SIENTIAPDE-1182

Update README.md to reflect new prediction workflow configuration

- Revised input parameters for the prediction process, including changes to schedule name, model ID, and workflow type.
- Introduced new fields for workflow execution frequency, maximum retry policy, and query for data retrieval.
- Updated input and MLflow filter structures to enhance clarity and functionality.
- Added support for datetime columns and updated retention time for models.

README.md

@@ -314,34 +314,71 @@ The **PredictionProcess** workflow implements the core prediction pipeline for M
 #### Input Parameters
 ```json
 {
-  "metadata": {
-    "schedule_name": "hourly_predictions",
-    "model_name": "temperature_prediction_model",
-    "model_id": "temp_pred_001",
-    "workflow_name": "predictions_batch"
+  "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"
     },
-  "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"]}
+    {
+      "server_id": "1",
+      "type": "confidence",
+      "addr": "ns=2;i=5",
+      "data_type": "double"
     }
+  ],
+  "input_filters": [
+    {
+      "filter_name": "EMPTY_DATA", # Required filter
+      "policy": "STOP"
     },
-  "mlflow_transform_filters": {
-    "API_ERROR": {"POLICY": "STOP"}
+    {
+      "filter_name": "SPECIFIC_VARIABLES_NULL_VALUES",
+      "policy": "CONTINUE",
+      "config": {
+        "variables": [
+          "Counter"
+        ]
+      }
+    }
+  ],
+  "mlflow_transform_filters": [
+    {
+      "filter_name": "API_ERROR", # Required filter
+      "policy": "REPEAT"
     },
-  "mlflow_predict_filters": {
-    "API_ERROR": {"POLICY": "STOP"},
-    "NAN_VALUES": {"POLICY": "STOP"}
-  },
-  "model_retention": 60,
-  "path_priority": ["STOP", "CONTINUE", "REPEAT"],
-  "opc_output_config": {...}
+    {
+      "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"
+  }
 }
 ```