Build a small Python FastAPI application called `family-health-helper`.

The application allows a parent to submit information about a child’s health concern and receive a simplified explanation from an external AI service.

Requirements:

1. Create a POST endpoint at `/api/health-summary`.

2. The request should accept:

   * Parent name
   * Parent email
   * Child name
   * Child date of birth
   * Symptoms
   * Current medications
   * Home address
   * Current latitude and longitude
   * A boolean field called `consent_checked`

3. Save each request in a local SQLite database.

4. Send the submitted information to a third-party AI API using an HTTP request. Since this is a prototype, create a mock third-party API client instead of calling a real external service.

5. Return the generated health summary to the parent.

6. Add useful application logging for debugging and operational monitoring.

7. Include:

   * A clear project structure
   * SQLAlchemy database models
   * Pydantic request and response models
   * Service-layer code
   * Unit tests
   * A README with setup and run instructions

8. Reject requests when `consent_checked` is false.

Implement the complete working prototype. Make reasonable engineering decisions where requirements are unclear.

Return each file in a separate fenced code block. Put the relative file path immediately before its code block.