add langchain-chatchat quickstart (#10652)

docs/readthedocs/source/_templates/sidebar_quicklinks.html

@@ -29,11 +29,14 @@
                         <a href="doc/LLM/Quickstart/docker_windows_gpu.html">Install IPEX-LLM in Docker on Windows with Intel GPU</a>
                     </li>
                     <li>
-                        <a href="doc/LLM/Quickstart/continue_quickstart.html">Run Code Copilot (Continue) in VSCode with Intel GPU</a>
+                        <a href="doc/LLM/Quickstart/chatchat_quickstart.html">Run Langchain-Chatchat (RAG Application) on Intel GPU</a>
                     </li>
                     <li>
                         <a href="doc/LLM/Quickstart/webui_quickstart.html">Run Text Generation WebUI on Intel GPU</a>
                     </li>
+                    <li>
+                        <a href="doc/LLM/Quickstart/continue_quickstart.html">Run Code Copilot (Continue) in VSCode with Intel GPU</a>
+                    </li>
                     <li>
                         <a href="doc/LLM/Quickstart/benchmark_quickstart.html">Run Performance Benchmarking with IPEX-LLM</a>
                     </li>

docs/readthedocs/source/_toc.yml

@@ -23,6 +23,7 @@ subtrees:
                 - file: doc/LLM/Quickstart/install_linux_gpu
                 - file: doc/LLM/Quickstart/install_windows_gpu
                 - file: doc/LLM/Quickstart/docker_windows_gpu
+                - file: doc/LLM/Quickstart/chatchat_quickstart
                 - file: doc/LLM/Quickstart/webui_quickstart
                 - file: doc/LLM/Quickstart/continue_quickstart
                 - file: doc/LLM/Quickstart/benchmark_quickstart

docs/readthedocs/source/doc/LLM/Quickstart/chatchat_quickstart.md

@@ -0,0 +1,74 @@
+# Run Langchain-Chatchat on Intel GPU
+
+[chatchat-space/Langchain-Chatchat](https://github.com/chatchat-space/Langchain-Chatchat) is a Knowledge Base QA application using RAG pipeline; by porting it to [`ipex-llm`](https://github.com/intel-analytics/ipex-llm), users can now easily use [Langchain-Chatchat](https://github.com/intel-analytics/Langchain-Chatchat) with LLMs and Embedding models running locally on Intel GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max); see the demos of running LLaMA2-7B (English) and ChatGLM-3-6B (Chinese) on an Intel Core Ultra laptop below.
+
+<table border="1" width="100%">
+  <tr>
+    <td align="center">English</td>
+    <td align="center">简体中文</td>
+  </tr>
+  <tr>
+    <td><video src="https://llm-assets.readthedocs.io/en/latest/_images/langchain-chatchat-en.mp4" width="100%" controls></video></td>
+    <td><video src="https://llm-assets.readthedocs.io/en/latest/_images/langchain-chatchat-cn.mp4" width="100%" controls></video></td>
+</tr>
+</table>
+
+
+
+>You can change the UI language in the left-side menu. We currently support **English** and **简体中文** (see video demos below). 
+
+## Langchain-Chatchat Architecture
+
+See the Langchain-Chatchat architecture below ([source](https://github.com/chatchat-space/Langchain-Chatchat/blob/master/img/langchain%2Bchatglm.png)).
+
+<img src="https://llm-assets.readthedocs.io/en/latest/_images/langchain-arch.png" height="50%" />
+
+## Quickstart
+
+
+  
+### Install and Run
+
+ Follow the guide that corresponds to your specific system and GPU type from the links provided below:
+
+- For systems with Intel Core Ultra integrated GPU: [Windows Guide](./INSTALL_win_mtl.md)
+- For systems with Intel Arc A-Series GPU: [Windows Guide](./INSTALL_windows_arc.md) | [Linux Guide](./INSTALL_linux_arc.md)
+- For systems with Intel Data Center Max Series GPU: [Linux Guide](./INSTALL_linux_max.md)
+
+
+### How to use RAG
+
+#### Step 1: Create Knowledge Base
+
+- Select `Manage Knowledge Base` from the menu on the left, then choose `New Knowledge Base` from the dropdown menu on the right side.
+  <p align="center"><img src="https://llm-assets.readthedocs.io/en/latest/_images/new-kb.png" alt="image1" width="70%" align="center"></p>
+- Fill in the name of your new knowledge base (example: "test") and press the `Create` button. Adjust any other settings as needed. 
+  <p align="center"><img src="https://llm-assets.readthedocs.io/en/latest/_images/create-kb.png" alt="image1" width="70%" align="center"></p>
+- Upload knowledge files from your computer and allow some time for the upload to complete. Once finished, click on `Add files to Knowledge Base` button to build the vector store. Note: this process may take several minutes.
+  <p align="center"><img src="https://llm-assets.readthedocs.io/en/latest/_images/build-kb.png" alt="image1" width="70%" align="center"></p>
+
+
+#### Step 2: Chat with RAG
+
+You can now click `Dialogue` on the left-side menu to return to the chat UI. Then in `Knowledge base settings` menu, choose the Knowledge Base you just created, e.g, "test". Now you can start chatting. 
+
+<p align="center"><img src="https://llm-assets.readthedocs.io/en/latest/_images/rag-menu.png" alt="rag-menu" width="60%" align="center"></p>
+
+<br/>
+
+For more information about how to use Langchain-Chatchat, refer to Official Quickstart guide in [English](./README_en.md), [Chinese](./README_chs.md), or the [Wiki](https://github.com/chatchat-space/Langchain-Chatchat/wiki/).
+
+
+
+### Trouble Shooting & Tips
+
+#### 1. Version Compatibility
+
+Ensure that you have installed `ipex-llm>=2.1.0b20240327`. To upgrade `ipex-llm`, use
+```bash
+pip install --pre --upgrade ipex-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu
+```
+
+#### 2. Prompt Templates
+
+In the left-side menu, you have the option to choose a prompt template. There're several pre-defined templates - those ending with '_cn' are Chinese templates, and those ending with '_en' are English templates. You can also define your own prompt templates in `configs/prompt_config.py`. Remember to restart the service to enable these changes. 

docs/readthedocs/source/doc/LLM/Quickstart/index.rst

@@ -13,8 +13,9 @@ This section includes efficient guide to show you how to:
 * `Install IPEX-LLM on Windows with Intel GPU <./install_windows_gpu.html>`_
 * `Install IPEX-LLM in Docker on Windows with Intel GPU <./docker_windows_gpu.html>`_
 * `Run Performance Benchmarking with IPEX-LLM <./benchmark_quickstart.html>`_
-* `Run Code Copilot (Continue) in VSCode with Intel GPU <./continue_quickstart.html>`_
+* `Run Langchain-Chatchat (RAG Application) on Intel GPU <./chatchat_quickstart.html>`_
 * `Run Text Generation WebUI on Intel GPU <./webui_quickstart.html>`_
+* `Run Code Copilot (Continue) in VSCode with Intel GPU <./continue_quickstart.html>`_
 * `Run llama.cpp with IPEX-LLM on Intel GPU <./llama_cpp_quickstart.html>`_
 
 .. |bigdl_llm_migration_guide| replace:: ``bigdl-llm`` Migration Guide