Create Context for Meeting Transcript Chunks

Anyone needing to summarize and contextualize meeting transcripts chunks. It helps researchers, project managers, and content creators. This workflow takes meeting transcript chunks and the full transcript to generate short, high-level summaries. These summaries highlight the importance of each chunk within the overall meeting context using AI. It then combines the chunk and its AI-generated context for further use. Set up an n8n instance and connect to an OpenRouter AI service with a valid API key. Configure the "Start" node to receive the transcript chunk and full transcript. Customize the AI prompt in the "Context Creator" node if needed. The workflow is ready to run once deployed and triggered. An n8n instance and an OpenRouter API key for AI services are necessary to run this workflow. Basic understanding of n8n and AI prompts will help in customization. You can customize the AI model using OpenRouter credentials and adjust the temperature parameter for creativity versus strictness. Modify the Context Creator node to change the AI prompt, snippet length, or add specific instructions for summarization. Adjust the Set nodes to format the output as desired. Key Technologies: n8n,OpenRouter (AI),Google Gemini (AI model) Automation Value: - Reduces manual effort in summarizing meeting transcripts. - Provides quick, high-level overviews of specific discussion points. - Improves content creation by identifying key takeaways from meetings. - Enhances meeting follow-up and knowledge management. Best Practices: - Regularly audit AI prompts to ensure accuracy and relevance of generated content. - Monitor AI usage costs to optimize OpenRouter API calls, especially with batching enabled. - Ensure the 'full\_transcript' is consistently available and accurately passed to the AI to maintain proper context. - Implement error handling for AI responses to manage unexpected outputs or API issues.