A compact n8n workflow that accepts a YouTube link or uploaded video, pulls a transcript via Supadata.ai, runs a langua…
A compact n8n workflow that accepts a YouTube link or uploaded video, pulls a transcript via Supadata.ai, runs a language-model-based video analysis agent to produce a structured report, extracts a title/metadata, then creates and updates a Google Doc with the analysis. It's designed to automate transcription → analysis → document creation for fast, repeatable video reviews. How it works Trigger — Upload File or YouTube Link A form trigger receives a youtube_url or an uploaded file/webhook event. Transcription — Transcription using Supadata.ai Calls the transcription API using the x-api-key header to retrieve the video transcript/text. Analysis — Analyser The transcript is passed to the Analyser LangChain agent which runs a tailored prompt (expert video analyst) and generates a plain-text report. Metadata extraction — File Name Detector The information extractor parses the analyser output to extract structured attributes such as the Title. Aggregation & Merge Merge/Aggregate nodes combine the analysis and extracted fields into a single payload. Document Creation Creating New File creates a Google Docs document using the extracted Title, and Updating Content in File inserts the analyser output into the document. Optional Follow-ups Additional nodes can forward the document link, send it to Slack, or store metadata in a database. Quick Setup Guide 👉 Demo & Setup Video 👉 Course Nodes of interest Upload File or YouTube Link** formTrigger (webhook) — Entry point for user-supplied links or files. Transcription using Supadata.ai** httpRequest — Fetches transcript from https://api.supadata.ai/... and requires the x-api-key header. OpenRouter Chat Model / OpenRouter Chat Model1** lmChatOpenRouter — Language model nodes connected to the Analyser and File Name Detector using the model deepseek/deepseek-r1-distill-llama-70b. Analyser** LangChain agent node that contains the expert analysis prompt and generates a full plain-text report from the transcript. Configuration includes hasOutputParser: true and retry enabled. File Name Detector** LangChain information extractor that extracts structured attributes like Title from the analysis output. Merge / Aggregate** Combines outputs from analysis and extraction into a single payload used for document creation. Creating New File / Updating Content in File** Google Docs nodes used to create and update documents using googleDocsOAuth2Api credentials. What you’ll need (credentials) OpenRouter account** Used by OpenRouter Chat Model nodes. API key stored in the openRouterApi credential. Supadata.ai API key** Added in the HTTP header x-api-key in the transcription request. Google Docs OAuth2** googleDocsOAuth2Api credential used for creating and updating Google Docs. Optional integrations** Slack webhook, Google Drive, or database credentials if adding notifications or persistent storage. Recommended settings & best practices Prompt control** Keep the Analyser prompt explicit about required sections, output style, and how to handle missing transcripts. Retries & timeouts** Enable retries for long-running model or HTTP calls. Configure proper HTTP request timeouts. Rate limits** Respect transcription and model provider rate limits. Add throttling if needed. Input validation** Validate the youtube_url before processing and handle transcript failures gracefully. Chunk transcripts** Split long transcripts into chunks before sending to the LLM to avoid context limit issues. Logging & audit** Store transcripts, analysis results, and metadata for debugging and traceability. Security** Store API keys as n8n credentials rather than plaintext. Document naming** Sanitize the extracted Title to prevent invalid filename characters. Monitoring** Add error notifications via email or Slack for failed runs. Customization ideas Alternative transcription providers** Replace Supadata.ai with AssemblyAI, Whisper (self-hosted), or YouTube captions. Multiple output formats** Export results to Google Docs, PDF, or JSON metadata. Speaker diarization** Include speaker labels and timestamps in the analysis. Summaries & highlights** Add TL;DR summaries and timestamped key moments. Content classification** Use additional LLM nodes to detect sentiment, category, or compliance issues. Thumbnail generation** Capture frames from the video to generate thumbnails. Webhook callbacks** Send the document link to Slack, email, or other systems. Model routing** Use smaller models for short videos and higher-quality models for long videos. Human review pipeline** Create a review queue for manual verification before publishing results. Tags video-analysis transcription n8n langchain automations google-docs openrouter supadata reporting workflow. An n8n automation workflow template by Pratyush Kumar Jha.
Pratyush Kumar Jha
web
free
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