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Generate YouTube Shorts from Telegram prompts with Gemini

Produces 30 fully tagged YouTube Shorts per month from simple text prompts. Built with Gemini and VEO for content creator clients.

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Content creators need a steady stream of short-form video but have no time for scripting, clip assembly, or metadata writing. This AI automation handles the entire production pipeline from a single Telegram message to a finished, tagged video asset.

What This Automation Does

  • Converts a plain-text Telegram prompt into a structured multi-segment short-form video script using Gemini
  • Generates individual cinematic video clips for each script segment using VEO
  • Merges all clips into a single ready-to-upload short video without any manual editing
  • Produces an optimised title, description, and hashtag set alongside the finished video and delivers everything back via Telegram or Google Drive

Tools Used

  • Telegram
  • Google Drive
  • OpenAI
  • n8n

Where to Get Hired for This Skill

On Contra, top freelancers across this stack have earned 251 combined verified reviews from real client projects.

Source: Contra freelancer search · refreshed 30 May 2026

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How To Build It

Wire Telegram as the content intake point

A Telegram bot receives the client's short content idea and passes it into the workflow as the trigger, so the entire pipeline fires the moment a new prompt arrives.

Generate a segmented video script with Gemini

Gemini receives the raw prompt and returns a structured, multi-part script where each segment is calibrated for the pacing and attention arc of short-form platforms like YouTube Shorts.

Produce individual video clips via VEO

Each script segment is sent to VEO as a separate generation request, producing distinct cinematic clips that correspond directly to the narrative beats in the script.

Merge clips into a single short video

The individual VEO-generated clips are assembled in sequence into one cohesive video file, eliminating the need for any manual editing or third-party video software on the client's end.

Package metadata and deliver finished assets

An AI step generates a platform-optimised title, description, and hashtag block for the video, then the finished file and all metadata are pushed to Google Drive and confirmed back to the client via Telegram.

Pitfalls

  • VEO generation requests can time out or return inconsistent clip lengths when the script segments are too long or ambiguous, so adding a validation step that checks clip duration before merging prevents silent failures from reaching the client.
  • Gemini prompt outputs can drift in tone and structure across repeated runs, especially when client prompts vary wildly in style, which means the system prompt needs strict output formatting constraints or the downstream clip generation breaks.
  • Google Drive OAuth tokens expire and are not always refreshed automatically in long-running workflows, so unattended pipelines can fail silently for days before a client notices their deliverables have stopped arriving.

FAQ

Can I build this without coding?

Yes. The workflow is built entirely in n8n using its visual interface with no custom code required. The most technical parts are configuring the Gemini and VEO API credentials and structuring the prompt templates, both of which are straightforward with the API documentation.

How long does it take?

Most freelancers can have a working version running within a day or two of focused setup. Polishing the prompt templates and testing the clip merge logic for edge cases typically adds another day before it is ready to hand off to a client.

What can I charge?

Pricing is yours to set based on your market and the scope you deliver. A productised retainer built around a fixed monthly volume of finished Shorts is a common packaging approach that creates predictable recurring income.

Which tool is required vs optional?

Telegram, Gemini, and VEO are core to the workflow and cannot be swapped without significant rebuilding. Google Drive is the default storage layer but can be replaced with another storage service. OpenAI is used for supporting tasks like structured output parsing and can be substituted or removed depending on how you configure those steps.

This is original DigiNo analysis. The underlying automation pattern is a community workflow template – view the original on n8n.

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