1 files changed, 86 insertions, 0 deletions
diff --git a/examples/redis-unstable/modules/vector-sets/tests/persistence.py b/examples/redis-unstable/modules/vector-sets/tests/persistence.py
new file mode 100644
index 0000000..79730f4
--- /dev/null
+++ b/examples/redis-unstable/modules/vector-sets/tests/persistence.py
@@ -0,0 +1,86 @@
+from test import TestCase, fill_redis_with_vectors, generate_random_vector
+import random
+
+class HNSWPersistence(TestCase):
+    def getname(self):
+        return "HNSW Persistence"
+
+    def estimated_runtime(self):
+        return 30
+
+    def _verify_results(self, key, dim, query_vec, reduced_dim=None):
+        """Run a query and return results dict"""
+        k = 10
+        args = ['VSIM', key]
+
+        if reduced_dim:
+            args.extend(['VALUES', dim])
+            args.extend([str(x) for x in query_vec])
+        else:
+            args.extend(['VALUES', dim])
+            args.extend([str(x) for x in query_vec])
+
+        args.extend(['COUNT', k, 'WITHSCORES'])
+        results = self.redis.execute_command(*args)
+
+        results_dict = {}
+        for i in range(0, len(results), 2):
+            key = results[i].decode()
+            score = float(results[i+1])
+            results_dict[key] = score
+        return results_dict
+
+    def test(self):
+        # Setup dimensions
+        dim = 128
+        reduced_dim = 32
+        count = 5000
+        random.seed(42)
+
+        # Create two datasets - one normal and one with dimension reduction
+        normal_data = fill_redis_with_vectors(self.redis, f"{self.test_key}:normal", count, dim)
+        projected_data = fill_redis_with_vectors(self.redis, f"{self.test_key}:projected",
+                                               count, dim, reduced_dim)
+
+        # Generate query vectors we'll use before and after reload
+        query_vec_normal = generate_random_vector(dim)
+        query_vec_projected = generate_random_vector(dim)
+
+        # Get initial results for both sets
+        initial_normal = self._verify_results(f"{self.test_key}:normal", 
+                                            dim, query_vec_normal)
+        initial_projected = self._verify_results(f"{self.test_key}:projected", 
+                                               dim, query_vec_projected, reduced_dim)
+
+        # Force Redis to save and reload the dataset
+        self.redis.execute_command('DEBUG', 'RELOAD')
+
+        # Verify results after reload
+        reloaded_normal = self._verify_results(f"{self.test_key}:normal", 
+                                             dim, query_vec_normal)
+        reloaded_projected = self._verify_results(f"{self.test_key}:projected", 
+                                                dim, query_vec_projected, reduced_dim)
+
+        # Verify normal vectors results
+        assert len(initial_normal) == len(reloaded_normal), \
+            "Normal vectors: Result count mismatch before/after reload"
+
+        for key in initial_normal:
+            assert key in reloaded_normal, f"Normal vectors: Missing item after reload: {key}"
+            assert abs(initial_normal[key] - reloaded_normal[key]) < 0.0001, \
+                f"Normal vectors: Score mismatch for {key}: " + \
+                f"before={initial_normal[key]:.6f}, after={reloaded_normal[key]:.6f}"
+
+        # Verify projected vectors results
+        assert len(initial_projected) == len(reloaded_projected), \
+            "Projected vectors: Result count mismatch before/after reload"
+
+        for key in initial_projected:
+            assert key in reloaded_projected, \
+                f"Projected vectors: Missing item after reload: {key}"
+            assert abs(initial_projected[key] - reloaded_projected[key]) < 0.0001, \
+                f"Projected vectors: Score mismatch for {key}: " + \
+                f"before={initial_projected[key]:.6f}, after={reloaded_projected[key]:.6f}"
+
+        self.redis.delete(f"{self.test_key}:normal")
+        self.redis.delete(f"{self.test_key}:projected")