diff --git a/.github/tests/rm_tests.py b/.github/tests/rm_tests.py
new file mode 100644
index 00000000..3940944a
--- /dev/null
+++ b/.github/tests/rm_tests.py
@@ -0,0 +1,138 @@
+import pandas as pd
+import pytest
+
+import lotus
+from lotus.models import CrossEncoderModel, E5Model
+
+# Set logger level to DEBUG
+lotus.logger.setLevel("DEBUG")
+
+
+@pytest.fixture
+def setup_models():
+    # Set up embedder and reranker model
+    rm = E5Model(model="intfloat/e5-small-v2")
+    reranker = CrossEncoderModel(model="mixedbread-ai/mxbai-rerank-xsmall-v1")
+    return rm, reranker
+
+
+def test_cluster_by(setup_models):
+    rm, _ = setup_models
+    lotus.settings.configure(rm=rm)
+
+    data = {
+        "Course Name": [
+            "Probability and Random Processes",
+            "Cooking",
+            "Food Sciences",
+            "Optimization Methods in Engineering",
+        ]
+    }
+    df = pd.DataFrame(data)
+    df = df.sem_index("Course Name", "index_dir")
+    df = df.sem_cluster_by("Course Name", 2)
+    groups = df.groupby("cluster_id")["Course Name"].apply(set).to_dict()
+    assert len(groups) == 2, groups
+    if "Cooking" in groups[0]:
+        cooking_group = groups[0]
+        probability_group = groups[1]
+    else:
+        cooking_group = groups[1]
+        probability_group = groups[0]
+
+    assert cooking_group == {"Cooking", "Food Sciences"}, groups
+    assert probability_group == {"Probability and Random Processes", "Optimization Methods in Engineering"}, groups
+
+
+def test_search_rm_only(setup_models):
+    rm, _ = setup_models
+    lotus.settings.configure(rm=rm)
+
+    data = {
+        "Course Name": [
+            "Probability and Random Processes",
+            "Cooking",
+            "Food Sciences",
+            "Optimization Methods in Engineering",
+        ]
+    }
+    df = pd.DataFrame(data)
+    df = df.sem_index("Course Name", "index_dir")
+    df = df.sem_search("Course Name", "Optimization", K=1)
+    assert df["Course Name"].tolist() == ["Optimization Methods in Engineering"]
+
+
+def test_search_reranker_only(setup_models):
+    _, reranker = setup_models
+    lotus.settings.configure(reranker=reranker)
+
+    data = {
+        "Course Name": [
+            "Probability and Random Processes",
+            "Cooking",
+            "Food Sciences",
+            "Optimization Methods in Engineering",
+        ]
+    }
+    df = pd.DataFrame(data)
+    df = df.sem_search("Course Name", "Optimization", n_rerank=2)
+    assert df["Course Name"].tolist() == ["Optimization Methods in Engineering", "Probability and Random Processes"]
+
+
+def test_search(setup_models):
+    rm, reranker = setup_models
+    lotus.settings.configure(rm=rm, reranker=reranker)
+
+    data = {
+        "Course Name": [
+            "Probability and Random Processes",
+            "Cooking",
+            "Food Sciences",
+            "Optimization Methods in Engineering",
+        ]
+    }
+    df = pd.DataFrame(data)
+    df = df.sem_index("Course Name", "index_dir")
+    df = df.sem_search("Course Name", "Optimization", K=2, n_rerank=1)
+    assert df["Course Name"].tolist() == ["Optimization Methods in Engineering"]
+
+
+def test_dedup(setup_models):
+    rm, _ = setup_models
+    lotus.settings.configure(rm=rm)
+    data = {
+        "Text": [
+            "Probability and Random Processes",
+            "Probability and Markov Chains",
+            "Harry Potter",
+            "Harry James Potter",
+        ]
+    }
+    df = pd.DataFrame(data)
+    df = df.sem_index("Text", "index_dir").sem_dedup("Text", threshold=0.85)
+    kept = df["Text"].tolist()
+    kept.sort()
+    assert len(kept) == 2, kept
+    assert "Harry" in kept[0], kept
+    assert "Probability" in kept[1], kept
+
+
+def test_sim_join(setup_models):
+    rm, _ = setup_models
+    lotus.settings.configure(rm=rm)
+
+    data1 = {
+        "Course Name": [
+            "History of the Atlantic World",
+            "Riemannian Geometry",
+        ]
+    }
+
+    data2 = {"Skill": ["Math", "History"]}
+
+    df1 = pd.DataFrame(data1)
+    df2 = pd.DataFrame(data2).sem_index("Skill", "index_dir")
+    joined_df = df1.sem_sim_join(df2, left_on="Course Name", right_on="Skill", K=1)
+    joined_pairs = set(zip(joined_df["Course Name"], joined_df["Skill"]))
+    expected_pairs = {("History of the Atlantic World", "History"), ("Riemannian Geometry", "Math")}
+    assert joined_pairs == expected_pairs, joined_pairs
diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 5d7d8d71..e5f7fc46 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -31,7 +31,7 @@ jobs:
         run: ruff check .
 
   test:
-    name: LM Tests
+    name: Python Tests
     runs-on: ubuntu-latest
     timeout-minutes: 5
 
@@ -57,4 +57,6 @@ jobs:
       - name: Run Python tests
         env:
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-        run: pytest .github/tests/lm_tests.py
+        run: |
+          pytest .github/tests/lm_tests.py
+          pytest .github/tests/rm_tests.py
\ No newline at end of file