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Update tests
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-65
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‎.github/copilot-instructions.md‎

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@@ -60,3 +60,9 @@ If the feature is a UI element, add an e2e test for it.
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If it is an API endpoint, add an app integration test for it.
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If it is a function or method, add a unit test for it.
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Use mocks from conftest.py to mock external services.
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When you're running tests, make sure you activate the .venv virtual environment first:
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```bash
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source .venv/bin/activate
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```

‎app/backend/app.py‎

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@@ -565,6 +565,7 @@ async def setup_clients():
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openai_organization=OPENAI_ORGANIZATION,
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)
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user_blob_container_client = None
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if USE_USER_UPLOAD:
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current_app.logger.info("USE_USER_UPLOAD is true, setting up user upload feature")
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if not AZURE_USERSTORAGE_ACCOUNT or not AZURE_USERSTORAGE_CONTAINER:

‎app/backend/approaches/chatreadretrieveread.py‎

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@@ -358,7 +358,7 @@ async def run_search_approach(
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# STEP 3: Generate a contextual and content specific answer using the search results and chat history
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text_sources, image_sources, citations = await self.get_sources_content(
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results, use_semantic_captions, use_image_sources=use_image_sources, user_oid=auth_claims["oid"]
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results, use_semantic_captions, use_image_sources=use_image_sources, user_oid=auth_claims.get("oid")
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)
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extra_info = ExtraInfo(
@@ -430,7 +430,7 @@ async def run_agentic_retrieval_approach(
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use_text_sources = llm_inputs_enum in [LLMInputType.TEXT_AND_IMAGES, LLMInputType.TEXTS]
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text_sources, image_sources, citations = await self.get_sources_content(
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results, use_semantic_captions=False, use_image_sources=use_image_sources, user_oid=auth_claims["oid"]
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results, use_semantic_captions=False, use_image_sources=use_image_sources, user_oid=auth_claims.get("oid")
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)
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extra_info = ExtraInfo(

‎app/backend/approaches/retrievethenread.py‎

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@@ -203,7 +203,7 @@ async def run_search_approach(
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)
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text_sources, image_sources, citations = await self.get_sources_content(
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results, use_semantic_captions, use_image_sources=use_image_sources, user_oid=auth_claims["oid"]
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results, use_semantic_captions, use_image_sources=use_image_sources, user_oid=auth_claims.get("oid")
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)
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return ExtraInfo(
@@ -264,7 +264,7 @@ async def run_agentic_retrieval_approach(
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use_image_sources = llm_inputs_enum in [LLMInputType.TEXT_AND_IMAGES, LLMInputType.IMAGES]
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text_sources, image_sources, citations = await self.get_sources_content(
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results, use_semantic_captions=False, use_image_sources=use_image_sources, user_oid=auth_claims["oid"]
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results, use_semantic_captions=False, use_image_sources=use_image_sources, user_oid=auth_claims.get("oid")
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)
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extra_info = ExtraInfo(

‎app/backend/prepdocs.py‎

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@@ -235,6 +235,8 @@ def setup_openai_client(
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logger.info(
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"OPENAI_HOST is not azure, setting up OpenAI client using OPENAI_API_KEY and OPENAI_ORGANIZATION environment variables"
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)
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if openai_api_key is None:
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raise ValueError("OpenAI key is required when using the non-Azure OpenAI API")
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openai_client = AsyncOpenAI(
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api_key=openai_api_key,
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organization=openai_organization,

‎docs/multimodal.md‎

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@@ -100,7 +100,7 @@ For more details on how this feature works, read [this blog post](https://techco
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## Compatibility
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* This feature is not fully compatible with the [agentic retrieval](./agentic_retrieval.md) feature.
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* This feature is **not** fully compatible with the [agentic retrieval](./agentic_retrieval.md) feature.
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The agent *will* perform the multimodal vector embedding search, but it will not return images in the response,
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so we cannot send the images to the chat completion model.
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* This feature is compatible with the [reasoning models](./reasoning.md) feature, as long as you use a model that [supports image inputs](https://learn.microsoft.com/azure/ai-services/openai/how-to/reasoning?tabs=python-secure%2Cpy#api--feature-support).
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* This feature *is* compatible with the [reasoning models](./reasoning.md) feature, as long as you use a model that [supports image inputs](https://learn.microsoft.com/azure/ai-services/openai/how-to/reasoning?tabs=python-secure%2Cpy#api--feature-support).

‎tests/conftest.py‎

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@@ -302,6 +302,17 @@ def mock_blob_container_client(monkeypatch):
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"AZURE_OPENAI_EMB_MODEL_NAME": "text-embedding-3-large",
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"AZURE_OPENAI_EMB_DIMENSIONS": "3072",
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},
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{
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"OPENAI_HOST": "azure",
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"AZURE_OPENAI_SERVICE": "test-openai-service",
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"AZURE_OPENAI_CHATGPT_DEPLOYMENT": "test-chatgpt",
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"AZURE_OPENAI_EMB_DEPLOYMENT": "test-ada",
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"AZURE_OPENAI_EMB_MODEL_NAME": "text-embedding-3-large",
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"AZURE_OPENAI_EMB_DIMENSIONS": "3072",
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},
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]
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vision_envs = [
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{
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"OPENAI_HOST": "azure",
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"AZURE_OPENAI_SERVICE": "test-openai-service",
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"AZURE_OPENAI_EMB_MODEL_NAME": "text-embedding-3-large",
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"AZURE_OPENAI_EMB_DIMENSIONS": "3072",
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"USE_MULTIMODAL": "true",
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"VISION_ENDPOINT": "https://testvision.cognitiveservices.azure.com/",
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"AZURE_VISION_ENDPOINT": "https://testvision.cognitiveservices.azure.com/",
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},
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]
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yield
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@pytest.fixture(params=vision_envs, ids=["client0"])
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def mock_vision_env(monkeypatch, request):
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with mock.patch.dict(os.environ, clear=True):
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monkeypatch.setenv("AZURE_STORAGE_ACCOUNT", "test-storage-account")
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monkeypatch.setenv("AZURE_STORAGE_CONTAINER", "test-storage-container")
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monkeypatch.setenv("AZURE_IMAGESTORAGE_CONTAINER", "test-image-container")
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monkeypatch.setenv("AZURE_STORAGE_RESOURCE_GROUP", "test-storage-rg")
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monkeypatch.setenv("AZURE_SUBSCRIPTION_ID", "test-storage-subid")
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monkeypatch.setenv("AZURE_SEARCH_INDEX", "test-search-index")
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monkeypatch.setenv("AZURE_SEARCH_SERVICE", "test-search-service")
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monkeypatch.setenv("AZURE_OPENAI_CHATGPT_MODEL", "gpt-4.1-mini")
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for key, value in request.param.items():
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monkeypatch.setenv(key, value)
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with mock.patch("app.AzureDeveloperCliCredential") as mock_default_azure_credential:
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mock_default_azure_credential.return_value = MockAzureCredential()
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yield
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@pytest_asyncio.fixture(scope="function")
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async def client(
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monkeypatch,
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yield client
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@pytest_asyncio.fixture(scope="function")
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async def vision_client(
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monkeypatch,
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mock_vision_env,
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mock_openai_chatcompletion,
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mock_openai_embedding,
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mock_acs_search,
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mock_blob_container_client,
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mock_azurehttp_calls,
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):
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quart_app = app.create_app()
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async with quart_app.test_app() as test_app:
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test_app.app.config.update({"TESTING": True})
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mock_openai_chatcompletion(test_app.app.config[app.CONFIG_OPENAI_CLIENT])
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mock_openai_embedding(test_app.app.config[app.CONFIG_OPENAI_CLIENT])
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yield test_app.test_client()
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@pytest.fixture
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def mock_validate_token_success(monkeypatch):
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async def mock_validate_access_token(self, token):

‎tests/snapshots/test_app/test_ask_prompt_template/client1/result.json‎

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"props": {
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"filter": null,
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"top": 3,
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"use_image_embeddings": true,
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"use_image_sources": true,
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"use_image_embeddings": false,
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"use_image_sources": false,
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"use_query_rewriting": false,
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"use_semantic_captions": false,
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"use_semantic_ranker": false,

‎tests/snapshots/test_app/test_ask_prompt_template_concat/client1/result.json‎

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"props": {
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"filter": null,
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"top": 3,
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"use_image_embeddings": true,
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"use_image_sources": true,
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"use_image_embeddings": false,
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"use_image_sources": false,
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"use_query_rewriting": false,
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"use_semantic_captions": false,
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"use_semantic_ranker": false,

‎tests/snapshots/test_app/test_ask_rtr_text/client1/result.json‎

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"props": {
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"filter": null,
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"top": 3,
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"use_image_embeddings": true,
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"use_image_sources": true,
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"use_image_embeddings": false,
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"use_image_sources": false,
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"use_query_rewriting": false,
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"use_semantic_captions": false,
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"use_semantic_ranker": false,

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