Upload & Split Docs with Q&A Analysis and Research with Wikipedia + Perplexity

Podcast creators, researchers, and content managers. This workflow automates the process of analyzing a podcast transcript. It summarizes the content, extracts key topics and questions, researches these topics using Wikipedia, and then compiles everything into a digestible email. 1. Input your podcast transcript into the "Podcast Episode Transcript" node. 2. Configure your Gmail credentials in the "Send Digest" node. 3. Execute the workflow manually to send the digest. n8n with Langchain nodes implemented using OpenAI API keys, and Gmail account access. You can customize the podcast transcript, the Gmail recipient and subject, and the specific prompt for extracting topics and questions. Key Technologies: n8n,OpenAI (GPT-4, GPT-3.5-turbo-16k),Langchain,Wikipedia API,Gmail Automation Value: - Reduces manual effort in summarizing and researching podcast content. - Provides quick insights into episode topics and generates thought-provoking questions. - Automates the creation and distribution of podcast digests, saving time for content creators and researchers. - Enhances content understanding and engagement for recipients. Best Practices: - Clearly define the purpose of each AI prompt to achieve desired outputs. - Use text splitting and document loaders for efficient AI processing of large texts. - Structure AI outputs with JSON schemas for consistency and easier downstream processing. - Integrate research tools like Wikipedia to enrich AI-generated content with factual information. - Format final outputs for readability and impact, especially for email delivery.