Fix

Signed-off-by: elronbandel <elronbandel@gmail.com>

src/unitxt/inference.py

@@ -15,12 +15,13 @@
 from tqdm import tqdm, trange
 from tqdm.asyncio import tqdm_asyncio
 
-from .artifact import Artifact, fetch_artifact
+from .artifact import Artifact
 from .dataclass import InternalField, NonPositionalField
 from .deprecation_utils import deprecation
 from .image_operators import data_url_to_image, extract_images
 from .logging_utils import get_logger
 from .operator import PackageRequirementsMixin
+from .operators import ArtifactFetcherMixin
 from .settings_utils import get_constants, get_settings
 
 constants = get_constants()
@@ -343,7 +344,7 @@ class IbmGenAiInferenceEngineParams(Artifact):
     typical_p: Optional[float] = None
 
 
-class GenericInferenceEngine(InferenceEngine):
+class GenericInferenceEngine(InferenceEngine, ArtifactFetcherMixin):
     default: Optional[str] = None
 
     def prepare_engine(self):
@@ -359,7 +360,7 @@ def prepare_engine(self):
                 "\nor passing a similar required engine in the default argument"
             )
             engine_reference = self.default
-        self.engine, _ = fetch_artifact(engine_reference)
+        self.engine = self.get_artifact(engine_reference)
 
     def get_engine_id(self):
         return "generic_inference_engine"

src/unitxt/llm_as_judge.py

@@ -2,12 +2,12 @@
 from typing import Any, Dict, List, Literal, Optional
 
 from .api import infer
-from .artifact import fetch_artifact
 from .dataclass import Field
 from .formats import Format, SystemFormat
 from .inference import InferenceEngine, LogProbInferenceEngine, OpenAiInferenceEngine
 from .metrics import BulkInstanceMetric
 from .operator import SequentialOperator
+from .operators import ArtifactFetcherMixin
 from .settings_utils import get_settings
 from .system_prompts import EmptySystemPrompt, SystemPrompt
 from .templates import Template
@@ -122,7 +122,7 @@ def get_metric_results_from_prediction_outputs(
         pass
 
 
-class LLMAsJudge(LLMAsJudgeBase):
+class LLMAsJudge(LLMAsJudgeBase, ArtifactFetcherMixin):
     """LLM-as-judge-based metric class for evaluating correctness of generated predictions.
 
     This class uses the source prompt given to the generator and the generator's predictions to evaluate
@@ -156,7 +156,7 @@ def _get_input_instances(self, task_data: List[Dict]) -> List:
             instances = []
             for task_data_instance in task_data:
                 template = task_data_instance["metadata"]["template"]
-                template, _ = fetch_artifact(template)
+                template = self.get_artifact(template)
                 instance = SequentialOperator(
                     steps=[template, "formats.empty"]
                 ).process_instance(

src/unitxt/metrics.py

@@ -17,7 +17,7 @@
 from scipy.stats import bootstrap
 from scipy.stats._warnings_errors import DegenerateDataWarning
 
-from .artifact import Artifact, fetch_artifact
+from .artifact import Artifact
 from .dataclass import (
     AbstractField,
     InternalField,
@@ -37,7 +37,7 @@
     StreamingOperator,
     StreamOperator,
 )
-from .operators import Copy, Set
+from .operators import ArtifactFetcherMixin, Copy, Set
 from .random_utils import get_seed
 from .settings_utils import get_settings
 from .stream import MultiStream, Stream
@@ -4812,7 +4812,7 @@ def _prepare_instances_for_model(self, texts: List[str]):
         return processed_stream.to_dataset()["test"]
 
 
-class MetricsEnsemble(InstanceMetric):
+class MetricsEnsemble(InstanceMetric, ArtifactFetcherMixin):
     """Metrics Ensemble class for creating ensemble of given metrics.
 
     Attributes:
@@ -4836,7 +4836,7 @@ def get_prefix_name(self, i):
 
     def prepare(self):
         super().prepare()
-        self.metrics = [fetch_artifact(metric)[0] for metric in self.metrics]
+        self.metrics = [self.get_artifact(metric) for metric in self.metrics]
         for i, metric in enumerate(self.metrics):
             metric.score_prefix = self.get_prefix_name(i)
         if self.weights is None:

src/unitxt/operators.py

@@ -1039,10 +1039,10 @@ class ArtifactFetcherMixin:
 
     @classmethod
     def get_artifact(cls, artifact_identifier: str) -> Artifact:
-        if artifact_identifier not in cls._artifacts_cache:
+        if str(artifact_identifier) not in cls._artifacts_cache:
             artifact, catalog = fetch_artifact(artifact_identifier)
-            cls._artifacts_cache[artifact_identifier] = artifact
-        return shallow_copy(cls._artifacts_cache[artifact_identifier])
+            cls._artifacts_cache[str(artifact_identifier)] = artifact
+        return shallow_copy(cls._artifacts_cache[str(artifact_identifier)])
 
 
 class ApplyOperatorsField(InstanceOperator):

src/unitxt/task.py

@@ -2,11 +2,11 @@
 from functools import lru_cache
 from typing import Any, Dict, List, Optional, Union
 
-from .artifact import fetch_artifact
 from .deprecation_utils import deprecation
 from .error_utils import Documentation, UnitxtError, UnitxtWarning
 from .logging_utils import get_logger
 from .operator import InstanceOperator
+from .operators import ArtifactFetcherMixin
 from .settings_utils import get_constants
 from .type_utils import (
     Type,
@@ -35,7 +35,7 @@ def parse_string_types_instead_of_actual_objects(obj):
     return parse_type_string(obj)
 
 
-class Task(InstanceOperator):
+class Task(InstanceOperator, ArtifactFetcherMixin):
     """Task packs the different instance fields into dictionaries by their roles in the task.
 
     Attributes:
@@ -184,10 +184,10 @@ def process_data_before_dump(self, data):
                 data["prediction_type"] = to_type_string(data["prediction_type"])
         return data
 
-    @staticmethod
+    @classmethod
     @lru_cache(maxsize=None)
-    def get_metric_prediction_type(metric_id: str):
-        metric = fetch_artifact(metric_id)[0]
+    def get_metric_prediction_type(cls, metric_id: str):
+        metric = cls.get_artifact(metric_id)
         return metric.prediction_type
 
     def check_metrics_type(self) -> None: