--- a
+++ b/test/features/conftest.py
@@ -0,0 +1,116 @@
+# Base Dependencies 
+# -----------------
+import pytest
+from typing import List
+from pathlib import Path
+
+# Local Dependencies
+# ------------------
+from models.relation import RelationN2C2
+from models import Relation, RelationCollection, Entity
+from nlp_pipeline import get_pipeline 
+
+# 3rd-Party Dependencies 
+# ----------------------
+from gensim.models import KeyedVectors
+
+
+# Fixtures 
+# ---------
+@pytest.fixture(scope="session")
+def n2c2_small_collection() -> RelationCollection:
+    small_collection = RelationCollection.from_datading(
+        "n2c2", Path("data/n2c2/small/relations.msgpack")
+    )
+    return small_collection
+
+@pytest.fixture(scope="session")
+def wv_model():
+    print("Loading bioword2vec model ...")
+    model = KeyedVectors.load_word2vec_format("data/bioword2vec/bio_embedding_extrinsic.txt", binary=False)
+    print("Bioword2vec loaded!")
+    return model 
+
+
+@pytest.fixture(scope="session")
+def NLP():
+    return get_pipeline()
+
+# Fixtures
+# ---------
+@pytest.fixture(scope="session")
+def entity1() -> Entity:
+
+    id = "T11"
+    text = "Ibuprofen"
+    type = "Drug"
+    doc_id = "doc1202"
+    start = 11
+    end = start + len(text)
+    return Entity(id=id, text=text, type=type, doc_id=doc_id, start=start, end=end)
+
+
+@pytest.fixture(scope="session")
+def entity2() -> Entity:
+
+    id = "T13"
+    text = "Paracetamol"
+    type = "Drug"
+    doc_id = "doc1202"
+    start = 24
+    end = start + len(text)
+    return Entity(id=id, text=text, type=type, doc_id=doc_id, start=start, end=end)
+
+@pytest.fixture(scope="session")
+def entity3() -> Entity:
+
+    id = "T11"
+    text = "500mg"
+    type = "Dosage"
+    doc_id = "doc1202"
+    start = 35
+    end = start + len(text)
+    return Entity(id=id, text=text, type=type, doc_id=doc_id, start=start, end=end)
+
+
+
+@pytest.fixture(scope="function")
+def relation_attributes(entity1, entity2, entity3) -> dict: 
+    attrs = {
+        "doc_id": "doc1202",
+        "type": "Dosage-Drug",
+        "entity1": entity1,
+        "entity2": entity3,
+        "label": 1,
+        "left_context": "He was administered ",
+        "middle_context": " and Paracetamol ",
+        "right_context": " for three days",
+        "middle_entities": [entity2],
+    }
+    return attrs
+
+
+@pytest.fixture(scope="function")
+def relation(relation_attributes) -> RelationN2C2:
+    return RelationN2C2(**relation_attributes)
+
+
+
+# @pytest.fixture(scope="session")
+# def n2c2_train_collection() -> RelationCollection:
+
+#     collections = RelationCollection.load_collections("n2c2", splits=["train"])
+#     collection = collections["train"]
+    
+#     assert len(collection) > 0
+    
+#     return collection
+
+
+# @pytest.fixture(scope="session")
+# def ddi_train_collection() -> RelationCollection:
+
+#     collections = RelationCollection.load_collections("ddi", splits=["train"])
+#     collection = collections["train"].type_subcollection("Strength-Drug")
+
+#     return collection
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