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A Python package for creating Gradio applications with OpenAI models

Project description

openai-gradio

is a Python package that makes it very easy for developers to create machine learning apps that are powered by OpenAI's API.

Installation

  1. Clone this repo: git clone https://github.com/AK391/openai-gradio.git
  2. Navigate into the folder that you cloned this repo into: cd openai-gradio
  3. Install this package: pip install -e .

That's it!

Basic Usage

Just like if you were to use the openai API, you should first save your OpenAI API key to this environment variable:

export OPENAI_API_KEY=<your token>

Then in a Python file, write:

import gradio as gr
import openai_gradio

gr.load(
    name='gpt-4-turbo',
    src=openai_gradio.registry,
).launch()

Run the Python file, and you should see a Gradio Interface connected to the model on OpenAI!

ChatInterface

Customization

Once you can create a Gradio UI from an OpenAI endpoint, you can customize it by setting your own input and output components, or any other arguments to gr.Interface. For example, the screenshot below was generated with:

import gradio as gr
import openai_gradio

gr.load(
    name='gpt-4-turbo',
    src=openai_gradio.registry,
    title='OpenAI-Gradio Integration',
    description="Chat with GPT-4-turbo model.",
    examples=["Explain quantum gravity to a 5-year old.", "How many R are there in the word Strawberry?"]
).launch()

ChatInterface with customizations

Composition

Or use your loaded Interface within larger Gradio Web UIs, e.g.

import gradio as gr
import openai_gradio

with gr.Blocks() as demo:
    with gr.Tab("GPT-4-turbo"):
        gr.load('gpt-4-turbo', src=openai_gradio.registry)
    with gr.Tab("GPT-3.5-turbo"):
        gr.load('gpt-3.5-turbo', src=openai_gradio.registry)

demo.launch()

Under the Hood

The openai-gradio Python library has two dependencies: openai and gradio. It defines a "registry" function openai_gradio.registry, which takes in a model name and returns a Gradio app.

Supported Models in OpenAI

Model Context Length Output Length Dtype / Precision
gpt-4-turbo 128000 Varies -
gpt-3.5-turbo 4096 Varies -
gpt-3.5-turbo-16k 16384 Varies -
gpt-4 8192 Varies -
gpt-4-32k 32768 Varies -

Note: if you are getting a 401 authentication error, then the OpenAI API Client is not able to get the API token from the environment variable. This happened to me as well, in which case save it in your Python session, like this:

import os

os.environ["OPENAI_API_KEY"] = ...

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