fix: Fix gliner2 1.3 compatibility (engine submodule removal)

sieves/model_wrappers/gliner_.py

@@ -12,7 +12,19 @@
 from sieves.model_wrappers.core import Executable, ModelWrapper
 from sieves.model_wrappers.types import TokenUsage
 
-PromptSignature = gliner2.inference.engine.Schema | gliner2.inference.engine.StructureBuilder
+# gliner2 1.3 removed the `gliner2.inference.engine` submodule and re-exports
+# `Schema`/`StructureBuilder` at the package root. Resolve them in a way that
+# works for both 1.2 (engine submodule) and 1.3+ (top-level re-export).
+try:
+    Schema = gliner2.Schema
+    StructureBuilder = gliner2.StructureBuilder
+except AttributeError:  # pragma: no cover - gliner2 < 1.3 fallback
+    from gliner2.inference import engine as _gliner2_engine
+
+    Schema = _gliner2_engine.Schema
+    StructureBuilder = _gliner2_engine.StructureBuilder
+
+PromptSignature = Schema | StructureBuilder
 Model = gliner2.GLiNER2
 Result = dict[str, str | list[str | dict[str, Any]]]
 

sieves/tasks/predictive/gliner_bridge.py

@@ -8,7 +8,6 @@
 from collections.abc import Sequence
 from typing import Any, Literal, override
 
-import gliner2
 import pydantic
 
 from sieves.data import Doc
@@ -36,7 +35,7 @@
 from sieves.tasks.predictive.utils import convert_to_signature
 
 
-class GliNERBridge(Bridge[gliner2.inference.engine.Schema, gliner_.Result, gliner_.InferenceMode]):
+class GliNERBridge(Bridge[gliner_.Schema, gliner_.Result, gliner_.InferenceMode]):
     """Bridge for GLiNER2 models."""
 
     def __init__(
@@ -78,7 +77,7 @@ def model_type(self) -> ModelType:
 
     @override
     @property
-    def prompt_signature(self) -> gliner2.inference.engine.Schema | gliner2.inference.engine.StructureBuilder:
+    def prompt_signature(self) -> gliner_.Schema | gliner_.StructureBuilder:
         # Map internal inference mode to GliNER utility mode.
         mode_map = {
             gliner_.InferenceMode.classification: "classification",
@@ -117,7 +116,7 @@ def prompt_signature(self) -> gliner2.inference.engine.Schema | gliner2.inferenc
             model_type=ModelType.gliner,
             **kwargs,
         )
-        assert isinstance(prompt_signature, gliner2.inference.engine.Schema | gliner2.inference.engine.StructureBuilder)
+        assert isinstance(prompt_signature, gliner_.Schema | gliner_.StructureBuilder)
 
         return prompt_signature
 

sieves/tasks/predictive/schemas/classification.py

@@ -3,7 +3,6 @@
 from __future__ import annotations
 
 import dspy
-import gliner2.inference.engine
 import pydantic
 
 from sieves.model_wrappers import dspy_, gliner_, huggingface_, langchain_, outlines_
@@ -98,10 +97,6 @@ class ResultMultiLabel(pydantic.BaseModel):
 
 TaskModel = dspy_.Model | gliner_.Model | langchain_.Model | huggingface_.Model | outlines_.Model
 TaskPromptSignature = (
-    type[dspy.Signature]
-    | type[pydantic.BaseModel]
-    | gliner2.inference.engine.Schema
-    | gliner2.inference.engine.StructureBuilder
-    | list[str]
+    type[dspy.Signature] | type[pydantic.BaseModel] | gliner_.Schema | gliner_.StructureBuilder | list[str]
 )
 TaskResult = ResultSingleLabel | ResultMultiLabel

sieves/tasks/predictive/schemas/information_extraction.py

@@ -3,7 +3,6 @@
 from __future__ import annotations
 
 import dspy
-import gliner2.inference.engine
 import pydantic
 
 from sieves.model_wrappers import dspy_, gliner_, langchain_, outlines_
@@ -73,10 +72,5 @@ class ResultMulti(pydantic.BaseModel):
 
 
 TaskModel = dspy_.Model | gliner_.Model | langchain_.Model | outlines_.Model
-TaskPromptSignature = (
-    type[dspy.Signature]
-    | type[pydantic.BaseModel]
-    | gliner2.inference.engine.Schema
-    | gliner2.inference.engine.StructureBuilder
-)
+TaskPromptSignature = type[dspy.Signature] | type[pydantic.BaseModel] | gliner_.Schema | gliner_.StructureBuilder
 TaskResult = ResultSingle | ResultMulti

sieves/tasks/predictive/schemas/ner.py

@@ -3,7 +3,6 @@
 from __future__ import annotations
 
 import dspy
-import gliner2.inference.engine
 import pydantic
 
 from sieves.model_wrappers import dspy_, gliner_, langchain_, outlines_
@@ -111,10 +110,5 @@ def target_fields(self) -> tuple[str, ...]:
 
 
 TaskModel = dspy_.Model | gliner_.Model | langchain_.Model | outlines_.Model
-TaskPromptSignature = (
-    type[dspy.Signature]
-    | type[pydantic.BaseModel]
-    | gliner2.inference.engine.Schema
-    | gliner2.inference.engine.StructureBuilder
-)
+TaskPromptSignature = type[dspy.Signature] | type[pydantic.BaseModel] | gliner_.Schema | gliner_.StructureBuilder
 TaskResult = Result

sieves/tasks/predictive/schemas/relation_extraction.py

@@ -3,7 +3,6 @@
 from __future__ import annotations
 
 import dspy
-import gliner2.inference.engine
 import pydantic
 
 from sieves.model_wrappers import dspy_, gliner_, langchain_, outlines_
@@ -102,10 +101,5 @@ def target_fields(self) -> tuple[str, ...]:
 
 
 TaskModel = dspy_.Model | gliner_.Model | langchain_.Model | outlines_.Model
-TaskPromptSignature = (
-    type[dspy.Signature]
-    | type[pydantic.BaseModel]
-    | gliner2.inference.engine.Schema
-    | gliner2.inference.engine.StructureBuilder
-)
+TaskPromptSignature = type[dspy.Signature] | type[pydantic.BaseModel] | gliner_.Schema | gliner_.StructureBuilder
 TaskResult = Result

sieves/tasks/predictive/utils.py

@@ -8,10 +8,11 @@
 from typing import Any, Literal, TypeVar, Union
 
 import dspy
-import gliner2.inference.engine
 import pydantic
 
 from sieves.model_wrappers import ModelType, dspy_, gliner_, huggingface_, outlines_
+from sieves.model_wrappers.gliner_ import Schema as _GlinerSchema
+from sieves.model_wrappers.gliner_ import StructureBuilder as _GlinerStructureBuilder
 
 _EntityType = TypeVar("_EntityType", bound=pydantic.BaseModel)
 
@@ -54,15 +55,15 @@ def _extract_labels_from_model(model_cls: type[pydantic.BaseModel]) -> list[str]
 
 def _pydantic_to_gliner(
     model_cls: type[pydantic.BaseModel], mode: str, **kwargs: Any
-) -> gliner2.inference.engine.Schema | gliner2.inference.engine.StructureBuilder:
+) -> _GlinerSchema | _GlinerStructureBuilder:
     """Convert Pydantic model to GliNER2 signature.
 
     :param model_cls: Pydantic model to convert.
     :param mode: GliNER2 mode (classification, entities, structure, relations).
     :param kwargs: Additional arguments for GliNER2 schema methods.
     :return: GliNER2 schema or structure builder.
     """
-    schema = gliner2.inference.engine.Schema()
+    schema = _GlinerSchema()
 
     if mode in ("classification", "entities", "relations"):
         labels = _extract_labels_from_model(model_cls)

sieves/tests/tasks/predictive/test_signature_utils.py

@@ -2,7 +2,7 @@
 from typing import Literal, Union, Any
 
 import dspy
-import gliner2.inference.engine
+from sieves.model_wrappers.gliner_ import Schema as _GlinerSchema
 import pydantic
 import pytest
 
@@ -70,7 +70,7 @@ class ExpectedSig(dspy.Signature):
 
 def test_convert_to_gliner_structure_full():
     # Expected manually constructed GliNER2 structure
-    expected = gliner2.inference.engine.Schema().structure("SimpleExtraction")
+    expected = _GlinerSchema().structure("SimpleExtraction")
     expected.field("name", dtype="str")
     expected.field("age", dtype="str")
 
@@ -80,7 +80,7 @@ def test_convert_to_gliner_structure_full():
 
 def test_convert_to_gliner_classification_full():
     # Expected manually constructed GliNER2 classification
-    expected = gliner2.inference.engine.Schema().classification(
+    expected = _GlinerSchema().classification(
         task="classification",
         labels=["A", "B", "C"]
     )
@@ -106,7 +106,7 @@ def test_convert_to_outlines_choice_full():
     assert actual == expected
 
 def test_convert_to_gliner_entities_full():
-    expected = gliner2.inference.engine.Schema().entities(
+    expected = _GlinerSchema().entities(
         entity_types=["science", "politics", "sports"]
     )
 
@@ -118,7 +118,7 @@ def test_convert_to_gliner_structure_choices_full():
     class ChoiceModel(pydantic.BaseModel):
         category: Literal["X", "Y"]
 
-    expected = gliner2.inference.engine.Schema().structure("ChoiceModel")
+    expected = _GlinerSchema().structure("ChoiceModel")
     expected.field("category", dtype="str", choices=["X", "Y"])
 
     actual = convert_to_signature(ChoiceModel, ModelType.gliner, mode="structure")

sieves/tests/tasks/predictive/test_task_signature_migration.py

@@ -2,7 +2,7 @@
 from typing import Literal, Union, Any
 
 import dspy
-import gliner2.inference.engine
+from sieves.model_wrappers.gliner_ import Schema as _GlinerSchema
 import pydantic
 import pytest
 
@@ -55,7 +55,7 @@ class ExpectedDSPy(dspy.Signature):
         score = dspy.OutputField(desc="Confidence score")
 
     # GliNER (classification mode)
-    expected_gliner = gliner2.inference.engine.Schema().classification(
+    expected_gliner = _GlinerSchema().classification(
         task="classification",
         labels=["science", "politics", "sports"]
     )
@@ -92,7 +92,7 @@ class ExpectedDSPy(dspy.Signature):
         sports = dspy.OutputField(desc="Score for sports category")
 
     # GliNER (classification mode)
-    expected_gliner = gliner2.inference.engine.Schema().classification(
+    expected_gliner = _GlinerSchema().classification(
         task="classification",
         labels=["science", "politics", "sports"]
     )
@@ -127,7 +127,7 @@ class ExpectedDSPy(dspy.Signature):
         age = dspy.OutputField(desc="Age in years")
 
     # GliNER (structure mode)
-    expected_gliner = gliner2.inference.engine.Schema().structure("Person")
+    expected_gliner = _GlinerSchema().structure("Person")
     expected_gliner.field("name", dtype="str")
     expected_gliner.field("age", dtype="str")
 
@@ -145,7 +145,7 @@ class NEROutput(pydantic.BaseModel):
     # 2. Define Expected Output Signatures
 
     # GliNER (entities mode)
-    expected_gliner = gliner2.inference.engine.Schema().entities(
+    expected_gliner = _GlinerSchema().entities(
         entity_types=["PER", "LOC", "ORG"]
     )
 
@@ -204,7 +204,7 @@ class RelationOutput(pydantic.BaseModel):
     # 2. Define Expected Output Signatures
 
     # GliNER (relations mode)
-    expected_gliner = gliner2.inference.engine.Schema().relations(
+    expected_gliner = _GlinerSchema().relations(
         relation_types=["head", "relation", "tail"] # Per instruction: all but score
     )