLM responses containing plain text and HTTP links to images, audio, or video into rich Telegram messages. It extracts and deduplicates URLs using a JavaScript Code node, classifies them by file extension, and routes media through a Switch node to the appropriate Telegram API (sendPhoto, sendAudio, sendVideo) for inline previews and players.
For text-only or remaining content, an IF node checks against Telegram's 1000-character limit. If exceeded, a Code node splits at line boundaries, and SplitInBatches sends chunks sequentially, ensuring no content loss. All paths converge in a single execution, making it efficient for bot responses.
Ideal for Telegram chatbots, AI assistants, or notification services. Benefits include seamless media handling, compliance with Telegram limits, and reduced manual processing. Customize by adjusting limits, adding captions/keyboards, or enhancing link filtering. Requires a Telegram bot token and parent workflow passing chatId and output.
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How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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