Python: chore(python): improve dependency range automation (#4343)

* chore(python): improve dependency range automation - tighten dependency bounds and coding standards guidance\n- add dependency range validation workflow, reporting, and issue automation\n- update related tests and dependency pins for compatibility Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated text and pyarrow * new lock * fixed workflow * updated deps * fix tiktoken * chore(python): refine dependency validation workflows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs(python): add high-level dependency validation comments Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * WIP * added additional comments and excludes * added dev dependency handling and workflow and updates to package ranges * added readme and simplified commands * fix markers * chore(python): address dependency review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Tighten dependency bounds, remove stale overrides, restore Python 3.10 support - Apply dependency bound policy across all packages: stable >=1.0 deps use >=floor,<next_major; pre-1.0/prerelease deps use validated hard-bounded ranges - Remove stale root tool.uv.override-dependencies (uvicorn, websockets, grpcio) - Lower github_copilot requires-python to >=3.10 with github-copilot-sdk gated behind python_version >= 3.11 marker; import raises ImportError on 3.10 - Skip github_copilot pyright/mypy/test tasks on Python <3.11 - Use version-conditional pyrightconfig for samples on Python 3.10 - Add compatibility fix in core responses client for older openai typed dicts - Normalize uv.lock prerelease mode and refresh dev dependencies - Update CODING_STANDARD.md, DEV_SETUP.md, and package management skill docs Closes #902 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * small tweaks * add note in workflow * fix workflows and several versions * fix duplicate --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-16 21:04:09 +08:00 · 2026-03-13 13:32:37 +01:00
parent 67b0282813
commit 50fdcbaf57
61 changed files with 5500 additions and 779 deletions
@@ -0,0 +1,159 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+from __future__ import annotations
+
+import os
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+from openai.types import CreateEmbeddingResponse
+from openai.types import Embedding as OpenAIEmbedding
+from openai.types.create_embedding_response import Usage
+
+from agent_framework.azure import AzureOpenAIEmbeddingClient
+from agent_framework.openai import OpenAIEmbeddingOptions
+
+
+def _make_openai_response(
+    embeddings: list[list[float]],
+    model: str = "text-embedding-3-small",
+    prompt_tokens: int = 5,
+    total_tokens: int = 5,
+) -> CreateEmbeddingResponse:
+    """Helper to create a mock OpenAI embeddings response."""
+    data = [OpenAIEmbedding(embedding=emb, index=i, object="embedding") for i, emb in enumerate(embeddings)]
+    return CreateEmbeddingResponse(
+        data=data,
+        model=model,
+        object="list",
+        usage=Usage(prompt_tokens=prompt_tokens, total_tokens=total_tokens),
+    )
+
+
+@pytest.fixture
+def azure_embedding_unit_test_env(monkeypatch: pytest.MonkeyPatch) -> None:
+    """Clear ambient Azure OpenAI embedding env vars for deterministic unit tests."""
+    for key in (
+        "AZURE_OPENAI_ENDPOINT",
+        "AZURE_OPENAI_API_KEY",
+        "AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME",
+        "AZURE_OPENAI_BASE_URL",
+        "AZURE_OPENAI_TOKEN_ENDPOINT",
+    ):
+        monkeypatch.delenv(key, raising=False)
+
+
+def test_azure_construction_with_deployment_name(azure_embedding_unit_test_env: None) -> None:
+    client = AzureOpenAIEmbeddingClient(
+        deployment_name="text-embedding-3-small",
+        api_key="test-key",
+        endpoint="https://test.openai.azure.com/",
+    )
+    assert client.model_id == "text-embedding-3-small"
+
+
+def test_azure_construction_with_existing_client(azure_embedding_unit_test_env: None) -> None:
+    mock_client = MagicMock()
+    client = AzureOpenAIEmbeddingClient(
+        deployment_name="my-deployment",
+        async_client=mock_client,
+    )
+    assert client.model_id == "my-deployment"
+    assert client.client is mock_client
+
+
+def test_azure_construction_missing_deployment_name_raises(azure_embedding_unit_test_env: None) -> None:
+    with pytest.raises(ValueError, match="deployment name is required"):
+        AzureOpenAIEmbeddingClient(
+            api_key="test-key",
+            endpoint="https://test.openai.azure.com/",
+        )
+
+
+def test_azure_construction_missing_credentials_raises(azure_embedding_unit_test_env: None) -> None:
+    with pytest.raises(ValueError, match="api_key, credential, or a client"):
+        AzureOpenAIEmbeddingClient(
+            deployment_name="test",
+            endpoint="https://test.openai.azure.com/",
+        )
+
+
+async def test_azure_get_embeddings(azure_embedding_unit_test_env: None) -> None:
+    mock_response = _make_openai_response(
+        embeddings=[[0.1, 0.2]],
+    )
+    mock_async_client = MagicMock()
+    mock_async_client.embeddings = MagicMock()
+    mock_async_client.embeddings.create = AsyncMock(return_value=mock_response)
+
+    client = AzureOpenAIEmbeddingClient(
+        deployment_name="text-embedding-3-small",
+        async_client=mock_async_client,
+    )
+
+    result = await client.get_embeddings(["hello"])
+
+    assert len(result) == 1
+    assert result[0].vector == [0.1, 0.2]
+
+
+def test_azure_otel_provider_name(azure_embedding_unit_test_env: None) -> None:
+    mock_client = MagicMock()
+    client = AzureOpenAIEmbeddingClient(
+        deployment_name="test",
+        async_client=mock_client,
+    )
+    assert client.OTEL_PROVIDER_NAME == "azure.ai.openai"
+
+
+skip_if_azure_openai_integration_tests_disabled = pytest.mark.skipif(
+    not os.getenv("AZURE_OPENAI_ENDPOINT")
+    or (not os.getenv("AZURE_OPENAI_API_KEY") and not os.getenv("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME")),
+    reason="No Azure OpenAI credentials provided; skipping integration tests.",
+)
+
+
+@pytest.mark.flaky
+@pytest.mark.integration
+@skip_if_azure_openai_integration_tests_disabled
+async def test_integration_azure_openai_get_embeddings() -> None:
+    """End-to-end test of Azure OpenAI embedding generation."""
+    client = AzureOpenAIEmbeddingClient()
+
+    result = await client.get_embeddings(["hello world"])
+
+    assert len(result) == 1
+    assert isinstance(result[0].vector, list)
+    assert len(result[0].vector) > 0
+    assert all(isinstance(v, float) for v in result[0].vector)
+    assert result[0].model_id is not None
+    assert result.usage is not None
+    assert result.usage["input_token_count"] > 0
+
+
+@pytest.mark.flaky
+@pytest.mark.integration
+@skip_if_azure_openai_integration_tests_disabled
+async def test_integration_azure_openai_get_embeddings_multiple() -> None:
+    """Test Azure OpenAI embedding generation for multiple inputs."""
+    client = AzureOpenAIEmbeddingClient()
+
+    result = await client.get_embeddings(["hello", "world", "test"])
+
+    assert len(result) == 3
+    dims = [len(e.vector) for e in result]
+    assert all(d == dims[0] for d in dims)
+
+
+@pytest.mark.flaky
+@pytest.mark.integration
+@skip_if_azure_openai_integration_tests_disabled
+async def test_integration_azure_openai_get_embeddings_with_dimensions() -> None:
+    """Test Azure OpenAI embedding generation with custom dimensions."""
+    client = AzureOpenAIEmbeddingClient()
+
+    options: OpenAIEmbeddingOptions = {"dimensions": 256}
+    result = await client.get_embeddings(["hello world"], options=options)
+
+    assert len(result) == 1
+    assert len(result[0].vector) == 256
@@ -10,7 +10,6 @@ from openai.types import CreateEmbeddingResponse
 from openai.types import Embedding as OpenAIEmbedding
 from openai.types.create_embedding_response import Usage

-from agent_framework.azure import AzureOpenAIEmbeddingClient
 from agent_framework.openai import (
    OpenAIEmbeddingClient,
    OpenAIEmbeddingOptions,
@@ -190,73 +189,6 @@ async def test_openai_empty_values_returns_empty(openai_unit_test_env: None) ->
    client.client.embeddings.create.assert_not_called()


-# --- Azure OpenAI unit tests ---
-
-
-def test_azure_construction_with_deployment_name() -> None:
-    client = AzureOpenAIEmbeddingClient(
-        deployment_name="text-embedding-3-small",
-        api_key="test-key",
-        endpoint="https://test.openai.azure.com/",
-    )
-    assert client.model_id == "text-embedding-3-small"
-
-
-def test_azure_construction_with_existing_client() -> None:
-    mock_client = MagicMock()
-    client = AzureOpenAIEmbeddingClient(
-        deployment_name="my-deployment",
-        async_client=mock_client,
-    )
-    assert client.model_id == "my-deployment"
-    assert client.client is mock_client
-
-
-def test_azure_construction_missing_deployment_name_raises(monkeypatch: pytest.MonkeyPatch) -> None:
-    monkeypatch.delenv("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME", raising=False)
-    with pytest.raises(ValueError, match="deployment name is required"):
-        AzureOpenAIEmbeddingClient(
-            api_key="test-key",
-            endpoint="https://test.openai.azure.com/",
-        )
-
-
-def test_azure_construction_missing_credentials_raises() -> None:
-    with pytest.raises(ValueError, match="api_key, credential, or a client"):
-        AzureOpenAIEmbeddingClient(
-            deployment_name="test",
-            endpoint="https://test.openai.azure.com/",
-        )
-
-
-async def test_azure_get_embeddings() -> None:
-    mock_response = _make_openai_response(
-        embeddings=[[0.1, 0.2]],
-    )
-    mock_async_client = MagicMock()
-    mock_async_client.embeddings = MagicMock()
-    mock_async_client.embeddings.create = AsyncMock(return_value=mock_response)
-
-    client = AzureOpenAIEmbeddingClient(
-        deployment_name="text-embedding-3-small",
-        async_client=mock_async_client,
-    )
-
-    result = await client.get_embeddings(["hello"])
-
-    assert len(result) == 1
-    assert result[0].vector == [0.1, 0.2]
-
-
-def test_azure_otel_provider_name() -> None:
-    mock_client = MagicMock()
-    client = AzureOpenAIEmbeddingClient(
-        deployment_name="test",
-        async_client=mock_client,
-    )
-    assert client.OTEL_PROVIDER_NAME == "azure.ai.openai"
-
-
 # --- Integration tests ---

 skip_if_openai_integration_tests_disabled = pytest.mark.skipif(
@@ -264,12 +196,6 @@ skip_if_openai_integration_tests_disabled = pytest.mark.skipif(
    reason="No real OPENAI_API_KEY provided; skipping integration tests.",
 )

-skip_if_azure_openai_integration_tests_disabled = pytest.mark.skipif(
-    not os.getenv("AZURE_OPENAI_ENDPOINT")
-    or (not os.getenv("AZURE_OPENAI_API_KEY") and not os.getenv("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME")),
-    reason="No Azure OpenAI credentials provided; skipping integration tests.",
-)
-

@skip_if_openai_integration_tests_disabled
@pytest.mark.flaky
@@ -315,49 +241,3 @@ async def test_integration_openai_get_embeddings_with_dimensions() -> None:

    assert len(result) == 1
    assert len(result[0].vector) == 256
-
-
-@skip_if_azure_openai_integration_tests_disabled
-@pytest.mark.flaky
-@pytest.mark.integration
-async def test_integration_azure_openai_get_embeddings() -> None:
-    """End-to-end test of Azure OpenAI embedding generation."""
-    client = AzureOpenAIEmbeddingClient()
-
-    result = await client.get_embeddings(["hello world"])
-
-    assert len(result) == 1
-    assert isinstance(result[0].vector, list)
-    assert len(result[0].vector) > 0
-    assert all(isinstance(v, float) for v in result[0].vector)
-    assert result[0].model_id is not None
-    assert result.usage is not None
-    assert result.usage["input_token_count"] > 0
-
-
-@skip_if_azure_openai_integration_tests_disabled
-@pytest.mark.flaky
-@pytest.mark.integration
-async def test_integration_azure_openai_get_embeddings_multiple() -> None:
-    """Test Azure OpenAI embedding generation for multiple inputs."""
-    client = AzureOpenAIEmbeddingClient()
-
-    result = await client.get_embeddings(["hello", "world", "test"])
-
-    assert len(result) == 3
-    dims = [len(e.vector) for e in result]
-    assert all(d == dims[0] for d in dims)
-
-
-@skip_if_azure_openai_integration_tests_disabled
-@pytest.mark.flaky
-@pytest.mark.integration
-async def test_integration_azure_openai_get_embeddings_with_dimensions() -> None:
-    """Test Azure OpenAI embedding generation with custom dimensions."""
-    client = AzureOpenAIEmbeddingClient()
-
-    options: OpenAIEmbeddingOptions = {"dimensions": 256}
-    result = await client.get_embeddings(["hello world"], options=options)
-
-    assert len(result) == 1
-    assert len(result[0].vector) == 256
@@ -1876,6 +1876,19 @@ def test_prepare_tools_for_openai_with_image_generation_options() -> None:
    assert image_tool["quality"] == "high"


+def test_prepare_tools_for_openai_with_custom_image_generation_model() -> None:
+    """Test image generation tool conversion with a custom model string."""
+    client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
+
+    tool = OpenAIResponsesClient.get_image_generation_tool(model="custom-image-model")
+
+    resp_tools = client._prepare_tools_for_openai([tool])
+    assert len(resp_tools) == 1
+    image_tool = resp_tools[0]
+    assert image_tool["type"] == "image_generation"
+    assert image_tool["model"] == "custom-image-model"
+
+
 def test_parse_chunk_from_openai_with_mcp_approval_request() -> None:
    """Test that a streaming mcp_approval_request event is parsed into FunctionApprovalRequestContent."""
    client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")