OpenAI WebUI

Latest version: 0.9.7 (20240718)

• 1. Description
  • 1.1. Supported models
  • 1.2. .env
  • 1.3. savedir
  • 1.4. password protecting the WebUI
• 2. Setup
  • 2.1. Python virtualenv
  • 2.2. Docker/Podman
  • 2.3. Docker compose
  • 2.4. Unraid
• 3. Misc
  • 3.1. Notes
  • 3.2. Version information/Changelog
  • 3.3. Acknowledgments

WebUI (streamlit-based) to ChatGPT and Dall-E's API (requires an OpenAI API key).

The tool's purpose is to enable a company to install a self-hosted version of a WebUI to access the capabilities of OpenAI's ChatGPT and DallE and share access to the tool's capabilities while consolidating billing through the OpenAI API key. Access to models is limited to those enabled with your API key.

Click on the links to see a screenshot of the GPT WebUI and the DallE WebUI.

Please see https://github.com/Infotrend-Inc/OpenAI_WebUI/blob/main/.env.example for details of possible values for the environment variables. Unless specified, even if a feature is not used, its environment variable should be set.

A pre-built container is available from our Docker account at https://hub.docker.com/r/infotrend/openai_webui

An Unraid-ready version is available directly from Unraid's `Community Applications``.

Note: this tool was initially developed in February 2023 and released to help end-users.

1. Description

The tool provides a WebUI to ChatGPT and Dall-E (that later one can be disabled).

The tool requires the use of an OpenAI API key to work. Check at https://platform.openai.com/account/api-keys to find yours.

Depending on your deployment solution (python virtualenv, docker image, or unraid), the deployment might differ slightly.

Once started, the WebUI will prompt the end user with a username. This username is here to make finding past conversations/images easier if you seek those; no authentication is associated with it.

ChatGPT (Text Generation) sidebar options (see "?" mark for specific details):

• model: choose between the different ChatGPT models that are enabled.
• role (user, system, assistant): define the role of the input text for tailored responses.
• max tokens: controls the length of generated text with a maximum token setting (dependent on the model)
• temperature: adjust the "surprisingness" of the generated text.

DALL-E (Image Generation) sidebar options (see "?" for specific details):

• mode: "image" for the time being.
• model: choose between the different DallE models that are enabled.
• image Size: specify the dimensions of the images to be generated.
• number of images (model dependent): number of images to generate
• quality (model dependent): fine-tune image quality to meet your requirements.
• style (model dependent): style of the generated images.

1.1. Supported models

We have added means to inform the end-user when a model is deprecated, legacy or current.

• deprecated models are not available for use anymore.
• legacy models will be deprecated at a specified date.
• current models are available.

The tool will automatically discard known (per the release) deprecated models and inform the end user. Similarly, the tool will note when a model is legacy. Please update your model selection accordingly.

The models.json file contains the list of models supported by each release (as introduced in v0.9.3). The following table shows the models listed in this file as well as the release it was added to:

Mode	Model	Status	Capability	Notes	From
DallE	dalle-e-2	active			0.9.3
DallE	dalle-e-3	active			0.9.3
GPT	gpt-3.5-turbo	active			0.9.3
GPT	gpt-3.5-turbo-0125	active			0.9.3
GPT	gpt-3.5-turbo-0613	deprecated		Deprecated on June 13, 2024	0.9.3
GPT	gpt-3.5-turbo-1106	active			0.9.3
GPT	gpt-3.5-turbo-16k	deprecated		Deprecated on June 13, 2024	0.9.3
GPT	gpt-3.5-turbo-16k-0613	deprecated		Deprecated on June 13, 2024	0.9.3
GPT	gpt-4	active			0.9.3
GPT	gpt-4-0125-preview	active			0.9.3
GPT	gpt-4-0613	active			0.9.3
GPT	gpt-4-1106-preview	active			0.9.3
GPT	gpt-4-32k	deprecated			0.9.3
GPT	gpt-4-32k-0613	deprecated			0.9.3
GPT	gpt-4-turbo-preview	active			0.9.3
GPT	gpt-4-turbo	active	vision		0.9.5
GPT	gpt-4-turbo-2024-04-09	active	vision		0.9.5
GPT	gpt-4o	active	vision		0.9.4
GPT	gpt-4o-2024-05-13	active	vision		0.9.4
GPT	gpt-4o-mini	active	vision		0.9.7
GPT	gpt-4o-mini-2024-07-18	active	vision		0.9.7

Once a model is deprecated, using it in your models list will have it discarded from the available list with a notification.

Similarly, if a used model is listed as legacy, a notification of the upcoming deprecation will be shown in the UI.

1.2. .env

The .env.example file contains the parameters needed to pass to the running tool:

• OPENAI_API_KEY as obtained from https://platform.openai.com/account/api-keys
• OAIWUI_SAVEDIR, the location to save content (make sure the directory exists)
• OAIWUI_GPT_ONLY, to request only to show the GPT tab otherwise, shows both GPT and DallE (authorized value: True or False)
• OAIWUI_GPT_MODELS is a comma-separated list of GPT model(s) your API key is authorized to use. See https://platform.openai.com/docs/api-reference/making-requests for more information.
• OAIWUI_DALLE_MODELS is a comma-separated list of DallE model(s) your API key is authorized to use.
• OAIWUI_USERNAME (optional) specifies a username and avoids being prompted at each re-run. The default mode is to run in multi-user settings so this is not enabled by default.
• OAIWUI_GPT_VISION will, for compatible models, disable their vision capabilities

Those values can be passed by making a .env file containing the expected values or using environment variables.

The .env file is not copied into the docker or unraid setup. Environment variables should be used in this case.

1.3. savedir

The OAIWUI_SAVEDIR variable specifies the location where persistent files will be created from run to run.

Its structure is: savedir/version/username/mode/UTCtime/<CONTENT>, with:

• username being the self-specified user name prompted when starting the WebUI
• version the tool's version, making it easier to debug
• mode on of gpt or dalle
• the UTCtime, a YYYYY-MM-DD T HH:MM:SS Z UTC-time of the request (the directory's content will be time ordered)
• <CONTENT> is often a json file containing the details of the run for gpt, but also the different png images generated for dalle

We do not check the directories for size. It is left to the end user to clean up space if required.

1.4. password protecting the WebUI

To do this, create a .streamlit/secrets.toml file in the directory where the streamlit app is started (for the python virtualenv setup, this should be the directory where this README.md is present, while for other deployment methods, please see the corresponding setup section) and add a password = "SET_YOUR_PASSWORD_HERE" value to it.

When the WebUI starts, it will see of secrets.toml file and challenge users for the password set within.

2. Setup

2.1. Python virtualenv

This mode is for use if you have python3 installed and want to test the tool.

1. Create and activate your virtual environment

   $ python3 -m venv venv
   $ source venv/bin/activate

2. Install the requirements within our activated virtual environment

   $ pip install -U pip
   $ pip3 install --trusted-host pypi.org --trusted-host files.pythonhosted.org -r requirements.txt

3. Copy the default .env.example file as .env, and manually edit the copy to add your OpenAI API key and the preferred save directory (which must exist before starting the program). You can also configure the GPT models you can access with ChatGPT and disable the UI for Dall-E if preferred. Do not distribute that file.

   $ cp .env.example .env
   $ code .env

4. For developers, edit the code as you would, and when you are ready to test, start the WebUI.

   $ streamlit run ./OpenAI_WebUI.py --server.port=8501 --server.address=127.0.0.1 --logger.level=debug

5. You can now open your browser to http://127.0.0.1:8501 to test the WebUI.

2.2. Docker/Podman

The container build is an excellent way to test in an isolated, easily redeployed environment.

This setup prefers the use of environment variable, using docker run ... -e VAR=val

1. Build the container

   $ make build_main

2. Run the built container, here specifying your OAIWUI_SAVEDIR to be /iti, which will be mounted from the current working directory's savedir and mounted to /iti within the container:

   $ docker run --rm -it -p 8501:8501 -v `pwd`/savedir:/iti -e OPENAI_API_KEY="Your_OpenAI_API_Key" -e OAIWUI_SAVEDIR=/iti -e OAIWUI_GPT_ONLY=False -e OAIWUI_GPT_MODELS="gpt-3.5-turbo,gpt-4" -e OAIWUI_DALLE_MODELS="dall-e-2,dall-e-3" openai_webui:latest

If you want to use the password protection for the WebUI, create and populate the .streamlit/secrets.toml file before you start the container (see password protecting the webui) then add -v PATH_TO/secrets.toml:/app/.streamlit/secrets.toml:ro to your command line (adapting PATH_TO with the full path location of the secrets file)

You can have the Makefile delete locally built containers:

$ make delete_main

2.3. Docker compose

To run the built or downloaded container using docker compose, decide on the directory where you want the compose.yaml to be, and place the following as the content of the file:

services:
  openai_webui:
    image: infotrend/openai_webui:latest
    container_name: openai_webui
    restart: unless-stopped
    volumes:
      - ./savedir:/iti
      # Uncomment the following and create a secrets.toml in the directory where this compose.yaml file is to password protect access to the application
      # - ./secrets.toml:/app/.streamlit/secrets.toml:ro
    ports:
      # host port:container port
      - 8501:8501
    environment:
      - OPENAI_API_KEY=${OPENAI_API_KEY}
      - OAIWUI_SAVEDIR=/iti
      # Adapt the following as best suits your deployment
      - OAIWUI_GPT_ONLY=False
      - OAIWUI_GPT_MODELS=gpt-4o
      - OAIWUI_GPT_VISION=True
      # Even if OAIWUI_GPT_ONLY is True, please set a model, it will be ignored
      - OAIWUI_DALLE_MODELS=dall-e-3
      # Uncomment and enter a value if you are using a single user deployment
      # - OAIWUI_USERNAME=user

In the directory where the compose.yaml is located, create a savedir directory (it will be mounted as /iti within the running container), and create a .env file that needs only contain the OPENAI_API_KEY=value entry. If using a secrets.toml file with a password=WEBUIPASSWORD content, uncomment the entry in the compose.yaml file.

As configured, the container will restart unless-stopped which also means that unless the container is stopped it will automatically restart after a host reboot.

Run using docker compose up -d

The WebUI will be accessible on port 8501 of your host.

2.4. Unraid

For Unraid users, a special build mode is available to get a container using unraid's preferred uid/gid, use make build_unraid to build it.

The pre-built container has been added to Unraid's Community Applications.

The configuration file contains many of the possible environment variables, as detailed in the .env section. Omitted from the configuration files are:

• a Variable named OAIWUI_USERNAME whose value will set a default username. The edited XML file would add a line similar to (adapting the username accordingly):

  <Config Name="OAIWUI_USERNAME" Target="OAIWUI_USERNAME" Default="username" Mode="" Description="Automatically use a default user" Type="Variable" Display="always" Required="false" Mask="false">username</Config>
  

• a Path mapping a secrets.toml file to the /app/.streamlit/secrets.toml location within the running docker container (read-only recommended). Before setting this, create and populate a file with the expected value (as described in password protecting the WebUI). For example, if your appdata location for the OpenAI WebUI was /mnt/user/appdata/openai_webui in which you placed the needed secrets.toml file, the expected XML addition would look similar to:

  <Config Name="/app/.streamlit/secrets.toml" Target="/app/.streamlit/secrets.toml" Default="/mnt/user/appdata/openai_webui/secrets.toml" Mode="ro" Description="WebUI password protection -- secrets.toml file must exist with a password variable" Type="Path" Display="always" Required="false" Mask="false">/mnt/user/appdata/openai_webui/secrets.toml</Config>
  

3. Misc

3.1. Notes

• If you run into an error when starting the tool. Clear the streamlit cache (right side menu) or deleting cookies should solve this.

3.2. Version information/Changelog

• v0.9.7 (20240718): Added gpt-4o-mini and deprecated older 32k models
• v0.9.6 (20240701): Added method to disable vision for capable models + added whole WebUI password protection using streamlit's secrets.toml method
• v0.9.5 (20240611): Added support for vision in capable models + Added gpt-4-turbo models + Deprecated some models in advance of 20240613 + Updated openai python package to 1.33.0 + Decoupled UI code to allow support for different frontends.
• v0.9.4 (20240513): Added support for gpt-4o, updated openai python package to 1.29.0
• v0.9.3 (20240306): Simplifying integration of new models and handling/presentation of their status (active, legacy, deprecated) + Cleaner handling of max_tokens vs context window tokens + updated openai python package to 1.13.3
• v0.9.2 (20241218): Keep prompt history for a given session + allow user to review/delete past prompts + updated openai python package: 1.8.0
• v0.9.1 (20231120): Print streamlit errors in case of errors with environment variables + Addition of gpt-3.5-turbo-1106 in the list of supported models (added in openai python package 1.3.0) + added optional OAIWUI_USERNAME environment variable
• v0.9.0 (20231108): Initial release -- incorporating modifications brought by the latest OpenAI Python package (tested against 1.2.0)
• Oct 2023: Preparation for public release
• Feb 2023: Initial version

3.3. Acknowledgments

This project includes contributions from Yan Ding and Muhammed Virk in March 2023.