docs: separted model docs
This commit is contained in:
Ho Duc Hieu
parent
0bf5685378
commit
770aebe7ba
@ -14,7 +14,6 @@ keywords:
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large language model,
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import-models-manually,
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local model,
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remote model,
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]
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---
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@ -26,25 +25,6 @@ This is currently under development.
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import Tabs from "@theme/Tabs";
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import TabItem from "@theme/TabItem";
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## Overview
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In this guide, we will walk you through how to import models manually. In Jan, you can use a local model directly on your computer or connect to a remote server.
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- Local Model: Jan is compatible with all GGUF models. 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 by following the [Steps to Manually Import a Local Model](#steps-to-manually-import-a-local-model) section.
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- Remote Model: Jan also supports integration with remote models. To establish a connection with these remote models, you can configure the client connection to a remote/ local server by following the [OpenAI Platform Configuration](#openai-platform-configuration) or [Engines with OAI Compatible Configuration](#engines-with-oai-compatible-configuration) section. Please note that at the moment, you can only connect to one OpenAI compatible server at a time (e.g. OpenAI Platform, Azure OpenAI, Jan API Server, etc).
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```mermaid
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graph TB
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Model --> LocalModel[Local model]
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Model --> RemoteModel[Remote model]
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LocalModel[Local Model] --> NitroEngine[Nitro Engine]
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RemoteModel[Remote Model] --> OpenAICompatible[OpenAI Compatible]
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OpenAICompatible --> OpenAIPlatform[OpenAI Platform]
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OpenAICompatible --> OAIEngines[Engines with OAI Compatible: Jan API server, Azure OpenAI, LM Studio, vLLM, etc]
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```
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## Steps to Manually Import a Local Model
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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.
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@ -185,123 +165,6 @@ Restart Jan and navigate to the Hub. Locate your model and click the `Download`
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Your model is now ready to use in Jan.
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## OpenAI Platform Configuration
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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.
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### 1. Create a Model JSON
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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:
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- Ensure the filename must be `model.json`.
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- Ensure the `id` property matches the folder name you created.
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- Ensure the `format` property is set to `api`.
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- Ensure the `engine` property is set to `openai`.
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- Ensure the `state` property is set to `ready`.
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```js
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{
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"source_url": "https://openai.com",
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// highlight-next-line
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"id": "gpt-3.5-turbo-16k",
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"object": "model",
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"name": "OpenAI GPT 3.5 Turbo 16k",
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"version": "1.0",
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"description": "OpenAI GPT 3.5 Turbo 16k model is extremely good",
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// highlight-start
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"format": "api",
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"settings": {},
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"parameters": {},
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"metadata": {
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"author": "OpenAI",
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"tags": ["General", "Big Context Length"]
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},
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"engine": "openai",
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"state": "ready"
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// highlight-end
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}
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```
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### 2. Configure OpenAI API Keys
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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.
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```js
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{
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"full_url": "https://api.openai.com/v1/chat/completions",
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// highlight-next-line
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"api_key": "sk-<your key here>"
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}
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```
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### 3. Start the Model
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Restart Jan and navigate to the Hub. Then, select your configured model and start the model.
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## Engines with OAI Compatible Configuration
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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.
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### 1. Configure a Client Connection
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Navigate to the `~/jan/engines` folder and modify the `openai.json` file. Please note that at the moment the code supports any openai compatible endpoint only read `engine/openai.json` file, thus, it will not search any other files in this directory.
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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 as follows:
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```js
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{
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// highlight-next-line
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"full_url": "http://<server-ip-address>:1337/v1/chat/completions",
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// Skip api_key if your local server does not require authentication
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// "api_key": "sk-<your key here>"
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}
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```
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### 2. Create a Model JSON
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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:
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- Ensure the filename must be `model.json`.
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- Ensure the `id` property matches the folder name you created.
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- Ensure the `format` property is set to `api`.
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- Ensure the `engine` property is set to `openai`.
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- Ensure the `state` property is set to `ready`.
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```js
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{
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"source_url": "https://jan.ai",
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// highlight-next-line
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"id": "mistral-ins-7b-q4",
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"object": "model",
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"name": "Mistral Instruct 7B Q4 on Jan API Server",
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"version": "1.0",
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"description": "Jan integration with remote Jan API server",
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// highlight-next-line
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"format": "api",
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"settings": {},
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"parameters": {},
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"metadata": {
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"author": "MistralAI, The Bloke",
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"tags": [
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"remote",
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"awesome"
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]
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},
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// highlight-start
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"engine": "openai",
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"state": "ready"
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// highlight-end
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}
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```
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### 3. Start the Model
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Restart Jan and navigate to the Hub. Locate your model and click the Use button.
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## Assistance and Support
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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.
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@ -0,0 +1,147 @@
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---
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title: Integrating With a Remote Server
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slug: /docs/guides/integrating-remote-server
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description: Jan is a ChatGPT-alternative that runs on your own computer, with a local API server.
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keywords:
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[
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Jan AI,
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Jan,
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ChatGPT alternative,
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local AI,
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private AI,
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conversational AI,
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no-subscription fee,
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large language model,
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import-models-manually,
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remote server,
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]
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---
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:::caution
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This is currently under development.
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:::
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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.
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## OpenAI Platform Configuration
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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.
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### 1. Create a Model JSON
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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:
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- Ensure the filename must be `model.json`.
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- Ensure the `id` property matches the folder name you created.
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- Ensure the `format` property is set to `api`.
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- Ensure the `engine` property is set to `openai`.
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- Ensure the `state` property is set to `ready`.
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```js
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{
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"source_url": "https://openai.com",
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// highlight-next-line
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"id": "gpt-3.5-turbo-16k",
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"object": "model",
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"name": "OpenAI GPT 3.5 Turbo 16k",
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"version": "1.0",
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"description": "OpenAI GPT 3.5 Turbo 16k model is extremely good",
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// highlight-start
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"format": "api",
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"settings": {},
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"parameters": {},
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"metadata": {
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"author": "OpenAI",
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"tags": ["General", "Big Context Length"]
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},
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"engine": "openai",
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"state": "ready"
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// highlight-end
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}
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```
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### 2. Configure OpenAI API Keys
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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.
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```js
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{
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"full_url": "https://api.openai.com/v1/chat/completions",
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// highlight-next-line
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"api_key": "sk-<your key here>"
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}
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```
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### 3. Start the Model
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Restart Jan and navigate to the Hub. Then, select your configured model and start the model.
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## Engines with OAI Compatible Configuration
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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.
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### 1. Configure a Client Connection
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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 read `engine/openai.json` file, thus, it will not search any other files in this directory.
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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 as follows:
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```js
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{
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// highlight-start
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// "full_url": "http://<server-ip-address>:<port>/v1/chat/completions"
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"full_url": "http://<server-ip-address>:1337/v1/chat/completions",
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// highlight-end
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// Skip api_key if your local server does not require authentication
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// "api_key": "sk-<your key here>"
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}
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```
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### 2. Create a Model JSON
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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:
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- Ensure the filename must be `model.json`.
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- Ensure the `id` property matches the folder name you created.
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- Ensure the `format` property is set to `api`.
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- Ensure the `engine` property is set to `openai`.
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- Ensure the `state` property is set to `ready`.
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```js
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{
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"source_url": "https://jan.ai",
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// highlight-next-line
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"id": "mistral-ins-7b-q4",
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"object": "model",
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"name": "Mistral Instruct 7B Q4 on Jan API Server",
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"version": "1.0",
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"description": "Jan integration with remote Jan API server",
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// highlight-next-line
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"format": "api",
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"settings": {},
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"parameters": {},
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"metadata": {
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"author": "MistralAI, The Bloke",
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"tags": [
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"remote",
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"awesome"
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]
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},
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// highlight-start
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"engine": "openai",
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"state": "ready"
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// highlight-end
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}
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```
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### 3. Start the Model
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Restart Jan and navigate to the Hub. Locate your model and click the Use button.
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## Assistance and Support
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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.
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