VectorMethods/videovector-python

What it solves

This SDK provides a standardized way for Python developers to interact with the VideoVector API. It simplifies complex tasks like uploading video files, defining search prompts, processing video content for metadata, and performing semantic searches across video libraries without needing to manage raw HTTP requests.

How it works

The SDK acts as a client wrapper that handles authentication, request retries, pagination, and error mapping. Developers initialize a client using an API key or OAuth token, then use high-level methods to trigger workflows—such as uploading a video, waiting for it to be processed, and running text or multimodal queries against the resulting data. It supports both synchronous and asynchronous programming styles.

Who it’s for

This tool is designed for developers building applications that require video analysis, search, or metadata extraction. It is ideal for those who need to integrate VideoVector's processing capabilities into existing Python-based backend services or data pipelines.

Highlights

• Simplified Workflows: Includes dedicated modules for managing uploads, prompt definitions, and search operations.
• Robust Reliability: Features built-in support for automatic retries, idempotency keys, and configurable timeouts.
• Flexible Authentication: Supports API keys, static bearer tokens, and custom OAuth token providers.
• Developer-Friendly: Provides automatic pagination for large datasets and clear mapping of API errors to Python exceptions.
• Production Ready: Includes tools for monitoring usage, managing webhooks, and handling bulk imports from cloud storage connectors.