[NET-968] refactor: Update evaluation module to enhance readability

CHANGELOG.md

@@ -281,4 +281,4 @@ Users can be now overwrite the input and ouput attributes of spans created by in
 
 - Added utility to set input and output data for any active span in a trace
 
-[0.1.86]: https://github.com/KeyValueSoftwareSystems/netra-sdk-py/tree/main
+[0.1.89]: https://github.com/KeyValueSoftwareSystems/netra-sdk-py/tree/main

netra/__init__.py

@@ -292,6 +292,20 @@ def shutdown(cls) -> None:
                 except Exception:
                     pass
 
+            # Close simulation HTTP client
+            if hasattr(cls, "simulation") and cls.simulation is not None:
+                try:
+                    cls.simulation.close()
+                except Exception:
+                    pass
+
+            # Close evaluation HTTP client
+            if hasattr(cls, "evaluation") and cls.evaluation is not None:
+                try:
+                    cls.evaluation.close()
+                except Exception:
+                    pass
+
     @classmethod
     def get_meter(cls, name: str = "netra", version: Optional[str] = None) -> otel_metrics.Meter:
         """
@@ -409,6 +423,47 @@ def set_custom_event(cls, event_name: str, attributes: Any) -> None:
         else:
             logger.warning("Both event_name and attributes must be provided for custom events.")
 
+    @classmethod
+    def record_exception(
+        cls,
+        exception: BaseException,
+        attributes: Optional[Dict[str, Any]] = None,
+    ) -> None:
+        """Record a caught exception on the currently active span.
+
+        Use this inside ``except`` blocks to attach exception details to the
+        current span when the exception is being handled and will not propagate
+        to the SDK's automatic capture logic.
+
+        The method adds a standard OpenTelemetry exception event (with type,
+        message, and stacktrace), sets the span status to ERROR, and records
+        the ``netra.error_message`` attribute for consistency with the rest of
+        the SDK.
+
+        Args:
+            exception: The exception instance to record.
+            attributes: Optional extra attributes to attach to the exception
+                event.
+
+        Example::
+
+            @workflow
+            def process_order(order_id: str) -> str:
+                try:
+                    result = call_payment_api(order_id)
+                except PaymentError as exc:
+                    Netra.record_exception(exc)
+                    return "fallback_result"
+                return result
+        """
+        if not isinstance(exception, BaseException):
+            logger.error(
+                "record_exception: exception must be a BaseException instance, got %s",
+                type(exception),
+            )
+            return
+        SessionManager.record_exception(exception, attributes=attributes)
+
     @classmethod
     def add_conversation(cls, conversation_type: ConversationType, role: str, content: Any) -> None:
         """
@@ -461,6 +516,28 @@ def set_root_output(cls, value: Any) -> None:
         """
         SessionManager.set_root_output(value)
 
+    @classmethod
+    def set_root_output_stream(cls, value: Any) -> Any:
+        """
+        Wrap a stream so the accumulated output is set on the root span when iteration ends.
+
+        The returned object is a transparent proxy — iterate over it instead of the original::
+
+            stream = Netra.set_root_output_stream(stream)
+            for chunk in stream:
+                ...
+
+        Supports both sync and async iterables.  Returns *value* unchanged if no active trace
+        context exists or if *value* is not iterable.
+
+        Args:
+            value: The stream to wrap (Netra-instrumented or any generic iterable).
+
+        Returns:
+            A wrapped stream proxy, or *value* unchanged if wrapping is not possible.
+        """
+        return SessionManager.set_root_output_stream(value)
+
     @classmethod
     def start_span(
         cls,

netra/evaluation/__init__.py

@@ -1,16 +1,20 @@
 from netra.evaluation.api import Evaluation
 from netra.evaluation.evaluator import BaseEvaluator
 from netra.evaluation.models import (
+    Dataset,
     DatasetItem,
     EvaluatorConfig,
     EvaluatorContext,
     EvaluatorOutput,
     LocalDataset,
     ScoreType,
+    TurnType,
 )
 
 __all__ = [
     "Evaluation",
+    "Dataset",
+    "TurnType",
     "DatasetItem",
     "BaseEvaluator",
     "EvaluatorContext",