Implementation:TobikoData Sqlmesh Model SqlmeshModel

Knowledge Sources	TobikoData_Sqlmesh
Domains	Web_UI, Data_Models, Model_Metadata
Last Updated	2026-02-07 20:00 GMT

Overview

Model representation for SQLMesh data models in the web UI containing metadata, schema, lineage, and source definitions.

Description

ModelSQLMeshModel represents a SQLMesh data model in the web application with comprehensive metadata including columns, description, SQL definitions, model type (sql, python, seed, external), and details for search indexing. The class provides intelligent property management with URI encoding for names/FQNs, computed search indexes combining all metadata fields, and type-specific utilities for determining model kinds.

Key features include automatic URI encoding/decoding for model names, details property with automatic indexing for search functionality, comprehensive search index property combining name/path/type/columns/details/dialect/description, model type detection (isModelPython, isModelSQL, isModelSeed, isModelExternal), and update() method for partial model updates.

The model includes optional lineage data for dependency tracking and supports catalog/schema organization through default_catalog property.

Usage

Use this class to display model information in the data catalog, search functionality, and model detail views throughout the SQLMesh web UI.

Code Reference

Source Location

Repository: TobikoData_Sqlmesh
File: web/client/src/models/sqlmesh-model.ts

Signature

export class ModelSQLMeshModel<
  T extends InitialSQLMeshModel = InitialSQLMeshModel
> extends ModelInitial<T> {
  _details: ModelDetails = {}
  _detailsIndex: string = ''

  name: string
  fqn: string
  path: string
  full_path: string
  dialect: string
  type: ModelType
  columns: Column[]
  default_catalog?: ModelDefaultCatalog
  description?: ModelDescription
  sql?: ModelSql
  definition?: ModelDefinition
  hash: string

  constructor(initial?: T | ModelSQLMeshModel)

  get defaultCatalog(): Optional<ModelDefaultCatalog>
  get details(): ModelDetails
  set details(details: ModelDetails)
  get index(): string
  get isModelPython(): boolean
  get isModelSQL(): boolean
  get isModelSeed(): boolean
  get isModelExternal(): boolean
  get displayName(): string

  update(initial: Partial<InitialSQLMeshModel>): void
}

Import

import { ModelSQLMeshModel } from '@models/sqlmesh-model'
import { ModelType } from '@api/client'

I/O Contract

Inputs

Name	Type	Required	Description
initial	ModelSQLMeshModel	No	Model metadata from API

Outputs

Property	Type	Description
name	string	URI-encoded model name
fqn	string	URI-encoded fully qualified name
displayName	string	Decoded display name for UI
path	string	File path to model definition
full_path	string	Full absolute file path
dialect	string	SQL dialect (e.g., "Default", "snowflake")
type	ModelType	Model type (sql, python, seed, external)
columns	Column[]	Schema column definitions
description	ModelDescription	Model description metadata
sql	ModelSql	Compiled SQL query
definition	ModelDefinition	Raw model definition source
hash	string	Model hash/fingerprint
index	string	Searchable text index of all metadata
details	ModelDetails	Additional structured metadata

Usage Examples

// Create model from API response
const model = new ModelSQLMeshModel({
  name: 'my_schema.my_model',
  fqn: 'prod.my_schema.my_model',
  path: 'models/my_model.sql',
  full_path: '/project/models/my_model.sql',
  dialect: 'snowflake',
  type: ModelType.sql,
  columns: [
    { name: 'id', type: 'INT' },
    { name: 'name', type: 'VARCHAR' }
  ],
  description: 'Customer data model',
  hash: 'abc123',
  details: {
    owner: 'data-team',
    tags: ['customer', 'core']
  }
})

// Display name (decoded)
console.log(model.displayName) // "my_schema.my_model"

// Check model type
if (model.isModelSQL) {
  console.log('SQL model:', model.sql)
} else if (model.isModelPython) {
  console.log('Python model:', model.definition)
}

// Search across all metadata
const searchQuery = 'customer'
if (model.index.toLowerCase().includes(searchQuery)) {
  console.log('Model matches search')
}

// Update specific fields
model.update({
  columns: [
    { name: 'id', type: 'BIGINT' },
    { name: 'name', type: 'VARCHAR' },
    { name: 'email', type: 'VARCHAR' }
  ],
  description: 'Updated customer data model'
})

// Access catalog information
if (model.defaultCatalog) {
  console.log(`Catalog: ${model.defaultCatalog}`)
}

// Check for specific file type
if (model.isModelSeed) {
  console.log('This is a seed data model')
}

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