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2 changes: 1 addition & 1 deletion docs/mddocs/Quickstart/README.md
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# IPEX-LLM Quickstart

> [!NOTE]
> We are adding more Quickstart guide.
> We are adding more Quickstart guides.
This section includes efficient guide to show you how to:

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9 changes: 9 additions & 0 deletions docs/mddocs/Quickstart/axolotl_quickstart.md
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Expand Up @@ -13,6 +13,15 @@ See the demo of finetuning LLaMA2-7B on Intel Arc GPU below.
</tr>
</table>

## Table of Contents
- [Prerequisites](./axolotl_quickstart.md#0-prerequisites)
- [Install IPEX-LLM for Axolotl](./axolotl_quickstart.md#1-install-ipex-llm-for-axolotl)
- [Example: Finetune Llama-2-7B with Axolotl](./axolotl_quickstart.md#2-example-finetune-llama-2-7b-with-axolotl)
- [Finetune Llama-3-8B (Experimental)](./axolotl_quickstart.md#3-finetune-llama-3-8b-experimental)
- [Troubleshooting](./axolotl_quickstart.md#troubleshooting)



## Quickstart

### 0. Prerequisites
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13 changes: 10 additions & 3 deletions docs/mddocs/Quickstart/benchmark_quickstart.md
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We can perform benchmarking for IPEX-LLM on Intel CPUs and GPUs using the benchmark scripts we provide.

## Prepare The Environment
## Table of Contents
- [Prepare the Environment](./benchmark_quickstart.md#prepare-the-environment)
- [Prepare the Scripts](./benchmark_quickstart.md#prepare-the-scripts)
- [Run on Windows](./benchmark_quickstart.md#run-on-windows)
- [Run on Linux](./benchmark_quickstart.md#run-on-linux)
- [Result](./benchmark_quickstart.md#result)

## Prepare the Environment

You can refer to [here](../Overview/install.md) to install IPEX-LLM in your environment. The following dependencies are also needed to run the benchmark scripts.

Expand All @@ -11,7 +18,7 @@ pip install pandas
pip install omegaconf
```

## Prepare The Scripts
## Prepare the Scripts

Navigate to your local workspace and then download IPEX-LLM from GitHub. Modify the `config.yaml` under `all-in-one` folder for your benchmark configurations.

Expand All @@ -21,7 +28,7 @@ git clone https://github.com/intel-analytics/ipex-llm.git
cd ipex-llm/python/llm/dev/benchmark/all-in-one/
```

## config.yaml
### config.yaml


```yaml
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5 changes: 5 additions & 0 deletions docs/mddocs/Quickstart/bigdl_llm_migration.md
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This guide helps you migrate your `bigdl-llm` application to use `ipex-llm`.

## Table of Contents
- [Upgrade `bigdl-llm` package to `ipex-llm`](./bigdl_llm_migration.md#1-upgrade-bigdl-llm-code-to-ipex-llm)
- [Migrate `bigdl-llm` code to `ipex-llm`](./bigdl_llm_migration.md#migrate-bigdl-llm-code-to-ipex-llm)


## Upgrade `bigdl-llm` package to `ipex-llm`

> [!NOTE]
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10 changes: 9 additions & 1 deletion docs/mddocs/Quickstart/chatchat_quickstart.md
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> [!NOTE]
> You can change the UI language in the left-side menu. We currently support **English** and **简体中文** (see video demos below).
## Table of Contents
- [Langchain-Chatchat Architecture](./chatchat_quickstart.md#langchain-chatchat-architecture)
- [Install and Run](./chatchat_quickstart.md#install-and-run)
- [How to Use RAG](./chatchat_quickstart.md#how-to-use-rag)
- [Troubleshooting & Tips](./chatchat_quickstart.md#troubleshooting--tips)


## Langchain-Chatchat Architecture

See the Langchain-Chatchat architecture below ([source](https://github.com/chatchat-space/Langchain-Chatchat/blob/master/docs/img/langchain%2Bchatglm.png)).

<img src="https://llm-assets.readthedocs.io/en/latest/_images/langchain-arch.png" height="50%" />


## Quickstart

### Install and Run
Expand Down Expand Up @@ -72,7 +80,7 @@ You can now click `Dialogue` on the left-side menu to return to the chat UI. The

For more information about how to use Langchain-Chatchat, refer to Official Quickstart guide in [English](https://github.com/chatchat-space/Langchain-Chatchat/blob/master/README_en.md#), [Chinese](https://github.com/chatchat-space/Langchain-Chatchat/blob/master/README.md#), or the [Wiki](https://github.com/chatchat-space/Langchain-Chatchat/wiki/).

### Trouble Shooting & Tips
### Troubleshooting & Tips

#### 1. Version Compatibility

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7 changes: 7 additions & 0 deletions docs/mddocs/Quickstart/continue_quickstart.md
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Expand Up @@ -14,6 +14,13 @@ Below is a demo of using `Continue` with [CodeQWen1.5-7B](https://huggingface.co
</tr>
</table>

## Table of Contents
- [Install and Run Ollama Serve](./continue_quickstart.md#1-install-and-run-ollama-serve)
- [Pull and Prepare the Model](./continue_quickstart.md#2-pull-and-prepare-the-model)
- [Install `Continue` Extension](./continue_quickstart.md#3-install-continue-extension)
- [`Continue` Configuration](./continue_quickstart.md#4-continue-configuration)
- [How to Use `Continue`](./continue_quickstart.md#5-how-to-use-continue)

## Quickstart

This guide walks you through setting up and running **Continue** within _Visual Studio Code_, empowered by local large language models served via [Ollama](./ollama_quickstart.md) with `ipex-llm` optimizations.
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5 changes: 5 additions & 0 deletions docs/mddocs/Quickstart/deepspeed_autotp_fastapi_quickstart.md
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This example demonstrates how to run IPEX-LLM serving on multiple [Intel GPUs](../../../python/llm/example/GPU/README.md) by leveraging DeepSpeed AutoTP.

## Table of Contents
- [Requirements](./deepspeed_autotp_fastapi_quickstart.md#requirements)
- [Example](./deepspeed_autotp_fastapi_quickstart.md#example)


## Requirements

To run this example with IPEX-LLM on Intel GPUs, we have some recommended requirements for your machine, please refer to [here](../../../python/llm/example/GPU/README.md#requirements) for more information. For this particular example, you will need at least two GPUs on your machine.
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7 changes: 7 additions & 0 deletions docs/mddocs/Quickstart/dify_quickstart.md
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</tr>
</table>

## Table of Contents
- [Install and Start Ollama Service on Intel GPU](./dify_quickstart.md#1-install-and-start-ollama-service-on-intel-gpu)
- [Install and Start Dify](./dify_quickstart.md#2-install-and-start-dify)
- [How to Use Dify](./dify_quickstart.md#3-how-to-use-dify)



## Quickstart

### 1. Install and Start `Ollama` Service on Intel GPU
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5 changes: 5 additions & 0 deletions docs/mddocs/Quickstart/fastchat_quickstart.md
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Expand Up @@ -4,6 +4,11 @@ FastChat is an open platform for training, serving, and evaluating large languag

IPEX-LLM can be easily integrated into FastChat so that user can use `IPEX-LLM` as a serving backend in the deployment.

## Table of Contents
- [Install IPEX-LLM with FastChat](./fastchat_quickstart.md#1-install-ipex-llm-with-fastchat)
- [Start the Service](./fastchat_quickstart.md#2-start-the-service)


## Quick Start

This quickstart guide walks you through installing and running `FastChat` with `ipex-llm`.
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9 changes: 9 additions & 0 deletions docs/mddocs/Quickstart/install_linux_gpu.md
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Expand Up @@ -4,6 +4,15 @@ This guide demonstrates how to install IPEX-LLM on Linux with Intel GPUs. It app

IPEX-LLM currently supports the Ubuntu 20.04 operating system and later, and supports PyTorch 2.0 and PyTorch 2.1 on Linux. This page demonstrates IPEX-LLM with PyTorch 2.1. Check the [Installation](../Overview/install_gpu.md#linux) page for more details.


## Table of Contents
- [Install Prerequisites](./install_linux_gpu.md#install-prerequisites)
- [Install ipex-llm](./install_linux_gpu.md#install-ipex-llm)
- [Verify Installation](./install_linux_gpu.md#verify-installation)
- [Runtime Configurations](./install_linux_gpu.md#runtime-configurations)
- [A Quick Example](./install_linux_gpu.md#a-quick-example)
- [Tips & Troubleshooting](./install_linux_gpu.md#tips--troubleshooting)

## Install Prerequisites

### Install GPU Driver
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8 changes: 8 additions & 0 deletions docs/mddocs/Quickstart/install_windows_gpu.md
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Expand Up @@ -4,6 +4,14 @@ This guide demonstrates how to install IPEX-LLM on Windows with Intel GPUs.

It applies to Intel Core Ultra and Core 11 - 14 gen integrated GPUs (iGPUs), as well as Intel Arc Series GPU.

## Table of Contents
- [Install Prerequisites](./install_windows_gpu.md#install-prerequisites)
- [Install ipex-llm](./install_windows_gpu.md#install-ipex-llm)
- [Verify Installation](./install_windows_gpu.md#verify-installation)
- [Monitor GPU Status](./install_windows_gpu.md#monitor-gpu-status)
- [A Quick Example](./install_windows_gpu.md#a-quick-example)
- [Tips & Troubleshooting](./install_windows_gpu.md#tips--troubleshooting)

## Install Prerequisites

### (Optional) Update GPU Driver
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6 changes: 6 additions & 0 deletions docs/mddocs/Quickstart/llama3_llamacpp_ollama_quickstart.md
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Expand Up @@ -15,6 +15,12 @@ See the demo of running Llama-3-8B-Instruct on Intel Arc GPU using `Ollama` belo
</tr>
</table>

## Table of Contents
- [Run Llama 3 using llama.cpp](./llama3_llamacpp_ollama_quickstart.md#1-run-llama-3-using-llamacpp)
- [Run Llama3 using Ollama](./llama3_llamacpp_ollama_quickstart.md#2-run-llama3-using-ollama)



## Quick Start
This quickstart guide walks you through how to run Llama 3 on Intel GPU using `llama.cpp` / `Ollama` with IPEX-LLM.

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Expand Up @@ -18,6 +18,15 @@ See the demo of running LLaMA2-7B on Intel Arc GPU below.
>
> Our latest version is consistent with [62bfef5](https://github.com/ggerganov/llama.cpp/commit/62bfef5194d5582486d62da3db59bf44981b7912) of llama.cpp.
## Table of Contents
- [Prerequisites](./llama_cpp_quickstart.md#0-prerequisites)
- [Install IPEX-LLM for llama.cpp](./llama_cpp_quickstart.md#1-install-ipex-llm-for-llamacpp)
- [Setup for running llama.cpp](./llama_cpp_quickstart.md#2-setup-for-running-llamacpp)
- [Example: Running community GGUF models with IPEX-LLM](./llama_cpp_quickstart.md#3-example-running-community-gguf-models-with-ipex-llm)
- [Troubleshooting](./llama_cpp_quickstart.md#troubleshooting)



## Quick Start
This quickstart guide walks you through installing and running `llama.cpp` with `ipex-llm`.

Expand All @@ -35,7 +44,7 @@ IPEX-LLM backend for llama.cpp only supports the more recent GPU drivers. Please

If you have lower GPU driver version, visit the [Install IPEX-LLM on Windows with Intel GPU Guide](./install_windows_gpu.md), and follow [Update GPU driver](./install_windows_gpu.md#optional-update-gpu-driver).

### 1 Install IPEX-LLM for llama.cpp
### 1. Install IPEX-LLM for llama.cpp

To use `llama.cpp` with IPEX-LLM, first ensure that `ipex-llm[cpp]` is installed.

Expand All @@ -59,7 +68,7 @@ To use `llama.cpp` with IPEX-LLM, first ensure that `ipex-llm[cpp]` is installed

**After the installation, you should have created a conda environment, named `llm-cpp` for instance, for running `llama.cpp` commands with IPEX-LLM.**

### 2 Setup for running llama.cpp
### 2. Setup for running llama.cpp

First you should create a directory to use `llama.cpp`, for instance, use following command to create a `llama-cpp` directory and enter it.
```cmd
Expand Down Expand Up @@ -127,7 +136,7 @@ To use GPU acceleration, several environment variables are required or recommend
> export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
> ```
### 3 Example: Running community GGUF models with IPEX-LLM
### 3. Example: Running community GGUF models with IPEX-LLM
Here we provide a simple example to show how to run a community GGUF model with IPEX-LLM.
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15 changes: 11 additions & 4 deletions docs/mddocs/Quickstart/ollama_quickstart.md
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Expand Up @@ -18,9 +18,16 @@ See the demo of running LLaMA2-7B on Intel Arc GPU below.
>
> Our current version is consistent with [v0.1.39](https://github.com/ollama/ollama/releases/tag/v0.1.39) of ollama.
## Table of Contents
- [Install IPEX-LLM for Ollama](./ollama_quickstart.md#1-install-ipex-llm-for-ollama)
- [Initialize Ollama](./ollama_quickstart.md#2-initialize-ollama)
- [Run Ollama Serve](./ollama_quickstart.md#3-run-ollama-serve)
- [Pull Model](./ollama_quickstart.md#4-pull-model)
- [Using Ollama](./ollama_quickstart.md#5-using-ollama)

## Quickstart

### 1 Install IPEX-LLM for Ollama
### 1. Install IPEX-LLM for Ollama

IPEX-LLM's support for `ollama` now is available for Linux system and Windows system.

Expand Down Expand Up @@ -53,7 +60,7 @@ Activate the `llm-cpp` conda environment and initialize Ollama by executing the
**Now you can use this executable file by standard ollama's usage.**

### 3 Run Ollama Serve
### 3. Run Ollama Serve

You may launch the Ollama service as below:

Expand Down Expand Up @@ -102,15 +109,15 @@ The console will display messages similar to the following:
</a>
### 4 Pull Model
### 4. Pull Model
Keep the Ollama service on and open another terminal and run `./ollama pull <model_name>` in Linux (`ollama.exe pull <model_name>` in Windows) to automatically pull a model. e.g. `dolphin-phi:latest`:
<a href="https://llm-assets.readthedocs.io/en/latest/_images/ollama_pull.png" target="_blank">
<img src="https://llm-assets.readthedocs.io/en/latest/_images/ollama_pull.png" width=100%; />
</a>
### 5 Using Ollama
### 5. Using Ollama
#### Using Curl
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11 changes: 9 additions & 2 deletions docs/mddocs/Quickstart/open_webui_with_ollama_quickstart.md
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Expand Up @@ -13,16 +13,23 @@
</tr>
</table>

## Table of Contents
- [Run Ollama with Intel GPU](./open_webui_with_ollama_quickstart.md#1-run-ollama-with-intel-gpu)
- [Install the Open-Webui](./open_webui_with_ollama_quickstart.md#2-install-the-open-webui)
- [Start the Open-WebUI](./open_webui_with_ollama_quickstart.md#3-start-the-open-webui)
- [Using the Open-Webui](./open_webui_with_ollama_quickstart.md#4-using-the-open-webui)
- [Troubleshooting](./open_webui_with_ollama_quickstart.md#5-troubleshooting)

## Quickstart

This quickstart guide walks you through setting up and using [Open WebUI](https://github.com/open-webui/open-webui) with Ollama (using the C++ interface of [`ipex-llm`](https://github.com/intel-analytics/ipex-llm) as an accelerated backend).


### 1 Run Ollama with Intel GPU
### 1. Run Ollama with Intel GPU

Follow the instructions on the [Run Ollama with Intel GPU](./ollama_quickstart.md) to install and run "Ollama Serve". Please ensure that the Ollama server continues to run while you're using the Open WebUI.

### 2 Install the Open-Webui
### 2. Install the Open-Webui

#### Install Node.js & npm

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6 changes: 6 additions & 0 deletions docs/mddocs/Quickstart/privateGPT_quickstart.md
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</tr>
</table>

## Table of Contents
- [Install and Start `Ollama` Service on Intel GPU](./privateGPT_quickstart.md#1-install-and-start-ollama-service-on-intel-gpu)
- [Install PrivateGPT](./privateGPT_quickstart.md#2-install-privategpt)
- [Start PrivateGPT](./privateGPT_quickstart.md#3-start-privategpt)
- [Using PrivateGPT](./privateGPT_quickstart.md#4-using-privategpt)

## Quickstart

### 1. Install and Start `Ollama` Service on Intel GPU
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12 changes: 10 additions & 2 deletions docs/mddocs/Quickstart/ragflow_quickstart.md
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Expand Up @@ -14,9 +14,17 @@
</tr>
</table>


## Table of Contents
- [Prerequisites](./ragflow_quickstart.md#0-prerequisites)
- [Install and Start Ollama Service on Intel GPU](./ragflow_quickstart.md#1-install-and-start-ollama-service-on-intel-gpu)
- [Pull Model](./ragflow_quickstart.md#2-pull-model)
- [Start `RAGFlow` Service](./ragflow_quickstart.md#3-start-ragflow-service)
- [Using `RAGFlow`](./ragflow_quickstart.md#4-using-ragflow)

## Quickstart

### 0 Prerequisites
### 0. Prerequisites

- CPU >= 4 cores
- RAM >= 16 GB
Expand Down Expand Up @@ -95,7 +103,7 @@ To make the change permanent and ensure it persists after a reboot, add or updat
vm.max_map_count=262144
```

### 3.3 Start the `RAGFlow` server using Docker
#### 3.3 Start the `RAGFlow` server using Docker

Build the pre-built Docker images and start up the server:

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