Agent Template · local RAG (pgvector) · retrieval as a model capability · seeded knowledge base

Handbook Q&A: Retrieval as a Model Capability

Retrieval as a model capability, fully local: the installer creates a retrieval source in your own Postgres (pgvector), seeds it with a fictional TheYgent company handbook, and wires it to a local model as a search tool the model decides to call — answers cite the handbook section they came from.

How It Works

The installer creates a retrieval source in your own Postgres (pgvector), seeds it with a fictional company handbook, and wires it to a local model as a search tool the model decides when to call. Answers cite the handbook section they came from.

Seeding embeds in the background with your embedding model; the RAG page shows the source's status.

Try It

In TheYgent, open Settings → Samples.
Fill the model slots below with models from your registry, then click Install on Handbook Q&A.
Open the installed agent and run it with the example input.

How long does TheYgent keep customer data, and who approves an exception?

The Graph

Every node in the agent and where its output goes, read from the template itself.

sample-handbook-qa

Node	Type	Sends its output to
Question	`input`	Answer from the handbook
Answer from the handbook	`llm`	Answer
Handbook search (LLM-driven)	`rag`	Answer from the handbook (on `use`, as a tool)
Answer	`output`	—

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