docs: update the content of integration & add discord + openinterpreter

docs/docs/quickstart/integration/azure.mdx

@@ -2,19 +2,15 @@
 sidebar_position: 3
 ---
 
-import azure from './img/azure.png';
+import azure from './assets/azure.png';
 
-# Azure Raycast
+# Azure OpenAI
 
 ## Overview
 
 This guide will show you how to integrate Azure OpenAI Service with Jan. The [Azure OpenAI Service](https://learn.microsoft.com/en-us/azure/ai-services/openai/overview?source=docs) offers robust APIs, making it simple for you to incorporate OpenAI's language models into your applications.
 
-## How to Integrate Azure
-
-<div class="text--center"> 
-    <img src={azure} width={800} alt="azure" />
-</div>
+## How to Integrate Azure OpenAI with Jan
 
 ### Step 1: Configure Azure OpenAI Service API Key
 
@@ -31,16 +27,15 @@ This guide will show you how to integrate Azure OpenAI Service with Jan. The [Az
 }
 ```
 
-### Step 2: Modify a JSON Model
+### Step 2: Model Configuration
 
 1. Go to the `~/jan/models` directory. 
 2. Make a new folder called `(your-deployment-name)`, like `gpt-35-hieu-jan`.
 3. Create a `model.json` file inside the folder with the specified configurations:
-    - Ensure the file is named `model.json`.
-    - Match the `id` property with both the folder name and your deployment name.
-    - Set the `format` property as `api`.
-    - Choose `openai` for the `engine` property.
-    - Set the `state` property as `ready`.
+  - Match the `id` property with both the folder name and your deployment name.
+  - Set the `format` property as `api`.
+  - Choose `openai` for the `engine` property.
+  - Set the `state` property as `ready`.
 
 ```json title="~/jan/models/gpt-35-hieu-jan/model.json"
 {
@@ -66,6 +61,28 @@ This guide will show you how to integrate Azure OpenAI Service with Jan. The [Az
 }
 ```
 
+#### Regarding `model.json`
+
+- In `settings`, two crucial values are:
+  - `ctx_len`: Defined based on the model's context size.
+  - `prompt_template`: Defined based on the model's trained template (e.g., ChatML, Alpaca).
+  - To set up the `prompt_template`:
+    1. Visit Hugging Face.
+    2. Locate the model (e.g., [Gemma 7b it](https://huggingface.co/google/gemma-7b-it)).
+    3. Review the text and identify the template.
+- In `parameters`, consider the following options. The fields in `parameters` are typically general and can be the same across models. An example is provided below:
+
+```json
+"parameters":{
+  "temperature": 0.7,
+  "top_p": 0.95,
+  "stream": true,
+  "max_tokens": 4096,
+  "frequency_penalty": 0,
+  "presence_penalty": 0
+}
+```
+
 ### Step 3: Start the Model
 
 Restart Jan and go to the Hub. Find your model and click on the Use button.

docs/docs/quickstart/integration/discord.mdx

@@ -0,0 +1,60 @@
+---
+sidebar_position: 5
+---
+
+import discord_repo from './assets/jan-ai-discord-repo.png';
+
+# Discord
+
+## Overview
+
+This tutorial demonstrates the process of integrating with a Discord bot using Jan.
+
+Using a Discord bot enhances server interaction. Integrating Jan with it can significantly boost responsiveness and user engagement.
+
+## How to Integrate Discord Bot with Jan
+
+### Step 1: Clone the repository
+
+To make this integration successful, it is necessary to clone the discord bot's [repository](https://github.com/jakobdylanc/discord-llm-chatbot).
+
+<div class="text--center"> 
+    <img src={discord_repo} width={600} alt="jan-ai-discord-repo" />
+</div>
+
+### Step 2: Install the requirement libraries
+
+After cloning the repository, run the following command:
+
+```sh
+pip install -r requirements.txt
+```
+
+### Step 3: Create a copy of `.env.example`, named `.env`, and set it up
+
+| Setting | Instructions |
+| ------- | ------------ |
+| DISCORD_BOT_TOKEN | Generate a new Discord application at [discord.com/developers/applications](https://discord.com/developers/applications), obtain a token from the Bot tab, and enable MESSAGE CONTENT INTENT. |
+| LLM | For [Jan](https://jan.ai/), set to `local/openai/(MODEL_NAME)`, where `(MODEL_NAME)` is your loaded model's name. |
+| CUSTOM_SYSTEM_PROMPT | Adjust the bot's behavior as needed. |
+| CUSTOM_DISCORD_STATUS | Set a custom message for the bot's Discord profile. (Max 128 characters) | 
+| ALLOWED_CHANNEL_IDS | Enter Discord channel IDs where the bot can send messages, separated by commas. Leave blank to allow all channels. |
+| ALLOWED_ROLE_IDS | Enter Discord role IDs allowed to use the bot, separated by commas. Leave blank to allow everyone. Including at least one role also disables DMs. |
+| MAX_IMAGES | Max number of image attachments allowed per message when using a vision model. (Default: `5`) |
+| MAX_MESSAGES | Max messages allowed in a reply chain. (Default: `20`) |
+| LOCAL_SERVER_URL | URL of your local API server for LLMs starting with `local/`. (Default: `http://localhost:5000/v1`) |
+| LOCAL_API_KEY | API key for your local API server with LLMs starting with `local/`. Usually safe to leave blank. |
+
+### Step 4: Invite the bot to your Discord server using this URL (replace `CLIENT_ID` with your Discord application's client ID from the OAuth2 tab)
+
+```
+https://discord.com/api/oauth2/authorize?client_id=(CLIENT_ID)&permissions=412317273088&scope=bot
+```
+
+### STep 5: Run the bot
+
+Run the bot by using the following command in your command prompt:
+
+```sh
+python llmcord.py
+```

docs/docs/quickstart/integration/openinterpreter.mdx

@@ -0,0 +1,49 @@
+---
+sidebar_position: 6
+---
+
+# Open Interpreter
+
+## Overview
+
+This tutorial illustrates how to integrate with Open Interpreter using Jan. [Open Interpreter](https://github.com/KillianLucas/open-interpreter/) lets LLMs run code (Python, Javascript, Shell, and more) locally. You can chat with Open Interpreter through a ChatGPT-like interface in your terminal by running `interpreter` after installing.
+
+## How to Integrate Open Interpreter with Jan
+
+### Step 1: Install Open Interpreter
+
+Install Open Interpreter by running:
+
+```sh
+pip install open-interpreter
+```
+
+A Rust compiler is required to install Open Interpreter. If not already installed, run the following command or go to [this page](https://rustup.rs/) if you are running on windows:
+
+```zsh
+sudo apt install rustc
+```
+
+### Step 2: Configure Jan's Local API Server
+
+Before using Open Interpreter, configure the model in `Settings` > `My Model` for Jan and activate its local API server.
+
+#### Enabling Jan API Server
+
+1. Click the `<>` button to access the **Local API Server** section in Jan.
+
+2. Configure the server settings, including **IP Port**, **Cross-Origin-Resource-Sharing (CORS)**, and **Verbose Server Logs**.
+
+3. Click **Start Server**.
+
+### Step 3: Run Open Interpreter with Specific Parameters
+
+For integration, provide the API Base (`http://localhost:1337/v1`) and the model ID (e.g., `mistral-ins-7b-q4`) when running Open Interpreter.
+
+For instance, if using **Mistral Instruct 7B Q4** as the model, execute:
+
+```zsh
+interpreter --api_base http://localhost:1337/v1 --model mistral-ins-7b-q4
+```
+
+Open Interpreter is now ready for use!

docs/docs/quickstart/integration/openrouter.mdx

@@ -2,8 +2,8 @@
 sidebar_position: 2
 ---
 
-import openrouterGIF from './img/jan-ai-openrouter.gif';
-import openrouter from './img/openrouter.png';
+import openrouterGIF from './assets/jan-ai-openrouter.gif';
+import openrouter from './assets/openrouter.png';
 
 # OpenRouter
 
@@ -13,10 +13,6 @@ This guide will show you how to integrate OpenRouter with Jan, allowing you to u
 
 ## How to Integrate OpenRouter
 
-<div class="text--center"> 
-    <img src={openrouter} width={800} alt="openrouter" />
-</div>
-
 ### Step 1: Configure OpenRouter API key
 
 1. Find your API keys in the OpenRouter API Key.

docs/docs/quickstart/integration/raycast.mdx

@@ -2,8 +2,8 @@
 sidebar_position: 4
 ---
 
-import raycast from './img/raycast.png';
-import raycastImage from './img/raycast-image.png';
+import raycast from './assets/raycast.png';
+import raycastImage from './assets/raycast-image.png';
 
 # Raycast
 
@@ -12,10 +12,6 @@ import raycastImage from './img/raycast-image.png';
 
 ## How to Integrate Raycast
 
-<div class="text--center"> 
-    <img src={raycast} width={800} alt="raycast" />
-</div>
-
 ### Step 1: Download the TinyLlama model from Jan
 
 Go to the **Hub** and download the TinyLlama model. The model will be available at `~jan/models/tinyllama-1.1b`.

docs/docs/quickstart/integration/vscode.mdx

@@ -1,9 +1,9 @@
 ---
 sidebar_position: 1
 ---
-import continue_ask from './img/jan-ai-continue-ask.png';
-import continue_comment from './img/jan-ai-continue-comment.gif';
-import vscode from './img/vscode.png';
+import continue_ask from './assets/jan-ai-continue-ask.png';
+import continue_comment from './assets/jan-ai-continue-comment.gif';
+import vscode from './assets/vscode.png';
 import Tabs from '@theme/Tabs';
 import TabItem from '@theme/TabItem';
 
@@ -13,11 +13,7 @@ import TabItem from '@theme/TabItem';
 
 This guide showcases integrating Continue with Jan and VS Code to boost your coding using the local AI language model's features. [Continue](https://continue.dev/docs/intro) is an open-source autopilot compatible with Visual Studio Code and JetBrains, offering the simplest method to code with any LLM (Local Language Model).
 
-## How to Integrate with Continue
-
-<div class="text--center"> 
-    <img src={vscode} width={800} alt="vscode" />
-</div>
+## How to Integrate with Continue VS Code
 
 ### Step 1: Installing Continue on Visal Studio Code