From aa45fc8b99248d89195d7750648bce1cd930da26 Mon Sep 17 00:00:00 2001
From: vitor-aignosi <vitor.santos@aignosi.com.br>
Date: Fri, 29 Aug 2025 15:59:46 -0300
Subject: [PATCH] SIENTIAPDE-1182  Update README.md to reflect changes in
 prediction workflow configuration

- Revised input parameters for the prediction process, including updates to schedule name, model ID, and workflow name.
- Enhanced structure of input filters and MLflow filter policies for improved clarity and functionality.
- Introduced new fields for model retention and output configuration, while maintaining backward compatibility with existing parameters.
---
 README.md | 170 +++++++++++++++++++++++++++++-------------------------
 1 file changed, 91 insertions(+), 79 deletions(-)

diff --git a/README.md b/README.md
index 3886d8b..e9562b0 100644
--- a/README.md
+++ b/README.md
@@ -314,71 +314,34 @@ The **PredictionProcess** workflow implements the core prediction pipeline for M
 #### Input Parameters
 ```json
 {
-  "schedule_name": "laborious-orchestrated-pipeline",
-  "model_id": "1",
-  "workflow_type": "predictions_batch",
-  "frequency": "30s", # Workflow execution frequency
-  "max_retry_policy": 1, # Maximum number of retries for the workflow
-  "query": "select * from sientia_data.laborious_data where model_id = 1 and \"timestamp\" > NOW() - INTERVAL '5 minutes' order by \"timestamp\" desc limit 30;",
-  "retention_time": 60, # Retention time for models in minutes
-  "write_tags": [
-    {
-      "server_id": "1",
-      "type": "prediction", # Type of tag to write, can be prediction or confidence
-      "addr": "ns=2;i=5",
-      "data_type": "double"
-    },
-    {
-      "server_id": "1",
-      "type": "confidence",
-      "addr": "ns=2;i=5",
-      "data_type": "double"
+  "metadata": {
+    "schedule_name": "hourly_predictions",
+    "model_name": "temperature_prediction_model",
+    "model_id": "temp_pred_001",
+    "workflow_name": "predictions_batch"
+  },
+  "data": {...},
+  "schema": {...},
+  "table_name": "predictions",
+  "model_id": "temp_pred_001",
+  "model_name": "temperature_prediction_model",
+  "input_filters": {
+    "EMPTY_DATA": {"POLICY": "STOP"},
+    "SPECIFIC_VARIABLES_NULL_VALUES": {
+      "POLICY": "STOP",
+      "config": {"variables": ["temperature", "humidity"]}
     }
-  ],
-  "input_filters": [
-    {
-      "filter_name": "EMPTY_DATA", # Required filter
-      "policy": "STOP"
-    },
-    {
-      "filter_name": "SPECIFIC_VARIABLES_NULL_VALUES",
-      "policy": "CONTINUE",
-      "config": {
-        "variables": [
-          "Counter"
-        ]
-      }
-    }
-  ],
-  "mlflow_transform_filters": [
-    {
-      "filter_name": "API_ERROR", # Required filter
-      "policy": "REPEAT"
-    },
-    {
-      "filter_name": "NAN_VALUES",
-      "policy": "STOP"
-    }
-  ],
-  "mlflow_predict_filters": [
-    {
-      "filter_name": "API_ERROR", # Required filter
-      "policy": "CONTINUE"
-    }
-  ],
-  "path_priority": [ # In case of multiple filters catch problems, this will determine the path to take
-    "STOP",
-    "CONTINUE",
-    "REPEAT"
-  ],
-  "active": true,
-  "datetime_columns": [ # Columns in data comming from query that are datetime
-    "timestamp",
-    "created_at"
-  ],
-  "updated_at": {
-    "$date": "2025-08-27T18:35:01.600Z"
-  }
+  },
+  "mlflow_transform_filters": {
+    "API_ERROR": {"POLICY": "STOP"}
+  },
+  "mlflow_predict_filters": {
+    "API_ERROR": {"POLICY": "STOP"},
+    "NAN_VALUES": {"POLICY": "STOP"}
+  },
+  "model_retention": 60,
+  "path_priority": ["STOP", "CONTINUE", "REPEAT"],
+  "opc_output_config": {...}
 }
 ```
 
@@ -659,22 +622,71 @@ Workflows are configured through input parameters and filter policies:
 
 ```json
 {
-  "input_filters": {
-    "EMPTY_DATA": {"POLICY": "STOP"},
-    "SPECIFIC_VARIABLES_NULL_VALUES": {
-      "POLICY": "STOP",
-      "config": {"variables": ["temperature", "humidity"]}
+  "schedule_name": "laborious-orchestrated-pipeline",
+  "model_id": "1",
+  "workflow_type": "predictions_batch",
+  "frequency": "30s", # Workflow execution frequency
+  "max_retry_policy": 1, # Maximum number of retries for the workflow
+  "query": "select * from sientia_data.laborious_data where model_id = 1 and \"timestamp\" > NOW() - INTERVAL '5 minutes' order by \"timestamp\" desc limit 30;",
+  "retention_time": 60, # Retention time for models in minutes
+  "write_tags": [
+    {
+      "server_id": "1",
+      "type": "prediction", # Type of tag to write, can be prediction or confidence
+      "addr": "ns=2;i=5",
+      "data_type": "double"
+    },
+    {
+      "server_id": "1",
+      "type": "confidence",
+      "addr": "ns=2;i=5",
+      "data_type": "double"
     }
-  },
-  "mlflow_transform_filters": {
-    "API_ERROR": {"POLICY": "STOP"}
-  },
-  "mlflow_predict_filters": {
-    "API_ERROR": {"POLICY": "STOP"},
-    "NAN_VALUES": {"POLICY": "STOP"}
-  },
-  "path_priority": ["STOP", "CONTINUE", "REPEAT"],
-  "model_retention": 60
+  ],
+  "input_filters": [
+    {
+      "filter_name": "EMPTY_DATA", # Required filter
+      "policy": "STOP"
+    },
+    {
+      "filter_name": "SPECIFIC_VARIABLES_NULL_VALUES",
+      "policy": "CONTINUE",
+      "config": {
+        "variables": [
+          "Counter"
+        ]
+      }
+    }
+  ],
+  "mlflow_transform_filters": [
+    {
+      "filter_name": "API_ERROR", # Required filter
+      "policy": "REPEAT"
+    },
+    {
+      "filter_name": "NAN_VALUES",
+      "policy": "STOP"
+    }
+  ],
+  "mlflow_predict_filters": [
+    {
+      "filter_name": "API_ERROR", # Required filter
+      "policy": "CONTINUE"
+    }
+  ],
+  "path_priority": [ # In case of multiple filters catch problems, this will determine the path to take
+    "STOP",
+    "CONTINUE",
+    "REPEAT"
+  ],
+  "active": true,
+  "datetime_columns": [ # Columns in data comming from query that are datetime
+    "timestamp",
+    "created_at"
+  ],
+  "updated_at": {
+    "$date": "2025-08-27T18:35:01.600Z"
+  }
 }
 ```