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
You can install openai-gradio
directly using pip:
pip install openai-gradio
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!
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()
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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