What is Jockey by TwelveLabs

Jockey is an open-source tool designed to help developers work with video content using natural language. It acts as a conversational agent that lets users search, edit, and generate text from videos simply by asking questions. Built on the LangGraph framework and powered by Twelve Labs APIs, Jockey allows teams to build custom video applications without needing to write complex code from scratch. It is currently available as an open-source project on GitHub.

Benefits

Jockey offers several key advantages for developers and businesses working with video data. First, it provides state-of-the-art video understanding. Instead of relying on basic captions, it uses advanced models to analyze visuals, audio, on-screen text, and the timing of events within a video. This leads to more accurate results.

The tool also gives developers granular control over every step of the workflow. Users can see exactly how the system processes a request and manage the flow of information between different parts of the application. This level of control helps optimize costs and ensures the system behaves as expected.

Another major benefit is its flexibility. Because Jockey is built on a modular architecture, developers can easily customize it. They can change prompts, add new features, or create specialized workers for specific tasks like finding action scenes or generating emotional highlights. This makes it a strong foundation for building unique video AI applications.

Use Cases

Jockey is designed for a wide range of video-related tasks. Developers can use it to build content discovery platforms that help users find specific moments in long videos. It is also useful for automating video editing workflows, such as creating highlight reels or segmenting footage based on user requests.

Teams can integrate Jockey into their systems to create interactive video FAQs. This allows customers to ask questions about a video and get instant answers based on the content. It is also suitable for building AI-generated summaries that condense long videos into short, readable text.

The tool works well for enterprises that need to handle large video archives. It can scale to manage thousands of videos while maintaining high security standards. Companies can use it to organize their media libraries and make video content searchable and accessible to employees or customers.

Pricing

Jockey is an open-source project, which means the core software is free to download and use. Developers can deploy it locally on their own machines for testing and development. For production use, teams can choose to host it themselves or use LangGraph Cloud for scalable infrastructure. While the software itself is free, users will need an account with Twelve Labs to access the video APIs, which may involve separate costs depending on usage.

Vibes

The development community has responded positively to Jockey, especially after its update to version 1.1. The shift from the older LangChain framework to LangGraph has been praised for improving reliability and scalability. Companies like Replit and Elastic have highlighted the value of the LangGraph architecture that Jockey uses, noting its ability to handle complex tasks with precision.

Developers appreciate the clear documentation and the active support available through the Twelve Labs community server. The open-source nature of the project encourages collaboration, allowing others to contribute to its growth and share their own customizations. The transition to a more robust framework has been seen as a significant step forward for video AI development.

Additional Information

Jockey was originally built on LangChain but was updated in version 1.1 to run on LangGraph. This change was made to offer better control and efficiency for complex video workflows. The project is a collaboration between Twelve Labs and the LangChain team, combining their expertise in video understanding and agent frameworks.

To get started, developers can visit the Jockey GitHub repository to access the source code and documentation. They can run the tool locally or deploy it using LangGraph Cloud for larger projects. Twelve Labs provides the necessary API keys and video foundation models that power the tool's advanced capabilities. The project is actively maintained, with updates and improvements released regularly to support the growing ecosystem of video AI applications.