fix

python/knext/knext/component/builder/mapping.py

@@ -422,8 +422,9 @@ class SubGraphMapping(Mapping):
                     operator_config=predicting_strategy.to_rest()
                 )
             elif not predicting_strategy:
-                if (self.spg_type_name, predicate_name) in PredictOp.bind_schemas:
-                    op_name = PredictOp.bind_schemas[(self.spg_type_name, predicate_name)]
+                object_type_name = spg_type.properties[predicate_name].object_type_name
+                if (self.spg_type_name, predicate_name, object_type_name) in PredictOp.bind_schemas:
+                    op_name = PredictOp.bind_schemas[(self.spg_type_name, predicate_name, object_type_name)]
                     op = PredictOp.by_name(op_name)()
                     strategy_config = rest.OperatorPredictingConfig(
                         operator_config=op.to_rest()
@@ -434,7 +435,7 @@ class SubGraphMapping(Mapping):
                 raise ValueError(f"Invalid predicting_strategy [{predicting_strategy}].")
             if strategy_config:
                 predicting_configs.append(
-                    strategy_config
+                    rest.PredictingConfig(target=predicate_name,predicting_config=strategy_config)
                 )
 
         if isinstance(self.subject_fusing_strategy, FuseOp):

python/knext/knext/examples/financial/builder/job/state_and_indicator.py

@@ -1,21 +1,20 @@
 # -*- coding: utf-8 -*-
 
 from knext.client.model.builder_job import BuilderJob
-from knext.api.component import CSVReader, SPGTypeMapping, KGWriter
-from knext.component.builder import LLMBasedExtractor, SubGraphMapping
+from knext.api.component import (
+    CSVReader,
+    LLMBasedExtractor,
+    KGWriter,
+    SubGraphMapping
+)
 from nn4k.invoker import LLMInvoker
 
-try:
-    from schema.financial_schema_helper import Financial
-except:
-    pass
-
 
 class StateAndIndicator(BuilderJob):
 
     def build(self):
         source = CSVReader(
-            local_path="/Users/jier/openspg/python/knext/knext/examples/financial/builder/job/data/document.csv",
+            local_path="builder/job/data/document.csv",
             columns=["input"],
             start_row=2
         )
@@ -23,7 +22,7 @@ class StateAndIndicator(BuilderJob):
         from knext.examples.financial.builder.operator.IndicatorNER import IndicatorNER
         from knext.examples.financial.builder.operator.IndicatorREL import IndicatorREL
         from knext.examples.financial.builder.operator.IndicatorLOGIC import IndicatorLOGIC
-        extract = LLMBasedExtractor(llm=LLMInvoker.from_config("/Users/jier/openspg/python/knext/knext/examples/financial/builder/model/openai_infer.json"),
+        extract = LLMBasedExtractor(llm=LLMInvoker.from_config("builder/model/openai_infer.json"),
                                     prompt_ops=[IndicatorNER(), IndicatorREL(), IndicatorLOGIC()]
                                     )
 
@@ -36,7 +35,6 @@ class StateAndIndicator(BuilderJob):
         indicator_mapping = SubGraphMapping(spg_type_name="Financial.Indicator")\
             .add_mapping_field("id", "id") \
             .add_mapping_field("name", "name")
-            # .add_predicting_field("isA")
 
         sink = KGWriter()
 

python/knext/knext/operator/op.py

@@ -134,7 +134,7 @@ class PredictOp(BaseOp, ABC):
 
     bind_to: Tuple[SPGTypeName, PropertyName, SPGTypeName]
 
-    bind_schemas: Dict[Tuple[SPGTypeName, PropertyName], str] = {}
+    bind_schemas: Dict[Tuple[SPGTypeName, PropertyName, SPGTypeName], str] = {}
 
     def invoke(self, subject_record: SPGRecord) -> List[SPGRecord]:
         raise NotImplementedError(
@@ -143,9 +143,7 @@ class PredictOp(BaseOp, ABC):
 
     @staticmethod
     def _pre_process(*inputs):
-        return [
-            SPGRecord.from_dict(input) for input in inputs[0]
-        ],
+        return SPGRecord.from_dict(inputs[0]),
 
     @staticmethod
     def _post_process(output) -> Dict[str, Any]: