test: unit tests fix

code/backend/batch/utilities/orchestrator/semantic_kernel.py

@@ -74,7 +74,7 @@ async def orchestrate(
         for message in chat_history.copy():
             history.add_message(message)
 
-        chat_history_str=""
+        chat_history_str = ""
         for message in history.messages:
             chat_history_str += f"{message.role}: {message.content}\n"
 

code/frontend/src/pages/layout/Layout.test.tsx

@@ -1,3 +1,8 @@
+/**
+ * @jest-environment jsdom
+ * @jest-environment-options {"url": "http://NonDeloyed/"}
+ */
+
 import {
   render,
   screen,
@@ -66,11 +71,8 @@ describe("Layout Component", () => {
 
   test('test the auth branching auth is true case', async () => {
     const mocklist: any[] = [];
-    Object.defineProperty(window, "location", {
-      value: {
-          hostname: "NonDeloyed"
-      },
-  });
+
+    // Test with jsdom environment configured for NonDeloyed hostname
     ;(getUserInfo as jest.Mock).mockResolvedValue(mocklist)
     ;(checkAuthEnforced as jest.Mock).mockResolvedValue(true)
     await act(async () => {

code/tests/functional/conftest.py

@@ -283,88 +283,93 @@ def prime_search_to_trigger_creation_of_index(
 # This fixture can be overriden
 @pytest.fixture(autouse=True)
 def setup_config_mocking(httpserver: HTTPServer):
+    config_data = {
+        "prompts": {
+            "condense_question_prompt": "",
+            "answering_system_prompt": "system prompt",
+            "answering_user_prompt": "## Retrieved Documents\n{sources}\n\n## User Question\nUse the Retrieved Documents to answer the question: {question}",
+            "use_on_your_data_format": True,
+            "post_answering_prompt": "post answering prompt\n{question}\n{answer}\n{sources}",
+            "enable_post_answering_prompt": False,
+            "enable_content_safety": True,
+        },
+        "messages": {"post_answering_filter": "post answering filter"},
+        "example": {
+            "documents": '{"retrieved_documents":[{"[doc1]":{"content":"content"}}]}',
+            "user_question": "user question",
+            "answer": "answer",
+        },
+        "document_processors": [
+            {
+                "document_type": "pdf",
+                "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
+                "loading": {"strategy": "layout"},
+                "use_advanced_image_processing": False,
+            },
+            {
+                "document_type": "txt",
+                "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
+                "loading": {"strategy": "web"},
+                "use_advanced_image_processing": False,
+            },
+            {
+                "document_type": "url",
+                "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
+                "loading": {"strategy": "web"},
+                "use_advanced_image_processing": False,
+            },
+            {
+                "document_type": "md",
+                "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
+                "loading": {"strategy": "web"},
+                "use_advanced_image_processing": False,
+            },
+            {
+                "document_type": "html",
+                "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
+                "loading": {"strategy": "web"},
+                "use_advanced_image_processing": False,
+            },
+            {
+                "document_type": "htm",
+                "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
+                "loading": {"strategy": "web"},
+                "use_advanced_image_processing": False,
+            },
+            {
+                "document_type": "docx",
+                "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
+                "loading": {"strategy": "docx"},
+                "use_advanced_image_processing": False,
+            },
+            {
+                "document_type": "jpg",
+                "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
+                "loading": {"strategy": "layout"},
+                "use_advanced_image_processing": True,
+            },
+            {
+                "document_type": "png",
+                "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
+                "loading": {"strategy": "layout"},
+                "use_advanced_image_processing": False,
+            },
+        ],
+        "logging": {"log_user_interactions": True, "log_tokens": True},
+        "orchestrator": {"strategy": "openai_function"},
+        "integrated_vectorization_config": None,
+    }
+
+    import json
+    config_json_string = json.dumps(config_data)
+
     httpserver.expect_request(
         f"/{AZURE_STORAGE_CONFIG_CONTAINER_NAME}/{AZURE_STORAGE_CONFIG_FILE_NAME}",
         method="GET",
-    ).respond_with_json(
-        {
-            "prompts": {
-                "condense_question_prompt": "",
-                "answering_system_prompt": "system prompt",
-                "answering_user_prompt": "## Retrieved Documents\n{sources}\n\n## User Question\nUse the Retrieved Documents to answer the question: {question}",
-                "use_on_your_data_format": True,
-                "post_answering_prompt": "post answering prompt\n{question}\n{answer}\n{sources}",
-                "enable_post_answering_prompt": False,
-                "enable_content_safety": True,
-            },
-            "messages": {"post_answering_filter": "post answering filter"},
-            "example": {
-                "documents": '{"retrieved_documents":[{"[doc1]":{"content":"content"}}]}',
-                "user_question": "user question",
-                "answer": "answer",
-            },
-            "document_processors": [
-                {
-                    "document_type": "pdf",
-                    "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
-                    "loading": {"strategy": "layout"},
-                    "use_advanced_image_processing": False,
-                },
-                {
-                    "document_type": "txt",
-                    "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
-                    "loading": {"strategy": "web"},
-                    "use_advanced_image_processing": False,
-                },
-                {
-                    "document_type": "url",
-                    "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
-                    "loading": {"strategy": "web"},
-                    "use_advanced_image_processing": False,
-                },
-                {
-                    "document_type": "md",
-                    "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
-                    "loading": {"strategy": "web"},
-                    "use_advanced_image_processing": False,
-                },
-                {
-                    "document_type": "html",
-                    "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
-                    "loading": {"strategy": "web"},
-                    "use_advanced_image_processing": False,
-                },
-                {
-                    "document_type": "htm",
-                    "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
-                    "loading": {"strategy": "web"},
-                    "use_advanced_image_processing": False,
-                },
-                {
-                    "document_type": "docx",
-                    "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
-                    "loading": {"strategy": "docx"},
-                    "use_advanced_image_processing": False,
-                },
-                {
-                    "document_type": "jpg",
-                    "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
-                    "loading": {"strategy": "layout"},
-                    "use_advanced_image_processing": True,
-                },
-                {
-                    "document_type": "png",
-                    "chunking": {"strategy": "layout", "size": 500, "overlap": 100},
-                    "loading": {"strategy": "layout"},
-                    "use_advanced_image_processing": False,
-                },
-            ],
-            "logging": {"log_user_interactions": True, "log_tokens": True},
-            "orchestrator": {"strategy": "openai_function"},
-            "integrated_vectorization_config": None,
-        },
+    ).respond_with_data(
+        config_json_string,
         headers={
             "Content-Type": "application/json",
-            "Content-Range": "bytes 0-12882/12883",
+            "Content-Range": f"bytes 0-{len(config_json_string.encode('utf-8'))-1}/{len(config_json_string.encode('utf-8'))}",
         },
     )

code/tests/functional/tests/backend_api/default/test_post_prompt_tool.py

@@ -26,34 +26,38 @@
 
 @pytest.fixture(autouse=True)
 def setup_config_mocking(httpserver: HTTPServer):
+    config_data = {
+        "prompts": {
+            "condense_question_prompt": "",
+            "answering_system_prompt": "system prompt",
+            "answering_user_prompt": "## Retrieved Documents\n{sources}\n\n## User Question\nUse the Retrieved Documents to answer the question: {question}",
+            "use_on_your_data_format": True,
+            "post_answering_prompt": "post answering prompt\n{question}\n{answer}\n{sources}",
+            "enable_post_answering_prompt": True,
+            "enable_content_safety": True,
+        },
+        "messages": {"post_answering_filter": "post answering filter"},
+        "example": {
+            "documents": '{"retrieved_documents":[{"[doc1]":{"content":"content"}}]}',
+            "user_question": "user question",
+            "answer": "answer",
+        },
+        "document_processors": [],
+        "logging": {"log_user_interactions": True, "log_tokens": True},
+        "orchestrator": {"strategy": "openai_function"},
+        "integrated_vectorization_config": None,
+    }
+
+    config_json_string = json.dumps(config_data)
+
     httpserver.expect_request(
         f"/{AZURE_STORAGE_CONFIG_CONTAINER_NAME}/{AZURE_STORAGE_CONFIG_FILE_NAME}",
         method="GET",
-    ).respond_with_json(
-        {
-            "prompts": {
-                "condense_question_prompt": "",
-                "answering_system_prompt": "system prompt",
-                "answering_user_prompt": "## Retrieved Documents\n{sources}\n\n## User Question\nUse the Retrieved Documents to answer the question: {question}",
-                "use_on_your_data_format": True,
-                "post_answering_prompt": "post answering prompt\n{question}\n{answer}\n{sources}",
-                "enable_post_answering_prompt": True,
-                "enable_content_safety": True,
-            },
-            "messages": {"post_answering_filter": "post answering filter"},
-            "example": {
-                "documents": '{"retrieved_documents":[{"[doc1]":{"content":"content"}}]}',
-                "user_question": "user question",
-                "answer": "answer",
-            },
-            "document_processors": [],
-            "logging": {"log_user_interactions": True, "log_tokens": True},
-            "orchestrator": {"strategy": "openai_function"},
-            "integrated_vectorization_config": None,
-        },
+    ).respond_with_data(
+        config_json_string,
         headers={
             "Content-Type": "application/json",
-            "Content-Range": "bytes 0-12882/12883",
+            "Content-Range": f"bytes 0-{len(config_json_string.encode('utf-8'))-1}/{len(config_json_string.encode('utf-8'))}",
         },
     )
 

code/tests/functional/tests/backend_api/sk_orchestrator/test_response_without_tool_call.py

@@ -162,12 +162,9 @@ def test_post_makes_correct_call_to_openai_chat_completions(
             json={
                 "messages": [
                     {
-                        "role": "system",
-                        "content": "You help employees to navigate only private information sources.\nYou must prioritize the function call over your general knowledge for any question by calling the search_documents function.\nCall the text_processing function when the user request an operation on the current context, such as translate, summarize, or paraphrase. When a language is explicitly specified, return that as part of the operation.\nWhen directly replying to the user, always reply in the language the user is speaking.\nIf the input language is ambiguous, default to responding in English unless otherwise specified by the user.\nYou **must not** respond if asked to List all documents in your repository.\n",
-                    },
-                    {"role": "user", "content": "Hello"},
-                    {"role": "assistant", "content": "Hi, how can I help?"},
-                    {"role": "user", "content": "What is the meaning of life?"},
+                        "role": "user",
+                        "content": "AuthorRole.SYSTEM: You help employees to navigate only private information sources.\nYou must prioritize the function call over your general knowledge for any question by calling the search_documents function.\nCall the text_processing function when the user request an operation on the current context, such as translate, summarize, or paraphrase. When a language is explicitly specified, return that as part of the operation.\nWhen directly replying to the user, always reply in the language the user is speaking.\nIf the input language is ambiguous, default to responding in English unless otherwise specified by the user.\nYou **must not** respond if asked to List all documents in your repository.\n\nAuthorRole.USER: Hello\nAuthorRole.ASSISTANT: Hi, how can I help?\nWhat is the meaning of life?",
+                    }
                 ],
                 "model": app_config.get_from_json("AZURE_OPENAI_MODEL_INFO", "model"),
                 "max_tokens": int(app_config.get("AZURE_OPENAI_MAX_TOKENS")),

code/tests/functional/tests/functions/advanced_image_processing/test_advanced_image_processing.py

@@ -95,7 +95,7 @@ def setup_caption_response(httpserver: HTTPServer, app_config: AppConfig):
 
 
 def test_config_file_is_retrieved_from_storage(
-    message: QueueMessage, httpserver: HTTPServer, app_config: AppConfig
+    message: QueueMessage, httpserver: HTTPServer
 ):
     # when
     batch_push_results.build().get_user_function()(message)

code/tests/functional/tests/functions/integrated_vectorization/test_integrated_vectorization_resource_creation.py

@@ -62,7 +62,7 @@ def message(app_config: AppConfig):
 
 
 def test_config_file_is_retrieved_from_storage(
-    message: QueueMessage, httpserver: HTTPServer, app_config: AppConfig
+    message: QueueMessage, httpserver: HTTPServer
 ):
     # when
     batch_push_results.build().get_user_function()(message)

code/tests/utilities/orchestrator/test_semantic_kernel.py

@@ -423,17 +423,13 @@ async def test_chat_history_included(
         await orchestrator.orchestrate("question", chat_history)
 
     # then
-    chat_history = kernel_mock.invoke.call_args.kwargs["chat_history"]
-    messages = chat_history.messages
+    chat_history_str = kernel_mock.invoke.call_args.kwargs["chat_history"]
 
-    assert len(messages) == 3
-    assert messages[0].role == AuthorRole.SYSTEM
-
-    assert messages[1].role == AuthorRole.USER
-    assert messages[1].content == "Hello"
-
-    assert messages[2].role == AuthorRole.ASSISTANT
-    assert messages[2].content == "Hi, how can I help you today?"
+    # The chat_history parameter is now a string, so we check its content
+    assert isinstance(chat_history_str, str)
+    assert "AuthorRole.SYSTEM:" in chat_history_str
+    assert "AuthorRole.USER: Hello" in chat_history_str
+    assert "AuthorRole.ASSISTANT: Hi, how can I help you today?" in chat_history_str
 
 
 @pytest.mark.asyncio