Analyze YouTube videos and auto-generate AI reports in Google Docs with DeepSeek

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 1. Trigger — Upload File or YouTube Link A form trigger receives a youtubeurl or an uploaded file/webhook event. 2. Transcription — Transcription using Supadata.ai Calls the transcription API using the x-api-key header to retrieve the video transcript/text. 3. 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. 4. Metadata extraction — File Name Detector The information extractor parses the analyser output to extract structured attributes such as the Title. 5. Aggregation & Merge Merge/Aggregate nodes combine the analysis and extracted fields into a single payload. 6. 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. 7. 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 youtubeurl 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 Ex