feat: enhance API key normalization and improve Space OAuth callback handling

tests/unit_tests/provider/test_model_service.py

@@ -17,6 +17,8 @@ from langbot.pkg.pipeline.preproc.preproc import PreProcessor
 from langbot.pkg.provider.modelmgr import requester
 from langbot.pkg.provider.modelmgr.modelmgr import ModelManager
 from langbot.pkg.provider.modelmgr.requesters.chatcmpl import OpenAIChatCompletions
+from langbot.pkg.provider.modelmgr.requesters.modelscopechatcmpl import ModelScopeChatCompletions
+from langbot.pkg.provider.modelmgr.token import TokenManager
 from langbot.pkg.provider.runners.localagent import LocalAgentRunner
 
 
@@ -66,6 +68,17 @@ def test_normalize_space_provider_api_keys_filters_blank_values():
     assert ModelProviderService._normalize_api_keys('') == []
     assert ModelProviderService._normalize_api_keys('   ') == []
     assert ModelProviderService._normalize_api_keys(None) == []
+    assert ModelProviderService._normalize_api_keys([' first-key ', '', 'first-key', 'second-key']) == [
+        'first-key',
+        'second-key',
+    ]
+
+
+def test_token_manager_filters_blank_and_duplicate_tokens():
+    token_mgr = TokenManager('provider-uuid', ['  first-key  ', '', 'first-key', 'second-key', '   '])
+
+    assert token_mgr.tokens == ['first-key', 'second-key']
+    assert token_mgr.get_token() == 'first-key'
 
 
 @pytest.mark.asyncio
@@ -85,6 +98,57 @@ async def test_openai_requester_initialize_uses_placeholder_api_key(monkeypatch)
     assert captured_kwargs['api_key'] == OpenAIChatCompletions.init_api_key
 
 
+@pytest.mark.asyncio
+async def test_modelscope_requester_initialize_uses_placeholder_api_key(monkeypatch):
+    captured_kwargs = {}
+
+    def fake_client(**kwargs):
+        captured_kwargs.update(kwargs)
+        return SimpleNamespace(**kwargs)
+
+    monkeypatch.setattr('langbot.pkg.provider.modelmgr.requesters.modelscopechatcmpl.openai.AsyncClient', fake_client)
+    monkeypatch.setattr('langbot.pkg.provider.modelmgr.requesters.modelscopechatcmpl.httpx.AsyncClient', fake_client)
+
+    requester_inst = ModelScopeChatCompletions(ap=SimpleNamespace(), config={})
+    await requester_inst.initialize()
+
+    assert captured_kwargs['api_key'] == ModelScopeChatCompletions.init_api_key
+
+
+@pytest.mark.asyncio
+async def test_openai_embedding_call_overrides_placeholder_api_key():
+    captured_request = {}
+
+    async def fake_create(**kwargs):
+        captured_request['api_key'] = fake_client.api_key
+        captured_request['kwargs'] = kwargs
+        return SimpleNamespace(
+            data=[SimpleNamespace(embedding=[0.1, 0.2])],
+            usage=SimpleNamespace(prompt_tokens=3, total_tokens=3),
+        )
+
+    fake_client = SimpleNamespace(
+        api_key=OpenAIChatCompletions.init_api_key,
+        embeddings=SimpleNamespace(create=fake_create),
+    )
+
+    requester_inst = OpenAIChatCompletions(ap=SimpleNamespace(), config={})
+    requester_inst.client = fake_client
+
+    embeddings, usage_info = await requester_inst.invoke_embedding(
+        model=requester.RuntimeEmbeddingModel(
+            model_entity=SimpleNamespace(name='text-embedding-3-small', extra_args={}),
+            provider=SimpleNamespace(token_mgr=TokenManager('provider-uuid', ['  runtime-key  ', '', 'runtime-key'])),
+        ),
+        input_text=['hello'],
+    )
+
+    assert captured_request['api_key'] == 'runtime-key'
+    assert captured_request['kwargs']['model'] == 'text-embedding-3-small'
+    assert embeddings == [[0.1, 0.2]]
+    assert usage_info == {'prompt_tokens': 3, 'total_tokens': 3}
+
+
 @pytest.mark.asyncio
 async def test_updated_llm_model_is_immediately_usable_by_local_agent_pipeline():
     from langbot.pkg.api.http.service.model import LLMModelsService