import gradio as gr
import pandas as pd
import numpy as np
import plotly.express as px
import re

# Fallacy Lexicon containing keywords, regex, descriptions, and plain-English corrections
FALLACY_PATTERNS = [
    {
        "name": "Ad Hominem (Personal Attack)",
        "patterns": [
            r'\b(idiot|fool|stupid|corrupt|liar|cheat|incompetent|naive|hypocrite|disgrace)\b',
            r'\b(you are|he is|she is) (unqualified|irrational|delusional)\b'
        ],
        "description": "Attacking the character or motives of a person rather than addressing their actual argument.",
        "correction": "Focus on the logic, evidence, or specific data points of the opponent's claim, not their character."
    },
    {
        "name": "Slippery Slope (Extreme Projections)",
        "patterns": [
            r'\b(inevitably lead to|slippery slope|disaster will follow|will cause the end of|road to ruin|downhill from here|avalanche of)\b',
            r'\bif we allow.*then everything.*will collapse\b'
        ],
        "description": "Claiming that a relatively small initial step will inevitably lead to a chain of disastrous events without supporting evidence.",
        "correction": "Provide empirical evidence showing a causal mechanism connecting the initial step to the final extreme outcome."
    },
    {
        "name": "False Dilemma (Either/Or)",
        "patterns": [
            r'\b(either we|either you|must choose between|no other choice|only two options|with us or against us|black or white)\b'
        ],
        "description": "Presenting only two alternative states or choices when in fact multiple middle grounds or other options exist.",
        "correction": "Acknowledge third-party options, compromise zones, or other collaborative solutions."
    },
    {
        "name": "Appeal to False Authority",
        "patterns": [
            r'\b(everyone knows|scientists agree that|as.*said once|common knowledge|unnamed sources say|trust me on this)\b'
        ],
        "description": "Claiming a statement must be true because an authority figure or 'everyone' asserts it, without citing verified evidence.",
        "correction": "Cite direct peer-reviewed academic studies, primary documents, or transparent data collections."
    },
    {
        "name": "Circular Reasoning (Begging the Question)",
        "patterns": [
            r'\b(because it is|obviously true since|by definition|self-evident|proved by the fact that it is)\b',
            r'\b(.*) is true because (\1) is true\b'
        ],
        "description": "An argument where the conclusion is already assumed in the premise, repeating the claim in different words.",
        "correction": "Introduce independent external facts, logic, or observations to support the premise."
    },
    {
        "name": "Strawman (Caricaturing Opponent)",
        "patterns": [
            r'\b(they want to destroy|their extreme goal|total ban on|completely wipe out|total elimination of|radical agenda to)\b'
        ],
        "description": "Oversimplifying, exaggerating, or misrepresenting an opponent's argument to make it easier to attack.",
        "correction": "State the opponent's argument in its strongest form (steelman) before attempting to refute it."
    }
]

def deconstruct_rhetoric(text):
    if not text.strip():
        return None, "<div style='color: #ef4444;'>Please paste debate transcripts or editorials.</div>", ""
        
    text_lower = text.lower()
    highlighted_text = text
    fallacies_found = []
    
    # Track statistics
    summary_counts = {item["name"]: 0 for item in FALLACY_PATTERNS}
    
    # Process each pattern
    for fallacy in FALLACY_PATTERNS:
        name = fallacy["name"]
        desc = fallacy["description"]
        corr = fallacy["correction"]
        
        for pat in fallacy["patterns"]:
            matches = list(re.finditer(pat, text_lower, re.IGNORECASE))
            if matches:
                summary_counts[name] += len(matches)
                for m in matches:
                    matched_str = m.group(0)
                    fallacies_found.append({
                        "Rhetorical Indicator": matched_str,
                        "Fallacy Category": name,
                        "Logic Description": desc,
                        "Constructive Correction": corr
                    })
                    
    # Generate highlighted HTML (using span wraps)
    # To prevent nested replacement bugs, we replace with placeholders and substitute at the end
    replacements = {}
    for idx, item in enumerate(fallacies_found):
        indicator = item["Rhetorical Indicator"]
        placeholder = f"___PLACEHOLDER_{idx}___"
        # Case insensitive substitution (first occurrence)
        pattern = re.compile(r'\b' + re.escape(indicator) + r'\b', re.IGNORECASE)
        highlighted_text, count = pattern.subn(placeholder, highlighted_text, 1)
        if count > 0:
            replacements[placeholder] = f'<span style="background-color: rgba(239, 68, 68, 0.25); border-bottom: 2px solid #ef4444; color: #f87171; padding: 2px 4px; border-radius: 4px; font-weight: 500;" title="{item["Fallacy Category"]}">{indicator}</span>'
            
    for placeholder, span in replacements.items():
        highlighted_text = highlighted_text.replace(placeholder, span)
        
    # Generate stats Plotly Chart
    df_counts = pd.DataFrame({
        "Fallacy Category": list(summary_counts.keys()),
        "Count": list(summary_counts.values())
    })
    
    fig = px.bar(
        df_counts[df_counts["Count"] > 0],
        x="Count",
        y="Fallacy Category",
        orientation="h",
        color="Fallacy Category",
        template="plotly_dark",
        title="Detected Rhetorical Fallacy Counts"
    )
    fig.update_layout(showlegend=False, paper_bgcolor='rgba(0,0,0,0)', plot_bgcolor='rgba(0,0,0,0)', font_family="Inter")
    
    # Generate deconstructed warnings table
    warnings_html = ""
    if fallacies_found:
        df_fallacies = pd.DataFrame(fallacies_found)
        table_html = df_fallacies.to_html(classes="styled-table", index=False)
        warnings_html = f"""
        <style>
            .styled-table {{ width: 100%; border-collapse: collapse; font-family: 'Inter', sans-serif; font-size: 13px; color: #cbd5e1; background: #0f172a; border-radius: 8px; overflow: hidden; border: 1px solid #334155; }}
            .styled-table th {{ background: #1e293b; color: #94a3b8; font-weight: 600; padding: 10px; text-align: left; border-bottom: 2px solid #334155; }}
            .styled-table td {{ padding: 8px 10px; border-bottom: 1px solid #1e293b; }}
            .styled-table tr:hover td {{ background: #1e293b; }}
        </style>
        <div style="overflow-x: auto;">
            {table_html}
        </div>
        """
    else:
        warnings_html = "<div style='color: #10b981; font-weight: 600; padding: 1.5rem; background: rgba(16, 185, 129, 0.1); border-radius: 8px; border: 1px solid #10b981; text-align: center;'>🎉 Clean Argument Scorecard! No major fallacious connectors detected in this text.</div>"
        
    highlighted_container = f"""
    <div style="background: #0f172a; border: 1px solid #334155; border-radius: 8px; padding: 1.5rem; max-height: 400px; overflow-y: auto; color: #e2e8f0; line-height: 1.6; font-size: 14px;">
        {highlighted_text}
    </div>
    """
    
    return fig, highlighted_container, warnings_html

# Premium styling
custom_css = """
body, .gradio-container { background-color: #0b0f19 !important; font-family: 'Inter', sans-serif !important; }
h1, h2, h3 { color: #f8fafc !important; }
.gr-button-primary { background: linear-gradient(135deg, #ef4444 0%, #b91c1c 100%) !important; border: none !important; }
"""

with gr.Blocks(theme=gr.themes.Soft(primary_hue="red", secondary_hue="slate"), css=custom_css) as demo:
    gr.HTML("""
    <div style="text-align: center; margin-bottom: 2rem; border-bottom: 1px solid #1e293b; padding-bottom: 1.5rem;">
        <h1 style="font-size: 2.2rem; font-weight: 800; background: linear-gradient(135deg, #f87171 0%, #ef4444 100%); -webkit-background-clip: text; -webkit-text-fill-color: transparent;">⚖️ Argument Fallacy Mapper & Rhetoric Deconstructor</h1>
        <p style="color: #94a3b8; font-size: 1.1rem; margin-top: 0.5rem;">Scan speeches, debate transcripts, and editorials for logical fallacies and receive constructive reasoning suggestions.</p>
    </div>
    """)
    
    with gr.Row():
        with gr.Column(scale=1):
            gr.Markdown("### 📜 Paste Speech / Debate Transcript")
            text_input = gr.Textbox(
                label="Argument Text", 
                placeholder="Paste speech copy here...", 
                lines=12
            )
            audit_btn = gr.Button("🔍 Deconstruct Arguments", variant="primary")
            
        with gr.Column(scale=1):
            gr.Markdown("### 📊 Fallacy Incidence Breakdown")
            chart_output = gr.Plot()
            
    gr.Markdown("### 🎨 Annotated Rhetorical Passage Visualizer")
    highlighted_output = gr.HTML("<div style='color: #64748b;'>Submit text to analyze and highlight fallacious reasoning.</div>")
    
    gr.Markdown("### ⚡ Deconstructed Logic & Constructive Recommendations")
    warnings_output = gr.HTML("<div style='color: #64748b;'>Scorecard grid will render here.</div>")
    
    audit_btn.click(
        fn=deconstruct_rhetoric,
        inputs=[text_input],
        outputs=[chart_output, highlighted_output, warnings_output]
    )

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