fix: fit values to x axis

app.py

@@ -1403,13 +1403,17 @@ def create_combined_roi_time_series_graph(df):
         title=None  # Remove the built-in axis title since we're using annotations
     )
     
-    # Update x-axis with better formatting and autoscaling
+    # Update x-axis with better formatting and dynamic date range from data
+    min_date = df['timestamp'].min()
+    max_date = df['timestamp'].max()
+    logger.info(f"ROI Graph - Dynamic date range: min_date = {min_date}, max_date = {max_date}")
     fig.update_xaxes(
         showgrid=True, 
         gridwidth=1, 
         gridcolor='rgba(0,0,0,0.1)',
-        # Use autoscaling instead of fixed range
-        autorange=True,  # Enable autoscaling
+        # Set dynamic range based on actual data min/max dates (autoscale OFF)
+        range=[min_date, max_date],
+        autorange=False,  # Explicitly disable autoscale
         tickformat="%b %d",  # Simplified date format without time
         tickangle=-30,  # Angle the labels for better readability
         tickfont=dict(size=14, family="Arial, sans-serif", color="black", weight="bold"),  # Adjusted font size
@@ -2107,13 +2111,17 @@ def create_combined_time_series_graph(df):
         title=None  # Remove the built-in axis title since we're using annotations
     )
     
-    # Update x-axis with better formatting and autoscaling
+    # Update x-axis with better formatting and dynamic date range from data
+    min_date = df['timestamp'].min()
+    max_date = df['timestamp'].max()
+    logger.info(f"APR Graph - Dynamic date range: min_date = {min_date}, max_date = {max_date}")
     fig.update_xaxes(
         showgrid=True, 
         gridwidth=1, 
         gridcolor='rgba(0,0,0,0.1)',
-        # Use autoscaling instead of fixed range
-        autorange=True,  # Enable autoscaling
+        # Set dynamic range based on actual data min/max dates (autoscale OFF)
+        range=[min_date, max_date],
+        autorange=False,  # Explicitly disable autoscale
         tickformat="%b %d",  # Simplified date format without time
         tickangle=-30,  # Angle the labels for better readability
         tickfont=dict(size=14, family="Arial, sans-serif", color="black", weight="bold"),  # Adjusted font size

debug_roi_data.csv

@@ -28,108 +28,113 @@
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+80,1.14,2025-06-07 19:15:56.087703,118,lonwus-patu86,False,ROI,293.55,291.09
+81,2.0,2025-06-08 20:18:54.565690,118,lonwus-patu86,False,ROI,296.37,292.05
+82,2.0,2025-06-08 19:12:17.097068,118,lonwus-patu86,False,ROI,302.04,297.72
+83,2.0,2025-06-08 17:00:30.730686,118,lonwus-patu86,False,ROI,313.93,309.6
+84,2.0,2025-06-08 18:06:00.793190,118,lonwus-patu86,False,ROI,307.91,303.58
+85,2.0,2025-06-08 21:24:29.536035,118,lonwus-patu86,False,ROI,290.99,286.67
+86,-25.3,2025-06-11 13:51:16.740004,118,lonwus-patu86,False,ROI,-25.3,-41.28
+87,0.0,2025-06-06 21:16:18.171681,119,lonlim-zapgi60,False,ROI,0.0,0.0
+88,1.14,2025-06-07 21:20:52.452249,119,lonlim-zapgi60,False,ROI,307.76,305.29
+89,2.0,2025-06-08 21:24:43.897906,119,lonlim-zapgi60,False,ROI,309.78,305.45
+90,1.67,2025-06-09 21:25:09.568709,119,lonlim-zapgi60,False,ROI,181.01,177.41
+91,5.04,2025-06-10 21:27:14.352202,119,lonlim-zapgi60,False,ROI,421.68,410.8
+92,4.08,2025-06-12 19:40:26.414300,119,lonlim-zapgi60,False,ROI,237.2,222.56
+93,2.48,2025-06-13 20:14:38.143005,119,lonlim-zapgi60,False,ROI,123.86,114.3
+94,0.92,2025-06-15 02:29:15.201154,119,lonlim-zapgi60,False,ROI,39.17,34.53
+95,1.1,2025-06-16 19:00:11.977194,119,lonlim-zapgi60,False,ROI,39.24,34.03
+96,1.32,2025-06-06 21:35:10.663781,120,joyus-goson39,False,ROI,2081.35,2081.35
+97,-28.02,2025-06-08 17:03:45.278780,120,joyus-goson39,False,ROI,-28.02,-32.34
+98,2.35,2025-06-08 22:12:15.454361,120,joyus-goson39,False,ROI,379.37,375.05
+99,3.99,2025-06-13 21:09:43.972117,120,joyus-goson39,False,ROI,201.84,192.27
+100,3.0,2025-06-14 21:11:33.782224,120,joyus-goson39,False,ROI,133.33,126.91
+101,1.33,2025-06-06 21:50:52.233090,121,cilwar-rimlu27,False,ROI,2108.94,2108.94
+102,0.66,2025-06-07 20:35:53.079934,122,tevi-kulo15,False,ROI,1038.47,1038.47
+103,1.24,2025-06-08 22:11:03.101491,122,tevi-kulo15,False,ROI,350.05,348.24
+104,3.25,2025-06-10 18:57:11.357853,122,tevi-kulo15,False,ROI,375.58,367.38
+105,4.51,2025-06-11 19:15:27.075172,122,tevi-kulo15,False,ROI,394.52,381.34
+106,4.1,2025-06-12 19:16:57.908495,122,tevi-kulo15,False,ROI,289.14,277.26
+107,2.53,2025-06-13 19:20:13.259482,122,tevi-kulo15,False,ROI,149.59,142.67
+108,1.56,2025-06-14 19:22:15.337790,122,tevi-kulo15,False,ROI,79.1,75.24
+109,1.19,2025-06-16 00:58:44.095764,122,tevi-kulo15,False,ROI,51.44,48.76
+110,1.35,2025-06-17 01:17:35.998975,122,tevi-kulo15,False,ROI,52.44,49.22
+111,-0.14,2025-06-09 00:31:18.357811,123,cordron-yelku44,False,ROI,-0.14,0.55
+112,1.97,2025-06-10 02:17:21.916446,123,cordron-yelku44,False,ROI,346.8,340.52
+113,3.47,2025-06-11 08:14:14.656064,123,cordron-yelku44,False,ROI,381.81,370.64
+114,3.09,2025-06-12 08:16:43.196306,123,cordron-yelku44,False,ROI,261.07,251.18
+115,1.59,2025-06-13 20:51:54.959756,123,cordron-yelku44,False,ROI,99.58,94.56
+116,0.7,2025-06-14 20:58:08.060349,123,cordron-yelku44,False,ROI,37.24,35.23
+117,0.34,2025-06-16 01:13:39.374306,123,cordron-yelku44,False,ROI,15.26,14.41
+118,0.49,2025-06-17 01:18:21.000045,123,cordron-yelku44,False,ROI,19.96,18.57
+119,0.0,2025-06-09 18:32:36.558142,126,tonvel-beeprel23,False,ROI,0.0,0.0
+120,3.31,2025-06-10 18:35:49.668890,126,tonvel-beeprel23,False,ROI,978.68,971.66
+121,4.84,2025-06-11 18:38:07.704650,126,tonvel-beeprel23,False,ROI,789.88,777.93
+122,4.41,2025-06-12 18:42:17.665709,126,tonvel-beeprel23,False,ROI,497.65,486.99
+123,1.43,2025-06-16 17:52:55.063058,126,tonvel-beeprel23,False,ROI,72.71,71.16
+124,0.81,2025-06-09 22:20:14.827769,127,lunel-luwus85,False,ROI,1280.5,1280.5
+125,2.83,2025-06-10 11:46:19.456686,127,lunel-luwus85,False,ROI,1305.08,1298.06
+126,4.45,2025-06-11 11:52:17.821684,127,lunel-luwus85,False,ROI,904.96,893.01
+127,4.04,2025-06-12 12:14:06.850694,127,lunel-luwus85,False,ROI,524.63,513.98
+128,2.42,2025-06-13 12:18:45.544337,127,lunel-luwus85,False,ROI,231.49,225.74
+129,1.44,2025-06-14 20:55:17.651663,127,lunel-luwus85,False,ROI,101.72,99.0
+130,0.88,2025-06-15 20:58:03.786280,127,lunel-luwus85,False,ROI,51.95,50.94
+131,1.06,2025-06-16 21:00:02.716458,127,lunel-luwus85,False,ROI,53.98,52.42
+132,-30.96,2025-06-10 09:06:37.010122,128,kozu-hanfil63,False,ROI,-30.96,-30.96
+133,-0.31,2025-06-10 09:29:20.119072,128,kozu-hanfil63,False,ROI,-0.31,-0.31
+134,1.2,2025-06-11 12:58:00.236662,128,kozu-hanfil63,False,ROI,314.71,310.11
+135,-0.69,2025-06-13 07:59:58.559461,128,kozu-hanfil63,False,ROI,-0.69,0.49
+136,-2.12,2025-06-15 20:59:08.057917,128,kozu-hanfil63,False,ROI,-2.12,3.5
+137,0.0,2025-06-15 21:22:42.073588,133,ronwus-yusrus90,False,ROI,0.0,0.0
+138,0.0,2025-06-16 21:26:14.464595,133,ronwus-yusrus90,False,ROI,1.43,0.89

initial_value_fixer.py

@@ -395,11 +395,14 @@ def fetch_optimism_transfers(
     address: str,
     last_timestamp: int
 ) -> Dict:
+    """
+    Fetch Optimism transfers for a given address with improved error handling and rate limiting.
+    """
     base_url = "https://safe-transaction-optimism.safe.global/api/v1"
     all_transfers_by_date = {}
     
     try:
-        logger.info("Fetching Optimism transfers using SafeGlobal API...")
+        logger.info(f"Fetching Optimism transfers for address {address}...")
 
         last_date = datetime.fromtimestamp(last_timestamp).strftime("%Y-%m-%d")
         
@@ -407,7 +410,13 @@ def fetch_optimism_transfers(
         transfers_url = f"{base_url}/safes/{address}/incoming-transfers/"
         
         processed_count = 0
-        while True:
+        page_count = 0
+        max_pages = 10  # Limit to prevent infinite loops
+        
+        while page_count < max_pages:
+            page_count += 1
+            logger.info(f"Fetching page {page_count} for address {address}")
+            
             success, response_json = request_with_retries(
                 endpoint=transfers_url,
                 headers={"Accept": "application/json"},
@@ -416,11 +425,12 @@ def fetch_optimism_transfers(
             )
             
             if not success:
-                logger.error("Failed to fetch Optimism transfers")
+                logger.error(f"Failed to fetch Optimism transfers for address {address} on page {page_count}")
                 break
                 
             transfers = response_json.get("results", [])
             if not transfers:
+                logger.info(f"No more transfers found for address {address} on page {page_count}")
                 break
                 
             for transfer in transfers:
@@ -449,11 +459,9 @@ def fetch_optimism_transfers(
                 if tx_date not in all_transfers_by_date:
                     all_transfers_by_date[tx_date] = []
 
-                should_include = should_include_transfer_optimism(
-                        from_address
-                    )
+                should_include = should_include_transfer_optimism(from_address)
                 if not should_include:
-                        continue
+                    continue
                     
                 # Process different transfer types
                 if transfer_type == "ERC20_TRANSFER":
@@ -471,7 +479,7 @@ def fetch_optimism_transfers(
                         symbol = token_info.get("symbol", "Unknown")
                         decimals = int(token_info.get("decimals", 18) or 18)
                         
-                    if symbol.lower() != "usdc":
+                    if symbol.lower() not in ["usdc", "eth"]:
                         continue
                         
                     value_raw = int(transfer.get("value", "0") or "0")
@@ -517,19 +525,22 @@ def fetch_optimism_transfers(
                 processed_count += 1
                 
             # Show progress
-            if processed_count % 100 == 0:
-                logger.info(f"Processed {processed_count} Optimism transfers...")
+            if processed_count % 50 == 0:
+                logger.info(f"Processed {processed_count} Optimism transfers for address {address}...")
                 
             # Check for next page
             cursor = response_json.get("next")
             if not cursor:
+                logger.info(f"No more pages for address {address}")
                 break
+            else:
+                transfers_url = cursor  # Update URL for next page
                 
-        logger.info(f"Completed Optimism transfers: {processed_count} found")
+        logger.info(f"Completed Optimism transfers for address {address}: {processed_count} found")
         return all_transfers_by_date
         
     except Exception as e:
-        logger.error(f"Error fetching Optimism transfers: {e}")
+        logger.error(f"Error fetching Optimism transfers for address {address}: {e}")
         return {}
     
 def calculate_initial_investment_value_from_funding_events(
@@ -700,43 +711,131 @@ def calculate_apr_and_roi(
 
 
 def fix_apr_and_roi(df: DataFrame) -> DataFrame:
-
+    """
+    Fix APR and ROI values by recalculating them based on actual blockchain data.
+    This function processes each row only once and includes proper error handling.
+    """
+    if df.empty:
+        logger.info("Empty DataFrame provided to fix_apr_and_roi, returning as-is")
+        return df
+
+    logger.info(f"Starting fix_apr_and_roi with {len(df)} rows")
+    
     # Remove rows with excluded addresses
+    original_count = len(df)
     df = df[~df['address'].isin(EXCLUDED_ADDRESSES)]
+    excluded_count = original_count - len(df)
+    if excluded_count > 0:
+        logger.info(f"Excluded {excluded_count} rows with excluded addresses")
 
     # Remove rows with timestamps before 2025-06-06
+    original_count = len(df)
     df = df[df['timestamp'] >= '2025-06-06 00:00:00.000000']
+    old_data_count = original_count - len(df)
+    if old_data_count > 0:
+        logger.info(f"Excluded {old_data_count} rows with timestamps before 2025-06-06")
+
+    # Check for future timestamps and filter them out
+    current_time = datetime.now().timestamp()
+    future_rows = df[df['timestamp'].apply(lambda x: x.timestamp()) > current_time]
+    if not future_rows.empty:
+        logger.warning(f"Found {len(future_rows)} rows with future timestamps, excluding them")
+        for idx, row in future_rows.iterrows():
+            logger.warning(f"Future timestamp found: {row['timestamp']} (timestamp: {row['timestamp'].timestamp()})")
+        df = df[df['timestamp'].apply(lambda x: x.timestamp()) <= current_time]
+
+    if df.empty:
+        logger.warning("No valid rows remaining after filtering, returning empty DataFrame")
+        return df
+
+    logger.info(f"Processing {len(df)} valid rows")
+    
+    # Create a copy to avoid modifying the original DataFrame during iteration
+    df_copy = df.copy()
+    rows_to_drop = []
+    processed_count = 0
+    
+    for idx, row in df_copy.iterrows():
+        try:
+            if row['is_dummy']:
+                logger.debug(f"Skipping dummy row {idx}")
+                continue
 
-    for idx, row in df.iterrows():
-        if row['is_dummy']:
-            continue
+            processed_count += 1
+            logger.info(f"Processing row {processed_count}/{len(df_copy)} - Address: {row['address']}")
+
+            final_timestamp = int(row['timestamp'].timestamp())
+            
+            # Validate timestamp is not in the future
+            if final_timestamp > current_time:
+                logger.warning(f"Skipping row {idx} with future timestamp: {final_timestamp}")
+                rows_to_drop.append(idx)
+                continue
+            
+            calculation_metrics = row['calculation_metrics']
+            
+            # Calculate initial value and timestamp with error handling
+            try:
+                initial_value, initial_timestamp = calculate_initial_value_from_address_and_timestamp(
+                    row['address'], final_timestamp
+                )
+            except Exception as e:
+                logger.error(f"Error calculating initial value for address {row['address']}: {e}")
+                rows_to_drop.append(idx)
+                continue
+            
+            # Calculate final value with error handling
+            try:
+                final_value = calculate_final_value_from_address_and_timestamp(
+                    row['address'], final_timestamp
+                )
+                if row["volume"] > 0:
+                    final_value += row["volume"]
+            except Exception as e:
+                logger.error(f"Error calculating final value for address {row['address']}: {e}")
+                rows_to_drop.append(idx)
+                continue
 
-        final_timestamp = int(row['timestamp'].timestamp())
-        calculation_metrics = row['calculation_metrics']
-        initial_value, initial_timestamp = calculate_initial_value_from_address_and_timestamp(row['address'], final_timestamp)
-        final_value = calculate_final_value_from_address_and_timestamp(row['address'], final_timestamp)
-        if row["volume"] > 0:
-            final_value += row["volume"]
+            if initial_value <= 0:
+                logger.warning(f"Initial value for address {row['address']} is non-positive ({initial_value}), skipping row.")
+                rows_to_drop.append(idx)
+                continue
 
-        if initial_value <= 0:
-            logger.warning(f"Initial value for address {row['address']} is non-positive, skipping row.")
-            df = df.drop(idx)
+            # Update calculation metrics
+            calculation_metrics['initial_value'] = initial_value
+            calculation_metrics['final_value'] = final_value
+            df.at[idx, 'calculation_metrics'] = calculation_metrics
+
+            # Calculate APR and ROI with error handling
+            try:
+                apr, adjusted_apr, roi = calculate_apr_and_roi(
+                    initial_value=initial_value,
+                    final_value=final_value,
+                    initial_timestamp=initial_timestamp,
+                    final_timestamp=final_timestamp
+                )
+                df.at[idx, 'apr'] = apr
+                df.at[idx, 'adjusted_apr'] = adjusted_apr
+                df.at[idx, 'roi'] = roi
+                
+                logger.info(f"Successfully processed address {row['address']}: APR={apr:.2f}, ROI={roi:.2f}")
+                
+            except Exception as e:
+                logger.error(f"Error calculating APR/ROI for address {row['address']}: {e}")
+                rows_to_drop.append(idx)
+                continue
+                
+        except Exception as e:
+            logger.error(f"Unexpected error processing row {idx}: {e}")
+            rows_to_drop.append(idx)
             continue
 
-        calculation_metrics['initial_value'] = initial_value
-        calculation_metrics['final_value'] = final_value
-        df.at[idx, 'calculation_metrics'] = calculation_metrics
-
-        apr, adjusted_apr, roi = calculate_apr_and_roi(
-            initial_value=initial_value,
-            final_value=final_value,
-            initial_timestamp=initial_timestamp,
-            final_timestamp=final_timestamp
-        )
-        df.at[idx, 'apr'] = apr
-        df.at[idx, 'adjusted_apr'] = adjusted_apr
-        df.at[idx, 'roi'] = roi
+    # Drop rows that had errors
+    if rows_to_drop:
+        logger.info(f"Dropping {len(rows_to_drop)} rows due to errors")
+        df = df.drop(rows_to_drop)
 
+    logger.info(f"Completed fix_apr_and_roi: {len(df)} rows remaining")
     return df
 
 
@@ -748,4 +847,4 @@ if __name__ == "__main__":
         test_address,
         test_final_timestamp
     )
-    print(v)
+    print(v)

optimus_apr_statistics.csv

@@ -1,17 +1,17 @@
 agent_id,agent_name,total_points,apr_points,performance_points,real_apr_points,real_performance_points,avg_apr,avg_performance,max_apr,min_apr,avg_adjusted_apr,max_adjusted_apr,min_adjusted_apr,latest_timestamp
 111,furtek-gilje55,5,5,0,5,0,48.2,,132.09,-1.5,49.162,125.13,5.19,2025-06-16 20:22:51
 112,vuzus-fazi89,1,1,0,1,0,-34.65,,-34.65,-34.65,-31.43,-31.43,-31.43,2025-06-08 02:03:32
-115,yenot-zoncen49,23,23,0,23,0,19.36826086956522,,190.0,-3.48,23.754782608695653,182.41,2.56,2025-06-15 04:17:24
+115,yenot-zoncen49,24,24,0,24,0,18.655833333333334,,190.0,-3.48,22.937916666666666,182.41,2.56,2025-06-17 02:16:08
 116,honji-hahi60,36,36,0,36,0,47.61749999999999,,159.56,-3.48,48.455000000000005,151.96,1.67,2025-06-16 13:54:43
-117,furye-himkon89,9,9,0,9,0,58.42777777777778,,228.68,-2.38,58.18555555555557,221.09,0.66,2025-06-15 20:54:19
+117,furye-himkon89,10,10,0,10,0,52.49400000000001,,228.68,-2.38,52.46400000000001,221.09,0.66,2025-06-17 04:52:36
 118,lonwus-patu86,11,11,0,11,0,277.7609090909091,,335.69,-25.3,273.22090909090906,333.22,-41.28,2025-06-11 13:51:16
 119,lonlim-zapgi60,9,9,0,9,0,184.41111111111113,,421.68,0.0,178.26333333333335,410.8,0.0,2025-06-16 19:00:11
 120,joyus-goson39,5,5,0,5,0,553.574,,2081.35,-28.02,548.6479999999999,2081.35,-32.34,2025-06-14 21:11:33
 121,cilwar-rimlu27,1,1,0,1,0,2108.94,,2108.94,2108.94,2108.94,2108.94,2108.94,2025-06-06 21:50:52
-122,tevi-kulo15,8,8,0,8,0,340.98625,,1038.47,51.44,334.92,1038.47,48.76,2025-06-16 00:58:44
-123,cordron-yelku44,7,7,0,7,0,163.0885714285714,,381.81,-0.14,158.1557142857143,370.64,0.55,2025-06-16 01:13:39
+122,tevi-kulo15,9,9,0,9,0,308.92555555555555,,1038.47,51.44,303.17555555555555,1038.47,48.76,2025-06-17 01:17:35
+123,cordron-yelku44,8,8,0,8,0,145.1975,,381.81,-0.14,140.70749999999998,370.64,0.55,2025-06-17 01:18:21
 126,tonvel-beeprel23,5,5,0,5,0,467.784,,978.68,0.0,461.54799999999994,971.66,0.0,2025-06-16 17:52:55
 127,lunel-luwus85,8,8,0,8,0,556.78875,,1305.08,51.95,551.7062500000001,1298.06,50.94,2025-06-16 21:00:02
 128,kozu-hanfil63,5,5,0,5,0,56.126,,314.71,-30.96,56.56600000000001,310.11,-30.96,2025-06-15 20:59:08
-133,ronwus-yusrus90,1,1,0,1,0,0.0,,0.0,0.0,0.0,0.0,0.0,2025-06-15 21:22:42
-ALL,All Agents,134,134,0,134,0,174.8294776119403,,2108.94,-34.65,173.7420895522388,2108.94,-41.28,2025-06-16 21:00:02
+133,ronwus-yusrus90,2,2,0,2,0,0.715,,1.43,0.0,0.445,0.89,0.0,2025-06-16 21:26:14
+ALL,All Agents,139,139,0,139,0,169.08158273381295,,2108.94,-34.65,168.02330935251797,2108.94,-41.28,2025-06-17 04:52:36

optimus_apr_values.csv

@@ -28,6 +28,7 @@ apr,adjusted_apr,timestamp,portfolio_snapshot,calculation_metrics,roi,agent_id,i
 142.55,136.2,2025-06-12 22:29:06.555260,"{'portfolio': {'portfolio_value': 30.351423879956, 'value_in_pools': 0.0, 'value_in_safe': 30.351423879956, 'initial_investment': 519.3005766438965, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xE4EAF37b1726634935f679a8f3e00EC2E4e650A0', 'last_updated': 1749745865}, 'positons': []}","{'initial_value': 44.91788354008114, 'final_value': 46.17661277882512, 'f_i_ratio': -0.9415532636683955, 'first_investment_timestamp': 1749747546, 'time_ratio': 8760.0}",2.8,115,False,0xE4EAF37b1726634935f679a8f3e00EC2E4e650A0,yenot-zoncen49,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,balanced,"[""balancer_pools_search"", ""uniswap_pools_search"", ""velodrome_pools_search""]"
 55.41,53.77,2025-06-13 22:40:52.426319,"{'portfolio': {'portfolio_value': 30.352911473112, 'value_in_pools': 0.0, 'value_in_safe': 30.352911473112, 'initial_investment': 833.7257614244643, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xE4EAF37b1726634935f679a8f3e00EC2E4e650A0', 'last_updated': 1749831611}, 'positons': []}","{'initial_value': 44.91788354008114, 'final_value': 45.47591008026921, 'f_i_ratio': -0.9635936504813616, 'first_investment_timestamp': 1749834652, 'time_ratio': 8760.0}",1.24,115,False,0xE4EAF37b1726634935f679a8f3e00EC2E4e650A0,yenot-zoncen49,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,balanced,"[""balancer_pools_search"", ""uniswap_pools_search"", ""velodrome_pools_search""]"
 -0.28,2.65,2025-06-15 04:17:24.547659,"{'portfolio': {'portfolio_value': 30.35054346768, 'value_in_pools': 0.0, 'value_in_safe': 30.35054346768, 'initial_investment': 1013.3972955847887, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xE4EAF37b1726634935f679a8f3e00EC2E4e650A0', 'last_updated': 1749941221}, 'positons': []}","{'initial_value': 44.91788354008114, 'final_value': 44.79423281705253, 'f_i_ratio': -0.970050696207783, 'first_investment_timestamp': 1749941244, 'time_ratio': 8760.0}",-0.28,115,False,0xE4EAF37b1726634935f679a8f3e00EC2E4e650A0,yenot-zoncen49,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,balanced,"['balancer_pools_search', 'uniswap_pools_search', 'velodrome_pools_search']"
+2.27,4.15,2025-06-17 02:16:08.931664,"{'portfolio': {'portfolio_value': 30.350118441064, 'value_in_pools': 0.0, 'value_in_safe': 30.350118441064, 'initial_investment': 1058.31517912487, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xE4EAF37b1726634935f679a8f3e00EC2E4e650A0', 'last_updated': 1750106742}, 'positons': []}","{'initial_value': 44.91788354008114, 'final_value': 44.94960010677301, 'f_i_ratio': -0.9713222308063645, 'first_investment_timestamp': 1750106768, 'time_ratio': 8760.0}",0.07,115,False,0xE4EAF37b1726634935f679a8f3e00EC2E4e650A0,yenot-zoncen49,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,risky,"[""velodrome_pools_search""]"
 -3.48,3.75,2025-06-06 11:29:18.913469,"{'portfolio': {'portfolio_value': 28.28379, 'value_in_pools': 0.0, 'value_in_safe': 28.28379, 'initial_investment': 61.7507349970131, 'volume': None, 'agent_hash': 'bafybeieck7zrejp6ttx2ulhejx3kqfzkg5d5kvirevdrlrrr7jnowghn7e', 'allocations': [], 'portfolio_breakdown': [{'asset': 'ETH', 'address': '0x0000000000000000000000000000000000000000', 'balance': 0.005, 'price': 2457.43, 'value_usd': 12.28715, 'ratio': 0.0}, {'asset': 'USDC', 'address': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'balance': 16.0, 'price': 0.99979, 'value_usd': 15.99664, 'ratio': 0.0}], 'address': '0xa11417aeBF3932ee895008eDE8eA95616f488bCf', 'last_updated': 1749189495}, 'positons': []}","{'initial_value': 30.87536749850655, 'final_value': 29.800137839954267, 'f_i_ratio': -0.5419683668321018, 'first_investment_timestamp': 1749189558, 'time_ratio': 8760.0}",-3.48,116,False,0xa11417aeBF3932ee895008eDE8eA95616f488bCf,honji-hahi60,APR,,bafybeieck7zrejp6ttx2ulhejx3kqfzkg5d5kvirevdrlrrr7jnowghn7e,,balanced,"[""balancer_pools_search"", ""uniswap_pools_search"", ""velodrome_pools_search""]"
 -3.48,3.75,2025-06-06 12:31:08.139923,"{'portfolio': {'portfolio_value': 28.28379, 'value_in_pools': 0.0, 'value_in_safe': 28.28379, 'initial_investment': 61.7507349970131, 'volume': None, 'agent_hash': 'bafybeieck7zrejp6ttx2ulhejx3kqfzkg5d5kvirevdrlrrr7jnowghn7e', 'allocations': [], 'portfolio_breakdown': [{'asset': 'ETH', 'address': '0x0000000000000000000000000000000000000000', 'balance': 0.005, 'price': 2457.43, 'value_usd': 12.28715, 'ratio': 0.0}, {'asset': 'USDC', 'address': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'balance': 16.0, 'price': 0.99979, 'value_usd': 15.99664, 'ratio': 0.0}], 'address': '0xa11417aeBF3932ee895008eDE8eA95616f488bCf', 'last_updated': 1749189495}, 'positons': []}","{'initial_value': 30.87536749850655, 'final_value': 29.800137839954267, 'f_i_ratio': -0.5419683668321018, 'first_investment_timestamp': 1749193268, 'time_ratio': 8760.0}",-3.48,116,False,0xa11417aeBF3932ee895008eDE8eA95616f488bCf,honji-hahi60,APR,,bafybeieck7zrejp6ttx2ulhejx3kqfzkg5d5kvirevdrlrrr7jnowghn7e,,balanced,"[""balancer_pools_search"", ""uniswap_pools_search"", ""velodrome_pools_search""]"
 -3.48,3.75,2025-06-06 22:15:03.771384,"{'portfolio': {'portfolio_value': 28.544854, 'value_in_pools': 0.0, 'value_in_safe': 28.544854, 'initial_investment': 92.62610249551965, 'volume': None, 'agent_hash': 'bafybeieck7zrejp6ttx2ulhejx3kqfzkg5d5kvirevdrlrrr7jnowghn7e', 'allocations': [], 'portfolio_breakdown': [{'asset': 'ETH', 'address': '0x0000000000000000000000000000000000000000', 'balance': 0.005, 'price': 2509.71, 'value_usd': 12.54855, 'ratio': 0.0}, {'asset': 'USDC', 'address': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'balance': 16.0, 'price': 0.999769, 'value_usd': 15.996304, 'ratio': 0.0}], 'address': '0xa11417aeBF3932ee895008eDE8eA95616f488bCf', 'last_updated': 1749228239}, 'positons': []}","{'initial_value': 30.87536749850655, 'final_value': 29.800137839954267, 'f_i_ratio': -0.6918271067123792, 'first_investment_timestamp': 1749228303, 'time_ratio': 8760.0}",-3.48,116,False,0xa11417aeBF3932ee895008eDE8eA95616f488bCf,honji-hahi60,APR,,bafybeieck7zrejp6ttx2ulhejx3kqfzkg5d5kvirevdrlrrr7jnowghn7e,,balanced,"[""balancer_pools_search"", ""uniswap_pools_search"", ""velodrome_pools_search""]"
@@ -73,6 +74,7 @@ apr,adjusted_apr,timestamp,portfolio_snapshot,calculation_metrics,roi,agent_id,i
 36.83,35.19,2025-06-13 20:08:14.584427,"{'portfolio': {'portfolio_value': 28.766334, 'value_in_pools': 0.0, 'value_in_safe': 28.766334, 'initial_investment': 895.3856574566896, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0x70FAE90eb66b779FC368350a051D83dc6C7fF068', 'last_updated': 1749822232}, 'positons': []}","{'initial_value': 30.87536749850655, 'final_value': 31.119770160623126, 'f_i_ratio': -0.9678726884215347, 'first_investment_timestamp': 1749825494, 'time_ratio': 8760.0}",0.79,117,False,0x70FAE90eb66b779FC368350a051D83dc6C7fF068,furye-himkon89,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,risky,"[""balancer_pools_search"", ""uniswap_pools_search"", ""velodrome_pools_search""]"
 -0.62,0.66,2025-06-14 20:11:08.489286,"{'portfolio': {'portfolio_value': 28.620052, 'value_in_pools': 0.0, 'value_in_safe': 28.620052, 'initial_investment': 957.1363924537027, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0x70FAE90eb66b779FC368350a051D83dc6C7fF068', 'last_updated': 1749909970}, 'positons': []}","{'initial_value': 30.87536749850655, 'final_value': 30.684659279118137, 'f_i_ratio': -0.9700982511733464, 'first_investment_timestamp': 1749912068, 'time_ratio': 8760.0}",-0.62,117,False,0x70FAE90eb66b779FC368350a051D83dc6C7fF068,furye-himkon89,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,risky,"[""balancer_pools_search"", ""uniswap_pools_search"", ""velodrome_pools_search""]"
 -1.41,1.51,2025-06-15 20:54:19.955496,"{'portfolio': {'portfolio_value': 28.73215, 'value_in_pools': 0.0, 'value_in_safe': 28.73215, 'initial_investment': 988.0117599522092, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0x70FAE90eb66b779FC368350a051D83dc6C7fF068', 'last_updated': 1750001038}, 'positons': []}","{'initial_value': 30.87536749850655, 'final_value': 30.4394509928197, 'f_i_ratio': -0.9709192226604775, 'first_investment_timestamp': 1750001059, 'time_ratio': 8760.0}",-1.41,117,False,0x70FAE90eb66b779FC368350a051D83dc6C7fF068,furye-himkon89,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,risky,"[""balancer_pools_search"", ""uniswap_pools_search"", ""velodrome_pools_search""]"
+-0.91,0.97,2025-06-17 04:52:36.207967,"{'portfolio': {'portfolio_value': 28.892858, 'value_in_pools': 0.0, 'value_in_safe': 28.892858, 'initial_investment': 1018.8871274507158, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0x70FAE90eb66b779FC368350a051D83dc6C7fF068', 'last_updated': 1750116124}, 'positons': []}","{'initial_value': 30.87536749850655, 'final_value': 30.594824226534584, 'f_i_ratio': -0.9716427293842737, 'first_investment_timestamp': 1750116156, 'time_ratio': 8760.0}",-0.91,117,False,0x70FAE90eb66b779FC368350a051D83dc6C7fF068,furye-himkon89,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,risky,"[""balancer_pools_search"", ""uniswap_pools_search"", ""velodrome_pools_search""]"
 324.01,321.54,2025-06-07 16:03:45.373863,"{'portfolio': {'portfolio_value': 28.437878, 'value_in_pools': 0.0, 'value_in_safe': 28.437878, 'initial_investment': 59.600275679908535, 'volume': None, 'agent_hash': 'bafybeieck7zrejp6ttx2ulhejx3kqfzkg5d5kvirevdrlrrr7jnowghn7e', 'allocations': [], 'portfolio_breakdown': [{'asset': 'ETH', 'address': '0x0000000000000000000000000000000000000000', 'balance': 0.005, 'price': 2488.35, 'value_usd': 12.44175, 'ratio': 0.0}, {'asset': 'USDC', 'address': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'balance': 16.0, 'price': 0.999758, 'value_usd': 15.996128, 'ratio': 0.0}], 'address': '0xc7d89Ed318CAC02Cf9719c50157541df2504EA3A', 'last_updated': 1749288375}, 'positons': []}","{'initial_value': 29.800137839954267, 'final_value': 30.140478299059993, 'f_i_ratio': -0.522856603000806, 'first_investment_timestamp': 1749292425, 'time_ratio': 8760.0}",1.14,118,False,0xc7d89Ed318CAC02Cf9719c50157541df2504EA3A,lonwus-patu86,APR,,bafybeieck7zrejp6ttx2ulhejx3kqfzkg5d5kvirevdrlrrr7jnowghn7e,,balanced,
 313.15,310.68,2025-06-07 17:07:58.993795,"{'portfolio': {'portfolio_value': 28.437878, 'value_in_pools': 0.0, 'value_in_safe': 28.437878, 'initial_investment': 59.600275679908535, 'volume': None, 'agent_hash': 'bafybeieck7zrejp6ttx2ulhejx3kqfzkg5d5kvirevdrlrrr7jnowghn7e', 'allocations': [], 'portfolio_breakdown': [{'asset': 'ETH', 'address': '0x0000000000000000000000000000000000000000', 'balance': 0.005, 'price': 2488.35, 'value_usd': 12.44175, 'ratio': 0.0}, {'asset': 'USDC', 'address': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'balance': 16.0, 'price': 0.999758, 'value_usd': 15.996128, 'ratio': 0.0}], 'address': '0xc7d89Ed318CAC02Cf9719c50157541df2504EA3A', 'last_updated': 1749288375}, 'positons': []}","{'initial_value': 29.800137839954267, 'final_value': 30.140478299059993, 'f_i_ratio': -0.522856603000806, 'first_investment_timestamp': 1749296278, 'time_ratio': 8760.0}",1.14,118,False,0xc7d89Ed318CAC02Cf9719c50157541df2504EA3A,lonwus-patu86,APR,,bafybeieck7zrejp6ttx2ulhejx3kqfzkg5d5kvirevdrlrrr7jnowghn7e,,balanced,
 335.69,333.22,2025-06-07 14:59:15.300909,"{'portfolio': {'portfolio_value': 28.437878, 'value_in_pools': 0.0, 'value_in_safe': 28.437878, 'initial_investment': 59.600275679908535, 'volume': None, 'agent_hash': 'bafybeieck7zrejp6ttx2ulhejx3kqfzkg5d5kvirevdrlrrr7jnowghn7e', 'allocations': [], 'portfolio_breakdown': [{'asset': 'ETH', 'address': '0x0000000000000000000000000000000000000000', 'balance': 0.005, 'price': 2488.35, 'value_usd': 12.44175, 'ratio': 0.0}, {'asset': 'USDC', 'address': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'balance': 16.0, 'price': 0.999758, 'value_usd': 15.996128, 'ratio': 0.0}], 'address': '0xc7d89Ed318CAC02Cf9719c50157541df2504EA3A', 'last_updated': 1749288375}, 'positons': []}","{'initial_value': 29.800137839954267, 'final_value': 30.140478299059993, 'f_i_ratio': -0.522856603000806, 'first_investment_timestamp': 1749288555, 'time_ratio': 8760.0}",1.14,118,False,0xc7d89Ed318CAC02Cf9719c50157541df2504EA3A,lonwus-patu86,APR,,bafybeieck7zrejp6ttx2ulhejx3kqfzkg5d5kvirevdrlrrr7jnowghn7e,,balanced,
@@ -107,6 +109,7 @@ apr,adjusted_apr,timestamp,portfolio_snapshot,calculation_metrics,roi,agent_id,i
 149.59,142.67,2025-06-13 19:20:13.259482,"{'portfolio': {'portfolio_value': 28.543246888948, 'value_in_pools': 0.0, 'value_in_safe': 28.543246888948, 'initial_investment': 279.4700980426851, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xb0Df5A11C1186201A588353F322128cb1fc1C6c7', 'last_updated': 1749818166}, 'positons': []}","{'initial_value': 41.55493662393751, 'final_value': 42.60709513953155, 'f_i_ratio': -0.8978665442605297, 'first_investment_timestamp': 1749822613, 'time_ratio': 8760.0}",2.53,122,False,0xb0Df5A11C1186201A588353F322128cb1fc1C6c7,tevi-kulo15,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,balanced,
 79.1,75.24,2025-06-14 19:22:15.337790,"{'portfolio': {'portfolio_value': 28.545673734743, 'value_in_pools': 0.0, 'value_in_safe': 28.545673734743, 'initial_investment': 362.57997129056014, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xb0Df5A11C1186201A588353F322128cb1fc1C6c7', 'last_updated': 1749907858}, 'positons': []}","{'initial_value': 41.55493662393751, 'final_value': 42.20142283252129, 'f_i_ratio': -0.9212706823459165, 'first_investment_timestamp': 1749909135, 'time_ratio': 8760.0}",1.56,122,False,0xb0Df5A11C1186201A588353F322128cb1fc1C6c7,tevi-kulo15,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,balanced,
 51.44,48.76,2025-06-16 00:58:44.095764,"{'portfolio': {'portfolio_value': 28.545730836997002, 'value_in_pools': 0.0, 'value_in_safe': 28.545730836997002, 'initial_investment': 404.13490791449766, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xb0Df5A11C1186201A588353F322128cb1fc1C6c7', 'last_updated': 1750015702}, 'positons': []}","{'initial_value': 41.55493662393751, 'final_value': 42.04761733525614, 'f_i_ratio': -0.9293658373034275, 'first_investment_timestamp': 1750015724, 'time_ratio': 8760.0}",1.19,122,False,0xb0Df5A11C1186201A588353F322128cb1fc1C6c7,tevi-kulo15,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,balanced,
+52.44,49.22,2025-06-17 01:17:35.998975,"{'portfolio': {'portfolio_value': 28.542561661900002, 'value_in_pools': 0.0, 'value_in_safe': 28.542561661900002, 'initial_investment': 611.9095910341852, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xb0Df5A11C1186201A588353F322128cb1fc1C6c7', 'last_updated': 1750103239}, 'positons': []}","{'initial_value': 41.55493662393751, 'final_value': 42.11768855931876, 'f_i_ratio': -0.9533549366113704, 'first_investment_timestamp': 1750103255, 'time_ratio': 8760.0}",1.35,122,False,0xb0Df5A11C1186201A588353F322128cb1fc1C6c7,tevi-kulo15,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,balanced,
 -0.14,0.55,2025-06-09 00:31:18.357811,"{'portfolio': {'portfolio_value': 20.48830040096, 'value_in_pools': 0.0, 'value_in_safe': 20.48830040096, 'initial_investment': 35.31977903399317, 'volume': 12.850468713455362, 'agent_hash': 'bafybeif5aifwpxf2bjfrtgivuruhrlsqtpr5ynzk5ygkjsujh4gt3fjrmm', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xF38820f03313535A4024DCCBE2689aa7cc158f5C', 'last_updated': 1749409011}, 'positons': [{'chain': 'optimism', 'pool_address': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x94b008aA00579c1307B0EF2c499aD98a8ce58e58', 'token0_symbol': 'USDC', 'token1_symbol': 'USDT', 'apr': 7.203504137155402, 'pool_id': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'is_stable': True, 'is_cl_pool': True, 'status': 'open', 'enter_tx_hash': '0x014828b184e2301849636d82e67614b62b6a83d207ea906c8fbdbc4c94abf6fb', 'enter_timestamp': 1749344469, 'amount0': 9927081, 'amount1': 2922255, 'positions': [{'token_id': 2701571, 'liquidity': 83208800509, 'amount0': 9710239, 'amount1': 2771695, 'current_liquidity': 83208800509}, {'token_id': 2701572, 'liquidity': 822967616, 'amount0': 178339, 'amount1': 109677, 'current_liquidity': 822967616}, {'token_id': 2701573, 'liquidity': 144365258, 'amount0': 38503, 'amount1': 40883, 'current_liquidity': 144365258}]}]}","{'initial_value': 35.31977903399317, 'final_value': 35.27006024007327, 'f_i_ratio': -0.4199199156585539, 'first_investment_timestamp': 1749344469, 'time_ratio': 486.5963969582805}",-0.14,123,False,0xF38820f03313535A4024DCCBE2689aa7cc158f5C,cordron-yelku44,APR,,bafybeif5aifwpxf2bjfrtgivuruhrlsqtpr5ynzk5ygkjsujh4gt3fjrmm,12.850468713455362,balanced,
 346.8,340.52,2025-06-10 02:17:21.916446,"{'portfolio': {'portfolio_value': 20.507856658, 'value_in_pools': 0.0, 'value_in_safe': 20.507856658, 'initial_investment': 2548.4297198347545, 'volume': 12.850468713455362, 'agent_hash': 'bafybeif5aifwpxf2bjfrtgivuruhrlsqtpr5ynzk5ygkjsujh4gt3fjrmm', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xF38820f03313535A4024DCCBE2689aa7cc158f5C', 'last_updated': 1749501754}, 'positons': [{'chain': 'optimism', 'pool_address': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x94b008aA00579c1307B0EF2c499aD98a8ce58e58', 'token0_symbol': 'USDC', 'token1_symbol': 'USDT', 'apr': 7.203504137155402, 'pool_id': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'is_stable': True, 'is_cl_pool': True, 'status': 'open', 'enter_tx_hash': '0x014828b184e2301849636d82e67614b62b6a83d207ea906c8fbdbc4c94abf6fb', 'enter_timestamp': 1749344469, 'amount0': 9927081, 'amount1': 2922255, 'positions': [{'token_id': 2701571, 'liquidity': 83208800509, 'amount0': 9710239, 'amount1': 2771695, 'current_liquidity': 83208800509}, {'token_id': 2701572, 'liquidity': 822967616, 'amount0': 178339, 'amount1': 109677, 'current_liquidity': 822967616}, {'token_id': 2701573, 'liquidity': 144365258, 'amount0': 38503, 'amount1': 40883, 'current_liquidity': 144365258}]}]}","{'initial_value': 47.69366419946237, 'final_value': 48.63267806279609, 'f_i_ratio': -0.9919527478045069, 'first_investment_timestamp': 1749344469, 'time_ratio': 200.13591619225525}",1.97,123,False,0xF38820f03313535A4024DCCBE2689aa7cc158f5C,cordron-yelku44,APR,,bafybeif5aifwpxf2bjfrtgivuruhrlsqtpr5ynzk5ygkjsujh4gt3fjrmm,12.850468713455362,balanced,
 381.81,370.64,2025-06-11 08:14:14.656064,"{'portfolio': {'portfolio_value': 20.497705024200002, 'value_in_pools': 0.0, 'value_in_safe': 20.497705024200002, 'initial_investment': 3693.0776606218556, 'volume': 12.850468713455362, 'agent_hash': 'bafybeif5aifwpxf2bjfrtgivuruhrlsqtpr5ynzk5ygkjsujh4gt3fjrmm', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xF38820f03313535A4024DCCBE2689aa7cc158f5C', 'last_updated': 1749609810}, 'positons': [{'chain': 'optimism', 'pool_address': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x94b008aA00579c1307B0EF2c499aD98a8ce58e58', 'token0_symbol': 'USDC', 'token1_symbol': 'USDT', 'apr': 7.203504137155402, 'pool_id': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'is_stable': True, 'is_cl_pool': True, 'status': 'open', 'enter_tx_hash': '0x014828b184e2301849636d82e67614b62b6a83d207ea906c8fbdbc4c94abf6fb', 'enter_timestamp': 1749344469, 'amount0': 9927081, 'amount1': 2922255, 'positions': [{'token_id': 2701571, 'liquidity': 83208800509, 'amount0': 9710239, 'amount1': 2771695, 'current_liquidity': 83208800509}, {'token_id': 2701572, 'liquidity': 822967616, 'amount0': 178339, 'amount1': 109677, 'current_liquidity': 822967616}, {'token_id': 2701573, 'liquidity': 144365258, 'amount0': 38503, 'amount1': 40883, 'current_liquidity': 144365258}]}]}","{'initial_value': 47.69366419946237, 'final_value': 49.35003012484369, 'f_i_ratio': -0.9944496956447029, 'first_investment_timestamp': 1749344469, 'time_ratio': 118.83083836449264}",3.47,123,False,0xF38820f03313535A4024DCCBE2689aa7cc158f5C,cordron-yelku44,APR,,bafybeif5aifwpxf2bjfrtgivuruhrlsqtpr5ynzk5ygkjsujh4gt3fjrmm,12.850468713455362,balanced,
@@ -114,6 +117,7 @@ apr,adjusted_apr,timestamp,portfolio_snapshot,calculation_metrics,roi,agent_id,i
 99.58,94.56,2025-06-13 20:51:54.959756,"{'portfolio': {'portfolio_value': 20.48904741152, 'value_in_pools': 0.0, 'value_in_safe': 20.48904741152, 'initial_investment': 9988.641334950877, 'volume': 12.850468713455362, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xF38820f03313535A4024DCCBE2689aa7cc158f5C', 'last_updated': 1749827812}, 'positons': [{'chain': 'optimism', 'pool_address': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x94b008aA00579c1307B0EF2c499aD98a8ce58e58', 'token0_symbol': 'USDC', 'token1_symbol': 'USDT', 'apr': 7.203504137155402, 'pool_id': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'is_stable': True, 'is_cl_pool': True, 'status': 'open', 'enter_tx_hash': '0x014828b184e2301849636d82e67614b62b6a83d207ea906c8fbdbc4c94abf6fb', 'enter_timestamp': 1749344469, 'amount0': 9927081, 'amount1': 2922255, 'positions': [{'token_id': 2701571, 'liquidity': 83208800509, 'amount0': 9710239, 'amount1': 2771695, 'current_liquidity': 83208800509}, {'token_id': 2701572, 'liquidity': 822967616, 'amount0': 178339, 'amount1': 109677, 'current_liquidity': 822967616}, {'token_id': 2701573, 'liquidity': 144365258, 'amount0': 38503, 'amount1': 40883, 'current_liquidity': 144365258}]}]}","{'initial_value': 47.69366419946237, 'final_value': 48.45435878622558, 'f_i_ratio': -0.9979487653300927, 'first_investment_timestamp': 1749344469, 'time_ratio': 65.20472127156118}",1.59,123,False,0xF38820f03313535A4024DCCBE2689aa7cc158f5C,cordron-yelku44,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,12.850468713455362,balanced,
 37.24,35.23,2025-06-14 20:58:08.060349,"{'portfolio': {'portfolio_value': 20.487553390400002, 'value_in_pools': 0.0, 'value_in_safe': 20.487553390400002, 'initial_investment': 14090.296456104577, 'volume': 12.850468713455362, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xF38820f03313535A4024DCCBE2689aa7cc158f5C', 'last_updated': 1749914572}, 'positons': [{'chain': 'optimism', 'pool_address': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x94b008aA00579c1307B0EF2c499aD98a8ce58e58', 'token0_symbol': 'USDC', 'token1_symbol': 'USDT', 'apr': 7.203504137155402, 'pool_id': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'is_stable': True, 'is_cl_pool': True, 'status': 'open', 'enter_tx_hash': '0x014828b184e2301849636d82e67614b62b6a83d207ea906c8fbdbc4c94abf6fb', 'enter_timestamp': 1749344469, 'amount0': 9927081, 'amount1': 2922255, 'positions': [{'token_id': 2701571, 'liquidity': 83208800509, 'amount0': 9710239, 'amount1': 2771695, 'current_liquidity': 83208800509}, {'token_id': 2701572, 'liquidity': 822967616, 'amount0': 178339, 'amount1': 109677, 'current_liquidity': 822967616}, {'token_id': 2701573, 'liquidity': 144365258, 'amount0': 38503, 'amount1': 40883, 'current_liquidity': 144365258}]}]}","{'initial_value': 47.69366419946237, 'final_value': 48.02699417703207, 'f_i_ratio': -0.9985459813812843, 'first_investment_timestamp': 1749344469, 'time_ratio': 55.28567011892272}",0.7,123,False,0xF38820f03313535A4024DCCBE2689aa7cc158f5C,cordron-yelku44,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,12.850468713455362,balanced,
 15.26,14.41,2025-06-16 01:13:39.374306,"{'portfolio': {'portfolio_value': 20.48846279456, 'value_in_pools': 0.0, 'value_in_safe': 20.48846279456, 'initial_investment': 15950.349359883581, 'volume': 12.850468713455362, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xF38820f03313535A4024DCCBE2689aa7cc158f5C', 'last_updated': 1750016309}, 'positons': [{'chain': 'optimism', 'pool_address': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x94b008aA00579c1307B0EF2c499aD98a8ce58e58', 'token0_symbol': 'USDC', 'token1_symbol': 'USDT', 'apr': 7.203504137155402, 'pool_id': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'is_stable': True, 'is_cl_pool': True, 'status': 'open', 'enter_tx_hash': '0x014828b184e2301849636d82e67614b62b6a83d207ea906c8fbdbc4c94abf6fb', 'enter_timestamp': 1749344469, 'amount0': 9927081, 'amount1': 2922255, 'positions': [{'token_id': 2701571, 'liquidity': 83208800509, 'amount0': 9710239, 'amount1': 2771695, 'current_liquidity': 83208800509}, {'token_id': 2701572, 'liquidity': 822967616, 'amount0': 178339, 'amount1': 109677, 'current_liquidity': 822967616}, {'token_id': 2701573, 'liquidity': 144365258, 'amount0': 38503, 'amount1': 40883, 'current_liquidity': 144365258}]}]}","{'initial_value': 47.69366419946237, 'final_value': 47.85373070064347, 'f_i_ratio': -0.9987154850133823, 'first_investment_timestamp': 1749344469, 'time_ratio': 46.918072511025315}",0.34,123,False,0xF38820f03313535A4024DCCBE2689aa7cc158f5C,cordron-yelku44,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,12.850468713455362,balanced,
+19.96,18.57,2025-06-17 01:18:21.000045,"{'portfolio': {'portfolio_value': 20.488372010281, 'value_in_pools': 0.0, 'value_in_safe': 20.488372010281, 'initial_investment': 17333.46562166797, 'volume': 12.850468713455362, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xF38820f03313535A4024DCCBE2689aa7cc158f5C', 'last_updated': 1750103262}, 'positons': [{'chain': 'optimism', 'pool_address': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x94b008aA00579c1307B0EF2c499aD98a8ce58e58', 'token0_symbol': 'USDC', 'token1_symbol': 'USDT', 'apr': 7.203504137155402, 'pool_id': '0x84Ce89B4f6F67E523A81A82f9f2F14D84B726F6B', 'is_stable': True, 'is_cl_pool': True, 'status': 'open', 'enter_tx_hash': '0x014828b184e2301849636d82e67614b62b6a83d207ea906c8fbdbc4c94abf6fb', 'enter_timestamp': 1749344469, 'amount0': 9927081, 'amount1': 2922255, 'positions': [{'token_id': 2701571, 'liquidity': 83208800509, 'amount0': 9710239, 'amount1': 2771695, 'current_liquidity': 83208800509}, {'token_id': 2701572, 'liquidity': 822967616, 'amount0': 178339, 'amount1': 109677, 'current_liquidity': 822967616}, {'token_id': 2701573, 'liquidity': 144365258, 'amount0': 38503, 'amount1': 40883, 'current_liquidity': 144365258}]}]}","{'initial_value': 47.69366419946237, 'final_value': 47.929195677066666, 'f_i_ratio': -0.9988179875590102, 'first_investment_timestamp': 1749344469, 'time_ratio': 41.55860585495515}",0.49,123,False,0xF38820f03313535A4024DCCBE2689aa7cc158f5C,cordron-yelku44,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,12.850468713455362,balanced,
 0.0,0.0,2025-06-09 18:32:36.558142,"{'portfolio': {'portfolio_value': 28.724588, 'value_in_pools': 0.0, 'value_in_safe': 28.724588, 'initial_investment': 30.2963222595072, 'volume': None, 'agent_hash': 'bafybeif5aifwpxf2bjfrtgivuruhrlsqtpr5ynzk5ygkjsujh4gt3fjrmm', 'allocations': [], 'portfolio_breakdown': [], 'address': '0x9f3AbFC3301093f39c2A137f87c525b4a0832ba9', 'last_updated': 1749474141}, 'positons': []}","{'initial_value': 30.2963222595072, 'final_value': 30.2963222595072, 'f_i_ratio': -0.05187871471805383, 'first_investment_timestamp': 1749474156, 'time_ratio': 8760.0}",0.0,126,False,0x9f3AbFC3301093f39c2A137f87c525b4a0832ba9,tonvel-beeprel23,APR,,bafybeif5aifwpxf2bjfrtgivuruhrlsqtpr5ynzk5ygkjsujh4gt3fjrmm,,balanced,
 978.68,971.66,2025-06-10 18:35:49.668890,"{'portfolio': {'portfolio_value': 29.825018, 'value_in_pools': 0.0, 'value_in_safe': 29.825018, 'initial_investment': 181.7779335570432, 'volume': None, 'agent_hash': 'bafybeiatbumpchrtaws3j6qwfycudkhcd6idqva5ffibiizy5xgucbsgii', 'allocations': [], 'portfolio_breakdown': [], 'address': '0x9f3AbFC3301093f39c2A137f87c525b4a0832ba9', 'last_updated': 1749559830}, 'positons': []}","{'initial_value': 42.64732311069726, 'final_value': 44.05696363847583, 'f_i_ratio': -0.8359260807052761, 'first_investment_timestamp': 1749560749, 'time_ratio': 8760.0}",3.31,126,False,0x9f3AbFC3301093f39c2A137f87c525b4a0832ba9,tonvel-beeprel23,APR,,bafybeiatbumpchrtaws3j6qwfycudkhcd6idqva5ffibiizy5xgucbsgii,,risky,"[""uniswap_pools_search""]"
 789.88,777.93,2025-06-11 18:38:07.704650,"{'portfolio': {'portfolio_value': 29.824845653892, 'value_in_pools': 0.0, 'value_in_safe': 29.824845653892, 'initial_investment': 354.51522614786535, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0x9f3AbFC3301093f39c2A137f87c525b4a0832ba9', 'last_updated': 1749645511}, 'positons': []}","{'initial_value': 43.72132318471379, 'final_value': 45.83533836834465, 'f_i_ratio': -0.9158714676998039, 'first_investment_timestamp': 1749647287, 'time_ratio': 8760.0}",4.84,126,False,0x9f3AbFC3301093f39c2A137f87c525b4a0832ba9,tonvel-beeprel23,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,risky,"[""uniswap_pools_search""]"
@@ -133,3 +137,4 @@ apr,adjusted_apr,timestamp,portfolio_snapshot,calculation_metrics,roi,agent_id,i
 -0.69,0.49,2025-06-13 07:59:58.559461,"{'portfolio': {'portfolio_value': 15.92175820919, 'value_in_pools': 0.0, 'value_in_safe': 15.92175820919, 'initial_investment': 729.7294822666192, 'volume': 13.377491477361414, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0x4b00f1a232C28254223C8c177E997Ab298e1E40a', 'last_updated': 1749781643}, 'positons': [{'chain': 'optimism', 'pool_address': '0x2FA71491F8070FA644d97b4782dB5734854c0f6F', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x7F5c764cBc14f9669B88837ca1490cCa17c31607', 'token0_symbol': 'USDC', 'token1_symbol': 'USDC.e', 'apr': 5.948351555846092, 'pool_id': '0x2FA71491F8070FA644d97b4782dB5734854c0f6F', 'is_stable': True, 'is_cl_pool': True, 'status': 'open', 'enter_tx_hash': '0x4e71cb688dbfd6ff1dc0621d64060bf7e8822b13b16fc8de2bfac197fbee89dc', 'enter_timestamp': 1749527585, 'amount0': 8357118, 'amount1': 5030943, 'positions': [{'token_id': 2725143, 'liquidity': 264979290127, 'amount0': 8308255, 'amount1': 4939809, 'current_liquidity': 264979290127}, {'token_id': 2725144, 'liquidity': 867486957, 'amount0': 27200, 'amount1': 59543, 'current_liquidity': 867486957}, {'token_id': 2725145, 'liquidity': 266293532, 'amount0': 21663, 'amount1': 31591, 'current_liquidity': 266293532}]}]}","{'initial_value': 43.651793124577026, 'final_value': 43.34997633402806, 'f_i_ratio': -0.9781812869068476, 'first_investment_timestamp': 1749527585, 'time_ratio': 124.05317822877024}",-0.69,128,False,0x4b00f1a232C28254223C8c177E997Ab298e1E40a,kozu-hanfil63,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,13.377491477361414,balanced,
 -2.12,3.5,2025-06-15 20:59:08.057917,"{'portfolio': {'portfolio_value': 15.91742693134, 'value_in_pools': 0.0, 'value_in_safe': 15.91742693134, 'initial_investment': 991.6402410140813, 'volume': 13.377491477361414, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0x4b00f1a232C28254223C8c177E997Ab298e1E40a', 'last_updated': 1750001244}, 'positons': [{'chain': 'optimism', 'pool_address': '0x2FA71491F8070FA644d97b4782dB5734854c0f6F', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x7F5c764cBc14f9669B88837ca1490cCa17c31607', 'token0_symbol': 'USDC', 'token1_symbol': 'USDC.e', 'apr': 5.948351555846092, 'pool_id': '0x2FA71491F8070FA644d97b4782dB5734854c0f6F', 'is_stable': True, 'is_cl_pool': True, 'status': 'open', 'enter_tx_hash': '0x4e71cb688dbfd6ff1dc0621d64060bf7e8822b13b16fc8de2bfac197fbee89dc', 'enter_timestamp': 1749527585, 'amount0': 8357118, 'amount1': 5030943, 'positions': [{'token_id': 2725143, 'liquidity': 264979290127, 'amount0': 8308255, 'amount1': 4939809, 'current_liquidity': 264979290127}, {'token_id': 2725144, 'liquidity': 867486957, 'amount0': 27200, 'amount1': 59543, 'current_liquidity': 867486957}, {'token_id': 2725145, 'liquidity': 266293532, 'amount0': 21663, 'amount1': 31591, 'current_liquidity': 266293532}]}]}","{'initial_value': 43.651793124577026, 'final_value': 42.725034164014204, 'f_i_ratio': -0.9839483854396002, 'first_investment_timestamp': 1749527585, 'time_ratio': 66.56491989613303}",-2.12,128,False,0x4b00f1a232C28254223C8c177E997Ab298e1E40a,kozu-hanfil63,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,13.377491477361414,balanced,
 0.0,0.0,2025-06-15 21:22:42.073588,"{'portfolio': {'portfolio_value': 15.996608, 'value_in_pools': 0.0, 'value_in_safe': 15.996608, 'initial_investment': 15.995250741464774, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xe8c7Bbf632BFf7239e53dAB45086Ac14d6974baC', 'last_updated': 1750002578}, 'positons': []}","{'initial_value': 15.995250741464774, 'final_value': 15.995250741464774, 'f_i_ratio': 8.485384550471764e-05, 'first_investment_timestamp': 1750002762, 'time_ratio': 8760.0}",0.0,133,False,0xe8c7Bbf632BFf7239e53dAB45086Ac14d6974baC,ronwus-yusrus90,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,balanced,
+1.43,0.89,2025-06-16 21:26:14.464595,"{'portfolio': {'portfolio_value': 15.9952, 'value_in_pools': 0.0, 'value_in_safe': 15.9952, 'initial_investment': 191.94300889757733, 'volume': None, 'agent_hash': 'bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby', 'allocations': [], 'portfolio_breakdown': [], 'address': '0xe8c7Bbf632BFf7239e53dAB45086Ac14d6974baC', 'last_updated': 1750083813}, 'positons': []}","{'initial_value': 15.995250741464774, 'final_value': 15.996026011060543, 'f_i_ratio': -0.9166669310235978, 'first_investment_timestamp': 1750089374, 'time_ratio': 8760.0}",0.0,133,False,0xe8c7Bbf632BFf7239e53dAB45086Ac14d6974baC,ronwus-yusrus90,APR,,bafybeidbt5azkdtdvj343jhtksv2jk4cuwaixchxbzmqplfiu5g36fogby,,balanced,

optimus_roi_values.csv

@@ -1,171 +1,399 @@
-roi,timestamp,agent_id,agent_name,is_dummy,metric_type
--0.0002765562977782299,2025-05-15 21:37:27.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:39:37.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:40:02.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:40:28.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:36:35.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:37:02.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:39:10.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:41:11.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:41:55.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:42:41.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:43:24.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:44:09.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:44:51.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:45:37.000000,86,nusus-tayar25,False,ROI
--0.0002765562977782299,2025-05-15 21:46:20.000000,86,nusus-tayar25,False,ROI
--0.00012649422506416652,2025-05-19 22:39:16.682649,86,nusus-tayar25,False,ROI
--0.00010449205744944567,2025-05-19 22:47:57.660329,86,nusus-tayar25,False,ROI
--0.00010449205744944567,2025-05-19 22:53:48.567618,86,nusus-tayar25,False,ROI
--0.00012649422506416652,2025-05-19 22:39:37.060636,86,nusus-tayar25,False,ROI
--0.00010449205744944567,2025-05-19 22:46:29.056289,86,nusus-tayar25,False,ROI
--0.00010449205744944567,2025-05-19 22:51:30.269824,86,nusus-tayar25,False,ROI
--0.00010449205744944567,2025-05-19 22:57:07.717697,86,nusus-tayar25,False,ROI
--0.0011357601313007892,2025-05-23 19:05:51.628406,86,nusus-tayar25,False,ROI
--0.0016374352988718366,2025-05-27 05:42:54.798079,86,nusus-tayar25,False,ROI
--0.8666050938279419,2025-06-04 21:48:07.115718,86,nusus-tayar25,False,ROI
--0.8666050938279419,2025-06-04 21:52:00.578098,86,nusus-tayar25,False,ROI
--0.999999999999975,2025-06-05 01:55:15.033359,86,nusus-tayar25,False,ROI
--0.1696775721419591,2025-06-05 18:27:57.578268,86,nusus-tayar25,False,ROI
-1.8675787957432175,2025-06-06 05:14:51.027065,86,nusus-tayar25,False,ROI
-1.8675787957432175,2025-06-06 03:39:44.505985,86,nusus-tayar25,False,ROI
-1.0420726955249058,2025-05-30 01:10:42.776945,102,kelrus-muha52,False,ROI
-1.0371385033661085,2025-05-30 16:11:26.814088,102,kelrus-muha52,False,ROI
--0.20964670158400078,2025-06-03 19:28:54.348419,102,kelrus-muha52,False,ROI
--0.6044365419107054,2025-06-04 12:35:13.593971,102,kelrus-muha52,False,ROI
--0.6040367838477997,2025-06-04 14:25:41.343980,102,kelrus-muha52,False,ROI
--0.5407000717190478,2025-06-06 13:40:55.755362,111,furtek-gilje55,False,ROI
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--0.9488224700727876,2025-06-12 21:50:15.066243,111,furtek-gilje55,False,ROI
--0.9708794234421507,2025-06-16 20:22:51.755115,111,furtek-gilje55,False,ROI
--0.36854758417016864,2025-06-05 20:46:51.369656,112,vuzus-fazi89,False,ROI
--0.7496728527619763,2025-06-08 02:03:32.248014,112,vuzus-fazi89,False,ROI
--0.5456503958801932,2025-06-06 06:06:41.681577,115,yenot-zoncen49,False,ROI
--0.5456503958801932,2025-06-06 08:19:44.944148,115,yenot-zoncen49,False,ROI
--0.5456503958801932,2025-06-06 09:23:09.755892,115,yenot-zoncen49,False,ROI
--0.5456503958801932,2025-06-06 07:13:18.351148,115,yenot-zoncen49,False,ROI
--0.5456503958801932,2025-06-06 10:29:34.181627,115,yenot-zoncen49,False,ROI
--0.5456503958801932,2025-06-06 11:29:53.721747,115,yenot-zoncen49,False,ROI
--0.6935346167526257,2025-06-06 18:03:43.542513,115,yenot-zoncen49,False,ROI
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--0.5419683668321018,2025-06-06 11:29:18.913469,116,honji-hahi60,False,ROI
--0.5419683668321018,2025-06-06 12:31:08.139923,116,honji-hahi60,False,ROI
--0.6918271067123792,2025-06-06 22:15:03.771384,116,honji-hahi60,False,ROI
--0.6918271067123792,2025-06-07 00:12:24.552821,116,honji-hahi60,False,ROI
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--0.7697658335453386,2025-06-07 15:35:09.317222,116,honji-hahi60,False,ROI
--0.8148303173953624,2025-06-08 00:16:07.222875,116,honji-hahi60,False,ROI
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--0.8842017831796516,2025-06-09 19:31:39.204380,116,honji-hahi60,False,ROI
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--0.8842017831796516,2025-06-10 00:05:22.986881,116,honji-hahi60,False,ROI
--0.8842017831796516,2025-06-10 01:11:09.610266,116,honji-hahi60,False,ROI
--0.8842017831796516,2025-06-09 21:40:11.196609,116,honji-hahi60,False,ROI
--0.8842017831796516,2025-06-09 22:59:27.051209,116,honji-hahi60,False,ROI
--0.8959727145977444,2025-06-10 02:15:06.888709,116,honji-hahi60,False,ROI
--0.8959727145977444,2025-06-10 03:16:08.200810,116,honji-hahi60,False,ROI
--0.9049633984067742,2025-06-10 13:06:56.183812,116,honji-hahi60,False,ROI
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--0.9049633984067742,2025-06-10 15:17:49.725694,116,honji-hahi60,False,ROI
--0.9122831964482513,2025-06-10 19:30:50.269289,116,honji-hahi60,False,ROI
--0.9122831964482513,2025-06-10 20:30:54.841382,116,honji-hahi60,False,ROI
--0.9049633984067742,2025-06-10 16:17:52.268774,116,honji-hahi60,False,ROI
--0.9049633984067742,2025-06-10 17:23:51.522272,116,honji-hahi60,False,ROI
--0.9122831964482513,2025-06-10 18:29:24.025681,116,honji-hahi60,False,ROI
--0.9182298315923811,2025-06-11 22:14:54.110285,116,honji-hahi60,False,ROI
--0.9182298315923811,2025-06-11 23:15:11.685382,116,honji-hahi60,False,ROI
--0.9435336077967746,2025-06-13 18:28:24.365605,116,honji-hahi60,False,ROI
--0.9515049258814656,2025-06-16 13:54:43.588418,116,honji-hahi60,False,ROI
--0.539434826138091,2025-06-07 12:07:37.903080,117,furye-himkon89,False,ROI
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--0.9405482339574164,2025-06-10 19:00:01.668753,117,furye-himkon89,False,ROI
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--0.522856603000806,2025-06-07 16:03:45.373863,118,lonwus-patu86,False,ROI
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--0.5209472494164171,2025-06-06 21:16:18.171681,119,lonlim-zapgi60,False,ROI
--0.8806121461884667,2025-06-07 21:20:52.452249,119,lonlim-zapgi60,False,ROI
--0.9494425475236697,2025-06-08 21:24:43.897906,119,lonlim-zapgi60,False,ROI
--0.9581661316409477,2025-06-09 21:25:09.568709,119,lonlim-zapgi60,False,ROI
--0.9718003547903387,2025-06-10 21:27:14.352202,119,lonlim-zapgi60,False,ROI
--0.9787591800715275,2025-06-12 19:40:26.414300,119,lonlim-zapgi60,False,ROI
--0.9794772304169566,2025-06-13 20:14:38.143005,119,lonlim-zapgi60,False,ROI
--0.9830628598456759,2025-06-15 02:29:15.201154,119,lonlim-zapgi60,False,ROI
--0.984600066632907,2025-06-16 19:00:11.977194,119,lonlim-zapgi60,False,ROI
--0.04228785271807323,2025-06-06 21:35:10.663781,120,joyus-goson39,False,ROI
--0.7433267707945117,2025-06-08 17:03:45.278780,120,joyus-goson39,False,ROI
--0.93143110654765,2025-06-08 22:12:15.454361,120,joyus-goson39,False,ROI
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--0.9958974311434143,2025-06-14 21:11:33.782224,120,joyus-goson39,False,ROI
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