Jockey

A conversational video agent combining large language models with video processing APIs.

CommonProductVideoConversational AgentVideo Processing

Jockey is a conversational video agent built on top of Twelve Labs API and LangGraph. It integrates the capabilities of existing Large Language Models (LLMs) with Twelve Labs' API, utilizing LangGraph for task allocation to distribute the workload of complex video workflows to appropriate base models. LLMs are used for logically planning execution steps and interacting with users, while video-related tasks are passed to the Twelve Labs API powered by Video Foundation Models (VFMs) for native video processing, eliminating the need for intermediary representations like pre-generated captions.

Distributes the workload of complex video workflows by combining large language models with video processing APIs.
Utilizes LangGraph for task allocation
improving video processing efficiency.
Leverages LLMs to logically plan execution steps
enhancing user interaction experience.
Processes video tasks directly using video foundation models
eliminating the need for intermediary representations.
Supports customization and extension to adapt to diverse video-related use cases.
Offers terminal and LangGraph API server deployment options
flexibly catering to development and testing needs.

Jockey is geared towards developers and teams handling complex video workflows
particularly those looking to leverage large language models to enhance their video content creation and editing processes. It caters to professional users requiring high customization and automation in video processing tasks.

Video editing teams automate video clipping and caption generation using Jockey.
Content creators utilize Jockey to generate video drafts and storyboards.
Educational institutions employ Jockey to create interactive video tutorials.

1. Install necessary external dependencies such as FFmpeg
Docker
and Docker Compose.
2. Clone the Jockey GitHub repository to your local environment.
3. Create and activate a Python virtual environment

Visit

Jockey Visit Over Time

Monthly Visits

488643166

Bounce Rate

37.28%

Page per Visit

5.7

Visit Duration

00:06:37

Jockey Visit Trend

Jockey Visit Geography

Jockey Traffic Sources

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