import gradio as gr
import pandas as pd
import time

# --- 1. Compliance Simulator Logic ---

def compliance_check(investor_country, accreditation_status, investment_amount):
    """
    Simulates the Kancil L1's native Compliance Engine pre-compile check.
    Compliance rules are hardcoded for demonstration purposes.
    """
    time.sleep(1) # Simulate network latency

    # Rule 1: Must be an accredited investor for high-value RWA
    if accreditation_status != "Accredited Investor":
        return f"❌ **Transaction Rejected**\n\nReason: Investor status '{accreditation_status}' does not meet the minimum requirement of 'Accredited Investor' for this RWA token. Compliance enforced at L1 protocol level."

    # Rule 2: Geo-fencing (e.g., cannot invest from a sanctioned country)
    if investor_country in ["North Korea", "Iran", "Syria"]:
        return f"❌ **Transaction Rejected**\n\nReason: Investor country '{investor_country}' is on the network's restricted list. Compliance enforced at L1 protocol level."

    # Rule 3: Minimum investment threshold
    if investment_amount < 10000:
        return f"❌ **Transaction Rejected**\n\nReason: Investment amount (${investment_amount:,.2f}) is below the minimum required threshold of $10,000. Compliance enforced at L1 protocol level."

    # If all checks pass
    return f"✅ **Transaction Approved**\n\nCompliance Engine Pre-Compile Check Passed. Token transfer is authorized."

# --- 2. DAO Voting Mockup Logic ---

# Initial state of the DAO proposal
dao_proposal = {
    "title": "K-DAO Proposal 001: Approve Tokenization of Dubai Office Tower (Asset ID: DXB-CRE-001)",
    "description": "Proposal to onboard a $50M Commercial Real Estate asset located in the Dubai International Financial Centre (DIFC).",
    "yes_votes": 1500000,
    "no_votes": 500000,
    "quorum": 2000000,
    "status": "Active",
    "end_date": "2026-01-31"
}

# Mock function to update the vote count
def cast_vote(vote_type, voting_power):
    global dao_proposal
    if dao_proposal["status"] != "Active":
        return "Voting is closed."

    try:
        power = int(voting_power)
    except ValueError:
        return "Invalid voting power. Please enter a number."

    if vote_type == "Yes":
        dao_proposal["yes_votes"] += power
    elif vote_type == "No":
        dao_proposal["no_votes"] += power

    # Check if quorum is met
    total_votes = dao_proposal["yes_votes"] + dao_proposal["no_votes"]
    if total_votes >= dao_proposal["quorum"]:
        dao_proposal["status"] = "Passed" if dao_proposal["yes_votes"] > dao_proposal["no_votes"] else "Failed"

    return display_dao_status()

# Function to display the current DAO status
def display_dao_status():
    total_votes = dao_proposal["yes_votes"] + dao_proposal["no_votes"]
    progress = (total_votes / dao_proposal["quorum"]) * 100
    
    status_text = f"""
    **Proposal:** {dao_proposal['title']}
    **Status:** {dao_proposal['status']}
    **Quorum Required:** {dao_proposal['quorum']:,} $KANCIL
    **Total Votes Cast:** {total_votes:,} $KANCIL
    **Yes Votes:** {dao_proposal['yes_votes']:,} $KANCIL
    **No Votes:** {dao_proposal['no_votes']:,} $KANCIL
    **Voting Ends:** {dao_proposal['end_date']}
    """
    return status_text

# --- 3. Asset Dashboard Mockup (Static) ---

asset_data = {
    "Metric": ["Asset ID", "Asset Type", "Location", "Total Value Tokenized", "Tokens Issued", "Compliance Status", "Last Income Distribution"],
    "Value": ["DXB-CRE-001", "Commercial Real Estate (Office)", "Dubai, UAE", "$50,000,000", "50,000,000", "Fully Compliant (Kancil L1 Enforced)", "2025-12-01 (Automated by Smart Contract)"]
}
asset_df = pd.DataFrame(asset_data)

# --- Gradio Interface Setup ---

# Compliance Simulator Tab
compliance_tab = gr.Interface(
    fn=compliance_check,
    inputs=[
        gr.Dropdown(["USA", "UAE", "Singapore", "Germany", "UK", "Japan"], label="Investor Country (Simulated Geo-Fencing)"),
        gr.Dropdown(["Accredited Investor", "Non-Accredited Investor", "Institutional Investor"], label="Accreditation Status (Simulated Whitelist)"),
        gr.Slider(minimum=1000, maximum=100000, step=1000, value=10000, label="Investment Amount (Simulated Threshold)")
    ],
    outputs=gr.Markdown(label="Kancil L1 Compliance Engine Result"),
    title="Kancil L1 Compliance Simulator",
    description="Demonstrates the L1's native pre-compile for enforcing RWA compliance rules before a transaction is executed."
)

# DAO Voting Tab
dao_status_output = gr.Markdown(value=display_dao_status())

dao_tab = gr.Interface(
    fn=cast_vote,
    inputs=[
        gr.Radio(["Yes", "No"], label="Your Vote"),
        gr.Number(label="Your Voting Power ($KANCIL)", value=1000)
    ],
    outputs=dao_status_output,
    title="Kancil Asset Management DAO (K-DAO) Mockup",
    description="Simulates the decentralized governance process for approving new assets and network changes."
)

# Asset Dashboard Tab
with gr.Blocks() as asset_tab:
    gr.Markdown("## Tokenized Asset Dashboard (Static Mockup)")
    gr.Markdown("A static view of a tokenized asset, showing the data transparency and visual representation enabled by the Kancil L1.")
    
    # FIX: Removed type="filepath" and relied on Gradio's static file serving for the value.
    # This avoids the internal file-moving logic that caused the NotADirectoryError.
    gr.Image(label="Tokenized Asset Visual (DXB-CRE-001)", value="assets/cre_exterior.png")
    gr.Dataframe(value=asset_df, label="Asset Metadata")


# Combine all tabs
demo = gr.TabbedInterface(
    [compliance_tab, dao_tab, asset_tab],
    ["Compliance Simulator", "K-DAO Voting", "Asset Dashboard"],
    title="Kancil: Autonomous RWA L1 MVP(Demo)"
)

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