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Pydantic Models Py by sahit-sai — Agent Skill

Name: Pydantic Models Py
Author: sahit-sai

Pydantic Models Py

Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants. Use when defining API request/response schemas, database models, or data validation in Python applications using Pydantic v2.

sahit-sai 2605b36 3 files · 6.2 KB Updated Sep 17, 2026

File contents

Pydantic Models

Create Pydantic models following the multi-model pattern for clean API contracts.

Quick Start

Copy the template from assets/template.py and replace placeholders:

{{ResourceName}} → PascalCase name (e.g., Project)
{{resource_name}} → snake_case name (e.g., project)

Multi-Model Pattern

Model	Purpose
`Base`	Common fields shared across models
`Create`	Request body for creation (required fields)
`Update`	Request body for updates (all optional)
`Response`	API response with all fields
`InDB`	Database document with `doc_type`

camelCase Aliases

class MyModel(BaseModel):
    workspace_id: str = Field(..., alias="workspaceId")
    created_at: datetime = Field(..., alias="createdAt")
    
    class Config:
        populate_by_name = True  # Accept both snake_case and camelCase

Optional Update Fields

class MyUpdate(BaseModel):
    """All fields optional for PATCH requests."""
    name: Optional[str] = Field(None, min_length=1)
    description: Optional[str] = None

Database Document

class MyInDB(MyResponse):
    """Adds doc_type for Cosmos DB queries."""
    doc_type: str = "my_resource"

Integration Steps

Create models in src/backend/app/models/
Export from src/backend/app/models/__init__.py
Add corresponding TypeScript types

Reference Files

File	Contents
references/capabilities.md	Additional non-hero capabilities, operation-group coverage, and production checklists.

---name: pydantic-models-pydescription: Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants. Use when defining API request/response schemas, database models, or data validation in Python applications using Pydantic v2.license: MIT---# Pydantic ModelsCreate Pydantic models following the multi-model pattern for clean API contracts.## Quick StartCopy the template from [assets/template.py](assets/template.py) and replace placeholders:- `{{ResourceName}}` → PascalCase name (e.g., `Project`)- `{{resource_name}}` → snake_case name (e.g., `project`)## Multi-Model Pattern| Model | Purpose ||-------|---------|| `Base` | Common fields shared across models || `Create` | Request body for creation (required fields) || `Update` | Request body for updates (all optional) || `Response` | API response with all fields || `InDB` | Database document with `doc_type` |## camelCase Aliases```pythonclass MyModel(BaseModel): workspace_id: str = Field(..., alias="workspaceId") created_at: datetime = Field(..., alias="createdAt") class Config: populate_by_name = True # Accept both snake_case and camelCase```## Optional Update Fields```pythonclass MyUpdate(BaseModel): """All fields optional for PATCH requests.""" name: Optional[str] = Field(None, min_length=1) description: Optional[str] = None```## Database Document```pythonclass MyInDB(MyResponse): """Adds doc_type for Cosmos DB queries.""" doc_type: str = "my_resource"```## Integration Steps1. Create models in `src/backend/app/models/`2. Export from `src/backend/app/models/__init__.py`3. Add corresponding TypeScript types## Reference Files| File | Contents ||------|----------|| [references/capabilities.md](references/capabilities.md) | Additional non-hero capabilities, operation-group coverage, and production checklists. |

Frequently asked questions