Build AI-powered apps on Google Cloud with pgvector, LangChain & LLMs

Make a copy of the Colab notebook → Read the launch blog → Read the demo blog → Showcasing various features of the Postgres extension pgvector, see an example of how you can extend your database application to build AI-powered experiences using LangChain and LLM. The pgvector extension can manage vector embeddings directly within your Cloud SQL and AlloyDB databases, making integrating Generative AI capabilities within your Postgres-powered applications easier. In this demo, we use Google’s PaLM models powered by VertexAI. Chapters: 0:00 - Intro 0:30 - Vector embeddings defined 1:04 - pgvector support 1:22 - Demo summary 2:24 - Demo start 7:24 - Conclusion Subscribe to Google Cloud Tech → #Databases #GenerativeAI #pgvector