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@@ -4,12 +4,12 @@ title: "🔎 Open WebUI RAG Tutorial"
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---
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:::warning
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This tutorial is a community contribution and is not supported by the OpenWebUI team. It serves only as a demonstration on how to customize OpenWebUI for your specific use case. Want to contribute? Check out the contributing tutorial.
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This tutorial is a community contribution and is not supported by the Open WebUI team. It serves only as a demonstration on how to customize Open WebUI for your specific use case. Want to contribute? Check out the contributing tutorial.
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:::
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# Tutorial: Configuring RAG with OpenWebUI Documentation
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# Tutorial: Configuring RAG with Open WebUI Documentation
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In this tutorial, you will learn how to use **Retrieval-Augmented Generation (RAG)** with OpenWebUI to load real-world documentation as a knowledge base. We will walk through how to use the latest **OpenWebUI Documentation** as an example for this setup.
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In this tutorial, you will learn how to use **Retrieval-Augmented Generation (RAG)** with Open WebUI to load real-world documentation as a knowledge base. We will walk through how to use the latest **Open WebUI Documentation** as an example for this setup.
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---
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@@ -21,7 +21,7 @@ Retrieval-Augmented Generation (RAG) combines **LLMs** with **retrieved knowledg
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This tutorial demonstrates how to:
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- Upload the latest OpenWebUI Documentation as a knowledge base.
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- Upload the latest Open WebUI Documentation as a knowledge base.
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- Connect it to a custom model.
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- Query the knowledge base for enhanced assistance.
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@@ -29,9 +29,9 @@ This tutorial demonstrates how to:
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## Setup
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### Step-by-Step Setup: OpenWebUI Documentation as Knowledge Base
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### Step-by-Step Setup: Open WebUI Documentation as Knowledge Base
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Follow these steps to set up RAG with **OpenWebUI Documentation**:
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Follow these steps to set up RAG with **Open WebUI Documentation**:
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1. **Download the Documentation**:
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- Download the latest documentation:
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@@ -45,13 +45,13 @@ Follow these steps to set up RAG with **OpenWebUI Documentation**:
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4. **Create a Knowledge Base**:
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- Navigate to **Workspace** > **Knowledge** > **+ Create a Knowledge Base**.
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- Name it: `OpenWebUI Documentation`
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- Name it: `Open WebUI Documentation`
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- Purpose: **Assistance**
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> Click **Create Knowledge**.
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5. **Upload the Files**:
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- Drag and drop the `.md` and `.mdx` files from the extracted folder into the **OpenWebUI Documentation** knowledge base.
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- Drag and drop the `.md` and `.mdx` files from the extracted folder into the **Open WebUI Documentation** knowledge base.
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---
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@@ -63,9 +63,9 @@ Follow these steps to set up RAG with **OpenWebUI Documentation**:
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- Go to **Workspace** > **Models** > **+ Add New Model**.
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2. **Configure the Model**:
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- **Name**: `OpenWebUI`
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- **Name**: `Open WebUI`
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- **Base Model**: *(Select the appropriate Llama or other available model)*
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- **Knowledge Source**: Select **OpenWebUI Documentation** from the dropdown.
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- **Knowledge Source**: Select **Open WebUI Documentation** from the dropdown.
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3. **Save the Model**.
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@@ -73,10 +73,10 @@ Follow these steps to set up RAG with **OpenWebUI Documentation**:
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## Examples and Usage
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### Query the OpenWebUI Documentation Model
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### Query the Open WebUI Documentation Model
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1. **Start a New Chat**:
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- Navigate to **New Chat** and select the `OpenWebUI` model.
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- Navigate to **New Chat** and select the `Open WebUI` model.
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2. **Example Queries**:
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@@ -86,7 +86,7 @@ Follow these steps to set up RAG with **OpenWebUI Documentation**:
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```
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```
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User: "How do I update OpenWebUI using Docker?"
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User: "How do I update Open WebUI using Docker?"
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System: "Refer to `docker/updating.md`: Use `docker pull` and restart the container."
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```
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@@ -102,4 +102,4 @@ Follow these steps to set up RAG with **OpenWebUI Documentation**:
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---
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With this setup, you can effectively use the **OpenWebUI Documentation** to assist users by retrieving relevant information for their queries. Enjoy building and querying your custom knowledge-enhanced models!
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With this setup, you can effectively use the **Open WebUI Documentation** to assist users by retrieving relevant information for their queries. Enjoy building and querying your custom knowledge-enhanced models!
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