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Update rag/ui.py
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rag/ui.py
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import gradio as gr
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def build_demo(retrieve_and_answer):
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"""
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Build the Gradio interface for the Financial RAG demo.
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The UI is intentionally minimal and technical, focusing on
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transparency of sources and system behavior rather than aesthetics.
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"""
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with gr.Blocks(title="Financial RAG Demo") as demo:
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gr.Markdown("# Financial RAG Demo")
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gr.Markdown(
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"Architecture: GLiNER (CPU Router) → GTE-7B (Retrieval) → Qwen2-VL (Vision Analysis)"
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)
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with gr.Row():
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query_input = gr.Textbox(
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label="User Question",
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submit_btn = gr.Button("Run Analysis", variant="primary")
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with gr.Row():
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output_gallery = gr.Gallery(
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label="Source Documents",
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columns=3,
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height=300,
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)
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output_meta = gr.Markdown(label="System Trace")
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output_text = gr.Markdown(label="Answer")
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import gradio as gr
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def build_demo(retrieve_and_answer):
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with gr.Blocks(title="Financial RAG Demo") as demo:
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gr.Markdown("# Financial RAG Demo")
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gr.Markdown(
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"Architecture: GLiNER (CPU Router) → GTE-7B (Retrieval) → Qwen2-VL (Vision Analysis)"
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)
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gr.Markdown(
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"""
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### About this demo
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- Entity-aware routing (Apple / Microsoft)
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- Explicit refusals for out-of-scope or ambiguous queries
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- Tables processed as images (no OCR flattening)
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### Try these prompts
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- `What was Apple’s total revenue in 2023?`
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- `What is Microsoft’s operating income?`
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- `Compare Apple and Microsoft revenues` → rejected or limited
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- `What was Google’s revenue in 2023?` → rejected
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ℹ️ Full details are in the Space README below (scroll) / GitHub repo.
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"""
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)
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with gr.Row():
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query_input = gr.Textbox(
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label="User Question",
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submit_btn = gr.Button("Run Analysis", variant="primary")
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with gr.Row():
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output_gallery = gr.Gallery(label="Source Documents", columns=3, height=300)
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output_meta = gr.Markdown(label="System Trace")
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output_text = gr.Markdown(label="Answer")
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