app.py

import gradio as gr
from services.llm_client import llm_service
from core.analyzer import PortfolioAnalyzer
from core.comparer import PortfolioComparer
from core.chat import ChatAssistant
from core.metrics import show_metrics_table
from core.visualization import build_alpha_chart

MODEL_NAME = "meta-llama/Meta-Llama-3.1-8B-Instruct"

analyzer = PortfolioAnalyzer(llm_service, MODEL_NAME)
comparer = PortfolioComparer(llm_service, MODEL_NAME)
chatbot = ChatAssistant(llm_service, MODEL_NAME)

# === Bloomberg-style dark theme ===
dark_theme = gr.themes.Base(
    primary_hue="violet",
    secondary_hue="gray",
    neutral_hue="zinc",
).set(
    body_background_fill="#0d1117",          # main background (dark navy)
    body_text_color="#e6edf3",               # main text
    block_background_fill="#161b22",         # card background
    block_border_color="#30363d",            # subtle border
    button_primary_background_fill="#4f46e5",# indigo-violet accent
    button_primary_background_fill_hover="#6366f1",
    button_primary_text_color="#ffffff",
    input_background_fill="#0d1117",
    block_shadow="0 2px 6px rgba(0,0,0,0.3)",
    block_label_text_color="#9da5b4",
    block_label_text_size="sm",
)

with gr.Blocks(theme=dark_theme, css="""
/* === Bloomberg / Dark Finance Style === */
.gradio-container {
    max-width: 1000px !important;
    margin: auto !important;
    font-family: 'Inter', sans-serif;
    background-color: #0d1117 !important;
}
/* === LLM Commentary Styling === */
#llm_comment_box textarea {
    max-height: 420px !important;   /* ограничение высоты */
    overflow-y: auto !important;    /* вертикальный скроллинг */
    background-color: #161b22 !important;
    color: #f0f6fc !important;
    border: 1px solid #30363d !important;
    border-radius: 6px !important;
    font-family: 'JetBrains Mono', monospace !important;
    font-size: 14px !important;
    line-height: 1.5 !important;
    padding: 12px !important;
}
/* === Comparison Table === */
#comparison_table {
    margin-top: 8px !important;
}

h2, h3, .gr-markdown {
    font-weight: 600;
    color: #f0f6fc !important;
}
.gr-button {
    border-radius: 6px !important;
    font-weight: 600 !important;
    letter-spacing: 0.3px;
    box-shadow: 0 2px 4px rgba(0,0,0,0.25);
}
.gr-textbox, .gr-dataframe {
    border-radius: 6px !important;
}
.gr-button.primary {
    background: linear-gradient(90deg, #6366f1, #4f46e5);
    border: none !important;
}
.gr-tab {
    background-color: #161b22 !important;
    color: #c9d1d9 !important;
}
.gr-tabs {
    border-bottom: 1px solid #30363d !important;
}
.gr-plot {
    background: #0d1117 !important;
}
/* Fix Gradio plot overlay */
#alpha_chart svg {
    display: none !important;
}
#alpha_chart .wrap {
    background: transparent !important;
    box-shadow: none !important;
}
/* === Styled comparison table === */
.gr-dataframe table {
    border-collapse: collapse !important;
    width: 100% !important;
    color: #c9d1d9 !important;
    background-color: #161b22 !important;
}
.gr-dataframe th {
    background-color: #21262d !important;
    color: #f0f6fc !important;
    font-weight: 600 !important;
    text-transform: uppercase;
    border-bottom: 1px solid #30363d !important;
}
.gr-dataframe td {
    border-top: 1px solid #30363d !important;
    padding: 8px !important;
}

""") as demo:
    gr.Markdown("## Investment Portfolio Analyzer")
    gr.Markdown(
        "A professional dashboard for analyzing and comparing investment portfolios using AI insights.",
        elem_classes="subtitle",
    )

    with gr.Tabs():
        # --- Analysis Tab ---
        with gr.TabItem("Analysis"):
            portfolio_input = gr.Textbox(
                label="Portfolio ID or Link",
                placeholder="Enter a portfolio ID (e.g. ea856c1b-...)",
                lines=1,
                value='b1ef37aa-5b9a-41b4-9394-8823f2de36bb',
            )
            analyze_button = gr.Button("Run Analysis", variant="primary")
            analyze_output = gr.Textbox(label="Analysis Result", lines=15)
            analyze_button.click(fn=analyzer.run, inputs=portfolio_input, outputs=analyze_output)

        # --- Comparison Table Tab ---
        with gr.TabItem("Comparison Table"):
            comp_input_1 = gr.Textbox(label="Portfolio A", value="3852a354-e66e-4bc5-97e9-55124e31e687")
            comp_input_2 = gr.Textbox(label="Portfolio B", value="b1ef37aa-5b9a-41b4-9394-8823f2de36bb")
            comp_button = gr.Button("Load Comparison", variant="primary")

            # комментарий теперь над таблицей
            comp_output_comment = gr.Textbox(
                label="AI Commentary",
                lines=8,
                interactive=False,
                show_copy_button=True,
                elem_id="llm_comment_box",
            )

            comp_output_table = gr.Dataframe(
                label="Comparative Metrics",
                wrap=True,
                elem_id="comparison_table",
            )

            from core.comparison_table import show_comparison_table

            comp_button.click(
                fn=show_comparison_table,
                inputs=[comp_input_1, comp_input_2],
                outputs=[comp_output_table, comp_output_comment],
            )

        # --- Chat Assistant Tab ---
        with gr.TabItem("Assistant"):
            chat_input = gr.Textbox(label="Ask about investments or analysis")
            chat_button = gr.Button("Send Question", variant="primary")
            chat_output = gr.Textbox(label="AI Response", lines=8)
            chat_button.click(fn=chatbot.run, inputs=chat_input, outputs=chat_output)

        # --- Metrics Table Tab ---
        with gr.TabItem("Metrics Table"):
            metrics_input = gr.Textbox(label="Portfolio ID", value='b1ef37aa-5b9a-41b4-9394-8823f2de36bb')
            metrics_button = gr.Button("Load Metrics", variant="primary")
            metrics_output = gr.Dataframe(label="Portfolio Metrics", wrap=True)
            metrics_button.click(fn=show_metrics_table, inputs=metrics_input, outputs=metrics_output)

        # --- AlphaBTC Chart Tab (fixed overlay) ---
        with gr.TabItem("AlphaBTC Chart"):
            chart_input = gr.Textbox(label="Portfolio ID", value="3852a354-e66e-4bc5-97e9-55124e31e687")
            chart_button = gr.Button("Generate Chart", variant="primary")
            chart_output = gr.Plot(
                label="Alpha vs BTC",
                show_label=False,
                elem_id="alpha_chart",
            )
            chart_button.click(fn=build_alpha_chart, inputs=chart_input, outputs=chart_output)

    gr.Markdown("---")
    gr.Markdown(
        "<center><small style='color:#6e7681;'>Developed with Featherless.ai • Powered by OpenAI-compatible API</small></center>",
        elem_classes="footer",
    )

if __name__ == "__main__":
    demo.launch()