Merge branch 'main' into NO-TASK-fix-flashing-logo-when-custom-logo-is-present

Author: iseabock

.github/workflows/python-app.yml

@@ -27,10 +27,28 @@ jobs:
         python -m pip install --upgrade pip
         pip install -r requirements-dev.txt
     - name: Test with pytest
+      env:
+        AZURE_OPENAI_ENDPOINT: ${{ secrets.AZUREOPENAIENDPOINT }}
+        AZURE_OPENAI_MODEL: ${{ secrets.AZUREOPENAIMODEL }}
+        AZURE_OPENAI_KEY: ${{ secrets.AZUREOPENAIKEY }}
+        AZURE_OPENAI_EMBEDDING_NAME: ${{ secrets.AZUREOPENAIEMBEDDINGNAME }}
+        AZURE_COSMOSDB_ACCOUNT: ${{ secrets.AZURECOSMOSDBACCOUNT }}
+        AZURE_COSMOSDB_DATABASE: ${{ secrets.AZURECOSMOSDBDATABASE }}
+        AZURE_COSMOSDB_CONVERSATIONS_CONTAINER: ${{ secrets.AZURECOSMOSDBCONVERSATIONSCONTAINER }}
+        AZURE_COSMOSDB_ACCOUNT_KEY: ${{ secrets.AZURECOSMOSDBACCOUNTKEY }}
+        AZURE_SEARCH_SERVICE: ${{ secrets.AZURESEARCHSERVICE }}
+        AZURE_SEARCH_INDEX: ${{ secrets.AZURESEARCHINDEX }}
+        AZURE_SEARCH_KEY: ${{ secrets.AZURESEARCHKEY }}
+        AZURE_SEARCH_QUERY: ${{ secrets.AZURESEARCHQUERY }}
+        ELASTICSEARCH_EMBEDDING_MODEL_ID: ${{ secrets.ELASTICSEARCHEMBEDDINGMODELID }}
+        ELASTICSEARCH_ENCODED_API_KEY: ${{ secrets.ELASTICSEARCHENCODEDAPIKEY }}
+        ELASTICSEARCH_ENDPOINT: ${{ secrets.ELASTICSEARCHENDPOINT }}
+        ELASTICSEARCH_INDEX: ${{ secrets.ELASTICSEARCHINDEX }}
+        ELASTICSEARCH_QUERY: ${{ secrets.ELASTICSEARCHQUERY }}
       run: |
         export PYTHONPATH=$(pwd)
-        coverage run --omit=tests/integration_tests -m pytest -v --show-capture=stdout -k "not integration"
-        coverage report -m
+        coverage run -m pytest -v --show-capture=stdout
+        coverage report -m --include=app.py,backend/*,tests/*
         coverage xml
 
     - name: Code Coverage Report
@@ -44,7 +62,7 @@ jobs:
         hide_complexity: true
         indicators: true
         output: both
-        thresholds: '60 80'
+        thresholds: '50 80'
 
   test_windows:
     runs-on:

tests/conftest.py

@@ -0,0 +1,14 @@
+import pytest
+
+
+def pytest_addoption(parser):
+    parser.addoption(
+        "--use-keyvault-secrets",
+        help='Get secrets from a keyvault instead of the environment.',
+        action='store_true', default=False
+)
+
+
+@pytest.fixture(scope="session")
+def use_keyvault_secrets(request) -> str:
+    return request.config.getoption("use_keyvault_secrets")

tests/integration_tests/conftest.py

@@ -3,6 +3,7 @@
 import pytest
 from azure.identity import AzureCliCredential
 from azure.keyvault.secrets import SecretClient
+from pydantic.alias_generators import to_snake
 
 
 VAULT_NAME = os.environ.get("VAULT_NAME")
@@ -17,12 +18,52 @@ def secret_client() -> SecretClient:
 
 
 @pytest.fixture(scope="module")
-def dotenv_template_params(secret_client: SecretClient) -> dict[str, str]:
+def dotenv_template_params_from_kv(secret_client: SecretClient) -> dict[str, str]:
     secrets_properties_list = secret_client.list_properties_of_secrets()
     secrets = {}
     for secret in secrets_properties_list:
-        secrets[secret.name] = secret_client.get_secret(secret.name).value
-        
+        secret_name = to_snake(secret.name).upper()
+        secrets[secret_name] = secret_client.get_secret(secret.name).value
+
     return secrets
 
 
+@pytest.fixture(scope="module")
+def dotenv_template_params_from_env() -> dict[str, str]:
+    def get_and_unset_variable(var_name):
+        # we need this function to ensure that the environment is clean before
+        # testing with generated dotenv files.
+        var_value = os.getenv(var_name)
+        os.environ[var_name] = ""
+        return var_value
+        
+    env_secrets = [
+        "AZURE_COSMOSDB_ACCOUNT",
+        "AZURE_COSMOSDB_ACCOUNT_KEY",
+        "AZURE_COSMOSDB_CONVERSATIONS_CONTAINER",
+        "AZURE_COSMOSDB_DATABASE",
+        "AZURE_OPENAI_EMBEDDING_NAME"
+        "AZURE_OPENAI_ENDPOINT",
+        "AZURE_OPENAI_MODEL",
+        "AZURE_OPENAI_KEY",
+        "AZURE_SEARCH_INDEX",
+        "AZURE_SEARCH_KEY",
+        "AZURE_SEARCH_QUERY",
+        "AZURE_SEARCH_SERVICE",
+        "ELASTICSEARCH_EMBEDDING_MODEL_ID",
+        "ELASTICSEARCH_ENCODED_API_KEY",
+        "ELASTICSEARCH_ENDPOINT",
+        "ELASTICSEARCH_INDEX",
+        "ELASTICSEARCH_QUERY"
+    ]
+    
+    return {s: get_and_unset_variable(s) for s in env_secrets}
+
+
+@pytest.fixture(scope="module")
+def dotenv_template_params(request, use_keyvault_secrets):
+    if use_keyvault_secrets:
+        return request.getfixturevalue("dotenv_template_params_from_kv")
+    
+    return request.getfixturevalue("dotenv_template_params_from_env")
+

tests/integration_tests/dotenv_templates/dotenv.jinja2

@@ -1,79 +1,79 @@
-DATASOURCE_TYPE={{ datasourceType }}
-AZURE_OPENAI_ENDPOINT={{ azureOpenaiEndpoint }}
-AZURE_OPENAI_MODEL={{ azureOpenaiModel }}
-AZURE_OPENAI_KEY={{ azureOpenaiKey }}
+DATASOURCE_TYPE={{ DATASOURCE_TYPE }}
+AZURE_OPENAI_ENDPOINT={{ AZURE_OPENAI_ENDPOINT }}
+AZURE_OPENAI_MODEL={{ AZURE_OPENAI_MODEL }}
+AZURE_OPENAI_KEY={{ AZURE_OPENAI_KEY }}
 AZURE_OPENAI_TEMPERATURE=0
 AZURE_OPENAI_TOP_P=1.0
 AZURE_OPENAI_MAX_TOKENS=1000
 AZURE_OPENAI_STOP_SEQUENCE=
 AZURE_OPENAI_SYSTEM_MESSAGE=You are an AI assistant that helps people find information.
 AZURE_OPENAI_PREVIEW_API_VERSION=2024-05-01-preview
-AZURE_OPENAI_STREAM={{ azureOpenaiStream }}
-{% if useAoaiEmbeddings and azureOpenaiEmbeddingName %}
-AZURE_OPENAI_EMBEDDING_NAME={{ azureOpenaiEmbeddingName }}
+AZURE_OPENAI_STREAM={{ AZURE_OPENAI_STREAM }}
+{% if USE_AOAI_EMBEDDINGS and AZURE_OPENAI_EMBEDDING_NAME %}
+AZURE_OPENAI_EMBEDDING_NAME={{ AZURE_OPENAI_EMBEDDING_NAME }}
 {% endif %}
-{% if useAoaiEmbeddings %}
-AZURE_OPENAI_EMBEDDING_ENDPOINT={{ azureOpenaiEndpoint }}/openai/deployments/ada/embeddings??api-version=2023-03-15-preview
-AZURE_OPENAI_EMBEDDING_KEY={{ azureOpenaiKey }}
+{% if USE_AOAI_EMBEDDINGS %}
+AZURE_OPENAI_EMBEDDING_ENDPOINT={{ AZURE_OPENAI_ENDPOINT }}/openai/deployments/ada/embeddings?api-version=2023-03-15-preview
+AZURE_OPENAI_EMBEDDING_KEY={{ AZURE_OPENAI_KEY }}
 {% endif %}
-{% if enableChatHistory %}
-AZURE_COSMOSDB_ACCOUNT={{ azureCosmosdbAccount }}
-AZURE_COSMOSDB_DATABASE={{ azureCosmosdbDatabase }}
-AZURE_COSMOSDB_CONVERSATIONS_CONTAINER={{ azureCosmosdbConversationsContainer }}
-AZURE_COSMOSDB_ACCOUNT_KEY={{ azureCosmosdbAccountKey }}
-AZURE_COSMOSDB_ENABLE_FEEDBACK={{ azureCosmosdbEnableFeedback }}
+{% if ENABLE_CHAT_HISTORY %}
+AZURE_COSMOSDB_ACCOUNT={{ AZURE_COSMOSDB_ACCOUNT }}
+AZURE_COSMOSDB_DATABASE={{ AZURE_COSMOSDB_DATABASE }}
+AZURE_COSMOSDB_CONVERSATIONS_CONTAINER={{ AZURE_COSMOSDB_CONVERSATIONS_CONTAINER }}
+AZURE_COSMOSDB_ACCOUNT_KEY={{ AZURE_COSMOSDB_ACCOUNT_KEY }}
+AZURE_COSMOSDB_ENABLE_FEEDBACK={{ AZURE_COSMOSDB_ENABLE_FEEDBACK }}
 {% endif %}
-{% if datasourceType == "AzureCognitiveSearch" %}
-AZURE_SEARCH_SERVICE={{ azureSearchService }}
-AZURE_SEARCH_INDEX={{ azureSearchIndex }}
-AZURE_SEARCH_KEY={{ azureSearchKey }}
+{% if DATASOURCE_TYPE == "AZURE_COGNITIVE_SEARCH" %}
+AZURE_SEARCH_SERVICE={{ AZURE_SEARCH_SERVICE }}
+AZURE_SEARCH_INDEX={{ AZURE_SEARCH_INDEX }}
+AZURE_SEARCH_KEY={{ AZURE_SEARCH_KEY }}
 AZURE_SEARCH_SEMANTIC_SEARCH_CONFIG=
 AZURE_SEARCH_CONTENT_COLUMNS=content
 AZURE_SEARCH_FILENAME_COLUMN=
 AZURE_SEARCH_TITLE_COLUMN=
 AZURE_SEARCH_URL_COLUMN=
 AZURE_SEARCH_VECTOR_COLUMNS=contentVector
-AZURE_SEARCH_QUERY_TYPE={{ azureSearchQueryType }}
-AZURE_SEARCH_PERMITTED_GROUPS_COLUMN={{ azureSearchPermittedGroupsColumn }}
-{% elif datasourceType == "Elasticsearch" %}
-ELASTICSEARCH_ENDPOINT={{ elasticsearchEndpoint }}
-ELASTICSEARCH_ENCODED_API_KEY={{ elasticsearchEncodedApiKey }}
-ELASTICSEARCH_INDEX={{ elasticsearchIndex }}
-ELASTICSEARCH_QUERY_TYPE={{ elasticsearchQueryType }}
+AZURE_SEARCH_QUERY_TYPE={{ AZURE_SEARCH_QUERY_TYPE }}
+AZURE_SEARCH_PERMITTED_GROUPS_COLUMN={{ AZURE_SEARCH_PERMITTED_GROUPS_COLUMN }}
+{% elif DATASOURCE_TYPE == "ELASTICSEARCH" %}
+ELASTICSEARCH_ENDPOINT={{ ELASTICSEARCH_ENDPOINT }}
+ELASTICSEARCH_ENCODED_API_KEY={{ ELASTICSEARCH_ENCODED_API_KEY }}
+ELASTICSEARCH_INDEX={{ ELASTICSEARCH_INDEX }}
+ELASTICSEARCH_QUERY_TYPE={{ ELASTICSEARCH_QUERY_TYPE }}
 ELASTICSEARCH_CONTENT_COLUMNS=text
 ELASTICSEARCH_FILENAME_COLUMN=
 ELASTICSEARCH_TITLE_COLUMN=
 ELASTICSEARCH_URL_COLUMN=
 ELASTICSEARCH_VECTOR_COLUMNS=text_embedding.predicted_value
-{% if useElasticsearchEmbeddings and elasticsearchEmbeddingModelId %}
-ELASTICSEARCH_EMBEDDING_MODEL_ID={{ elasticsearchEmbeddingModelId }}
+{% if USE_ELASTICSEARCH_EMBEDDINGS and ELASTICSEARCH_EMBEDDING_MODEL_ID %}
+ELASTICSEARCH_EMBEDDING_MODEL_ID={{ ELASTICSEARCH_EMBEDDING_MODEL_ID }}
 {% endif %}
-{% elif datasourceType == "AzureCosmosDb" %}
-AZURE_COSMOSDB_MONGO_VCORE_CONNECTION_STRING={{ azureCosmosdbMongoVcoreConnectionString }}
-AZURE_COSMOSDB_MONGO_VCORE_DATABASE={{ azureCosmosdbMongoVcoreDatabase }}
-AZURE_COSMOSDB_MONGO_VCORE_CONTAINER={{ azureCosmosdbMongoVcoreContainer }}
-AZURE_COSMOSDB_MONGO_VCORE_INDEX={{ azureCosmosdbMongoVcoreIndex }}
-AZURE_COSMOSDB_MONGO_VCORE_CONTENT_COLUMNS={{ azureCosmosdbMongoVcoreContentColumns }}
+{% elif DATASOURCE_TYPE == "AZURE_COSMOS_DB" %}
+AZURE_COSMOSDB_MONGO_VCORE_CONNECTION_STRING={{ AZURE_COSMOSDB_MONGO_VCORE_CONNECTION_STRING }}
+AZURE_COSMOSDB_MONGO_VCORE_DATABASE={{ AZURE_COSMOSDB_MONGO_VCORE_DATABASE }}
+AZURE_COSMOSDB_MONGO_VCORE_CONTAINER={{ AZURE_COSMOSDB_MONGO_VCORE_CONTAINER }}
+AZURE_COSMOSDB_MONGO_VCORE_INDEX={{ AZURE_COSMOSDB_MONGO_VCORE_INDEX }}
+AZURE_COSMOSDB_MONGO_VCORE_CONTENT_COLUMNS={{ AZURE_COSMOSDB_MONGO_VCORE_CONTENT_COLUMNS }}
 AZURE_COSMOSDB_MONGO_VCORE_FILENAME_COLUMN=
 AZURE_COSMOSDB_MONGO_VCORE_TITLE_COLUMN=
 AZURE_COSMOSDB_MONGO_VCORE_URL_COLUMN=
-AZURE_COSMOSDB_MONGO_VCORE_VECTOR_COLUMNS={{ azureCosmosdbMongoVcoreVectorColumns }}
-{% elif datasourceType == "Pinecone" %}
-PINECONE_ENVIRONMENT={{ pineconeEnvironment }}
-PINECONE_API_KEY={{ pineconeApiKey }}
-PINECONE_INDEX_NAME={{ pineconeIndexName }}
-PINECONE_CONTENT_COLUMNS={{ pineconeContentColumns }}
+AZURE_COSMOSDB_MONGO_VCORE_VECTOR_COLUMNS={{ AZURE_COSMOSDB_MONGO_VCORE_VECTOR_COLUMNS }}
+{% elif DATASOURCE_TYPE == "PINECONE" %}
+PINECONE_ENVIRONMENT={{ PINECONE_ENVIRONMENT }}
+PINECONE_API_KEY={{ PINECONE_API_KEY }}
+PINECONE_INDEX_NAME={{ PINECONE_INDEX_NAME }}
+PINECONE_CONTENT_COLUMNS={{ PINECONE_CONTENT_COLUMNS }}
 PINECONE_FILENAME_COLUMN=
 PINECONE_TITLE_COLUMN=
 PINECONE_URL_COLUMN=
-PINECONE_VECTOR_COLUMNS={{ pineconeVectorColumns }}
-{% elif datasourceType == "AzureMLIndex" %}
-AZURE_MLINDEX_NAME={{ azureMlIndexName }}
-AZURE_MLINDEX_VERSION={{ azureMlIndexVersion }}
-AZURE_ML_PROJECT_RESOURCE_ID={{ azureMlProjectResourceId }}
-AZURE_MLINDEX_CONTENT_COLUMNS={{ azureMlIndexContentColumns }}
+PINECONE_VECTOR_COLUMNS={{ PINECONE_VECTOR_COLUMNS }}
+{% elif DATASOURCE_TYPE == "AZURE_ML_INDEX" %}
+AZURE_MLINDEX_NAME={{ AZURE_ML_INDEX_NAME }}
+AZURE_MLINDEX_VERSION={{ AZURE_ML_INDEX_VERSION }}
+AZURE_ML_PROJECT_RESOURCE_ID={{ AZURE_ML_PROJECT_RESOURCE_ID }}
+AZURE_MLINDEX_CONTENT_COLUMNS={{ AZURE_ML_INDEX_CONTENT_COLUMNS }}
 AZURE_MLINDEX_FILENAME_COLUMN=
 AZURE_MLINDEX_TITLE_COLUMN= 
 AZURE_MLINDEX_URL_COLUMN= 
-AZURE_MLINDEX_VECTOR_COLUMNS={{ azureMlIndexVectorColumns }}
+AZURE_MLINDEX_VECTOR_COLUMNS={{ AZURE_ML_INDEX_VECTOR_COLUMNS }}
 {% endif %}

tests/integration_tests/test_datasources.py

@@ -83,25 +83,25 @@ def dotenv_rendered_template_path(
     )
 
     if datasource != "none":
-        dotenv_template_params["datasourceType"] = datasource
+        dotenv_template_params["DATASOURCE_TYPE"] = datasource
 
     if datasource != "Elasticsearch" and use_elasticsearch_embeddings:
         pytest.skip("Elasticsearch embeddings not supported for test.")
 
     if datasource == "Elasticsearch":
-        dotenv_template_params["useElasticsearchEmbeddings"] = use_elasticsearch_embeddings
+        dotenv_template_params["USE_ELASTICSEARCH_EMBEDDINGS"] = use_elasticsearch_embeddings
 
-    dotenv_template_params["useAoaiEmbeddings"] = use_aoai_embeddings
+    dotenv_template_params["USE_AOAI_EMBEDDINGS"] = use_aoai_embeddings
 
     if use_aoai_embeddings or use_elasticsearch_embeddings:
-        dotenv_template_params["azureSearchQueryType"] = "vector"
-        dotenv_template_params["elasticsearchQueryType"] = "vector"
+        dotenv_template_params["AZURE_SEARCH_QUERY_TYPE"] = "vector"
+        dotenv_template_params["ELASTICSEARCH_QUERY_TYPE"] = "vector"
     else:
-        dotenv_template_params["azureSearchQueryType"] = "simple"
-        dotenv_template_params["elasticsearchQueryType"] = "simple"
+        dotenv_template_params["AZURE_SEARCH_QUERY_TYPE"] = "simple"
+        dotenv_template_params["ELASTICSEARCH_QUERY_TYPE"] = "simple"
 
-    dotenv_template_params["enableChatHistory"] = enable_chat_history
-    dotenv_template_params["azureOpenaiStream"] = stream
+    dotenv_template_params["ENABLE_CHAT_HISTORY"] = enable_chat_history
+    dotenv_template_params["AZURE_OPENAI_STREAM"] = stream
 
     return render_template_to_tempfile(
         rendered_template_name,
@@ -122,11 +122,11 @@ def test_app(dotenv_rendered_template_path) -> Quart:
 
 @pytest.mark.asyncio
 async def test_dotenv(test_app: Quart, dotenv_template_params: dict[str, str]):
-    if dotenv_template_params["datasourceType"] == "AzureCognitiveSearch":
-        message_content = dotenv_template_params["azureSearchQuery"]
+    if dotenv_template_params["DATASOURCE_TYPE"] == "AzureCognitiveSearch":
+        message_content = dotenv_template_params["AZURE_SEARCH_QUERY"]
 
-    elif dotenv_template_params["datasourceType"] == "Elasticsearch":
-        message_content = dotenv_template_params["elasticsearchQuery"]
+    elif dotenv_template_params["DATASOURCE_TYPE"] == "Elasticsearch":
+        message_content = dotenv_template_params["ELASTICSEARCH_QUERY"]
 
     else:
         message_content = "What is Contoso?"