Merge pull request #4009 from zwpaper/dev

docs: add tabby coding integration

docs/src/pages/integrations/coding/tabby.mdx

@@ -0,0 +1,104 @@
+---
+title: Tabby
+description: A step-by-step guide on integrating Jan with Tabby and VSCode, JetBrains, or other IDEs.
+keywords:
+  [
+    Jan,
+    Customizable Intelligence, LLM,
+    local AI,
+    privacy focus,
+    free and open source,
+    private and offline,
+    conversational AI,
+    no-subscription fee,
+    large language models,
+    Tabby integration,
+    VSCode integration,
+    JetBrains integration,
+  ]
+---
+
+import { Tabs, Steps } from 'nextra/components'
+
+# Tabby
+
+## Integrate Jan with Tabby and Your Favorite IDEs
+
+[Tabby](https://www.tabbyml.com/) is an open-source, self-hosted AI coding assistant.
+With Tabby, teams can easily set up their own LLM-powered code completion server.
+
+Tabby provides integrations with VSCode, JetBrains, and other IDEs to help developers code more efficiently,
+and it can be used with various LLM services, including Jan.
+
+To integrate Jan with Tabby, follow these steps:
+
+<Steps>
+
+### Step 1: Enable the Jan API Server
+
+To set up Tabby with Jan's Local Server, you must activate the Jan API Server with your chosen model.
+
+1. Click the `Local API Server` (`<>`) button above the Settings. Jan will direct you to the **Local API Server** section.
+2. Configure the server, including the **IP Port**, **Cross-Origin Resource Sharing (CORS)**, and **Verbose Server Logs**.
+3. Press the **Start Server** button.
+
+### Step 2: Find the Model ID and Ensure the Model is Activated
+
+1. Go to `Settings` > `My Models`.
+2. Models are listed with their **Model ID** beneath their names.
+3. Click the **three dots (⋮)** button next to the model.
+4. Select **Start Model** to activate the model.
+
+### Step 3: Installing Tabby Server
+
+Use the following documentation to install the Tabby server:
+- [Docker](https://tabby.tabbyml.com/docs/quick-start/installation/docker/)
+- [Apple Silicon](https://tabby.tabbyml.com/docs/quick-start/installation/apple/)
+- [Linux](https://tabby.tabbyml.com/docs/quick-start/installation/linux/)
+- [Windows](https://tabby.tabbyml.com/docs/quick-start/installation/windows/)
+
+Then, follow the steps to connect Jan with the Tabby server:
+[Connect Jan with Tabby](https://tabby.tabbyml.com/docs/references/models-http-api/jan.ai/).
+
+For example, to connect Jan with Tabby, save the following configuration under `~/.tabby/config.toml`:
+
+```toml title="~/.tabby/config.toml"
+# Chat model
+[model.chat.http]
+kind = "openai/chat"
+model_name = "model_id"
+api_endpoint = "http://localhost:1337/v1"
+api_key = ""
+```
+
+Currently, the Jan completion and embedding API is under construction.
+Once completed, you can also connect Jan with Tabby for completion and embedding tasks.
+
+### Step 4: Installing Tabby on Your Favorite IDEs
+
+Refer to the following documentation to install the Tabby extension on your favorite IDEs:
+- [Visual Studio Code](https://tabby.tabbyml.com/docs/extensions/installation/vscode/)
+- [JetBrains IntelliJ Platform](https://tabby.tabbyml.com/docs/extensions/installation/intellij/)
+- [VIM / NeoVIM](https://tabby.tabbyml.com/docs/extensions/installation/vim/)
+
+</Steps>
+
+## How to Use Tabby with Jan Integration
+
+### Answer Engine: Chat with Your Codes and Documentation
+
+Tabby offers an [Answer Engine](https://tabby.tabbyml.com/docs/administration/answer-engine/) on the homepage,
+which can leverage the Jan LLM and related contexts like code, documentation, and web pages to answer user questions.
+
+Simply open the Tabby homepage at [localhost:8080](http://localhost:8080) and ask your questions.
+
+![Answer Engine](./_assets/tabby-answer-engine.png)
+
+### IDE Chat Sidebar
+
+After installing the Tabby extension on your preferred IDEs, you can engage in a conversation with Jan to:
+
+1. Discuss your code, receive suggestions, and seek assistance.
+2. Request Jan to inline edit your code, and then review and accept the proposed changes.
+
+![Chat Sidebar](./_assets/tabby-chat-sidebar.png)