SUMMARIZATION

Weekly multilingual release digest with audio to Slack

Every Friday, summarize the week's merged GitHub releases into a digest, translate and voice it per language, and post the text plus audio links to regional Slack channels.

CategorySummarization
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule (Friday)
  • ActionCollect week's GitHub releasesGitHubGitHub
  • ActionSummarize into highlights digestHugging FaceHugging Face
  • ActionTranslate + voice per regionElevenLabsElevenLabs
  • OutputPost localized digest to Slack channelsSlack

What it does

Rolls up everything you shipped in a week into one digest, then localizes it for each region. It collects the week's releases from GitHub, writes a short summary, translates it, generates a voiceover per language, and posts each region's text-and-audio digest into its Slack channel.

When to use it

Use it for distributed teams or regional communities where a single end-of-week "here's what shipped" message — in each group's language, with an optional audio clip — keeps everyone aligned without manual reporting.

How it works

  1. 1A weekly schedule fires Friday afternoon (trigger).
  2. 2The flow queries GitHub for releases published in the last seven days and merges their notes.
  3. 3An LLM condenses them into a tight highlights digest.
  4. 4Per configured region, a Hugging Face model translates the digest and ElevenLabs renders a short voiceover.
  5. 5The flow posts each localized digest, with its audio file, to the matching regional Slack channel.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect Hugging FaceModels, datasets, spaces — the open-source hub.
  3. 3
    Connect ElevenLabsText-to-speech, voice cloning.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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