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OpenWebUI Filters and Tools

Mirrored at Github: https://github.com/ProjectMoon/open-webui-filters

Documentation (HTML): https://agnos.is/projects/open-webui-filters/

Documentation (Gemini): gemini://agnos.is/projects/open-webui-filters/

My collection of OpenWebUI Filters and Tools.

So far:

  • Checkpoint Summarization Filter: A work-in-progress replacement for the narrative memory filter for more generalized use cases.
  • GPU Scaling Filter: Reduce number of GPU layers in use if Ollama crashes due to running out of VRAM. Deprecated.
  • Output Sanitization Filter: Remove words, phrases, or characters from the start of model replies.
  • OpenStreetMap Tool: Tool for querying OpenStreetMap to look up address details and nearby points of interest.
  • Collapsible Thought Filter: Hide LLM reasoning/thinking in a collapisble block.

Checkpoint Summarization Filter

A new filter for managing context use by summarizing previous parts of the chat as the conversation continues. Designed for both general chats and narrative/roleplay use. Work in progress.

Configuration

There are currently 4 settings:

  • Summarizer Model: The model used to summarize the conversation as the chat continues. This must be a base model.
  • Large Context Summarizer Model: If large context summarization is turned on, use this model for summarizing huge contexts.
  • Summarize Large Contexts: If enabled, the filter will attempt to load the entire context into the large summarizer model for creating an initial checkpoint of an existing conversation.
  • Wiggle Room: This is the amount of 'wiggle room' for estimating a context shift. This number is subtracted from num_ctx for the purposes of determining whether or not a context shift has occurred.

Usage

In general, you should only need to specify the summarizer model and enable the filter on the OpenWebUI models that you want it to work on. Or even enable it globally. The filter works best when used from a new conversation, but it does have the (currently limited) ability to deal with existing conversations.

  • When the filter detects a context shift in the conversation, it will summarize the pre-existing context. After that, the summary is appended to the system prompt, and old messages before summarization are dropped.
  • When the filter detects the next context shift, this process is repeated, and a new summarization checkpoint is created. And so on.

If the filter is used in an existing conversation, it will summarize on the first time that it detects a context shift in the conversation:

  • If there are enough messages that the conversation is considered "big," and large context summarization is disabled, all but the last 4 messages will be dropped to form the summary.
  • If the conversation is considered "big," and large context summarization is enabled, then the large context model will be loaded to do the summarization, and the entire conversation will be given to it.

User Commands

There are some basic commands the user can use to interact with the filter in a conversation:

  • !nuke: Deletes all summary checkpoints in the chat, and the filter will attempt to summarize from scratch the next time it detects a context shift.

Limitations

There are some limitations to be aware of:

  • If you enable large context summarization, you need to make sure your system is capable of loading and summarizing an entire conversation.
  • Handling of branching conversations and regenerated responses is currently rather messy. It will kind of work. There are some plans to improve this.
  • If large context summarization is disabled, pre-existing large conversations will only summarize the previous 4 messages when the first summarization is detected.
  • The filter only loads the most recent summary, and thus the AI might "forget" much older information.

GPU Scaling Filter

Deprecated. Use the setting in OpenWebUI chat controls.

This is a simple filter that reduces the number of GPU layers in use by Ollama when it detects that Ollama has crashed (via empty response coming in to OpenWebUI). Right now, the logic is very basic, just using static numbers to reduce GPU layer counts. It doesn't take into account the number of layers in models or dynamically monitor VRAM use.

There are three settings:

  • Initial Reduction: Number of layers to immediately set when an Ollama crash is detected. Defaults to 20.
  • Scaling Step: Number of layers to reduce by on subsequent crashes (down to a minimum of 0, i.e. 100% CPU inference). Defaults to 5.
  • Show Status: Whether or not to inform the user that the conversation is running slower due to GPU layer downscaling.

Output Sanitization Filter

This filter is intended for models that often output unwanted characters or terms at the beginning of replies. I have noticed this especially with Beyonder V3 and related models. They sometimes output a ":" or "Name:" in front of replies. For example, if system prompt is "You are Quinn, a helpful assistant." the model will often reply with "Quinn:" as its first word.

There is one setting:

  • Terms: List of terms or characters to remove. This is a list, and in the UI, each item should be separated by a comma.

For the above example, the setting textbox should have :,Quinn: in it, to remove a single colon from the start of replies, and Quinn: from the start of replies.

Other Notes

Terms are removed in the order defined by the setting. The filter loops through each term and attempts to remove it from the start of the LLM's reply.

OpenStreetMap Tool

Recommended models: Llama 3.1+, Mistral Nemo, Mistral Small, Qwen 2.5.

A tool that can find certain points of interest (POIs) nearby a requested address or place.

These are the current settings:

  • User Agent: The custom user agent to set for OSM and Overpass Turbo API requests.
  • From Header: The email address for the From header for OSM and Overpass API requests.
  • Nominatim API URL: URL of the API endpoint for Nominatim, the reverse geocoding (address lookup) service. Defaults to the public instance. This must be the root URL, for example: https://nominatim.openstreetmap.org/.
  • Overpass Turbo API URL: URL of the API endpoint for Overpass Turbo, for searching OpenStreetMap. Defaults to the public endpoint.
  • Instruction Oriented Interpretation: Controls the level of detail in the instructions for interpreting results given to the LLM. By default, it gives detailed instructions. Turn this setting off if results are inconsistent, wrong, or missing.
  • Status Indicators: If enabled, emit update events to the web UI, showing what the tool is doing and what search results it has found, or if it has encountered an error.
  • ORS API Key: Provide an API key for Open Route Service to calculate navigational routes to nearby places, to provide more accurate search results.
  • ORS Instance: By default, use the public Open Route Service instance. Can be changed to point to another ORS instance.

The tool will not run without the User Agent and From headers set. This is because the public instance of the Nominatim API will block you if you do not set these. Use of the public Nominatim instance is governed by their terms of use.

The default API services are suitable for applications with a low volume of traffic (absolute max 1 API call per second). If you are running a production service, you should set up your own Nominatim and Overpass services with caching.

How to enable 'Where is the closest X to my location?'

In order to have the OSM tool be able to answer questions like "where is the nearest grocery store to me?", it needs access to your realtime location. This can be accomplished with the following steps:

  • Enable user location in your user settings.
  • Create a model with a system prompt that references the variable {{USER_LOCATION}}.
  • OpenWebUI will automatically substitute the GPS coordinates reported by the browser into the model's system prompt on every message.

Collapsible Thought Filter

Hides model reasoning/thinking processes in a collapisble block in the UI response, similar to OpenAI o1 replies in ChatGPT. Designed to be used with Reflection 70b and similar models.

Current settings:

  • Priority: what order to run this filter in.
  • Thought Title: the title of the collapsed thought block.
  • Thought Tag: The XML tag that contains the model's reasoning.
  • Output Tag: The XML tag that contains the model's final output.
  • Use Thoughts As Context: Whether or not to send LLM reasoning text as context. Disabled by default because it drastically increases token use.

Note on XML tag settings: These should be tags WITHOUT the <>. If you customize the tag setting, make sure your setting is just mytag and not <mytag> or anything else.

License

AGPLv3

All filters are licensed under AGPL v3.0+. The code is free software, that you can run, redistribute, modify, study, and learn from as you see fit, as long as you extend that same freedom to others, in accordance with the terms of the AGPL. Make sure you are aware how this might affect your OpenWebUI deployment, if you are deploying OpenWebUI in a public environment!

Some filters may have code in them subject to other licenses. In those cases, the licenses and what parts of the code they apply to are detailed in that specific file.