Gradio is an open-source python library for building interactive web applications to showcase machine learning models, APIs, and python functions. The sambanova-gradio package extends Gradio’s capabilities by simplifying SambaNova model integration. It provides a user-friendly interface for developers to connect SambaNova models to their applications.

The sambanova-gradio package has two dependencies: OpenAI and Gradio. It streamlines the setup process with a built-in registry function, sambanova_gradio.registry, which facilitates seamless connections to various models. The registry function accepts a model ID as the name parameter. Executing the script automatically generates an application interface using the specified model.;

For implementation details and additional configurations, see the Github repository.

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Installation

Follow these steps to integrate SambaNova models with Gradio.

pip install sambanova-gradio

export SAMBANOVA_API_KEY=<your token>

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Create a Gradio interface

Use the sambanova_gradio.registry function to build and launch your Gradio application, as shown below.

import gradio as gr
import sambanova_gradio

gr.load(
    name='Meta-Llama-3.1-405B-Instruct',
    src=sambanova_gradio.registry,
).launch()

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Customize your interface

You can personalize the interface by modifying the model, input/output components, and additional settings to gr.Interface, as shown below.

import gradio as gr
import sambanova_gradio

gr.load(
    name='Meta-Llama-3.1-405B-Instruct',
    src=sambanova_gradio.registry,
    title='Sambanova-Gradio Integration',
    description="Chat with Meta-Llama-3.1-405B-Instruct model.",
    examples=["Explain quantum gravity to a 5-year old.", "How many R are there in the word Strawberry?"]
).launch()

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Example screenshot

The following interface was generated using the above code snippet.

See more examples of Gradio applications in our SambaNova HuggingFace space.