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orchardcore-ai-data-sources

Skill for CrestApps AI Data Sources in Orchard Core 4.0 (CrestApps.OrchardCore 3.0). Covers knowledge base indexes, RAG retrieval, the source types SearchIndexProfile, Elasticsearch, AzureAISearch, PostgreSQL, Web and File, embedding deployments picked by the embedding slot, OData filters and translators, preemptive RAG and IsInScope, citations and IAIReferenceLinkResolver, sync and alignment, the AIDataSource recipe and deployment steps, global Elasticsearch and PostgreSQL connections, AIDataSourceOptions through IOptionsMonitor, and the AIDataSources admin list. Use it for CrestApps.OrchardCore.AI.DataSources, CrestApps.OrchardCore.AI.DataSources.Elasticsearch, CrestApps.OrchardCore.AI.DataSources.AzureAI, CrestApps.OrchardCore.AI.DataSources.PostgreSQL, AIDataSource, AIDataSourceRagMetadata, DataSourceMetadata, PostgreSQLSourceMetadata, IAIDataSourceIndexingQueue, IAIDataSourceSourceHandler, IODataFilterTranslator, and ManageAIDataSources.

src/CrestApps.AgentSkills/crestapps-orchardcore/orchardcore-ai-data-sources/SKILL.md

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Oct 21, 2026
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# Orchard Core AI Data Sources

## Configure AI data sources and knowledge base retrieval

You are an Orchard Core expert. Generate configuration, recipes, and code for CrestApps AI data sources: a data source reads documents from a source, chunks and embeds them into a shared **AI knowledge base index**, and AI profiles, chat interactions, workflow tasks, and tool instances retrieve from it (RAG).

### Guidelines

- `CrestApps.OrchardCore.AI.DataSources` is `EnabledByDependencyOnly`. Enable a provider feature (Elasticsearch, Azure AI Search, PostgreSQL), `CrestApps.OrchardCore.AI.WebCrawlers`, or `CrestApps.OrchardCore.AI.FileSources` and it comes along. It depends on `CrestApps.OrchardCore.AI` and `OrchardCore.Indexing`.
- The knowledge base index is an Orchard index profile of type `DataSourceIndex`, created under **Search > Indexing** as **AI Knowledge Base Index (Elasticsearch)** or **AI Knowledge Base Index (Azure AI Search)**. Lucene cannot hold a knowledge base.
- Each knowledge base index names one **embedding deployment**. The picker lists deployments that fill the `embedding` slot, so the deployment must declare the `textEmbedding` capability. The deployment is locked once the index exists, because it fixes the vector dimensions.
- A `SearchIndexProfile` source must be an Elasticsearch or Azure AI Search index profile. Only those providers register an `IDataSourceDocumentReader`; a Lucene index or an AI-managed index (AI Documents, AI Memory, another knowledge base) is rejected.
- The source type is chosen in the **Add Data Source** dialog and stays fixed. The destination index and field mapping lock once the data source is configured.
- Field mapping (key, title, content) is shown and required only for `SearchIndexProfile`, `Elasticsearch`, `AzureAISearch`, and `PostgreSQL`. `Web` and `File` sources shape their own documents.