docs: update using models documentation (#1288)

docs: update using models documentation

docs/docs/guides/04-using-models/02-import-manually.mdx

@@ -13,6 +13,7 @@ keywords:
     no-subscription fee,
     large language model,
     import-models-manually,
+    local model,
   ]
 ---
 
@@ -24,16 +25,12 @@ This is currently under development.
 import Tabs from "@theme/Tabs";
 import TabItem from "@theme/TabItem";
 
-Jan is compatible with all GGUF models.
+## Steps to Manually Import a Local Model
 
-If you can not find the model you want in the Hub or have a custom model you want to use, you can import it manually.
+In this section, we will show you how to import a GGUF model from [HuggingFace](https://huggingface.co/), using our latest model, [Trinity](https://huggingface.co/janhq/trinity-v1-GGUF), as an example.
-
-In this guide, we will show you how to import a GGUF model from [HuggingFace](https://huggingface.co/), using our lastest model, [Trinity](https://huggingface.co/janhq/trinity-v1-GGUF), as an example.
 
 > We are fast shipping a UI to make this easier, but it's a bit manual for now. Apologies.
 
-## Steps to Manually Import a Model
-
 ### 1. Create a Model Folder
 
 Navigate to the `~/jan/models` folder. You can find this folder by going to `App Settings` > `Advanced` > `Open App Directory`.
@@ -126,7 +123,7 @@ Edit `model.json` and include the following configurations:
 - Ensure the filename must be `model.json`.
 - Ensure the `id` property matches the folder name you created.
 - Ensure the GGUF filename should match the `id` property exactly.
-- Ensure the `source_url` property is the direct binary download link ending in `.gguf`. In HuggingFace, you can find the direct links in `Files and versions` tab.
+- Ensure the `source_url` property is the direct binary download link ending in `.gguf`. In HuggingFace, you can find the direct links in the `Files and versions` tab.
 - Ensure you are using the correct `prompt_template`. This is usually provided in the HuggingFace model's description page.
 - Ensure the `state` property is set to `ready`.
 
@@ -154,17 +151,17 @@ Edit `model.json` and include the following configurations:
     "tags": ["7B", "Merged"],
     "size": 4370000000
   },
+  "engine": "nitro",
   // highlight-next-line
-    "state": "ready",
+  "state": "ready"
-    "engine": "nitro"
+}
-  }
 ```
 
 ### 3. Download the Model
 
 Restart Jan and navigate to the Hub. Locate your model and click the `Download` button to download the model binary.
 
-![image](assets/download-model.png)
+![image-01](assets/02-manually-import-local-model.png)
 
 Your model is now ready to use in Jan.
 

docs/docs/guides/04-using-models/03-integrate-with-remote-server.mdx

@@ -0,0 +1,148 @@
+---
+title: Integrate With a Remote Server
+slug: /guides/using-models/integrate-with-remote-server
+description: Jan is a ChatGPT-alternative that runs on your own computer, with a local API server.
+keywords:
+  [
+    Jan AI,
+    Jan,
+    ChatGPT alternative,
+    local AI,
+    private AI,
+    conversational AI,
+    no-subscription fee,
+    large language model,
+    import-models-manually,
+    remote server,
+    OAI compatible,
+  ]
+---
+
+:::caution
+This is currently under development.
+:::
+
+In this guide, we will show you how to configure Jan as a client and point it to any remote & local (self-hosted) API server.
+
+## OpenAI Platform Configuration
+
+In this section, we will show you how to configure with OpenAI Platform, using the OpenAI GPT 3.5 Turbo 16k model as an example.
+
+### 1. Create a Model JSON
+
+Navigate to the `~/jan/models` folder. Create a folder named `gpt-3.5-turbo-16k` and create a `model.json` file inside the folder including the following configurations:
+
+- Ensure the filename must be `model.json`.
+- Ensure the `id` property matches the folder name you created.
+- Ensure the `format` property is set to `api`.
+- Ensure the `engine` property is set to `openai`.
+- Ensure the `state` property is set to `ready`.
+
+```js
+{
+  "source_url": "https://openai.com",
+  // highlight-next-line
+  "id": "gpt-3.5-turbo-16k",
+  "object": "model",
+  "name": "OpenAI GPT 3.5 Turbo 16k",
+  "version": "1.0",
+  "description": "OpenAI GPT 3.5 Turbo 16k model is extremely good",
+  // highlight-start
+  "format": "api",
+  "settings": {},
+  "parameters": {},
+  "metadata": {
+    "author": "OpenAI",
+    "tags": ["General", "Big Context Length"]
+  },
+  "engine": "openai",
+  "state": "ready"
+  // highlight-end
+}
+```
+
+### 2. Configure OpenAI API Keys
+
+You can find your API keys in the [OpenAI Platform](https://platform.openai.com/api-keys) and set the OpenAI API keys in `~/jan/engines/openai.json` file.
+
+```js
+{
+  "full_url": "https://api.openai.com/v1/chat/completions",
+  // highlight-next-line
+  "api_key": "sk-<your key here>"
+}
+```
+
+### 3. Start the Model
+
+Restart Jan and navigate to the Hub. Then, select your configured model and start the model.
+
+![image-01](assets/03-openai-platform-configuration.png)
+
+## Engines with OAI Compatible Configuration
+
+In this section, we will show you how to configure a client connection to a remote/local server, using Jan's API server that is running model `mistral-ins-7b-q4` as an example.
+
+### 1. Configure a Client Connection
+
+Navigate to the `~/jan/engines` folder and modify the `openai.json` file. Please note that at the moment the code that supports any openai compatible endpoint only reads `engine/openai.json` file, thus, it will not search any other files in this directory.
+
+Configure `full_url` properties with the endpoint server that you want to connect. For example, if you want to connect to Jan's API server, you can configure it as follows:
+
+```js
+{
+  // highlight-start
+  // "full_url": "https://<server-ip-address>:<port>/v1/chat/completions"
+  "full_url": "https://<server-ip-address>:1337/v1/chat/completions",
+  // highlight-end
+  // Skip api_key if your local server does not require authentication
+  // "api_key": "sk-<your key here>"
+}
+```
+
+### 2. Create a Model JSON
+
+Navigate to the `~/jan/models` folder. Create a folder named `mistral-ins-7b-q4` and create a `model.json` file inside the folder including the following configurations:
+
+- Ensure the filename must be `model.json`.
+- Ensure the `id` property matches the folder name you created.
+- Ensure the `format` property is set to `api`.
+- Ensure the `engine` property is set to `openai`.
+- Ensure the `state` property is set to `ready`.
+
+```js
+{
+  "source_url": "https://jan.ai",
+  // highlight-next-line
+  "id": "mistral-ins-7b-q4",
+  "object": "model",
+  "name": "Mistral Instruct 7B Q4 on Jan API Server",
+  "version": "1.0",
+  "description": "Jan integration with remote Jan API server",
+  // highlight-next-line
+  "format": "api",
+  "settings": {},
+  "parameters": {},
+  "metadata": {
+    "author": "MistralAI, The Bloke",
+    "tags": [
+      "remote",
+      "awesome"
+    ]
+  },
+  // highlight-start
+  "engine": "openai",
+  "state": "ready"
+  // highlight-end
+}
+```
+
+### 3. Start the Model
+
+Restart Jan and navigate to the Hub. Locate your model and click the Use button.
+
+![image-02](assets/03-oai-compatible-configuration.png)
+
+## Assistance and Support
+
+If you have questions or are looking for more preconfigured GGUF models, please feel free to join our [Discord community](https://discord.gg/Dt7MxDyNNZ) for support, updates, and discussions.