only one onboarding

tests/integration/test_api_endpoints.py

@@ -41,8 +41,11 @@ def dump_docker_logs(container_name_pattern: str = "langflow", tail: int = 100):
 async def perform_onboarding(client: httpx.AsyncClient, embedding_model: str = "text-embedding-3-small", llm_model: str = "gpt-4o-mini"):
     """Perform onboarding configuration to properly initialize the system.
 
-    This should be called after wait_for_service_ready() and before uploading documents.
+    This should be called once at the beginning of test session, or per-test if config is reset.
     It configures the embedding model, LLM model, and initializes the OpenSearch index.
+
+    If onboarding has already been performed (config.edited=True), this will use the /settings
+    endpoint instead to update the configuration.
     """
     onboarding_payload = {
         "model_provider": "openai",
@@ -52,11 +55,26 @@ async def perform_onboarding(client: httpx.AsyncClient, embedding_model: str = "
         "sample_data": False,
     }
     onboarding_resp = await client.post("/onboarding", json=onboarding_payload)
-    if onboarding_resp.status_code not in (200, 204):
+
+    # If onboarding fails because config is already edited, use /settings endpoint instead
+    if onboarding_resp.status_code == 403:
+        print(f"[DEBUG] Config already onboarded, using /settings endpoint instead")
+        settings_payload = {
+            "embedding_model": embedding_model,
+            "llm_model": llm_model,
+        }
+        settings_resp = await client.post("/settings", json=settings_payload)
+        if settings_resp.status_code not in (200, 204):
+            raise AssertionError(
+                f"Settings update failed: {settings_resp.status_code} {settings_resp.text}"
+            )
+        print(f"[DEBUG] Settings updated: embedding_model={embedding_model}, llm_model={llm_model}")
+    elif onboarding_resp.status_code not in (200, 204):
         raise AssertionError(
             f"Onboarding failed: {onboarding_resp.status_code} {onboarding_resp.text}"
         )
-    print(f"[DEBUG] Onboarding completed: embedding_model={embedding_model}, llm_model={llm_model}")
+    else:
+        print(f"[DEBUG] Onboarding completed: embedding_model={embedding_model}, llm_model={llm_model}")
 
 
 async def wait_for_service_ready(client: httpx.AsyncClient, timeout_s: float = 30.0):
@@ -414,7 +432,6 @@ async def test_langflow_chat_and_nudges_endpoints():
     try:
         async with httpx.AsyncClient(transport=transport, base_url="http://testserver") as client:
             await wait_for_service_ready(client)
-            await perform_onboarding(client)
 
             warmup_file = Path("./nudges_seed.md")
             warmup_file.write_text(
@@ -509,7 +526,6 @@ async def test_search_multi_embedding_models(
     try:
         async with httpx.AsyncClient(transport=transport, base_url="http://testserver") as client:
             await wait_for_service_ready(client)
-            await perform_onboarding(client)
 
             async def _upload_doc(name: str, text: str) -> None:
                 file_path = tmp_path / name