init

.gradio/flagged/dataset1.csv

@@ -0,0 +1,7 @@
+Initial Base Reserve (tokens),Initial Quote Reserve (SOL),Migration Quote Threshold (SOL),Trading Fee %,Creator Fee % of Trading Fees,Partner Fee % of Trading Fees,Meteora Fee % of Trading Fees,SOL Step Size Per Trade,Base Token Decimals,Quote Token Decimals,Bonding Curve,Fee Breakdown,timestamp
+1000000,1000,5000,1,40,40,20,10,9,9,"{""type"": ""matplotlib"", ""plot"": 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""}","🧾 Trading Fee Breakdown:
+---------------------------
+Total Trading Fees Collected: 50.0000 SOL
+- Creator Fee: 20.0000 SOL
+- Partner Fee: 20.0000 SOL
+- Meteora Fee: 10.0000 SOL",2025-06-02 13:01:47.368004

app.py

@@ -0,0 +1,161 @@
+import gradio as gr
+import numpy as np
+import matplotlib.pyplot as plt
+from decimal import Decimal
+
+def simulate_full_bonding_curve_with_fees(
+    initial_market_cap_sol, migration_market_cap_sol, total_token_supply,
+    token_decimals, quote_decimals,
+    migration_fee_percent, creator_migration_fee_percent,
+    partner_lp_percentage, creator_lp_percentage,
+    partner_locked_lp_percentage, creator_locked_lp_percentage,
+    trading_fee_bps, total_trading_volume_sol
+):
+    total_trading_volume_sol = float(total_trading_volume_sol)
+    percentage_supply = Decimal(100)
+
+    migration_quote_amount = Decimal(initial_market_cap_sol) * percentage_supply / Decimal(100)
+    migration_quote_threshold = migration_quote_amount * Decimal(100) / (Decimal(100) - Decimal(migration_fee_percent))
+
+    circulating_supply = Decimal(total_token_supply) * percentage_supply / Decimal(100)
+    start_price = Decimal(initial_market_cap_sol) / circulating_supply
+    end_price = Decimal(migration_market_cap_sol) / circulating_supply
+
+    # Calculate k for the price formula P(x) = k / (C - x)^2
+    # S(x) = integral P(x)dx from 0 to x = k/(C-x) - k/C
+    # initial_market_cap_sol is the SOL value for 0 tokens sold (conceptually)
+    # For the purpose of plotting the amount of SOL raised against tokens sold:
+    # Let C = float(circulating_supply)
+    # The price at a given number of tokens sold 's' is P(s) = k / (C - s)^2
+    # The SOL raised to sell 's' tokens is Integral(P(x)dx) from 0 to s which is k/(C-s) - k/C
+    # We use migration_quote_amount as the SOL raised when 0 tokens are sold for the *start* of the curve for simplicity in k calc.
+    # This interpretation aligns k with the initial SOL amount rather than price directly.
+    C_float = float(circulating_supply)
+    if C_float == 0: # Avoid division by zero if circulating supply is zero
+        x = np.array([0])
+        prices = np.array([0])
+        x_end_plot = 0
+    else:
+        # k is derived from the initial state: initial_market_cap_sol is the SOL value for 0 tokens sold (conceptually)
+        # P(x) = k / (C-x)^2. SOL_raised(x) = k/(C-x) - k/C.
+        # if initial_market_cap_sol is S(0), then k = initial_market_cap_sol * C_float. This is wrong, initial_market_cap_sol is not S(0).
+        # initial_market_cap_sol is effectively the amount of SOL in the pool at the start for pricing calculations.
+        # Let's use the definition that migration_quote_amount (SOL before fees) is the target SOL to be in the curve before it migrates.
+        # The curve starts with some implicit SOL amount that gives start_price.
+        # Price(x) = k / (C-x)^2. So, Price(0) = k / C^2 = start_price.
+        # k = start_price * C^2
+        k = float(start_price) * (C_float**2)
+
+        if k == 0 or (float(migration_quote_threshold) + k / C_float) == 0: # Handle division by zero or k=0
+            x_end_plot = C_float # Sell all tokens if k is 0 or threshold makes denominator 0
+        else:
+            # Calculate x_end_plot: number of tokens sold to reach migration_quote_threshold SOL
+            # SOL_raised(x_end_plot) = migration_quote_threshold
+            # migration_quote_threshold = k/(C_float - x_end_plot) - k/C_float
+            # k/(C_float - x_end_plot) = migration_quote_threshold + k/C_float
+            # C_float - x_end_plot = k / (migration_quote_threshold + k/C_float)
+            x_end_plot = C_float - (k / (float(migration_quote_threshold) + k / C_float))
+            # Ensure x_end_plot is not negative or greater than C_float
+            x_end_plot = max(0, min(x_end_plot, C_float * 0.9999)) # Plot up to 99.99% to avoid infinity
+
+        if x_end_plot <= 1e-9: # If effectively no tokens are sold to reach threshold (e.g. threshold is 0)
+            x_end_plot = C_float * 0.01 # Plot a small portion to show something
+            if x_end_plot <= 1e-9: # If C_float is also tiny
+                 x_end_plot = 1 # Default to 1 token if supply is extremely small
+
+        num_points = 100
+        if x_end_plot == 0:
+            x = np.array([0]) # Handle case with single point
+            prices = np.array([float(start_price)])
+        else:
+            x = np.linspace(0.0, x_end_plot, num_points) 
+            prices = k / (C_float - x + 1e-9)**2 # Add small epsilon to avoid division by zero if x reaches C_float
+            prices = [float(p) for p in prices]
+
+    total_fee = float(migration_quote_threshold) * float(migration_fee_percent) / 100
+    creator_migration_fee = total_fee * (creator_migration_fee_percent / 100)
+    partner_migration_fee = total_fee - creator_migration_fee
+
+    total_lp_tokens = float(migration_quote_threshold)
+    creator_lp_tokens = total_lp_tokens * (creator_lp_percentage / 100)
+    partner_lp_tokens = total_lp_tokens * (partner_lp_percentage / 100)
+    creator_locked_lp = creator_lp_tokens * (creator_locked_lp_percentage / 100)
+    partner_locked_lp = partner_lp_tokens * (partner_locked_lp_percentage / 100)
+
+    trading_fee_rate = trading_fee_bps / 10000
+    total_trading_fee = total_trading_volume_sol * trading_fee_rate
+    creator_trading_fee = total_trading_fee * (creator_lp_percentage / 100)
+    partner_trading_fee = total_trading_fee * (partner_lp_percentage / 100)
+
+    fig, ax = plt.subplots()
+    ax.plot(x, prices)
+    ax.set_xlabel("Tokens Sold")
+    ax.set_ylabel("Price (in SOL)")
+    ax.set_title("Bonding Curve Simulation (in SOL)")
+
+    note = """
+Bonding Curve Unit: SOL
+
+Parameter Explanations:
+- Initial Market Cap: Total valuation (in SOL) at curve start.
+- Migration Market Cap: Valuation (in SOL) when curve ends and migrates to AMM.
+- Migration Quote Amount: Amount of SOL raised before fees.
+- Migration Threshold: Total SOL needed to trigger migration (includes fees).
+- LP Tokens: Represents user's share in the post-migration AMM liquidity pool. Approximated here as equal to the migration threshold in SOL.
+- Trading Fee BPS: The fee rate applied to all swaps post-migration. BPS = Basis Points (e.g., 100 BPS = 1%).
+- Creator/Partner Trading Fee: Earnings from swap volume based on LP share.
+- All SOL values are approximated assuming quote token = SOL.
+    """
+
+    return (
+        fig,
+        f"Initial Price: {start_price:.8f} SOL",
+        f"Migration Price: {end_price:.8f} SOL",
+        f"Migration Quote Amount: {migration_quote_amount:.2f} SOL",
+        f"Migration Threshold (after fee): {migration_quote_threshold:.2f} SOL",
+        f"Bonding Curve Unit: SOL",
+        f"Creator Migration Fee: {creator_migration_fee:.2f} SOL",
+        f"Partner Migration Fee: {partner_migration_fee:.2f} SOL",
+        f"Total LP Tokens: {total_lp_tokens:.2f}",
+        f"Creator LP: {creator_lp_tokens:.2f} (Locked: {creator_locked_lp:.2f})",
+        f"Partner LP: {partner_lp_tokens:.2f} (Locked: {partner_locked_lp:.2f})",
+        f"Creator Trading Fee: {creator_trading_fee:.2f} SOL",
+        f"Partner Trading Fee: {partner_trading_fee:.2f} SOL",
+        note.strip()
+    )
+
+gr.Interface(
+    fn=simulate_full_bonding_curve_with_fees,
+    inputs=[
+        gr.Textbox(label="Initial Market Cap (SOL)", value="1000"),
+        gr.Textbox(label="Migration Market Cap (SOL)", value="10000"),
+        gr.Textbox(label="Total Token Supply", value="1000000"),
+        gr.Textbox(label="Token Decimals", value="6"),
+        gr.Textbox(label="Quote Token Decimals", value="9"),
+        gr.Slider(label="Migration Fee Percent (%)", minimum=0, maximum=50, step=0.5, value=10),
+        gr.Slider(label="Creator Fee Share of Migration Fee (%)", minimum=0, maximum=100, step=1, value=50),
+        gr.Slider(label="Partner LP %", minimum=0, maximum=100, step=1, value=50),
+        gr.Slider(label="Creator LP %", minimum=0, maximum=100, step=1, value=50),
+        gr.Slider(label="Partner Locked LP %", minimum=0, maximum=100, step=1, value=100),
+        gr.Slider(label="Creator Locked LP %", minimum=0, maximum=100, step=1, value=100),
+        gr.Slider(label="Post-Migration Trading Fee (bps)", minimum=0, maximum=1000, step=5, value=30),
+        gr.Textbox(label="Total Trading Volume (SOL)", value="1000"),
+    ],
+    outputs=[
+        gr.Plot(label="Bonding Curve"),
+        gr.Textbox(label="Initial Price", lines=1, interactive=False),
+        gr.Textbox(label="Migration Price", lines=1, interactive=False),
+        gr.Textbox(label="Migration Quote Amount", lines=1, interactive=False),
+        gr.Textbox(label="Migration Threshold", lines=1, interactive=False),
+        gr.Textbox(label="Bonding Curve Unit", lines=1, interactive=False),
+        gr.Textbox(label="Creator Migration Fee", lines=1, interactive=False),
+        gr.Textbox(label="Partner Migration Fee", lines=1, interactive=False),
+        gr.Textbox(label="Total LP Tokens", lines=1, interactive=False),
+        gr.Textbox(label="Creator LP", lines=1, interactive=False),
+        gr.Textbox(label="Partner LP", lines=1, interactive=False),
+        gr.Textbox(label="Creator Trading Fee", lines=1, interactive=False),
+        gr.Textbox(label="Partner Trading Fee", lines=1, interactive=False),
+        gr.Textbox(label="Explanation", lines=12, interactive=False),
+    ],
+    title="Dynamic Bonding Curve Simulator (with Full Fee + LP Breakdown)"
+).launch()

requirements.txt

@@ -0,0 +1,3 @@
+gradio
+numpy
+matplotlib