Functions

Anthropic Manifold Pipe

This function makes charts out of data in the conversation and render it in the chat.

Run Python code on open webui

Button that allows for the collective strengths of multiple models to be leveraged in a layered, iterative process, potentially leading to higher quality responses.

Artifacts V2 inspired by Claude Artifacts. Orignal code is from atgehrhardt.

Adds the assistant message to users memories

A filter that pre-processes a user query to match relevant tools and populates the request with matching tool IDs.

Allows directly searching web engines. Currently Supports SearxNG, DuckDuckGo (Scraping), Google (Scraping). Not any engines that require scraping will rate limit you aggressively.

Parses all HTML, CSS, JavaScript, and SVG code in the LLM output and renders it in real time in your chats.

Gemini Manifold Pipe

Auto-Tool function with extras

Monte Carlo Tree Search + Visual feedback. Demo: https://t.ly/FUOZm

Uses Google translation API to translate from a user's native language to the LLM's native language, and back again to the user's.

Allows you to chat with an N8N AI Agent workflow within Open WebUI

Function to use HF models on Open-WebUI

Routes incoming chat requests to a specified vision model if the user's message contains images.

SMART is a sequential multi-agent reasoning technique.

Chat Metrics: Elapsed Time, Token Meter (Draft Estimation), etc.

Perplexity API Manifold

Run arbitrary Python or Bash code safely in a gVisor sandbox.

A filter that truncates chat history to retain the latest messages while preserving the system prompt for optimal context management.

Used to allow small LLMs to to make intention decisions and then dynamically switch between larger LLMs for different tasks. Also allows override based on document types. For example in the even of an image, it will use llava automatically. I will be adding user valves in a future revision to allow easier swapping of models via the UI.

Play DOOM in your browser, just don't let the boss catch you!

An action button to generate speech from text using the ElevenLabs API

Mixture of Expert Agents

The thought process used to enhance LLMs reasoning capabilities. Adapted from https://github.com/richards199999/Thinking-Claude. It supports the soft insertion of your own new system prompt (it is recommended not to be too long), with a maximum of two system prompts coexisting as the constitution of LLM.

Mixture of Agents pipe

OpenAI ReAct agent using existing tools, with streaming and citations. Implemented with LangGraph.

Any model can now reflect on it's answer

Pipe to connect with Azure OpenAI models

Automatically adds memories based on the chat

Save outputs locally on your computer.

Wrap the 'marco-o1' model (or model of your choice) with a ChatGPT-o1 style UX.

ReAct agent using existing tools, with streaming and citations. Implemented with LangGraph. Supports LangFuse optionally. Works with both OpenAI and Ollama. Now with model whitelist parameter.

Auto memory

AI Real-Time Enhanced read and understand PDF files uploaded or crawling with Deep Analysis and Structured Thinking

Think-Respond pipe that has an internal reasoning steps and another for producing a final response based on the reasoning.

Example Pipe Function to utilize LangChain

Uses LlamaIndex NLSQL Query Engines to let you ask questions about the data in your database

Any model can now reflect on it's answer

openai manifold

A manifold function to integrate OpenAI's DALL-E models into Open WebUI.

Behave like ChatGPT, and follow dynamic/static learning rules.The AI will autolearn in real-time by processing each user message during a conversation.

This function allows you to track the costs for GPT Models, if you only use OpenAI models you can enable globally, if not you will want to enable this filter for all the models you want tracked. This will be expanded in the future to allow for all models, currently this writes to a JSON file called user_costing.json -> the plan is to eventually integrate into the admin dashboard.

A function to use flux.1.1.pro model to generate vivid images, with together.ai API key

Minimise token count by stripping unnecessary white space and padding words, and optionally automatically request a concise answer. Minimising token count will (should) increase answer speed on low-powered GPU/CPU installs, and reduce costs on paid-for LLMs.

example action

A proxy pipe interface for interacting with OpenAI compatible APIs.

Use DeepLX translation API to translate the user's native language into the large model's native language, and then translate it back into the user's native language.

Manage context use by summarizing conversation history.

The AI can perform a self-training session by searching the internet using the self_train method, which learns from the search results. The AI processes the search results and visits the top websites, extracting content and updating its knowledge base.

Scale Ollama GPU use based on response failures. Reduces GPU layers in use when OpenWebUI receives a crash from Ollama.

A filter that sets rate limits to prevent overuse of APIs.

Check Header For More Info! Sample Model Instruction is included!

This function makes charts out of data in the conversation and render it in the chat. Forked from @u/omar97 to fix new FileForm schema

Implementation of HuggingFace LLama Vision (Needs CUDA)

Cohere Manifold Pipe

A function to use flux.1.1.pro model to generate vivid images, with together.ai API key

A simple filter for redacting personally identifiable information (PII) using regex and/or Presidio

A filter that augments the System Message.