Postgres Semantic

PostgreSQL Semantic Model Integration

Load semantic models before any database operation. They contain business rules, exact field expressions, and validated metrics that make queries correct.

Workflow

Step 1: Check for semantic models (MANDATORY FIRST STEP)

Before calling any database tool, list the semantic models at /products:

list_files(path="/products")

If the directory is empty or missing, skip to Step 5 and query directly.

Step 2: Load relevant models

Load model files matching the user's question:

read_file(path="/products/sales-transaction-ledger/osi.yml")
read_file(path="/products/customer-demographic-master/osi.yml")
read_file(path="/products/inventory-snapshot/osi.yml")

Step 3: Extract from each model

• ai_context.instructions (top level) — critical business rules for all queries
• datasets[].source — actual schema.table name to query
• datasets[].fields[].expression — exact SQL expression to use (never guess)
• metrics[].expression — pre-validated SQL calculation (use as-is)
• relationships[] — correct join conditions across domains

Step 4: Apply context

1. Apply domain instructions (e.g., divide cents by 100 for dollar amounts)
2. Use exact field expression values — never invent column names
3. Use pre-defined metric expressions verbatim
4. Use relationships for cross-domain joins
5. Respect field-level ai_context warnings

Step 5: Query the database

show_tables()           # list available tables
describe_table(table="schema.table")  # table structure
run_query(query="SELECT ...")         # execute SQL

Always cite which semantic rule or metric you applied in your response.

Source: conveyordata/data-product-portal — distributed by TomeVault.