From f09b5b0ea4d4f11f5255fd923db60951cc809538 Mon Sep 17 00:00:00 2001
From: Anish Sarkar <104695310+AnishSarkar22@users.noreply.github.com>
Date: Fri, 27 Feb 2026 00:17:39 +0530
Subject: [PATCH] refactor: replace hardcoded embedding dimension with dynamic
 configuration

- Updated the embedding dimension in test configurations to use the value from the application config, enhancing maintainability and consistency across tests.
---
 surfsense_backend/tests/integration/conftest.py              | 3 ++-
 .../integration/indexing_pipeline/test_index_document.py     | 5 ++++-
 2 files changed, 6 insertions(+), 2 deletions(-)

diff --git a/surfsense_backend/tests/integration/conftest.py b/surfsense_backend/tests/integration/conftest.py
index 119045d29..9dff257df 100644
--- a/surfsense_backend/tests/integration/conftest.py
+++ b/surfsense_backend/tests/integration/conftest.py
@@ -8,6 +8,7 @@ from sqlalchemy import text
 from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
 from sqlalchemy.pool import NullPool
 
+from app.config import config as app_config
 from app.db import (
     Base,
     DocumentType,
@@ -18,7 +19,7 @@ from app.db import (
 )
 from app.indexing_pipeline.connector_document import ConnectorDocument
 
-_EMBEDDING_DIM = 1024  # must match the Vector() dimension used in DB column creation
+_EMBEDDING_DIM = app_config.embedding_model_instance.dimension
 
 _DEFAULT_TEST_DB = (
     "postgresql+asyncpg://postgres:postgres@localhost:5432/surfsense_test"
diff --git a/surfsense_backend/tests/integration/indexing_pipeline/test_index_document.py b/surfsense_backend/tests/integration/indexing_pipeline/test_index_document.py
index 0065a03e1..2e8ee4d92 100644
--- a/surfsense_backend/tests/integration/indexing_pipeline/test_index_document.py
+++ b/surfsense_backend/tests/integration/indexing_pipeline/test_index_document.py
@@ -1,9 +1,12 @@
 import pytest
 from sqlalchemy import select
 
+from app.config import config as app_config
 from app.db import Chunk, Document, DocumentStatus
 from app.indexing_pipeline.indexing_pipeline_service import IndexingPipelineService
 
+_EMBEDDING_DIM = app_config.embedding_model_instance.dimension
+
 pytestmark = pytest.mark.integration
 
 
@@ -144,7 +147,7 @@ async def test_embedding_written_to_db(
     reloaded = result.scalars().first()
 
     assert reloaded.embedding is not None
-    assert len(reloaded.embedding) == 1024
+    assert len(reloaded.embedding) == _EMBEDDING_DIM
 
 
 @pytest.mark.usefixtures(