Support client-side schema validation using Pydantic

[tylerhutcherson]

This PR implements a layered architecture for managing and validating searchable data in Redis, with clear separation of concerns between schema definition, data validation, and storage operations.

Key Components

1. Schema Definition Layer

• IndexSchema provides the blueprint for data structure and constraints
  • Defines fields with specific types (TEXT, TAG, NUMERIC, GEO, VECTOR)
  • Supports different storage types (HASH, JSON) with appropriate configuration

2. Validation Layer

• SchemaModelGenerator dynamically creates Pydantic models from schema definitions
• Implements a caching mechanism to avoid redundant model generation
• Maps Redis field types to appropriate Python/Pydantic types
• Provides type-specific validators:
  • VECTOR: validates dimensions and value ranges (e.g., INT8 range checks)
  • GEO: validates geographic coordinate format
  • NUMERIC: prevents boolean values

3. Storage Layer

• BaseStorage is the abstract class provides the foundation for Redis operations
• Specialized implementations (HashStorage, JsonStorage) for different Redis data types
• Enforces schema validation during write operations when set to True
• Implements optimized batch operations using Redis pipelines
• Supports both synchronous and asynchronous interfaces
• Handles key generation, preprocessing, and error handling

4. Index Layer

The SearchIndex contains the setting validate_on_load, which defaults on False.

Data Flow

Write Flow:

Objects are preprocessed and validated against the schema
Objects are prepared with appropriate keys
Batch writing occurs using Redis pipelines for efficiency
TTL (expiration) can be applied if specified

Read Flow:

Keys are fetched in batches using pipelines
Data is converted from Redis format to Python objects
Bytes are automatically converted to appropriate types

[abrookins]

This is EPIC! Looks great, too. Love the validation test coverage. I had a couple of comments, and probably the only thing I felt strongly about was using an actual JSONPath library for traversing objects.

[abrookins]

Looks great! 👍