Automated Script Dialogue Analysis with n8n

This workflow enables automated analysis of script dialogues using natural language processing (NLP) and vector similarity search to derive insights and store them efficiently. It begins with a webhook trigger capturing dialogue input, then splits the text into manageable chunks. The chunks are embedded using Hugging Face embeddings for semantic understanding and stored in Pinecone’s vector database. The workflow supports querying similar dialogues or segments for comparison or retrieval purposes, using Pinecone for fast, similarity-based searches. An OpenAI language model processes inputs for contextual understanding, while a custom agent manages prompt definitions. Finally, the results, including analysis and insights, are logged into a Google Sheets document for record-keeping and further review. Practically, this setup is ideal for writers, content creators, or QA teams to analyze and categorize dialogue scripts, enhancing editing, review, or training processes.