import gradio as gr
from RAG_AGENT import gemini_explain_file, extract_clean_pdf_text
import os

css = """
.gradio-container {
    font-family: 'Inter', sans-serif;
    max-width: 850px !important;
    margin: auto;
    padding: 2rem;
    background-color: #121212;
    color: #e0e0e0;
}

.main-header {
    text-align: center;
    margin-bottom: 2rem;
}
.main-header h1 {
    font-size: 2.2rem;
    font-weight: 600;
    color: #ffffff;
}
.main-header p {
    font-size: 1rem;
    color: #bbbbbb;
}

.upload-area {
    border: 1px dashed #444 !important;
    border-radius: 10px !important;
    background-color: #1e1e1e !important;
    padding: 1rem;
    transition: 0.3s;
}
.upload-area:hover {
    border-color: #777 !important;
}

.btn-primary {
    background-color: #4F46E5 !important;
    color: white !important;
    border: none !important;
    padding: 12px 20px !important;
    border-radius: 8px !important;
    font-size: 1rem;
    font-weight: 500;
}
.btn-primary:hover {
    background-color: #3730A3 !important;
}

#custom-output {
    background-color: #1e1e1e;
    border-radius: 10px;
    padding: 1.5rem;
    border: 1px solid #333;
    min-height: 250px;
    font-size: 1rem;
    line-height: 1.6;
    color: #e0e0e0;
    margin-top: 2rem;
}

.footer {
    text-align: center;
    margin-top: 3rem;
    font-size: 0.85rem;
    color: #777;
}
"""

def analyze_file(file, question, analysis_type):
    if not file:
        return "⚠️ Please upload a file."

    if analysis_type == "Extract PDF Text":
        if not file.name.lower().endswith('.pdf'):
            return "⚠️ This option only works with PDF files."
        try:
            text = extract_clean_pdf_text(file.name)
            return f"**Extracted Text:**\n\n{text}"
        except Exception as e:
            return f"❌ Error: {e}"

    elif analysis_type == "AI Analysis":
        if not os.getenv('GEMINI_API_KEY'):
            return "⚠️ Gemini API key not found in environment."
        return gemini_explain_file(file, question)

    return "⚠️ Invalid analysis type."

# Gradio UI
with gr.Blocks(css=css, title="Science Analyzer - Dark UI") as demo:
    gr.HTML("""
        <div class="main-header">
            <h1>🧠 Science Analyzer</h1>
            <p>Upload scientific documents and get AI-powered analysis</p>
        </div>
    """)

    with gr.Column():
        with gr.Row():
            with gr.Column():
                file_input = gr.File(
                    label="📁 Upload File",
                    file_types=[".pdf", ".png", ".jpg", ".jpeg"],
                    file_count="single",
                    elem_classes=["upload-area"]
                )

                analysis_type = gr.Radio(
                    choices=["AI Analysis", "Extract PDF Text"],
                    value="AI Analysis",
                    label="🔍 Analysis Type"
                )

                question_input = gr.Textbox(
                    label="Ask a Question (Optional)",
                    placeholder="Type your question here...",
                    lines=2
                )

                analyze_btn = gr.Button(
                    "🚀 Analyze",
                    variant="primary",
                    elem_classes=["btn-primary"]
                )

        output_box = gr.Markdown(
            value="📄 Upload a file and click Analyze.",
            elem_id="custom-output",
            show_label=False
        )

    gr.HTML("""
        <div class="footer">
            <p>© 2025 • Built with Gradio & Gemini API</p>
        </div>
    """)

    analyze_btn.click(
        fn=analyze_file,
        inputs=[file_input, question_input, analysis_type],
        outputs=output_box
    )

    file_input.change(
        fn=lambda: "📤 File uploaded. Click 'Analyze' to begin.",
        outputs=output_box
    )

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860, share=False, show_error=True)