import gradio as gr
import matplotlib.pyplot as plt
import json
import tempfile
import os

from backend_app import analyzer  # your original MedicalReportAnalyzer instance

def process_single_report(file):
    result = analyzer.process_user_report(file.name)
    if result['status'] != 'success':
        return result['message'], None, None, None, None, None, None

    analysis = analyzer.generate_single_report_analysis(result['report_id'])

    suggestions = analysis['health_suggestions']
    parameters = analysis['categorized_parameters']
    abnormal_parameters = analysis['abnormal_parameters']

    vis = analysis['visualizations']

    status_chart_img = analyzer.generate_visualization_image(vis['status_chart'])
    abnormal_chart_img = analyzer.generate_visualization_image(vis['abnormal_chart']) if vis['abnormal_chart'] else None
    category_chart_img = analyzer.generate_visualization_image(vis['category_chart'])

    return (
        f"✅ Report Processed Successfully!\nAbnormal Parameters Detected: {analysis['abnormal_count']}",
        suggestions,
        status_chart_img,
        abnormal_chart_img,
        category_chart_img,
        parameters,
        abnormal_parameters
    )


def compare_multiple_reports(files):
    if not files or len(files) < 2:
        return "Please upload at least 2 reports.", None, None, None

    paths = [file.name for file in files]
    result = analyzer.process_multiple_reports(paths)

    if result['status'] != 'success':
        return result['message'], None, None, None

    comparison = analyzer.compare_reports(result['report_ids'])

    if comparison['status'] != 'success':
        return comparison['message'], None, None, None

    health_insights = comparison['health_insights']

    summary_chart_img = analyzer.generate_visualization_image(comparison['summary_chart'])

    trends_imgs = []
    for category, charts in comparison['categorized_charts'].items():
        for chart in charts:
            img = analyzer.generate_visualization_image(chart)
            trends_imgs.append((chart['title'], img))

    return (
        f"Reports Compared Successfully!\nCommon Parameters: {comparison['common_parameters_count']}",
        health_insights,
        summary_chart_img,
        trends_imgs
    )

def ask_question(question):
    if not question.strip():
        return "Please type a question."

    answer = analyzer.answer_question(question)
    return answer

with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("""
    # MediVeda Medical Report Analyzer

    Upload your medical reports to analyze health parameters, detect abnormalities, track changes, and get health advice! 
    """)

    with gr.Tab("Single Report Analysis"):
        with gr.Row():
            file_input = gr.File(label="Upload Medical Report (PDF)")
            analyze_btn = gr.Button("Analyze Report")
        output_text = gr.Markdown()
        health_suggestions = gr.Markdown(label="Health Suggestions")
        with gr.Row():
            status_chart = gr.Image()
            abnormal_chart = gr.Image()
            category_chart = gr.Image()
        with gr.Row():
            extracted_parameters = gr.JSON(label="Extracted Parameters")
            abnormalities = gr.JSON(label="Abnormal Parameters")

        analyze_btn.click(
            fn=process_single_report,
            inputs=[file_input],
            outputs=[output_text, health_suggestions, status_chart, abnormal_chart, category_chart, extracted_parameters, abnormalities]
            )

    with gr.Tab("Multiple Reports Comparison"):
        with gr.Row():
            files_input = gr.Files(label="Upload 2-3 Reports (PDF)")
            compare_btn = gr.Button("Compare Reports")
        comparison_text = gr.Markdown()
        health_insights = gr.Markdown(label="Health Insights")
        summary_chart = gr.Image()
        trend_charts_gallery = gr.Gallery(label="Parameter Trends", columns=2)

        compare_btn.click(
            fn=compare_multiple_reports,
            inputs=[files_input],
            outputs=[comparison_text, health_insights, summary_chart, trend_charts_gallery]
        )

    with gr.Tab("Ask Medical Questions"):
        question_input = gr.Textbox(label="Ask a Question", placeholder="e.g., What does a high creatinine level mean?")
        ask_btn = gr.Button("Get Answer")
        answer_output = gr.Markdown()

        ask_btn.click(
            fn=ask_question,
            inputs=[question_input],
            outputs=[answer_output]
        )

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