SurrealDantic

Overview

This repository hosts a cutting-edge web application framework designed to harness the full potential of SurrealDB. Our framework integrates robust REST API generation, real-time data streaming using Server-Sent Events (SSE), and advanced computational functionalities including vector embeddings and cosine similarity analysis. This innovative approach positions the framework as a pioneering solution in the realm of modern web applications, particularly for those requiring real-time data handling and complex data interactions.

Features

AutoAPI: Automates REST API creation for various data models, ensuring rapid development and deployment. Controller and Repository Pattern: Streamlines CRUD operations with SurrealDB, abstracting database complexities. Real-Time Data Streaming: Utilizes SSE for live data updates, ideal for applications requiring instant data refresh like dashboards. Vector Embedding Support: Advanced handling of vector embeddings with built-in cosine similarity calculations, catering to applications in machine learning and data analysis. Asynchronous Processing: Decorators async_cpu and async_io for efficient handling of CPU-bound and I/O-bound operations. Robust Error Handling: A robust decorator enhances functions with sophisticated error handling and retry mechanisms. Pydantic Integration: Leverages Pydantic for robust data validation and serialization, ensuring data integrity and security.

Getting Started

Prerequisites

• Python 3.8+
• SurrealDB docker pull surrealdb/surrealdb:latest

Installation

pip install surrealdantic

Usage

from surrealdantic import AutoAPI, Embedding

# Initialize AutoAPI
api = AutoAPI()

# add the Embedding model
api.add(Embedding,Embedding)

# run the API

```bash
uvicorn main:api --reload