Automated Content Workflow from Unsplash to Pinterest

This workflow automates the process of capturing images or content from Unsplash and creating visually appealing Pinterest posts, while also logging and analyzing the content for better curation and insights.

The process begins with a Webhook trigger that activates the workflow whenever new Unsplash content is available. The content is then split into manageable text chunks for processing. These chunks are embedded using Cohere’s embedding model to generate vector representations, which are stored in a Supabase vector database for efficient retrieval.

Next, the workflow queries the database for relevant content similarities and utilizes LangChain’s tools, including a vector store and a language model, to analyze and contextually understand the data. A retrieval-augmented generation (RAG) agent leverages this understanding to generate meaningful insights or descriptions related to the Unsplash content.

Finally, the workflow logs the status and insights into a Google Sheet for record-keeping and sends Slack alerts if any errors occur, ensuring that the entire process from content ingestion, analysis, to logging is automated, efficient, and reliable.

This setup is ideal for digital marketers, content creators, or social media managers aiming to streamline their content curation and publishing workflows, especially those integrating visual content from Unsplash with Pinterest marketing strategies.