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import gradio as gr
import gemini_gradio
import openai_gradio
import anthropic_gradio
import sambanova_gradio
import xai_gradio
import hyperbolic_gradio
with gr.Blocks(fill_height=True) as demo:
with gr.Tab("Gemini"):
gr.load(
name='gemini-1.5-pro-002',
src=gemini_gradio.registry,
accept_token=True
)
with gr.Tab("ChatGPT"):
with gr.Row():
model_choice = gr.Dropdown(
choices=['gpt-4-turbo', 'gpt-4', 'gpt-3.5-turbo'],
value='gpt-4-turbo',
label="Select Model",
interactive=True
)
chatgpt_interface = gr.load(
name=model_choice.value,
src=openai_gradio.registry,
accept_token=True
)
def update_model(new_model):
return gr.load(
name=new_model,
src=openai_gradio.registry,
accept_token=True
)
model_choice.change(
fn=update_model,
inputs=[model_choice],
outputs=[chatgpt_interface]
)
with gr.Tab("Claude"):
with gr.Row():
claude_model = gr.Dropdown(
choices=['claude-3-sonnet-20240229', 'claude-3-opus-20240229'],
value='claude-3-sonnet-20240229',
label="Select Model",
interactive=True
)
claude_interface = gr.load(
name=claude_model.value,
src=anthropic_gradio.registry,
accept_token=True
)
def update_claude_model(new_model):
return gr.load(
name=new_model,
src=anthropic_gradio.registry,
accept_token=True
)
claude_model.change(
fn=update_claude_model,
inputs=[claude_model],
outputs=[claude_interface]
)
with gr.Tab("Meta Llama-3.2-90B-Vision-Instruct"):
gr.load(
name='Llama-3.2-90B-Vision-Instruct',
src=sambanova_gradio.registry,
accept_token=True,
multimodal=True,
description="Requires SambaNova API key"
)
with gr.Tab("Grok"):
gr.load(
name='grok-beta',
src=xai_gradio.registry,
accept_token=True
)
with gr.Tab("Qwen2.5 72B"):
gr.load(
name='Qwen/Qwen2.5-72B-Instruct',
src=hyperbolic_gradio.registry,
accept_token=True
)
demo.launch()
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