FlowSync
Open App
中文
ProMedia4 nodes
Score 72

Podcast Episode Pipeline

Drop a podcast audio file — faster-whisper transcribes with speaker diarisation, LLM generates show notes, chapter markers, pull-quotes, and social-ready highlights, exports as structured DOCX.

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What does this workflow do?

Audio ingestion → Faster-Whisper transcription with speaker diarisation → LLM chapter detection & highlight extraction → LLM show notes drafting → Python-DOCX formatted export

System flow

Audio ingestion → Faster-Whisper transcription with speaker diarisation → LLM chapter detection & highlight extraction → LLM show notes drafting → Python-DOCX formatted export

Pipeline breakdown

Faster-Whisper audio LLM Reasoning json LLM Reasoning json Python-DOCX markdown
  1. Faster-Whisper faster-whisper — Local speech-to-text transcription with timestamps and speaker turns audio → json
  2. LLM Reasoning llm — Large-language-model step that extracts, classifies, validates or writes structured output json → json
  3. LLM Reasoning llm — Large-language-model step that extracts, classifies, validates or writes structured output json → markdown
  4. Python-DOCX python-docx — Renders the final Word document with headings, tables and styling markdown → docx

Workflow Reputation Score

Based on executions, success rate, update frequency, component quality, and user rating.

72Overall
★★★★★ 4.3
▶Executions
30
✓Success rate
99
↻Update frequency
70
⚙Component quality
87
★User rating
86

Based on executions, success rate, update frequency, component quality, and user rating.

Components used

Faster-Whisperfaster-whisper

Local speech-to-text transcription with timestamps and speaker turns

SYSTRAN/faster-whisper ↗
LLM Reasoningllm

Large-language-model step that extracts, classifies, validates or writes structured output

FlowSync proprietary
Python-DOCXpython-docx

Renders the final Word document with headings, tables and styling

python-openxml/python-docx ↗

How is this different from n8n or Zapier?

Unlike generic workflow builders, FlowSync workflows ship pre-configured with AI skills baked into every node — OCR, LLM reasoning, transcription, super-resolution — not just webhook triggers. Each node is white-box auditable: you see input, output, and config. Deployment is instant — no self-hosting, no API-key per node.

Use cases

  • Weekly podcast production
  • Interview transcription
  • Show notes generation
  • Social media clip extraction

Author & Source

This workflow is maintained by the FlowSync team. All components are open-source or commercially licensed. Source code for each component is linked in the Components section above.

Pricing: Free tier available · PRO tier · Official

Field notes

每期 40 分钟节目，以前手动写 shownotes 要 2 小时。现在跑完 pipeline 只需要核对一下人名拼写，省下大量时间做内容。

— 播客主理人 张, 独立播客

Data handling

Data is processed in-memory during pipeline execution only. No files are stored permanently unless you choose to save outputs to your account.

FlowSync Workflow Marketplace · 72 reputation score · 30% execution · 99% success · 4-node white-box pipeline · maintained by FlowSync Official

Ready to run?

Drop a podcast audio file — faster-whisper transcribes with speaker diarisation, LLM generates show notes, chapter markers, pull-quotes, and social-ready highlights, exports as structured DOCX.

Run Podcast Episode Pipeline → Browse all workflows →