# ---------------- APP ----------------
# This is the main file to run the Gradio application.
# It imports logic from logic.py and configuration from config.py

import gradio as gr

# Import constants needed for the UI
from config import CRISIS_PERIODS, EXAMPLE_PORTFOLIOS, CRISIS_SUMMARY

# Import the main simulation function
from logic import run_crisis_simulation

# --- UI Helper Functions ---

def load_example(example_name):
    """Updates ticker and weight textboxes based on selection."""
    portfolio = EXAMPLE_PORTFOLIOS.get(example_name, {"tickers": "", "weights": ""})
    return gr.update(value=portfolio["tickers"]), gr.update(value=portfolio["weights"])

def update_crisis_summary(crisis_name):
    """Updates the crisis summary text when a crisis is selected."""
    summary = CRISIS_SUMMARY.get(crisis_name, "")
    if summary:
        return f"**Crisis summary:** _{summary}_"
    return ""

# ---------------- UI DEFINITION ----------------

with gr.Blocks(title="Crisis Lens (India)") as demo:

    gr.Markdown(
        """
        # 🇮🇳 Crisis Lens — Indian Stock Stress Simulator
        How would your portfolio have performed during a major market crisis? 
        Select a historical crisis and your portfolio to find out.
        """
    )
    
    with gr.Row():
        with gr.Column(scale=2):
            crisis_dd = gr.Dropdown(
                list(CRISIS_PERIODS.keys()),
                label="Select Crisis",
                value="COVID-19 Crash (India)",
            )
            crisis_info = gr.Markdown(
                f"**Crisis summary:** _{CRISIS_SUMMARY['COVID-19 Crash (India)']}_",
                elem_classes="crisis-summary",
            )
        with gr.Column(scale=1):
            example_loader_dd = gr.Dropdown(
                list(EXAMPLE_PORTFOLIOS.keys()), 
                label="Load Example Portfolio", 
                value="Select Example...",  # will be overridden by .load()
            )

    with gr.Row():
        with gr.Column(scale=1):
            gr.Markdown("### 1. Define Your Portfolio")
            upload_csv = gr.File(
                label="Upload Portfolio CSV (Ticker,Weight)",
                file_types=[".csv"]
            )
            gr.Markdown("...or enter manually below:")
            
            tickers_input = gr.Textbox(
                label="Tickers (comma separated)",
                value=""
            )
            weights_input = gr.Textbox(
                label="Weights (comma separated)",
                value=""
            )
            
            add_etf_cb = gr.Checkbox(
                label="Add 5% NIFTYBEES.NS to portfolio (diversify)",
                value=False
            )

            gr.Markdown("---")
            gr.Markdown("### 🤖 2. AI Insights (Optional)")
            gemini_api_key_in = gr.Textbox(
                label="Gemini API Key (optional, not stored)",
                placeholder="Paste your Gemini API key here to get AI-generated insights",
                type="password",
            )
            gemini_extra_prompt_in = gr.Textbox(
                label="Extra instructions for AI (optional)",
                placeholder="e.g., Focus more on risk, or write in simple language, etc.",
                lines=2,
            )

            gr.Markdown("---")
            run_btn = gr.Button("Run Simulation", variant="primary")
            logs_txt = gr.Textbox(label="Status / Logs", interactive=False)

        with gr.Column(scale=3):
            gr.Markdown("### 3. Analyze the Results")
            plot_performance = gr.Plot()
            with gr.Row():
                metrics_output = gr.Markdown()
                pie_chart = gr.Plot()
            with gr.Row():
                sector_plot_output = gr.Plot()
                insights_output = gr.Markdown()

            gr.Markdown("### 🤖 AI-Generated Insights")
            gemini_insights_md = gr.Markdown(
                value="*AI insights will appear here after running simulation with a Gemini API key.*"
            )

    # ---------------- EVENT HANDLERS ----------------
    
    crisis_dd.change(
        fn=update_crisis_summary,
        inputs=[crisis_dd],
        outputs=[crisis_info],
    )
    
    example_loader_dd.change(
        fn=load_example,
        inputs=[example_loader_dd],
        outputs=[tickers_input, weights_input],
    )

    run_btn.click(
        run_crisis_simulation,
        inputs=[
            crisis_dd,
            upload_csv,
            tickers_input,
            weights_input,
            add_etf_cb,
            gemini_api_key_in,
            gemini_extra_prompt_in,
        ],
        outputs=[
            plot_performance,
            metrics_output,
            sector_plot_output,
            insights_output,
            pie_chart,
            logs_txt,
            gemini_insights_md,
        ],
    )
    
    def load_default_example():
        default_name = "Large-Cap (Default)"
        portfolio = EXAMPLE_PORTFOLIOS.get(default_name, {"tickers": "", "weights": ""})
        summary = CRISIS_SUMMARY.get("COVID-19 Crash (India)", "")
        return (
            gr.update(value=default_name),
            gr.update(value=portfolio["tickers"]),
            gr.update(value=portfolio["weights"]),
            f"**Crisis summary:** _{summary}_",
        )

    demo.load(
        fn=load_default_example,
        inputs=None,
        outputs=[example_loader_dd, tickers_input, weights_input, crisis_info],
    )


# ---------------- LAUNCH ----------------

if __name__ == "__main__":
    demo.launch(share=True, debug=True)