(feat) add config and backtesting pages

pages/config/xemm_controller/README.md

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+# XEMM Configuration Tool
+
+Welcome to the XEMM Configuration Tool! This tool allows you to create, modify, visualize, backtest, and save configurations for the XEMM (Cross-Exchange Market Making) strategy. Here’s how you can make the most out of it.
+
+## Features
+
+- **Start from Default Configurations**: Begin with a default configuration or use the values from an existing configuration.
+- **Modify Configuration Values**: Change various parameters of the configuration to suit your trading strategy.
+- **Visualize Results**: See the impact of your changes through visual charts.
+- **Backtest Your Strategy**: Run backtests to evaluate the performance of your strategy.
+- **Save and Deploy**: Once satisfied, save the configuration to deploy it later.
+
+## How to Use
+
+### 1. Load Default Configuration
+
+Start by loading the default configuration for the XEMM strategy. This provides a baseline setup that you can customize to fit your needs.
+
+### 2. User Inputs
+
+Input various parameters for the strategy configuration. These parameters include:
+
+- **Maker Connector**: Select the maker trading platform or exchange where limit orders will be placed.
+- **Maker Trading Pair**: Choose the trading pair on the maker exchange.
+- **Taker Connector**: Select the taker trading platform or exchange where market orders will be executed to hedge the imbalance.
+- **Taker Trading Pair**: Choose the trading pair on the taker exchange.
+- **Min Profitability**: Set the minimum profitability percentage at which orders will be refreshed to avoid risking liquidity.
+- **Max Profitability**: Set the maximum profitability percentage at which orders will be refreshed to avoid being too far from the mid-price.
+- **Buy Maker Levels**: Specify the number of buy maker levels.
+- **Buy Targets and Amounts**: Define the target profitability and amounts for each buy maker level.
+- **Sell Maker Levels**: Specify the number of sell maker levels.
+- **Sell Targets and Amounts**: Define the target profitability and amounts for each sell maker level.
+
+### 3. Visualize Order Distribution
+
+Visualize the order distribution with profitability targets using Plotly charts. This helps you understand how your buy and sell orders are distributed across different profitability levels.
+
+### Min and Max Profitability
+
+The XEMM strategy uses min and max profitability bounds to manage the placement of limit orders:
+
+- **Min Profitability**: If the expected profitability of a limit order drops below this value, the order will be refreshed to avoid risking liquidity.
+- **Max Profitability**: If the expected profitability of a limit order exceeds this value, the order will be refreshed to avoid being too far from the mid-price.
+
+### Combining Profitability Targets and Order Amounts
+
+- **Buy Orders**: Configure the target profitability and amounts for each buy maker level. The orders will be refreshed if they fall outside the min and max profitability bounds.
+- **Sell Orders**: Similarly, configure the target profitability and amounts for each sell maker level, with orders being refreshed based on the profitability bounds.
+
+### 4. Save and Download Configuration
+
+Once you have configured your strategy, you can save and download the configuration as a YAML file. This allows you to deploy the strategy later without having to reconfigure it from scratch.
+
+### 5. Upload Configuration to Backend API
+
+You can also upload the configuration directly to the Backend API for immediate deployment. This ensures that your strategy is ready to be executed in real-time.
+
+## Conclusion
+
+By following these steps, you can efficiently configure your XEMM strategy, visualize its potential performance, and deploy it for trading. Feel free to experiment with different configurations to find the optimal setup for your trading needs. Happy trading!

pages/config/xemm_controller/app.py

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+import streamlit as st
+import plotly.graph_objects as go
+import yaml
+
+from CONFIG import BACKEND_API_HOST, BACKEND_API_PORT
+from backend.services.backend_api_client import BackendAPIClient
+from frontend.st_utils import initialize_st_page, get_backend_api_client
+
+# Initialize the Streamlit page
+initialize_st_page(title="XEMM Multiple Levels", icon="⚡️")
+
+# Page content
+st.text("This tool will let you create a config for XEMM Controller and upload it to the BackendAPI.")
+st.write("---")
+c1, c2, c3, c4, c5 = st.columns([1, 1, 1, 1, 1])
+
+with c1:
+    maker_connector = st.text_input("Maker Connector", value="kucoin")
+    maker_trading_pair = st.text_input("Maker Trading Pair", value="LBR-USDT")
+with c2:
+    taker_connector = st.text_input("Taker Connector", value="okx")
+    taker_trading_pair = st.text_input("Taker Trading Pair", value="LBR-USDT")
+with c3:
+    min_profitability = st.number_input("Min Profitability (%)", value=0.2, step=0.01) / 100
+    max_profitability = st.number_input("Max Profitability (%)", value=1.0, step=0.01) / 100
+with c4:
+    buy_maker_levels = st.number_input("Buy Maker Levels", value=1, step=1)
+    buy_targets_amounts = []
+    c41, c42 = st.columns([1, 1])
+    for i in range(buy_maker_levels):
+        with c41:
+            target_profitability = st.number_input(f"Target Profitability {i+1} B% ", value=0.3, step=0.01)
+        with c42:
+            amount = st.number_input(f"Amount {i+1}B Quote", value=10, step=1)
+        buy_targets_amounts.append([target_profitability / 100, amount])
+with c5:
+    sell_maker_levels = st.number_input("Sell Maker Levels", value=1, step=1)
+    sell_targets_amounts = []
+    c51, c52 = st.columns([1, 1])
+    for i in range(sell_maker_levels):
+        with c51:
+            target_profitability = st.number_input(f"Target Profitability {i+1}S %", value=0.3, step=0.001)
+        with c52:
+            amount = st.number_input(f"Amount {i+1} S Quote", value=10, step=1)
+        sell_targets_amounts.append([target_profitability / 100, amount])
+
+
+def create_order_graph(order_type, targets, min_profit, max_profit):
+    # Create a figure
+    fig = go.Figure()
+
+    # Convert profit targets to percentage for x-axis and prepare data for bar chart
+    x_values = [t[0] * 100 for t in targets]  # Convert to percentage
+    y_values = [t[1] for t in targets]
+    x_labels = [f"{x:.2f}%" for x in x_values]  # Format x labels as strings with percentage sign
+
+    # Add bar plot for visualization of targets
+    fig.add_trace(go.Bar(
+        x=x_labels,
+        y=y_values,
+        width=0.01,
+        name=f'{order_type.capitalize()} Targets',
+        marker=dict(color='gold')
+    ))
+
+    # Convert min and max profitability to percentages for reference lines
+    min_profit_percent = min_profit * 100
+    max_profit_percent = max_profit * 100
+
+    # Add vertical lines for min and max profitability
+    fig.add_shape(type="line",
+                  x0=min_profit_percent, y0=0, x1=min_profit_percent, y1=max(y_values, default=10),
+                  line=dict(color="red", width=2),
+                  name='Min Profitability')
+    fig.add_shape(type="line",
+                  x0=max_profit_percent, y0=0, x1=max_profit_percent, y1=max(y_values, default=10),
+                  line=dict(color="red", width=2),
+                  name='Max Profitability')
+
+    # Update layouts with x-axis starting at 0
+    fig.update_layout(
+        title=f"{order_type.capitalize()} Order Distribution with Profitability Targets",
+        xaxis=dict(
+            title="Profitability (%)",
+            range=[0, max(max(x_values + [min_profit_percent, max_profit_percent]) + 0.1, 1)]  # Adjust range to include a buffer
+        ),
+        yaxis=dict(
+            title="Order Amount"
+        ),
+        height=400,
+        width=600
+    )
+
+    return fig
+
+# Use the function for both buy and sell orders
+buy_order_fig = create_order_graph('buy', buy_targets_amounts, min_profitability, max_profitability)
+sell_order_fig = create_order_graph('sell', sell_targets_amounts, min_profitability, max_profitability)
+
+# Display the Plotly graphs in Streamlit
+st.plotly_chart(buy_order_fig, use_container_width=True)
+st.plotly_chart(sell_order_fig, use_container_width=True)
+
+# Display in Streamlit
+c1, c2, c3 = st.columns([2, 2, 1])
+with c1:
+    config_base = st.text_input("Config Base", value=f"xemm-{maker_connector}-{taker_connector}-{maker_trading_pair.split('-')[0]}")
+with c2:
+    config_tag = st.text_input("Config Tag", value="1.1")
+
+id = f"{config_base}_{config_tag}"
+config = {
+        "id": id.lower(),
+        "controller_name": "xemm_multiple_levels",
+        "controller_type": "generic",
+        "maker_connector": maker_connector,
+        "maker_trading_pair": maker_trading_pair,
+        "taker_connector": taker_connector,
+        "taker_trading_pair": taker_trading_pair,
+        "min_profitability": min_profitability,
+        "max_profitability": max_profitability,
+        "buy_levels_targets_amount": buy_targets_amounts,
+        "sell_levels_targets_amount": sell_targets_amounts
+}
+yaml_config = yaml.dump(config, default_flow_style=False)
+
+with c3:
+    upload_config_to_backend = st.button("Upload Config to BackendAPI")
+
+
+if upload_config_to_backend:
+    backend_api_client = get_backend_api_client()
+    backend_api_client.add_controller_config(config)
+    st.success("Config uploaded successfully!")

pages/config/xemm_controller/user_inputs.py

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+import streamlit as st
+
+
+def user_inputs():
+    c1, c2, c3, c4, c5 = st.columns([1, 1, 1, 1, 1])
+    with c1:
+        maker_connector = st.text_input("Maker Connector", value="kucoin")
+        maker_trading_pair = st.text_input("Maker Trading Pair", value="LBR-USDT")
+    with c2:
+        taker_connector = st.text_input("Taker Connector", value="okx")
+        taker_trading_pair = st.text_input("Taker Trading Pair", value="LBR-USDT")
+    with c3:
+        min_profitability = st.number_input("Min Profitability (%)", value=0.2, step=0.01) / 100
+        max_profitability = st.number_input("Max Profitability (%)", value=1.0, step=0.01) / 100
+    with c4:
+        buy_maker_levels = st.number_input("Buy Maker Levels", value=1, step=1)
+        buy_targets_amounts = []
+        c41, c42 = st.columns([1, 1])
+        for i in range(buy_maker_levels):
+            with c41:
+                target_profitability = st.number_input(f"Target Profitability {i + 1} B% ", value=0.3, step=0.01)
+            with c42:
+                amount = st.number_input(f"Amount {i + 1}B Quote", value=10, step=1)
+            buy_targets_amounts.append([target_profitability / 100, amount])
+    with c5:
+        sell_maker_levels = st.number_input("Sell Maker Levels", value=1, step=1)
+        sell_targets_amounts = []
+        c51, c52 = st.columns([1, 1])
+        for i in range(sell_maker_levels):
+            with c51:
+                target_profitability = st.number_input(f"Target Profitability {i + 1}S %", value=0.3, step=0.001)
+            with c52:
+                amount = st.number_input(f"Amount {i + 1} S Quote", value=10, step=1)
+            sell_targets_amounts.append([target_profitability / 100, amount])
+    return {
+        "controller_name": "xemm_multiple_levels",
+        "controller_type": "generic",
+        "maker_connector": maker_connector,
+        "maker_trading_pair": maker_trading_pair,
+        "taker_connector": taker_connector,
+        "taker_trading_pair": taker_trading_pair,
+        "min_profitability": min_profitability,
+        "max_profitability": max_profitability,
+        "buy_levels_targets_amount": buy_targets_amounts,
+        "sell_levels_targets_amount": sell_targets_amounts
+    }