diff --git a/learning_resources_search/api.py b/learning_resources_search/api.py
index 8c6ee6fb01..fb7f96e0c9 100644
--- a/learning_resources_search/api.py
+++ b/learning_resources_search/api.py
@@ -922,19 +922,17 @@ def _qdrant_similar_results(doc, num_resources):
         list of dict:
             list of serialized resources
     """
-    from learning_resources_search.indexing_api import qdrant_client
+    from learning_resources_search.indexing_api import qdrant_client, vector_point_id
 
     client = qdrant_client()
     return [
-        hit.metadata
-        for hit in client.query(
+        hit.payload
+        for hit in client.query_points(
             collection_name=f"{settings.QDRANT_BASE_COLLECTION_NAME}.resources",
-            query_text=(
-                f'{doc.get("title")} {doc.get("description")} '
-                f'{doc.get("full_description")} {doc.get("content")}'
-            ),
+            query=vector_point_id(doc["readable_id"]),
             limit=num_resources,
-        )
+            using=settings.QDRANT_SEARCH_VECTOR_NAME,
+        ).points
     ]
 
 
diff --git a/learning_resources_search/indexing_api.py b/learning_resources_search/indexing_api.py
index 9c606bfe61..ac91446815 100644
--- a/learning_resources_search/indexing_api.py
+++ b/learning_resources_search/indexing_api.py
@@ -4,6 +4,7 @@
 
 import json
 import logging
+import uuid
 from math import ceil
 
 from django.conf import settings
@@ -143,6 +144,10 @@ def create_qdrand_collections(force_recreate):
         )
 
 
+def vector_point_id(readable_id):
+    return str(uuid.uuid5(uuid.NAMESPACE_DNS, readable_id))
+
+
 def embed_learning_resources(ids, resource_type):
     # update embeddings
     client = qdrant_client()
@@ -168,7 +173,13 @@ def embed_learning_resources(ids, resource_type):
             f'{doc.get("full_description")} {doc.get("content")}'
         )
         metadata.append(doc)
-        ids.append(doc["id"])
+        if resource_type != CONTENT_FILE_TYPE:
+            vector_point_key = doc["readable_id"]
+        else:
+            vector_point_key = (
+                f"{doc['key']}.{doc['run_readable_id']}.{doc['resource_readable_id']}"
+            )
+        ids.append(vector_point_id(vector_point_key))
     client.add(
         collection_name=collection_name,
         ids=ids,
diff --git a/learning_resources_search/indexing_api_test.py b/learning_resources_search/indexing_api_test.py
index cfae97d13e..f10126e6d9 100644
--- a/learning_resources_search/indexing_api_test.py
+++ b/learning_resources_search/indexing_api_test.py
@@ -13,6 +13,7 @@
 from learning_resources.factories import (
     ContentFileFactory,
     CourseFactory,
+    LearningResourceFactory,
     LearningResourceRunFactory,
 )
 from learning_resources.models import ContentFile
@@ -37,6 +38,7 @@
     deindex_percolators,
     deindex_run_content_files,
     delete_orphaned_indexes,
+    embed_learning_resources,
     get_reindexing_alias_name,
     index_content_files,
     index_course_content_files,
@@ -45,8 +47,10 @@
     index_run_content_files,
     switch_indices,
     update_document_with_partial,
+    vector_point_id,
 )
 from learning_resources_search.models import PercolateQuery
+from learning_resources_search.serializers import serialize_bulk_content_files
 from learning_resources_search.utils import remove_child_queries
 from main.utils import chunks
 
@@ -896,3 +900,31 @@ def test_clear_featured_rank(mocked_es, mocker, clear_all_greater_than):
             "query": query,
         },
     )
+
+
+@pytest.mark.parametrize("content_type", ["learning_resource", "content_file"])
+def test_vector_point_id_used_for_embed(mocker, content_type):
+    # test the vector ids we generate for embedding resources and files
+    if content_type == "learning_resource":
+        resources = LearningResourceFactory.create_batch(5)
+    else:
+        resources = ContentFileFactory.create_batch(5)
+    mock_qdrant = mocker.patch("qdrant_client.QdrantClient")
+    mock_qdrant.query.return_value = []
+    mocker.patch(
+        "learning_resources_search.indexing_api.qdrant_client",
+        return_value=mock_qdrant,
+    )
+
+    embed_learning_resources([resource.id for resource in resources], content_type)
+
+    if content_type == "learning_resource":
+        point_ids = [vector_point_id(resource.readable_id) for resource in resources]
+    else:
+        point_ids = [
+            vector_point_id(
+                f"{resource['key']}.{resource['run_readable_id']}.{resource['resource_readable_id']}"
+            )
+            for resource in serialize_bulk_content_files([r.id for r in resources])
+        ]
+    assert sorted(mock_qdrant.add.mock_calls[0].kwargs["ids"]) == sorted(point_ids)
diff --git a/main/settings.py b/main/settings.py
index 8b95c15ec9..be81dee2db 100644
--- a/main/settings.py
+++ b/main/settings.py
@@ -794,6 +794,9 @@ def get_all_config_keys():
     name="QDRANT_COLLECTION_NAME", default="resource_embeddings"
 )
 
+QDRANT_SEARCH_VECTOR_NAME = get_string(
+    name="QDRANT_SEARCH_VECTOR_NAME", default="fast-bge-small-en"
+)
 
 QDRANT_DENSE_MODEL = get_string(
     name="QDRANT_DENSE_MODEL", default="sentence-transformers/all-MiniLM-L6-v2"