AI Setup

This doc explains how to setup your AI providers, their APIs and credentials.

"Endpoints" refer to the AI provider, configuration or API to use, which determines what models and settings are available for the current chat request.

For example, OpenAI, Google, Plugins, Azure OpenAI, Anthropic, are all different "endpoints". Since OpenAI was the first supported endpoint, it's listed first by default.

Using the default environment values from /.env.example will enable several endpoints, with credentials to be provided on a per-user basis from the web app. Alternatively, you can provide credentials for all users of your instance.

This guide will walk you through setting up each Endpoint as needed.

For custom endpoint configuration, such as adding Mistral AI or Openrouter refer to the librechat.yaml configuration guide .

Reminder: If you use docker, you should rebuild the docker image (here's how) each time you update your credentials

Note: Configuring pre-made Endpoint/model/conversation settings as singular options for your users is a planned feature. See the related discussion here: System-wide custom model settings (lightweight GPTs) #1291

General

Free AI APIs

Setting a Default Endpoint

In the case where you have multiple endpoints setup, but want a specific one to be first in the order, you need to set the following environment variable.

# .env file
# No spaces between values
ENDPOINTS=azureOpenAI,openAI,assistants,google

Note that LibreChat will use your last selected endpoint when creating a new conversation. So if Azure OpenAI is first in the order, but you used or view an OpenAI conversation last, when you hit "New Chat," OpenAI will be selected with its default conversation settings.

To override this behavior, you need a preset and you need to set that specific preset as the default one to use on every new chat.

Setting a Default Preset

See the Presets Guide for more details

A preset refers to a specific Endpoint/Model/Conversation Settings that you can save.

The default preset will always be used when creating a new conversation.

Here's a video to demonstrate: Setting a Default Preset

OpenAI

To get your OpenAI API key, you need to:

Go to https://platform.openai.com/account/api-keys
Create an account or log in with your existing one
Add a payment method to your account (this is not free, sorry 😬)
Copy your secret key (sk-...) and save it in ./.env as OPENAI_API_KEY

Notes:

Selecting a vision model for messages with attachments is not necessary as it will be switched behind the scenes for you. If you didn't outright select a vision model, it will only be used for the vision request and you should still see the non-vision model you had selected after the request is successful
OpenAI Vision models allow for messages without attachments

Assistants

The Assistants API by OpenAI has a dedicated endpoint.
The Assistants API enables the creation of AI assistants, offering functionalities like code interpreter, knowledge retrieval of files, and function execution.
- Read here for an in-depth documentation of the feature, how it works, what it's capable of.
As with the regular OpenAI API , go to https://platform.openai.com/account/api-keys to get a key.
You will need to set the following environment variable to your key or you can set it to user_provided for users to provide their own.

ASSISTANTS_API_KEY=your-key

You can determine which models you would like to have available with ASSISTANTS_MODELS ; otherwise, the models list fetched from OpenAI will be used (only Assistants API compatible models will be shown).

# without spaces
ASSISTANTS_MODELS=gpt-3.5-turbo-0125,gpt-3.5-turbo-16k-0613,gpt-3.5-turbo-16k,gpt-3.5-turbo,gpt-4,gpt-4-0314,gpt-4-32k-0314,gpt-4-0613,gpt-3.5-turbo-0613,gpt-3.5-turbo-1106,gpt-4-0125-preview,gpt-4-turbo-preview,gpt-4-1106-preview

If necessary, you can also set an alternate base URL instead of the official one with ASSISTANTS_BASE_URL , which is similar to the OpenAI counterpart OPENAI_REVERSE_PROXY

ASSISTANTS_BASE_URL=http://your-alt-baseURL:3080/

There is additional, optional configuration, depending on your needs, such as disabling the assistant builder UI, that are available via the librechat.yaml custom config file :
- Control the visibility and use of the builder interface for assistants. More info
- Specify the polling interval in milliseconds for checking run updates or changes in assistant run states. More info
- Set the timeout period in milliseconds for assistant runs. Helps manage system load by limiting total run operation time. More info
- Specify which assistant Ids are supported or excluded More info

Notes:

At the time of writing, only the following models support the Retrieval capability:
- gpt-3.5-turbo-0125
- gpt-4-0125-preview
- gpt-4-turbo-preview
- gpt-4-1106-preview
- gpt-3.5-turbo-1106
Vision capability is not yet supported.
If you have previously set the ENDPOINTS value in your .env file , you will need to add the value assistants

Anthropic

Create an account at https://console.anthropic.com/
Go to https://console.anthropic.com/account/keys and get your api key
add it to ANTHROPIC_API_KEY= in the .env file

Google

For the Google Endpoint, you can either use the Generative Language API (for Gemini models), or the Vertex AI API (for PaLM2 & Codey models, Gemini support coming soon).

The Generative Language API uses an API key, which you can get from Google AI Studio .

For Vertex AI, you need a Service Account JSON key file, with appropriate access configured.

Instructions for both are given below.

Generative Language API (Gemini)

60 Gemini requests/minute are currently free until early next year when it enters general availability.

⚠️ Google will be using that free input/output to help improve the model, with data de-identified from your Google Account and API key. ⚠️ During this period, your messages “may be accessible to trained reviewers.”

To use Gemini models, you'll need an API key. If you don't already have one, create a key in Google AI Studio.

Get an API key here: makersuite.google.com

Once you have your key, provide the key in your .env file, which allows all users of your instance to use it.

GOOGLE_KEY=mY_SeCreT_w9347w8_kEY

Or, you can make users provide it from the frontend by setting the following:

GOOGLE_KEY=user_provided

Notes: - PaLM2 and Codey models cannot be accessed through the Generative Language API, only through Vertex AI. - Selecting gemini-pro-vision for messages with attachments is not necessary as it will be switched behind the scenes for you - Since gemini-pro-vision does not accept non-attachment messages, messages without attachments are automatically switched to use gemini-pro (otherwise, Google responds with an error)

Setting GOOGLE_KEY=user_provided in your .env file will configure both the Vertex AI Service Account JSON key file and the Generative Language API key to be provided from the frontend like so:

Vertex AI (PaLM 2 & Codey)

To setup Google LLMs (via Google Cloud Vertex AI), first, signup for Google Cloud: cloud.google.com

You can usually get $300 starting credit , which makes this option free for 90 days.

1. Once signed up, Enable the Vertex AI API on Google Cloud:

Go to Vertex AI page on Google Cloud console
Click on Enable API if prompted

2. Create a Service Account with Vertex AI role:

Click here to create a Service Account
Select or create a project
Enter a service account ID (required), name and description are optional
Click on "Create and Continue" to give at least the "Vertex AI User" role
Click on "Continue/Done"

3. Create a JSON key to Save in your Project Directory:

Go back to the Service Accounts page
Select your service account
Click on "Keys"
Click on "Add Key" and then "Create new key"
Choose JSON as the key type and click on "Create"
Download the key file and rename it as 'auth.json'
Save it within the project directory, in /api/data/

Saving your JSON key file in the project directory which allows all users of your LibreChat instance to use it.

Alternatively, you can make users provide it from the frontend by setting the following:

# Note: this configures both the Vertex AI Service Account JSON key file
# and the Generative Language API key to be provided from the frontend.
GOOGLE_KEY=user_provided

Note: Using Gemini models through Vertex AI is possible but not yet supported.

Azure OpenAI

Please see the dedicated Azure OpenAI Setup Guide.

This was done to improve upon legacy configuration settings, to allow multiple deployments/model configurations setup with ease: #1390

OpenRouter

OpenRouter is a legitimate proxy service to a multitude of LLMs, both closed and open source, including:

OpenAI models (great if you are barred from their API for whatever reason)
Anthropic Claude models (same as above)
Meta's Llama models
pygmalionai/mythalion-13b
and many more open source models. Newer integrations are usually discounted, too!

See their available models and pricing here: Supported Models

OpenRouter is integrated to the LibreChat by overriding the OpenAI endpoint.

Important : As of v0.6.6, you can use OpenRouter as its own standalone endpoint:

Review the Custom Config Guide (click here) to add an `OpenRouter` Endpoint

Setup (legacy):

Note: It is NOT recommended to setup OpenRouter this way with versions 0.6.6 or higher of LibreChat as it may be removed in future versions.

As noted earlier, review the Custom Config Guide (click here) to add an OpenRouter Endpoint instead.

Signup to OpenRouter and create a key. You should name it and set a limit as well.
Set the environment variable OPENROUTER_API_KEY in your .env file to the key you just created.
Set something in the OPENAI_API_KEY , it can be anyting, but do not leave it blank or set to user_provided
Restart your LibreChat server and use the OpenAI or Plugins endpoints.

Notes (legacy):

This will override the official OpenAI API or your reverse proxy settings for both Plugins and OpenAI.
On initial setup, you may need to refresh your page twice to see all their supported models populate automatically.
Plugins: Functions Agent works with OpenRouter when using OpenAI models.
Plugins: Turn functions off to try plugins with non-OpenAI models (ChatGPT plugins will not work and others may not work as expected).
Plugins: Make sure PLUGINS_USE_AZURE is not set in your .env file when wanting to use OpenRouter and you have Azure configured.

Unofficial APIs

Important: Stability for Unofficial APIs are not guaranteed. Access methods to these APIs are hacky, prone to errors, and patching, and are marked lowest in priority in LibreChat's development.

BingAI

I recommend using Microsoft Edge for this:

Navigate to Bing Chat
Login if you haven't already
Initiate a conversation with Bing
Open Dev Tools , usually with F12 or Ctrl + Shift + C
Navigate to the Network tab
Look for lsp.asx (if it's not there look into the other entries for one with a very long cookie)
Copy the whole cookie value. (Yes it's very long 😉)
Use this "full cookie string" for your "BingAI Token"

copilot-gpt4-service

For this setup, an additional docker container will need to be setup.

It is necessary to obtain your token first.

Follow these instructions provided at copilot-gpt4-service#obtaining-token and keep your token for use within the service. Additionally, more detailed instructions for setting copilot-gpt4-service are available at the GitHub repo .

It is not recommended to use the copilot token obtained directly, instead use the SUPER_TOKEN variable. (You can generate your own SUPER_TOKEN with the OpenSSL command openssl rand -hex 16 and set the ENABLE_SUPER_TOKEN variable to true )

Once your Docker environment is ready and your tokens are generated, proceed with this Docker run command to start the service:

docker run -d \
  --name copilot-gpt4-service \
  -e HOST=0.0.0.0 \
  -e COPILOT_TOKEN=ghp_xxxxxxx \
  -e SUPER_TOKEN=your_super_token \
  -e ENABLE_SUPER_TOKEN=true \
  --restart always \
  -p 8080:8080 \
  aaamoon/copilot-gpt4-service:latest

For Docker Compose users, use the equivalent yaml configuration provided below:

version: '3.8'
services:
  copilot-gpt4-service:
    image: aaamoon/copilot-gpt4-service:latest
    environment:
      - HOST=0.0.0.0
      - COPILOT_TOKEN=ghp_xxxxxxx # Default GitHub Copilot Token, if this item is set, the Token carried with the request will be ignored. Default is empty.
      - SUPER_TOKEN=your_super_token # Super Token is a user-defined standalone token that can access COPILOT_TOKEN above. This allows you to share the service without exposing your COPILOT_TOKEN. Multiple tokens are separated by commas. Default is empty.
      - ENABLE_SUPER_TOKEN=true # Whether to enable SUPER_TOKEN, default is false. If false, but COPILOT_TOKEN is not empty, COPILOT_TOKEN will be used without any authentication for all requests.
    ports:
      - 8080:8080
    restart: unless-stopped
    container_name: copilot-gpt4-service

After setting up the Docker container for copilot-gpt4-service , you can add it to your librechat.yaml configuration. Here is an example configuration:
```
version: 1.0.1
cache: true
endpoints:
  custom:
    - name: "OpenAI via Copilot"
      apiKey: "your_super_token"
      baseURL: "http://[copilotgpt4service_host_ip]:8080/v1"
      models:
        default: ["gpt-4", "gpt-3.5-turbo"] # *See Notes
      titleConvo: true
      titleModel: "gpt-3.5-turbo"
      summarize: true
      summaryModel: "gpt-3.5-turbo"
      forcePrompt: false
      modelDisplayLabel: "OpenAI"
      dropParams: ["user"]
```
Replace your_super_token with the token you obtained following the instructions highlighted above and [copilotgpt4service_host_ip] with the IP of your Docker host. * See Notes *

Restart Librechat after adding the needed configuration, and select OpenAI via Copilot to start using!

Notes: - Only allowed models are gpt-4 and gpt-3.5-turbo . - *Advanced users can add this to their existing docker-compose file/existing docker network and avoid having to expose port 8080 (or any port) to the copilot-gpt4-service container.

Conclusion

That's it! You're all set. 🎉

⚠️ Note: If you're having trouble, before creating a new issue, please search for similar ones on our #issues thread on our discord or our troubleshooting discussion on our Discussions page. If you don't find a relevant issue, feel free to create a new one and provide as much detail as possible.