Semantic Search With Ollama and PostgreSQL in 10 Minutes

This summary highlights the key points of using Ollama with PostgreSQL extensions like pgvector and pgai to build a semantic search system. The tool enables deployment of popular large language models (LLMs) on any server, making it easy to create sovereign AI applications that can be deployed locally or on cloud servers. By combining Ollama with tools like pgvector and pgai, developers can create fully private AI solutions that leverage semantic search capabilities for applications such as retrieval-augmented generation, AI agents, AI assistants, or recommendation systems. The system uses vector embeddings to represent the semantic content of text, enabling more accurate results even when exact keywords aren't present. A step-by-step guide provides a quick setup using Ollama, pgai, and PostgreSQL extensions, allowing developers to build a semantic search system in under 10 minutes.

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