diff --git a/docs/features/chat-features/conversation-organization.md b/docs/features/chat-features/conversation-organization.md
index 11c9d21..b372eca 100644
--- a/docs/features/chat-features/conversation-organization.md
+++ b/docs/features/chat-features/conversation-organization.md
@@ -12,7 +12,7 @@ Folders allow you to group related conversations together for quick access and b
- **Creating a Folder**: You can create a new folder to store specific conversations. This is useful if you want to keep conversations of a similar topic or purpose together.
- **Moving Conversations into Folders**: Conversations can be moved into folders by dragging and dropping them. This allows you to structure your workspace in a way that suits your workflow.
-
+
### Example Use Case
@@ -25,7 +25,7 @@ If you are managing multiple projects, you can create separate folders for each
Tags provide an additional layer of organization by allowing you to label conversations with keywords or phrases.
- **Adding Tags to Conversations**: Tags can be applied to conversations based on their content or purpose. Tags are flexible and can be added or removed as needed.
-
+
- **Using Tags for Searching**: Tags make it easy to locate specific conversations by using the search feature. You can filter conversations by tags to quickly find those related to specific topics.
### Example Use Case
diff --git a/docs/features/evaluation/index.mdx b/docs/features/evaluation/index.mdx
index b59ffe0..fbcc990 100644
--- a/docs/features/evaluation/index.mdx
+++ b/docs/features/evaluation/index.mdx
@@ -59,11 +59,11 @@ For your feedback to affect the leaderboard, you need what’s called a **siblin
Here’s a sneak peek at how the Arena Model interface works:
-
+
Need more depth? You can even replicate a [**Chatbot Arena**](https://lmarena.ai/)-style setup!
-
+
### **2. Normal Interaction**
@@ -71,11 +71,11 @@ No need to switch to “arena mode” if you don't want to. You can use Open Web
For instance, this is how you can rate during a normal interaction:
-
+
And here's an example of setting up a multi-model comparison, similar to an arena:
-
+
---
@@ -85,7 +85,7 @@ After rating, check out the **Leaderboard** under the Admin Panel. This is where
This is a sample leaderboard layout:
-
+
### Topic-Based Reranking
@@ -100,7 +100,7 @@ Don't skip this! Tagging is super powerful because it allows you to **re-rank mo
Here’s an example of how re-ranking looks:
-
+
---
diff --git a/docs/features/plugin/functions/action.mdx b/docs/features/plugin/functions/action.mdx
index 969eeed..e276763 100644
--- a/docs/features/plugin/functions/action.mdx
+++ b/docs/features/plugin/functions/action.mdx
@@ -14,7 +14,7 @@ An example of a graph visualization Action can be seen in the video below.
- 
+ 
diff --git a/docs/getting-started/quick-start/starting-with-ollama.mdx b/docs/getting-started/quick-start/starting-with-ollama.mdx
index 88a3619..f1c5faf 100644
--- a/docs/getting-started/quick-start/starting-with-ollama.mdx
+++ b/docs/getting-started/quick-start/starting-with-ollama.mdx
@@ -27,9 +27,9 @@ To manage your Ollama instance in Open WebUI, follow these steps:
Here’s what the management screen looks like:
-
+
-
+
## A Quick and Efficient Way to Download Models
@@ -38,7 +38,7 @@ If you’re looking for a faster option to get started, you can download models
Here’s an example of how it works:
-
+
This method is perfect if you want to skip navigating through the Admin Settings menu and get right to using your models.
diff --git a/docs/intro.mdx b/docs/intro.mdx
index 72f3b0b..ec3dd99 100644
--- a/docs/intro.mdx
+++ b/docs/intro.mdx
@@ -24,7 +24,7 @@ import { SponsorList } from "@site/src/components/SponsorList";
[](https://discord.gg/5rJgQTnV4s)
[](https://github.com/sponsors/tjbck)
-
+
## Quick Start with Docker 🐳
diff --git a/docs/pipelines/filters.md b/docs/pipelines/filters.md
index c4a98e5..490901a 100644
--- a/docs/pipelines/filters.md
+++ b/docs/pipelines/filters.md
@@ -9,7 +9,7 @@ Filters are used to perform actions against incoming user messages and outgoing
- 
+ 
diff --git a/docs/pipelines/index.mdx b/docs/pipelines/index.mdx
index 9cfda58..bd99661 100644
--- a/docs/pipelines/index.mdx
+++ b/docs/pipelines/index.mdx
@@ -5,7 +5,7 @@ title: "⚡ Pipelines"
- 
+ 
@@ -37,7 +37,7 @@ Welcome to **Pipelines**, an [Open WebUI](https://github.com/open-webui) initiat
- 
+ 
diff --git a/docs/pipelines/pipes.md b/docs/pipelines/pipes.md
index 3c75b75..aa31e7c 100644
--- a/docs/pipelines/pipes.md
+++ b/docs/pipelines/pipes.md
@@ -8,7 +8,7 @@ Pipes are functions that can be used to perform actions prior to returning LLM m
- 
+ 
@@ -16,6 +16,6 @@ Pipes that are defined in your WebUI show up as a new model with an "External" d
- 
+ 
diff --git a/docs/tutorials/images.md b/docs/tutorials/images.md
index 88e346c..2b71a78 100644
--- a/docs/tutorials/images.md
+++ b/docs/tutorials/images.md
@@ -160,7 +160,7 @@ Using Azure OpenAI Dall-E directly is unsupported, but you can [set up a LiteLLM
## Using Image Generation
-
+
1. First, use a text generation model to write a prompt for image generation.
2. After the response has finished, you can click the Picture icon to generate an image.
diff --git a/docs/tutorials/integrations/deepseekr1-dynamic.md b/docs/tutorials/integrations/deepseekr1-dynamic.md
index e69de29..a94c78b 100644
--- a/docs/tutorials/integrations/deepseekr1-dynamic.md
+++ b/docs/tutorials/integrations/deepseekr1-dynamic.md
@@ -0,0 +1,169 @@
+---
+sidebar_position: 1
+title: "🦥 Run DeepSeek R1 Dynamic 1.58-bit with Llama.cpp"
+---
+
+A huge shoutout to **UnslothAI** for their incredible efforts! Thanks to their hard work, we can now run the **full DeepSeek-R1** 671B parameter model in its dynamic 1.58-bit quantized form (compressed to just 131GB) on **Llama.cpp**! And the best part? You no longer have to despair about needing massive enterprise-class GPUs or servers — it’s possible to run this model on your personal machine (albeit slowly for most consumer hardware).
+
+:::note
+The only true **DeepSeek-R1** model on Ollama is the **671B version** available here: [https://ollama.com/library/deepseek-r1:671b](https://ollama.com/library/deepseek-r1:671b). Other versions are **distilled** models.
+:::
+
+This guide focuses on running the **full DeepSeek-R1 Dynamic 1.58-bit quantized model** using **Llama.cpp** integrated with **Open WebUI**. For this tutorial, we’ll demonstrate the steps with an **M4 Max + 128GB RAM** machine. You can adapt the settings to your own configuration.
+
+---
+
+## Step 1: Install Llama.cpp
+
+You can either:
+- [Download the prebuilt binaries](https://github.com/ggerganov/llama.cpp/releases)
+- **Or build it yourself**: Follow the instructions here: [Llama.cpp Build Guide](https://github.com/ggerganov/llama.cpp/blob/master/docs/build.md)
+
+## Step 2: Download the Model Provided by UnslothAI
+
+Head over to [Unsloth’s Hugging Face page](https://huggingface.co/unsloth/DeepSeek-R1-GGUF) and download the appropriate **dynamic quantized version** of DeepSeek-R1. For this tutorial, we’ll use the **1.58-bit (131GB)** version, which is highly optimized yet remains surprisingly functional.
+
+
+:::tip
+Know your "working directory" — where your Python script or terminal session is running. The model files will download to a subfolder of that directory by default, so be sure you know its path! For example, if you're running the command below in `/Users/yourname/Documents/projects`, your downloaded model will be saved under `/Users/yourname/Documents/projects/DeepSeek-R1-GGUF`.
+:::
+
+To understand more about UnslothAI’s development process and why these dynamic quantized versions are so efficient, check out their blog post: [UnslothAI DeepSeek R1 Dynamic Quantization](https://unsloth.ai/blog/deepseekr1-dynamic).
+
+Here’s how to download the model programmatically:
+```python
+# Install Hugging Face dependencies before running this:
+# pip install huggingface_hub hf_transfer
+
+from huggingface_hub import snapshot_download
+
+snapshot_download(
+ repo_id = "unsloth/DeepSeek-R1-GGUF", # Specify the Hugging Face repo
+ local_dir = "DeepSeek-R1-GGUF", # Model will download into this directory
+ allow_patterns = ["*UD-IQ1_S*"], # Only download the 1.58-bit version
+)
+```
+
+Once the download completes, you’ll find the model files in a directory structure like this:
+```
+DeepSeek-R1-GGUF/
+├── DeepSeek-R1-UD-IQ1_S/
+│ ├── DeepSeek-R1-UD-IQ1_S-00001-of-00003.gguf
+│ ├── DeepSeek-R1-UD-IQ1_S-00002-of-00003.gguf
+│ ├── DeepSeek-R1-UD-IQ1_S-00003-of-00003.gguf
+```
+
+:::info
+🛠️ Update paths in the later steps to **match your specific directory structure**. For example, if your script was in `/Users/tim/Downloads`, the full path to the GGUF file would be:
+`/Users/tim/Downloads/DeepSeek-R1-GGUF/DeepSeek-R1-UD-IQ1_S/DeepSeek-R1-UD-IQ1_S-00001-of-00003.gguf`.
+:::
+
+## Step 3: Make Sure Open WebUI is Installed and Running
+
+If you don’t already have **Open WebUI** installed, no worries! It’s a simple setup. Just follow the [Open WebUI documentation here](https://docs.openwebui.com/). Once installed, start the application — we’ll connect it in a later step to interact with the DeepSeek-R1 model.
+
+
+## Step 4: Serve the Model Using Llama.cpp
+
+Now that the model is downloaded, the next step is to run it using **Llama.cpp’s server mode**. Before you begin:
+
+1. **Locate the `llama-server` binary.**
+ If you built from source (as outlined in Step 1), the `llama-server` executable will be located in `llama.cpp/build/bin`. Navigate to this directory by using the `cd` command:
+ ```bash
+ cd [path-to-llama-cpp]/llama.cpp/build/bin
+ ```
+
+ Replace `[path-to-llama-cpp]` with the location where you cloned or built Llama.cpp. For example:
+ ```bash
+ cd ~/Documents/workspace/llama.cpp/build/bin
+ ```
+
+2. **Point to your model folder.**
+ Use the full path to the downloaded GGUF files created in Step 2. When serving the model, specify the first part of the split GGUF files (e.g., `DeepSeek-R1-UD-IQ1_S-00001-of-00003.gguf`).
+
+Here’s the command to start the server:
+```bash
+./llama-server \
+ --model /[your-directory]/DeepSeek-R1-GGUF/DeepSeek-R1-UD-IQ1_S/DeepSeek-R1-UD-IQ1_S-00001-of-00003.gguf \
+ --port 10000 \
+ --ctx-size 1024 \
+ --n-gpu-layers 40
+```
+
+> 🔑 **Parameters to Customize Based on Your Machine:**
+> - **`--model`:** Replace `/[your-directory]/` with the path where the GGUF files were downloaded in Step 2.
+> - **`--port`:** The server default is `8080`, but feel free to change it based on your port availability.
+> - **`--ctx-size`:** Determines context length (number of tokens). You can increase it if your hardware allows, but be cautious of rising RAM/VRAM usage.
+> - **`--n-gpu-layers`:** Set the number of layers you want to offload to your GPU for faster inference. The exact number depends on your GPU’s memory capacity — reference Unsloth’s table for specific recommendations. For CPU-only setups, set it to `0`.
+
+For example, if your model was downloaded to `/Users/tim/Documents/workspace` and you have an RTX 4090 GPU with 24GB VRAM, your command would look like this:
+```bash
+./llama-server \
+ --model /Users/tim/Documents/workspace/DeepSeek-R1-GGUF/DeepSeek-R1-UD-IQ1_S/DeepSeek-R1-UD-IQ1_S-00001-of-00003.gguf \
+ --port 10000 \
+ --ctx-size 1024 \
+ --n-gpu-layers 40
+```
+
+Once the server starts, it will host a **local OpenAI-compatible API** endpoint at:
+```
+http://127.0.0.1:10000
+```
+
+:::info
+🖥️ **Llama.cpp Server Running**
+
+
+
+After running the command, you should see a message confirming the server is active and listening on port 10000.
+:::
+
+Be sure to **keep this terminal session running**, as it serves the model for all subsequent steps.
+
+## Step 5: Connect Llama.cpp to Open WebUI
+
+1. Go to **Admin Settings** in Open WebUI.
+2. Navigate to **Connections > OpenAI Connections.**
+3. Add the following details for the new connection:
+ - URL: `http://127.0.0.1:10000/v1`
+ - API Key: `none`
+
+:::info
+🖥️ **Adding Connection in Open WebUI**
+
+
+
+After running the command, you should see a message confirming the server is active and listening on port 10000.
+:::
+
+Once the connection is saved, you can start querying **DeepSeek-R1** directly from Open WebUI! 🎉
+
+---
+
+## Example: Generating Responses
+
+You can now use Open WebUI’s chat interface to interact with the **DeepSeek-R1 Dynamic 1.58-bit model**.
+
+:::info
+🖥️ **DeepSeek-R1 Response in Open WebUI**
+
+
+:::
+
+---
+
+## Notes and Considerations
+
+- **Performance:**
+ Running a massive 131GB model like DeepSeek-R1 on personal hardware will be **slow**. Even with our M4 Max (128GB RAM), inference speeds were modest. But the fact that it works at all is a testament to UnslothAI’s optimizations.
+
+- **VRAM/Memory Requirements:**
+ Ensure sufficient VRAM and system RAM for optimal performance. With low-end GPUs or CPU-only setups, expect slower speeds (but it’s still doable!).
+
+---
+
+Thanks to **UnslothAI** and **Llama.cpp**, running one of the largest open-source reasoning models, **DeepSeek-R1** (1.58-bit version), is finally accessible to individuals. While it’s challenging to run such models on consumer hardware, the ability to do so without massive computational infrastructure is a significant technological milestone.
+
+⭐ Big thanks to the community for pushing the boundaries of open AI research.
+
+Happy experimenting! 🚀
diff --git a/docs/tutorials/tips/contributing-tutorial.md b/docs/tutorials/tips/contributing-tutorial.md
index b620411..7a169cd 100644
--- a/docs/tutorials/tips/contributing-tutorial.md
+++ b/docs/tutorials/tips/contributing-tutorial.md
@@ -60,7 +60,7 @@ b. **Modify `docusaurus.config.ts` to Use Environment Variables**
const config: Config = {
title: "Open WebUI",
tagline: "ChatGPT-Style WebUI for LLMs (Formerly Ollama WebUI)",
- favicon: "img/favicon.png",
+ favicon: "images/favicon.png",
url: process.env.SITE_URL || "https://openwebui.com",
baseUrl: process.env.BASE_URL || "/",
...
diff --git a/docs/tutorials/web_search.md b/docs/tutorials/web_search.md
index 931c8b4..32ac31a 100644
--- a/docs/tutorials/web_search.md
+++ b/docs/tutorials/web_search.md
@@ -348,7 +348,7 @@ docker exec -it open-webui curl http://host.docker.internal:8080/search?q=this+i
5. Adjust the `Search Result Count` and `Concurrent Requests` values accordingly
6. Save changes
-
+
## 5. Using Web Search in a Chat
@@ -356,7 +356,7 @@ To access Web Search, Click on the + next to the message input field.
Here you can toggle Web Search On/Off.
-
+
By following these steps, you will have successfully set up SearXNG with Open WebUI, enabling you to perform web searches using the SearXNG engine.
@@ -379,14 +379,14 @@ This is enabled on a per session basis eg. reloading the page, changing to anoth
7. Fill `Google PSE API Key` with the `API key` and `Google PSE Engine Id` (# 4)
8. Click `Save`
-
+
#### Note
You have to enable `Web search` in the prompt field, using plus (`+`) button.
Search the web ;-)
-
+
## Brave API
@@ -444,13 +444,13 @@ services:
6. [Optional] Enter the `SearchApi engine` name you want to query. Example, `google`, `bing`, `baidu`, `google_news`, `bing_news`, `google_videos`, `google_scholar` and `google_patents.` By default, it is set to `google`.
7. Click `Save`.
-
+
#### Note
You have to enable `Web search` in the prompt field, using plus (`+`) button to search the web using [SearchApi](https://www.searchapi.io/) engines.
-
+
## Kagi API
diff --git a/docusaurus.config.ts b/docusaurus.config.ts
index ad581fe..8efa918 100644
--- a/docusaurus.config.ts
+++ b/docusaurus.config.ts
@@ -6,7 +6,7 @@ import { themes as prismThemes } from "prism-react-renderer";
const config: Config = {
title: "Open WebUI",
tagline: "ChatGPT-Style WebUI for LLMs (Formerly Ollama WebUI)",
- favicon: "img/favicon.png",
+ favicon: "images/favicon.png",
// Set the production url of your site here
url: "https://openwebui.com",
@@ -65,12 +65,12 @@ const config: Config = {
themeConfig: {
// Replace with your project's social card
- // image: "img/docusaurus-social-card.jpg",
+ // image: "images/docusaurus-social-card.jpg",
navbar: {
title: "Open WebUI",
logo: {
- src: "img/logo.png",
- srcDark: "img/logo-dark.png",
+ src: "images/logo.png",
+ srcDark: "images/logo-dark.png",
},
items: [
// {
@@ -108,7 +108,7 @@ const config: Config = {
},
footer: {
logo: {
- src: "img/logo-dark.png",
+ src: "images/logo-dark.png",
height: 100,
},
style: "light",
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similarity index 100%
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