How do I set up combine ChatGPT with vector databases for SEO to audit titles and metas for duplicates across the site?

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To combine ChatGPT with vector databases for SEO title and meta duplicate auditing, first, you'll need to crawl your website to collect all existing titles and meta descriptions. Next, use an embedding model, such as OpenAI's `text-embedding-ada-002`, to convert each title and meta description into a unique high-dimensional vector. These vectors are then stored in a vector database like Pinecone, Weaviate, or Qdrant, which is optimized for fast similarity searches. To identify duplicates or highly similar content, you'll query the vector database with each embedding to find close matches based on cosine similarity scores. Finally, for any identified potential duplicates, leverage ChatGPT's API to analyze the context, confirm the duplication, and suggest unique alternative titles or meta descriptions, ensuring your site avoids content cannibalization and improves search visibility. This powerful setup effectively automates the identification and remediation of crucial on-page SEO issues across large websites.