| import gradio as gr | |
| from rag import rbc_product | |
| from tool import rival_product | |
| with gr.Blocks() as demo: | |
| with gr.Tab("RAG"): | |
| gr.Markdown(""" | |
| Marketing | |
| ------------ | |
| GraphRAG: Models customer-product relationship networks for next-best-action predictions | |
| DSPy: Optimizes cross-sell/upsell prompt variations through A/B testing | |
| Risk & Audit | |
| ------------ | |
| GraphRAG: Maps transactional relationships into dynamic knowledge graphs to detect multi-layered fraud patterns | |
| Tool Use: Integrates fraud detection APIs, anomaly scoring models, and regulatory compliance checkers | |
| DSPy: Optimizes fraud explanation prompts for regulatory reporting | |
| Other Use Case | |
| ------------ | |
| https://huggingface.co/spaces/kevinhug/clientX | |
| https://kevinwkc.github.io/davinci/ | |
| """) | |
| gr.Markdown(""" | |
| Retrieval: Public RBC Product Data | |
| Recommend: RBC Product | |
| """) | |
| in_verbatim = gr.Textbox(label="Verbatim") | |
| out_product = gr.Textbox(label="Product") | |
| gr.Examples( | |
| [ | |
| ["Low APR and great customer service. I would highly recommend if you’re looking for a great credit card company and looking to rebuild your credit. I have had my credit limit increased annually and the annual fee is very low."] | |
| ], | |
| [in_verbatim] | |
| ) | |
| btn_recommend=gr.Button("Recommend") | |
| btn_recommend.click(fn=rbc_product, inputs=in_verbatim, outputs=out_product) | |
| with gr.Tab("Tool Use"): | |
| gr.Markdown(""" | |
| Retrieval: Public Product Data using Tavily Search | |
| Recommend: Competition Product | |
| """) | |
| in_verbatim = gr.Textbox(label="Verbatim") | |
| out_product = gr.Textbox(label="Product") | |
| gr.Examples( | |
| [ | |
| ["Low APR and great customer service. I would highly recommend if you’re looking for a great credit card company and looking to rebuild your credit. I have had my credit limit increased annually and the annual fee is very low."] | |
| ], | |
| [in_verbatim] | |
| ) | |
| btn_recommend=gr.Button("Recommend") | |
| btn_recommend.click(fn=rival_product, inputs=in_verbatim, outputs=out_product) | |
| demo.launch(allowed_paths=["./xgb","./ts"]) |