Pipelines — Design skill for Claude Code

Pipelines: UI-Agnostic OpenAI API Plugin Framework

[!TIP] **DO NOT USE PIPELINES!**

If your goal is simply to add support for additional providers like Anthropic or basic filters, you likely don't need Pipelines . For those cases, Open WebUI Functions are a better fit—it's built-in, much more convenient, and easier to configure. Pipelines, however, comes into play when you're dealing with computationally heavy tasks (e.g., running large models or complex logic) that you want to offload from your main Open WebUI instance for better performance and scalability.

Welcome to **Pipelines**, an [Open WebUI](https://github.com/open-webui) initiative. Pipelines bring modular, customizable workflows to any UI client supporting OpenAI API specs – and much more! Easily extend functionalities, integrate unique logic, and create dynamic workflows with just a few lines of code.

🚀 Why Choose Pipelines?

• Limitless Possibilities: Easily add custom logic and integrate Python libraries, from AI agents to home automation APIs.
• Seamless Integration: Compatible with any UI/client supporting OpenAI API specs. (Only pipe-type pipelines are supported; filter types require clients with Pipelines support.)
• Custom Hooks: Build and integrate custom pipelines.

Examples of What You Can Achieve:

• **Function Calling Pipeline**: Easily handle function calls and enhance your applications with custom logic.
• **Custom RAG Pipeline**: Implement sophisticated Retrieval-Augmented Generation pipelines tailored to your needs.
• **Message Monitoring Using Langfuse**: Monitor and analyze message interactions in real-time using Langfuse.
• [Message Monitoring Using Opik](/examples/filters/opik_filter_pipeline.py