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Version: 2.1
Technical Manual

AI Data Sources - PostgreSQL

Feature NameAI Data Sources - PostgreSQL
Feature IDCrestApps.OrchardCore.AI.DataSources.PostgreSQL

Adds PostgreSQL source support for AI data sources.

Overview​

This module lets AI data sources read documents directly from a PostgreSQL table instead of an Orchard-managed search index profile. It is useful when your knowledge-base pipeline needs to pull source records from an external relational store while still writing embeddings into an Orchard-managed AI knowledge base index.

The PostgreSQL source editor captures:

  • Connection string
  • Table name
  • Key field
  • Title field
  • Content field

The handler reads rows in batches, supports targeted reads by key for explicit reprocessing, and falls back to the id column when no key field is configured.

Getting started​

  1. Enable AI Data Sources and AI Data Sources - PostgreSQL.
  2. Create an AI knowledge base index under Search > Indexing.
  3. Create a new data source under Artificial Intelligence > Data Sources.
  4. Choose PostgreSQL as the Source type.
  5. Enter the PostgreSQL connection string and source table name.
  6. Map the key, title, and content fields, then save the data source.

Notes​

  • Table names can include schema-qualified names such as public.articles.
  • Store the connection string securely and avoid committing it to source control.
  • Incremental Orchard content-event sync only applies to Orchard-managed source index profiles. External PostgreSQL sources are intended for full sync or provider-specific reprocessing flows.