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import gradio as gr | |
from inference import get_evo_response, get_gpt_response | |
def advisor_interface(prompt, option1, option2): | |
evo_result = get_evo_response(prompt, option1, option2) | |
gpt_result = get_gpt_response(prompt, option1, option2) | |
return evo_result, gpt_result | |
with gr.Blocks() as demo: | |
gr.Markdown("## π§ EvoRAG β Retrieval-Augmented Adaptive AI for Reasoning") | |
gr.Markdown("Ask a commonsense or financial reasoning question with two options. Evo and GPT-3.5 will both suggest the better one.") | |
with gr.Row(): | |
prompt = gr.Textbox(label="π Your Question", placeholder="e.g. Should we reduce exposure to Tech Fund A this quarter?") | |
with gr.Row(): | |
option1 = gr.Textbox(label="πΉ Option 1", placeholder="Yes, reduce exposure this quarter.") | |
option2 = gr.Textbox(label="πΈ Option 2", placeholder="No, maintain current allocation.") | |
with gr.Row(): | |
evo_output = gr.Textbox(label="π¬ EvoRAG Suggestion") | |
gpt_output = gr.Textbox(label="π€ GPT-3.5 Suggestion") | |
run_btn = gr.Button("Run Advisors") | |
run_btn.click(fn=advisor_interface, inputs=[prompt, option1, option2], outputs=[evo_output, gpt_output]) | |
demo.launch() | |