Optimus-Agent-Performance

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gauravlochab commited on Jul 10

Commit

ae827bb

1 Parent(s): 75be6c1

chore:update values

Browse files

Files changed (5) hide show

app.py +6 -6
debug_graph_data.csv +18 -0
debug_roi_data.csv +0 -0
optimus_apr_values.csv +19 -1
optimus_roi_values.csv +755 -529

app.py CHANGED Viewed

@@ -1173,7 +1173,7 @@ def create_combined_roi_time_series_graph(df):
     # IMPORTANT: Filter data by hardcoded date range (June 6 to July 8, 2025)
     min_date = datetime(2025, 6, 6)
-    max_date = datetime(2025, 7, 8, 23, 59, 59)  # Include all of July 8th
     logger.info(f"Filtering ROI data to date range: {min_date} to {max_date}")
     # Count data points before filtering
@@ -1367,7 +1367,7 @@ def create_combined_roi_time_series_graph(df):
     # Update x-axis with better formatting and hardcoded date range (June 6 to July 8)
     min_date = datetime(2025, 6, 6)  # Hardcoded start date: June 6, 2025
-    max_date = datetime(2025, 7, 8)  # Hardcoded end date: July 8, 2025
     logger.info(f"ROI Graph - Hardcoded date range: min_date = {min_date}, max_date = {max_date}")
     fig.update_xaxes(
         showgrid=True,
@@ -1776,9 +1776,9 @@ def create_combined_time_series_graph(df):
     logger.info(f"Unique agents after APR filter: {apr_data['agent_id'].nunique()}")
     logger.info(f"Agent IDs after APR filter: {sorted(apr_data['agent_id'].unique().tolist())}")
-    # Filter APR outliers (±200% range)
     before_outlier_filter = len(apr_data)
-    apr_data = apr_data[(apr_data['apr'] <= 200) & (apr_data['apr'] >= -200)]
     after_outlier_filter = len(apr_data)
     excluded_by_outlier = before_outlier_filter - after_outlier_filter
@@ -1786,7 +1786,7 @@ def create_combined_time_series_graph(df):
     # IMPORTANT: Filter data by hardcoded date range (June 6 to July 8, 2025)
     min_date = datetime(2025, 6, 6)
-    max_date = datetime(2025, 7, 8, 23, 59, 59)  # Include all of July 8th
     logger.info(f"Filtering APR data to date range: {min_date} to {max_date}")
     # Count data points before filtering
@@ -2133,7 +2133,7 @@ def create_combined_time_series_graph(df):
     # Update x-axis with better formatting and hardcoded date range (June 6 to July 8)
     min_date = datetime(2025, 6, 6)  # Hardcoded start date: June 6, 2025
-    max_date = datetime(2025, 7, 8)  # Hardcoded end date: July 8, 2025
     logger.info(f"APR Graph - Hardcoded date range: min_date = {min_date}, max_date = {max_date}")
     fig.update_xaxes(
         showgrid=True,

     # IMPORTANT: Filter data by hardcoded date range (June 6 to July 8, 2025)
     min_date = datetime(2025, 6, 6)
+    max_date = datetime(2025, 7, 9, 23, 59, 59)  # Include all of July 8th
     logger.info(f"Filtering ROI data to date range: {min_date} to {max_date}")
     # Count data points before filtering
     # Update x-axis with better formatting and hardcoded date range (June 6 to July 8)
     min_date = datetime(2025, 6, 6)  # Hardcoded start date: June 6, 2025
+    max_date = datetime(2025, 7, 9)  # Hardcoded end date: July 8, 2025
     logger.info(f"ROI Graph - Hardcoded date range: min_date = {min_date}, max_date = {max_date}")
     fig.update_xaxes(
         showgrid=True,
     logger.info(f"Unique agents after APR filter: {apr_data['agent_id'].nunique()}")
     logger.info(f"Agent IDs after APR filter: {sorted(apr_data['agent_id'].unique().tolist())}")
+    # Filter APR outliers (±500% range)
     before_outlier_filter = len(apr_data)
+    apr_data = apr_data[(apr_data['apr'] <= 500) & (apr_data['apr'] >= -500)]
     after_outlier_filter = len(apr_data)
     excluded_by_outlier = before_outlier_filter - after_outlier_filter
     # IMPORTANT: Filter data by hardcoded date range (June 6 to July 8, 2025)
     min_date = datetime(2025, 6, 6)
+    max_date = datetime(2025, 7, 9, 23, 59, 59)  # Include all of July 8th
     logger.info(f"Filtering APR data to date range: {min_date} to {max_date}")
     # Count data points before filtering
     # Update x-axis with better formatting and hardcoded date range (June 6 to July 8)
     min_date = datetime(2025, 6, 6)  # Hardcoded start date: June 6, 2025
+    max_date = datetime(2025, 7, 9)  # Hardcoded end date: July 8, 2025
     logger.info(f"APR Graph - Hardcoded date range: min_date = {min_date}, max_date = {max_date}")
     fig.update_xaxes(
         showgrid=True,

debug_graph_data.csv CHANGED Viewed

@@ -379,3 +379,21 @@
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 378,539.01,537.62,2025-07-08 21:59:35,"{'portfolio': {'portfolio_value': 30.588488152927663, 'value_in_pools': 28.036751870994866, 'value_in_safe': 2.5517362819327993, 'initial_investment': 30.2963222595072, 'volume': 40.814503767337364, 'roi': 0.96, 'agent_hash': 'bafybeigh6rnrtyhhku2qgd3aerv3lqxodjlxs4vg7v25qdjonh5tcresuy', 'allocations': [{'chain': 'optimism', 'type': 'velodrome', 'id': '0xA56a25Dee5B3199A9198Bbd48715EE3D0ed98378', 'assets': ['USDC', 'DOLA'], 'apr': 1.29, 'details': 'Velodrome Pool', 'ratio': 100.0, 'address': '0x8Ed5ae443fBb1a36E364ac154887f3150669702a'}], 'portfolio_breakdown': [{'asset': 'USDC', 'address': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'balance': 12.10508229581217, 'price': 0.999904, 'value_usd': 12.103920207911774, 'ratio': 0.395702}, {'asset': 'DOLA', 'address': '0x8aE125E8653821E851F12A49F7765db9a9ce7384', 'balance': 18.524432523807125, 'price': 0.997848, 'value_usd': 18.484567945015893, 'ratio': 0.604298}, {'asset': 'LUSD', 'address': '0xc40F949F8a4e094D1b49a23ea9241D289B7b2819', 'balance': 7.15e-16, 'price': 1.002, 'value_usd': 7.1643e-16, 'ratio': 0.0}], 'address': '0x8Ed5ae443fBb1a36E364ac154887f3150669702a', 'last_updated': 1751992020}, 'positons': [{'chain': 'optimism', 'pool_address': '0x2FA71491F8070FA644d97b4782dB5734854c0f6F', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x7F5c764cBc14f9669B88837ca1490cCa17c31607', 'token0_symbol': 'USDC', 'token1_symbol': 'USDC.e', 'apr': 5.949749137116604, 'pool_id': '0x2FA71491F8070FA644d97b4782dB5734854c0f6F', 'is_stable': True, 'is_cl_pool': True, 'status': 'closed', 'enter_tx_hash': '0x965989b30376a87b48a0b7a8eb6aa3a27d3536f5a44819195e9cfbdbb9d50cce', 'enter_timestamp': 1749535827, 'amount0': 7197322, 'amount1': 5578609, 'positions': [{'token_id': 2726290, 'liquidity': 255535328664, 'amount0': 7197322, 'amount1': 5578609, 'current_liquidity': 255535328664}], 'il_risk_score': -4.072206051841395e-13, 'sharpe_ratio': 2.099770154866077, 'depth_score': 1036.9652330166891, 'max_position_size': 10000000.0, 'last_metrics_update': 1751350277.886024, 'exit_tx_hash': '0x9ae93371c59d1b4fb2eb1c9f005236635140a4b1a5a9979b78b3fbb9b7443b88', 'exit_timestamp': 1751351170}, {'chain': 'optimism', 'pool_address': '0xA56a25Dee5B3199A9198Bbd48715EE3D0ed98378', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x8aE125E8653821E851F12A49F7765db9a9ce7384', 'token0_symbol': 'USDC', 'token1_symbol': 'DOLA', 'apr': 1.2908064024200456, 'pool_id': '0xA56a25Dee5B3199A9198Bbd48715EE3D0ed98378', 'is_stable': True, 'is_cl_pool': False, 'amount0': 12467455, 'amount1': 15603398850121910555, 'enter_timestamp': 1751351305, 'status': 'open', 'enter_tx_hash': '0xd81627b62b3cf4bef9c4e5d243fdb4f7a0393e596c940a3d79d847bfe94d4b2c', 'current_liquidity': 14034876077371}]}","{'initial_value': 30.2963222595072, 'final_value': 43.36761896693886, 'f_i_ratio': 0.009643609244642803, 'first_investment_timestamp': 1749535827, 'time_ratio': 12.83857231539205}",43.14,127,False,0x8Ed5ae443fBb1a36E364ac154887f3150669702a,lunel-luwus85,APR,,bafybeigh6rnrtyhhku2qgd3aerv3lqxodjlxs4vg7v25qdjonh5tcresuy,40.81450377,balanced,
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debug_roi_data.csv CHANGED Viewed

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optimus_apr_values.csv CHANGED Viewed

@@ -378,4 +378,22 @@ apr,adjusted_apr,timestamp,portfolio_snapshot,calculation_metrics,roi,agent_id,i
 541.93,536.89,2025-07-08 21:00:52,"{'portfolio': {'portfolio_value': 31.39162409804939, 'value_in_pools': 3.263840491369392, 'value_in_safe': 28.12778360668, 'initial_investment': 29.800137839954267, 'volume': 3.264870839882845, 'roi': 5.34, 'agent_hash': 'bafybeigh6rnrtyhhku2qgd3aerv3lqxodjlxs4vg7v25qdjonh5tcresuy', 'allocations': [{'chain': 'optimism', 'type': 'velodrome', 'id': '0x4F3da11c5caDf644ae023Dbad01008a934C993E2', 'assets': ['USDC', 'LUSD'], 'apr': 1.14, 'details': 'Velodrome Pool', 'ratio': 100.0, 'address': '0xD32613ED605be41D9c7FBc85f2cCb4fBa59778Ac'}], 'portfolio_breakdown': [{'asset': 'USDC', 'address': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'balance': 29.597543024402114, 'price': 0.999905, 'value_usd': 29.594731257814797, 'ratio': 0.942759}, {'asset': 'LUSD', 'address': '0xc40F949F8a4e094D1b49a23ea9241D289B7b2819', 'balance': 1.7950977424921033, 'price': 1.001, 'value_usd': 1.7968928402345954, 'ratio': 0.057241}], 'address': '0xD32613ED605be41D9c7FBc85f2cCb4fBa59778Ac', 'last_updated': 1751982585}, 'positons': [{'chain': 'optimism', 'pool_address': '0x4F3da11c5caDf644ae023Dbad01008a934C993E2', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0xc40F949F8a4e094D1b49a23ea9241D289B7b2819', 'token0_symbol': 'USDC', 'token1_symbol': 'LUSD', 'apr': 1.1446389466076325, 'pool_id': '0x4F3da11c5caDf644ae023Dbad01008a934C993E2', 'is_stable': True, 'is_cl_pool': False, 'amount0': 1516664, 'amount1': 1745457009367349211, 'enter_timestamp': 1751328819, 'status': 'open', 'enter_tx_hash': '0x8b9608f47a0ef16d4b33a5ed94e76d807437737e9527df2920dab175ea801296', 'current_liquidity': 1630885960066}]}","{'initial_value': 29.800137839954267, 'final_value': 44.10938310259678, 'f_i_ratio': 0.05340533210424803, 'first_investment_timestamp': 1751328819, 'time_ratio': 47.79390248771273}",48.02,119,FALSE,0xD32613ED605be41D9c7FBc85f2cCb4fBa59778Ac,lonlim-zapgi60,APR,,bafybeigh6rnrtyhhku2qgd3aerv3lqxodjlxs4vg7v25qdjonh5tcresuy,3.26487084,risky,"[""balancer_pools_search"", ""uniswap_pools_search"", ""velodrome_pools_search""]"
 -3.62,-1.07,2025-07-08 21:47:31,"{'portfolio': {'portfolio_value': 29.75548043486413, 'value_in_pools': 3.0403111059061274, 'value_in_safe': 26.715169328958, 'initial_investment': 30.87536749850655, 'volume': 3.0417491735476907, 'roi': -3.63, 'agent_hash': 'bafybeia2kyreljqwdzhg27g6wv6uwjnoa4qdn5j4kz6jjkmfst4mkyzo3e', 'allocations': [{'chain': 'optimism', 'type': 'velodrome', 'id': '0xA56a25Dee5B3199A9198Bbd48715EE3D0ed98378', 'assets': ['USDC', 'DOLA'], 'apr': 1.29, 'details': 'Velodrome Pool', 'ratio': 100.0, 'address': '0x70FAE90eb66b779FC368350a051D83dc6C7fF068'}], 'portfolio_breakdown': [{'asset': 'USDC', 'address': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'balance': 28.032838645372003, 'price': 0.999813, 'value_usd': 28.02759650454532, 'ratio': 0.941931}, {'asset': 'DOLA', 'address': '0x8aE125E8653821E851F12A49F7765db9a9ce7384', 'balance': 1.7315131819481715, 'price': 0.997904, 'value_usd': 1.727883930318808, 'ratio': 0.058069}], 'address': '0x70FAE90eb66b779FC368350a051D83dc6C7fF068', 'last_updated': 1751990088}, 'positons': [{'chain': 'optimism', 'pool_address': '0xA56a25Dee5B3199A9198Bbd48715EE3D0ed98378', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x8aE125E8653821E851F12A49F7765db9a9ce7384', 'token0_symbol': 'USDC', 'token1_symbol': 'DOLA', 'apr': 1.2907884736104978, 'pool_id': '0xA56a25Dee5B3199A9198Bbd48715EE3D0ed98378', 'is_stable': True, 'is_cl_pool': False, 'amount0': 1352538, 'amount1': 1691492194309012144, 'enter_timestamp': 1751406473, 'status': 'open', 'enter_tx_hash': '0xfc37df1a45d0276566ec626b7abde12d674b10bf07b0eb1ebd8fbc64b7e14c2e', 'current_liquidity': 1521956066056}]}","{'initial_value': 30.87536749850655, 'final_value': 29.756661555593578, 'f_i_ratio': -0.036271214057503554, 'first_investment_timestamp': 1751406473, 'time_ratio': 53.909753780727755}",-3.62,117,FALSE,0x70FAE90eb66b779FC368350a051D83dc6C7fF068,furye-himkon89,APR,,bafybeia2kyreljqwdzhg27g6wv6uwjnoa4qdn5j4kz6jjkmfst4mkyzo3e,3.041749174,risky,"[""balancer_pools_search"", ""uniswap_pools_search"", ""velodrome_pools_search""]"
 539.01,537.62,2025-07-08 21:59:35,"{'portfolio': {'portfolio_value': 30.588488152927663, 'value_in_pools': 28.036751870994866, 'value_in_safe': 2.5517362819327993, 'initial_investment': 30.2963222595072, 'volume': 40.814503767337364, 'roi': 0.96, 'agent_hash': 'bafybeigh6rnrtyhhku2qgd3aerv3lqxodjlxs4vg7v25qdjonh5tcresuy', 'allocations': [{'chain': 'optimism', 'type': 'velodrome', 'id': '0xA56a25Dee5B3199A9198Bbd48715EE3D0ed98378', 'assets': ['USDC', 'DOLA'], 'apr': 1.29, 'details': 'Velodrome Pool', 'ratio': 100.0, 'address': '0x8Ed5ae443fBb1a36E364ac154887f3150669702a'}], 'portfolio_breakdown': [{'asset': 'USDC', 'address': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'balance': 12.10508229581217, 'price': 0.999904, 'value_usd': 12.103920207911774, 'ratio': 0.395702}, {'asset': 'DOLA', 'address': '0x8aE125E8653821E851F12A49F7765db9a9ce7384', 'balance': 18.524432523807125, 'price': 0.997848, 'value_usd': 18.484567945015893, 'ratio': 0.604298}, {'asset': 'LUSD', 'address': '0xc40F949F8a4e094D1b49a23ea9241D289B7b2819', 'balance': 7.15e-16, 'price': 1.002, 'value_usd': 7.1643e-16, 'ratio': 0.0}], 'address': '0x8Ed5ae443fBb1a36E364ac154887f3150669702a', 'last_updated': 1751992020}, 'positons': [{'chain': 'optimism', 'pool_address': '0x2FA71491F8070FA644d97b4782dB5734854c0f6F', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x7F5c764cBc14f9669B88837ca1490cCa17c31607', 'token0_symbol': 'USDC', 'token1_symbol': 'USDC.e', 'apr': 5.949749137116604, 'pool_id': '0x2FA71491F8070FA644d97b4782dB5734854c0f6F', 'is_stable': True, 'is_cl_pool': True, 'status': 'closed', 'enter_tx_hash': '0x965989b30376a87b48a0b7a8eb6aa3a27d3536f5a44819195e9cfbdbb9d50cce', 'enter_timestamp': 1749535827, 'amount0': 7197322, 'amount1': 5578609, 'positions': [{'token_id': 2726290, 'liquidity': 255535328664, 'amount0': 7197322, 'amount1': 5578609, 'current_liquidity': 255535328664}], 'il_risk_score': -4.072206051841395e-13, 'sharpe_ratio': 2.099770154866077, 'depth_score': 1036.9652330166891, 'max_position_size': 10000000.0, 'last_metrics_update': 1751350277.886024, 'exit_tx_hash': '0x9ae93371c59d1b4fb2eb1c9f005236635140a4b1a5a9979b78b3fbb9b7443b88', 'exit_timestamp': 1751351170}, {'chain': 'optimism', 'pool_address': '0xA56a25Dee5B3199A9198Bbd48715EE3D0ed98378', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x8aE125E8653821E851F12A49F7765db9a9ce7384', 'token0_symbol': 'USDC', 'token1_symbol': 'DOLA', 'apr': 1.2908064024200456, 'pool_id': '0xA56a25Dee5B3199A9198Bbd48715EE3D0ed98378', 'is_stable': True, 'is_cl_pool': False, 'amount0': 12467455, 'amount1': 15603398850121910555, 'enter_timestamp': 1751351305, 'status': 'open', 'enter_tx_hash': '0xd81627b62b3cf4bef9c4e5d243fdb4f7a0393e596c940a3d79d847bfe94d4b2c', 'current_liquidity': 14034876077371}]}","{'initial_value': 30.2963222595072, 'final_value': 43.36761896693886, 'f_i_ratio': 0.009643609244642803, 'first_investment_timestamp': 1749535827, 'time_ratio': 12.83857231539205}",43.14,127,FALSE,0x8Ed5ae443fBb1a36E364ac154887f3150669702a,lunel-luwus85,APR,,bafybeigh6rnrtyhhku2qgd3aerv3lqxodjlxs4vg7v25qdjonh5tcresuy,40.81450377,balanced,
-466.29,465.6,2025-07-08 22:52:37,"{'portfolio': {'portfolio_value': 35.409517803737295, 'value_in_pools': 32.201910924357904, 'value_in_safe': 3.2076068793793917, 'initial_investment': 35.31977903399317, 'volume': 45.04515215024694, 'roi': 0.25, 'agent_hash': 'bafybeigh6rnrtyhhku2qgd3aerv3lqxodjlxs4vg7v25qdjonh5tcresuy', 'allocations': [{'chain': 'optimism', 'type': 'velodrome', 'id': '0xA56a25Dee5B3199A9198Bbd48715EE3D0ed98378', 'assets': ['USDC', 'DOLA'], 'apr': 1.29, 'details': 'Velodrome Pool', 'ratio': 100.0, 'address': '0xF38820f03313535A4024DCCBE2689aa7cc158f5C'}], 'portfolio_breakdown': [{'asset': 'USDC', 'address': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'balance': 13.902874202908865, 'price': 0.999805, 'value_usd': 13.900163142439297, 'ratio': 0.392554}, {'asset': 'DOLA', 'address': '0x8aE125E8653821E851F12A49F7765db9a9ce7384', 'balance': 21.551466226302054, 'price': 0.998046, 'value_usd': 21.50935466129586, 'ratio': 0.607446}, {'asset': 'ETH', 'address': '0x0000000000000000000000000000000000000000', 'balance': 8.4e-16, 'price': 2542.79, 'value_usd': 2.1359436e-12, 'ratio': 0.0}, {'asset': 'LUSD', 'address': '0xc40F949F8a4e094D1b49a23ea9241D289B7b2819', 'balance': 1.146e-15, 'price': 1.002, 'value_usd': 1.148292e-15, 'ratio': 0.0}], 'address': '0xF38820f03313535A4024DCCBE2689aa7cc158f5C', 'last_updated': 1751994860}, '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': 'closed', '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}], 'il_risk_score': -8.510250350090276e-12, 'sharpe_ratio': 1.0343385680307111, 'depth_score': 1162.849768076878, 'max_position_size': 10000000.0, 'last_metrics_update': 1751159186.298078, 'exit_tx_hash': '0xbfb170fda9e5614f008a6cd6cd589fb7b47c8d831a5d4a0b3e8e870c0451bc40', 'exit_timestamp': 1751159352}, {'chain': 'optimism', 'pool_address': '0xA56a25Dee5B3199A9198Bbd48715EE3D0ed98378', 'dex_type': 'velodrome', 'token0': '0x0b2C639c533813f4Aa9D7837CAf62653d097Ff85', 'token1': '0x8aE125E8653821E851F12A49F7765db9a9ce7384', 'token0_symbol': 'USDC', 'token1_symbol': 'DOLA', 'apr': 1.2907413138010941, 'pool_id': '0xA56a25Dee5B3199A9198Bbd48715EE3D0ed98378', 'is_stable': True, 'is_cl_pool': False, 'amount0': 13649004, 'amount1': 18593021233907056326, 'enter_timestamp': 1751159541, 'status': 'open', 'enter_tx_hash': '0x48c5280931b620ff55cb117c35ca44b6780ff8dcb0fdfca2ff04a0aea368af09', 'current_liquidity': 16118778992940}]}","{'initial_value': 35.31977903399317, 'final_value': 49.275624809858726, 'f_i_ratio': 0.0025407511654520487, 'first_investment_timestamp': 1749344469, 'time_ratio': 11.896390284530234}",39.51,123,FALSE,0xF38820f03313535A4024DCCBE2689aa7cc158f5C,cordron-yelku44,APR,,bafybeigh6rnrtyhhku2qgd3aerv3lqxodjlxs4vg7v25qdjonh5tcresuy,45.04515215,balanced,

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optimus_roi_values.csv CHANGED Viewed

@@ -1,529 +1,755 @@
-roi,timestamp,agent_id,agent_name,is_dummy,metric_type
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--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
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