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commit af900c8803
Author: Silentoplayz <50341825+Silentoplayz@users.noreply.github.com>
Date:   Thu Dec 26 14:56:03 2024 -0500

    Update env-configuration.md

    update for v0.4.8 list of env vars

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Author: Timothy Jaeryang Baek <tim@openwebui.com>
Date:   Wed Dec 25 13:31:27 2024 -0800

    Merge pull request #339 from jtslear/main

    Details model default for ComfyUI

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Author: Timothy Jaeryang Baek <tim@openwebui.com>
Date:   Tue Dec 24 20:37:54 2024 -0700

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Author: Timothy Jaeryang Baek <tim@openwebui.com>
Date:   Mon Dec 23 13:06:36 2024 -0700

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commit 41f918c408
Author: John T Skarbek <jtslear@users.noreply.github.com>
Date:   Mon Dec 23 08:45:24 2024 -0500

    Details model default for ComfyUI

    Adds concise detail for the Set Default Model option in the Image configuration pane for ComfyUI

commit 6b2523cf35
Author: Timothy Jaeryang Baek <tim@openwebui.com>
Date:   Mon Dec 23 01:59:26 2024 -0700

    Update roadmap.mdx

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    Merge pull request #337 from silentoplayz/main

    Updated DockerUpdating.md page

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Author: Timothy Jaeryang Baek <tim@openwebui.com>
Date:   Sat Dec 21 18:21:30 2024 -0700

    Update roadmap.mdx

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    New Apache Tika & Artifacts Docs Pages

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    Merge pull request #330 from xiaowuap/patch-1

    Add BingAPI in web_search.md

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Date:   Sat Dec 21 01:09:45 2024 +0800

    Add BingAPI in web_search.md

    First time to contribute~
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@ -1,25 +0,0 @@
---
sidebar_position: 12
title: "📝 Model Whitelisting"
---
Open WebUI allows you to filter specific models for use in your instance. This feature is especially useful for administrators who want to control which models are available to users. Filtering can be done through the WebUI or by adding environment variables to the backend.
## Filtering via WebUI
![Model Filter Configuration](/img/tutorial_model_filter.png)
1. Go to **Admin Panel > Settings > Users**.
2. In the **Manage Models** section, you can enable or disable the model whitelisting feature, and add or remove models from the whitelist.
3. Click **Save** to apply your changes.
## Filtering via Environment Variables
You can also whitelist models by adding environment variables to the backend. This method is useful for automated deployments and can be done by adding the following environment variables to your `docker run` command:
```bash
-e ENABLE_MODEL_FILTER=True \
-e MODEL_FILTER_LIST="llama2:13b;mistral:latest;gpt-3.5-turbo" \
```
In this example, the `ENABLE_MODEL_FILTER` variable is set to `True` to enable the feature, and the `MODEL_FILTER_LIST` variable lists the models to be whitelisted. The format for the `MODEL_FILTER_LIST` variable is `model_name:version;model_name:version;...`.

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@ -39,5 +39,4 @@ Get essential information for API integration and automation using our models.
---
Looking for installation instructions? Head over to our [Quick Start Guide](/getting-started/quick-start).
Need to explore core features? Check out [Using OpenWebUI](/getting-started/using-openwebui).
Looking for installation instructions? Head over to our [Quick Start Guide](/getting-started/quick-start).

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@ -15,12 +15,6 @@ Get up and running quickly with our [Quick Start Guide](./quick-start).
---
## 📚 Using OpenWebUI
Learn the basics and explore key concepts in our [Using OpenWebUI Guide](./using-openwebui).
---
## 🛠️ Advanced Topics
Take a deeper dive into configurations and development tips in our [Advanced Topics Guide](./advanced-topics).

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@ -140,7 +140,7 @@ After installing, visit:
- [http://localhost:3000](http://localhost:3000) to access OpenWebUI.
- or [http://localhost:8080/](http://localhost:8080/) when using a Python deployment.
You are now ready to start **[Using OpenWebUI](../using-openwebui/index.mdx)**!
You are now ready to start using OpenWebUI!
## Join the Community

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## Why isn't my Open WebUI updating?
## Updating
To update your local Docker installation of Open WebUI to the latest version available, you can either use **Watchtower** or manually update the container. Follow either of the steps provided below to be guided through updating your existing Open WebUI image.
To update your local Docker installation to the latest version, you can either use **Watchtower** or manually update the container.
### Manual Update
### Option 1: Using Watchtower
1. **Stop and remove the current container**:
This will stop the running container and remove it, but it won't delete the data stored in the Docker volume. (Replace `open-webui` with your container's name throughout the updating process if it's different for you.)
```bash
docker rm -f open-webui
```
2. **Pull the latest Docker image**:
This will update the Docker image, but it won't update the running container or its data.
```bash
docker pull ghcr.io/open-webui/open-webui:main
```
3. **Remove any existing data in the Docker volume (NOT RECOMMENDED UNLESS ABSOLUTELY NECCESSARY!)**. Skip this step entirely if not needed and move on to the last step:
If you want to start with a clean slate, you can remove the existing data in the Docker volume. Be careful, as this will delete all your chat histories and other data.
The data is stored in a Docker volume named `open-webui`. You can remove it with the following command:
```bash
docker volume rm open-webui
```
4. **Start the container again with the updated image and existing volume attached**:
If you didn't remove the existing data, this will start the container with the updated image and the existing data. If you removed the existing data, this will start the container with the updated image and a new, empty volume. **For Nvidia GPU support, add `--gpus all` to the docker run command**
```bash
docker run -d -p 3000:8080 -v open-webui:/app/backend/data --name open-webui ghcr.io/open-webui/open-webui:main
```
## Automatically Updating Open WebUI with Watchtower
You can use [Watchtower](https://containrrr.dev/watchtower/) to automate the update process for Open WebUI. Here are three options:
### Option 1: One-time Update
You can run Watchtower as a one-time update to stop the current container, pull the latest image, and start a new container with the updated image and existing volume attached (**For Nvidia GPU support, add `--gpus all` to the docker run command**):
With [Watchtower](https://containrrr.dev/watchtower/), you can automate the update process:
```bash
docker run --rm --volume /var/run/docker.sock:/var/run/docker.sock containrrr/watchtower --run-once open-webui
```
### Option 2: Running Watchtower as a Separate Container
_(Replace `open-webui` with your container's name if it's different.)_
You can run Watchtower as a separate container that watches and updates your Open WebUI container:
### Option 2: Manual Update
```bash
docker run -d --name watchtower \
--volume /var/run/docker.sock:/var/run/docker.sock \
containrrr/watchtower -i 300 open-webui
```
1. Stop and remove the current container:
This will start Watchtower in detached mode, watching your Open WebUI container for updates every 5 minutes.
```bash
docker rm -f open-webui
```
### Option 3: Integrating Watchtower with a `docker-compose.yml` File
2. Pull the latest version:
You can also integrate Watchtower with your `docker-compose.yml` file to automate updates for Open WebUI (**For Nvidia GPU support, add `--gpus all` to the docker run command**):
```bash
docker pull ghcr.io/open-webui/open-webui:main
```
```yml
version: '3'
services:
open-webui:
image: ghcr.io/open-webui/open-webui:main
ports:
- "3000:8080"
volumes:
- open-webui:/app/backend/data
3. Start the container again:
watchtower:
image: containrrr/watchtower
volumes:
- /var/run/docker.sock:/var/run/docker.sock
command: --interval 300 open-webui
depends_on:
- open-webui
```bash
docker run -d -p 3000:8080 -v open-webui:/app/backend/data --name open-webui ghcr.io/open-webui/open-webui:main
```
volumes:
open-webui:
```
In this example, Watchtower is integrated with the `docker-compose.yml` file and watches the Open WebUI container for updates every 5 minutes.
## Persistent Data in Docker Volumes
The data is stored in a Docker volume named `open-webui`. The path to the volume is not directly accessible, but you can inspect the volume with the following command:
```bash
docker volume inspect open-webui
```
This will show you the details of the volume, including the mountpoint, which is usually located in `/var/lib/docker/volumes/open-webui/_data`.
Both methods will get your Docker instance updated and running with the latest build.

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---
sidebar_position: 300
title: "🔄 Updating Open WebUI"
---
## Why isn't my Open WebUI updating?
To update your local Docker installation of Open WebUI to the latest version available, you can either use **Watchtower** or manually update the container. Follow either of the steps provided below to be guided through updating your existing Open WebUI image.
### Manual Update
1. **Stop and remove the current container**:
This will stop the running container and remove it, but it won't delete the data stored in the Docker volume. (Replace `open-webui` with your container's name throughout the updating process if it's different for you.)
```bash
docker rm -f open-webui
```
2. **Pull the latest Docker image**:
This will update the Docker image, but it won't update the running container or its data.
```bash
docker pull ghcr.io/open-webui/open-webui:main
```
:::info
**Remove any existing data in the Docker volume (NOT RECOMMENDED UNLESS ABSOLUTELY NECCESSARY!)**. Skip this step entirely if not needed and move on to the last step:
If you want to start with a clean slate, you can remove the existing data in the Docker volume. Be careful, as this will delete all your chat histories and other data.
The data is stored in a Docker volume named `open-webui`. You can remove it with the following command:
```bash
docker volume rm open-webui
```
:::
3. **Start the container again with the updated image and existing volume attached**:
If you didn't remove the existing data, this will start the container with the updated image and the existing data. If you removed the existing data, this will start the container with the updated image and a new, empty volume. **For Nvidia GPU support, add `--gpus all` to the docker run command**
```bash
docker run -d -p 3000:8080 -v open-webui:/app/backend/data --name open-webui ghcr.io/open-webui/open-webui:main
```
## Automatically Updating Open WebUI with Watchtower
You can use [Watchtower](https://containrrr.dev/watchtower/) to automate the update process for Open WebUI. Here are three options:
### Option 1: One-time Update
You can run Watchtower as a one-time update to stop the current container, pull the latest image, and start a new container with the updated image and existing volume attached (**For Nvidia GPU support, add `--gpus all` to the docker run command**):
```bash
docker run --rm --volume /var/run/docker.sock:/var/run/docker.sock containrrr/watchtower --run-once open-webui
```
### Option 2: Running Watchtower as a Separate Container
You can run Watchtower as a separate container that watches and updates your Open WebUI container:
```bash
docker run -d --name watchtower \
--volume /var/run/docker.sock:/var/run/docker.sock \
containrrr/watchtower -i 300 open-webui
```
This will start Watchtower in detached mode, watching your Open WebUI container for updates every 5 minutes.
### Option 3: Integrating Watchtower with a `docker-compose.yml` File
You can also integrate Watchtower with your `docker-compose.yml` file to automate updates for Open WebUI (**For Nvidia GPU support, add `--gpus all` to the docker run command**):
```yml
version: '3'
services:
open-webui:
image: ghcr.io/open-webui/open-webui:main
ports:
- "3000:8080"
volumes:
- open-webui:/app/backend/data
watchtower:
image: containrrr/watchtower
volumes:
- /var/run/docker.sock:/var/run/docker.sock
command: --interval 300 open-webui
depends_on:
- open-webui
volumes:
open-webui:
```
In this example, Watchtower is integrated with the `docker-compose.yml` file and watches the Open WebUI container for updates every 5 minutes.
## Persistent Data in Docker Volumes
The data is stored in a Docker volume named `open-webui`. The path to the volume is not directly accessible, but you can inspect the volume with the following command:
```bash
docker volume inspect open-webui
```
This will show you the details of the volume, including the mountpoint, which is usually located in `/var/lib/docker/volumes/open-webui/_data`.

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@ -1,23 +0,0 @@
---
sidebar_position: 3
title: "🧑‍💻 Using OpenWebUI"
---
# Using OpenWebUI
Explore the essential concepts and features of Open WebUI, including models, knowledge, prompts, pipes, actions, and more.
---
## 🌐 Additional Resources and Integrations
Find community tools, integrations, and official resources.
[Additional Resources Guide](./resources)
## 📖 Community Tutorials
If you like the documentation you are reading right now, then check out this tutorial on [Configuring RAG with OpenWebUI Documentation](../../tutorials/tips/rag-tutorial.md).
Then go on to explore other community-submitted tutorials to enhance your OpenWebUI experience.
[Explore Community Tutorials](/category/-tutorials)
---
Stay tuned for more updates as we continue to expand these sections!

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@ -1,39 +0,0 @@
---
sidebar_position: 4
title: "🌐 Additional Resources"
---
# 🌐 Additional Resources
Explore more resources, community tools, and integration options to make the most out of Open WebUI.
---
## 🔥 Open WebUI Website
Visit [Open WebUI](https://openwebui.com/) for official documentation, tools, and resources:
- **Leaderboard**: Check out the latest high-ranking models, tools, and integrations.
- **Featured Models and Tools**: Discover models and tools created by community members.
- **New Integrations**: Find newly released integrations, plugins, and models to expand your setup.
---
## 🌍 Community Platforms
Connect with the Open WebUI community for support, tips, and discussions.
- **Discord**: Join our community on Discord to chat with other users, ask questions, and stay updated.
[Join the Discord Server](https://discord.com/invite/5rJgQTnV4s)
- **Reddit**: Follow the Open WebUI subreddit for announcements, discussions, and user-submitted content.
[Visit Reddit Community](https://www.reddit.com/r/OpenWebUI/)
- **GitHub Community**: Participate in discussions, propose feature requests, and report issues specific to the Open WebUI Community Platform website.
[Explore the GitHub Community](https://github.com/open-webui/community)
---
## 📖 Tutorials and User Guides
Explore community-created tutorials to enhance your Open WebUI experience:
- [Explore Community Tutorials](/category/-tutorials)
- Learn how to configure RAG and advanced integrations with the [RAG Configuration Guide](../../tutorials/tips/rag-tutorial.md).
---
Stay connected and make the most out of Open WebUI through these community resources and integrations!

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@ -20,7 +20,11 @@ Our roadmap for interface innovations aims to create a highly intuitive and acce
- 📈 **Advanced User Tracking and Cost Management Tools**: Users will gain access to comprehensive tools designed for tracking application performance and user activities, as well as managing costs effectively. These tools will empower users with the data they need to make informed decisions, improve user experiences, and maintain budget control, optimizing the use of resources across their AI applications.
- 💬 **"Channels" Feature**: Integrating a built-in chat solution for Open WebUI users that includes AI moderation and assistance capabilities can significantly enhance user engagement and provide timely assistance, improving overall user satisfaction and retention.
- 💬 **"Channels" Feature**: Channels will function like Discord/Slack chat rooms, facilitating real-time collaboration among users and AIs. These dedicated communication spaces can host human-to-human interactions or AI-assisted discussions, fostering dynamic and context-driven collaboration. As we transition towards multi-agent and proactive agent workflows, true asynchronous communication will be essential, and Open WebUI will provide a Bot SDK tutorial to empower users in building proactive AI agents that can initiate conversations and integrate seamlessly into the platform.
- 👤 **User Page**: A personal User Page feature where users can create posts. The functionality will also include features like followers, likes, and comments. This allows users to effectively share their model configurations, prompts, and files with a broader community, creating a richer, more connected ecosystem around the platform.
- 📝 **AI Powered Notes**: Inspired by tools like Notion and Obsidian, we plan to introduce a robust note-taking feature that includes AI integration. From simple note-taking to full-fledged document creation, this tool will offer a seamless experience, all locally integrated within the platform.
- 🧠 **AI Workflow Tool**: A node-based tool to orchestrate and compose multiple aspects of AI systems. This tool will allow users to visually connect different AI modules and services, creating complex workflows with ease. It's designed to empower users to harness the full potential of AI without needing deep technical knowledge in AI programming.

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@ -114,6 +114,7 @@ To integrate ComfyUI into Open WebUI, follow these steps:
3. Return to Open WebUI and click the **Click here to upload a workflow.json file** button.
4. Select the `workflow_api.json` file to import the exported workflow from ComfyUI into Open WebUI.
5. After importing the workflow, you must map the `ComfyUI Workflow Nodes` according to the imported workflow node IDs.
6. Set `Set Default Model` to the name of the model file being used, such as `flux1-dev.safetensors`
:::info
You may need to adjust an `Input Key` or two within Open WebUI's `ComfyUI Workflow Nodes` section to match a node within your workflow.

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@ -500,6 +500,12 @@ Coming Soon
## Bing API
Coming Soon
### Setup
1. Navigate to the [AzurePortal](https://portal.azure.com/#create/Microsoft.BingSearch) and create a new resource. After creation, you’ll be redirected to the resource overview page. From there, select "Click here to manage keys." ![click here to manage keys](https://github.com/user-attachments/assets/dd2a3c67-d6a7-4198-ba54-67a3c8acff6d)
2. On the key management page, locate Key1 or Key2 and copy your desired key.
3. Open the Open WebUI Admin Panel, switch to the Settings tab, and then select Web Search.
4. Enable the Web search option and set the Web Search Engine to bing.
5. Fill `SearchApi API Key` with the `API key` that you copied in step 2 from [AzurePortal](https://portal.azure.com/#create/Microsoft.BingSearch) dashboard.
6. Click `Save`.