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feature/python-add-workflow-reset
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Python: [BREAKING] Python: move Azure AI embeddings to Foundry (#5056)
* renamed AzureAIINferenceEmbeddings and lazy load azure-cosmos and env var rename * updated coverage * fix readme
Eduard van Valkenburg ·
2026-04-02 11:26:35 +00:00 -
Python: Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference (#4207)
* Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference Add embedding client implementations to existing provider packages: - OllamaEmbeddingClient: Text embeddings via Ollama's embed API - BedrockEmbeddingClient: Text embeddings via Amazon Titan on Bedrock - AzureAIInferenceEmbeddingClient: Text and image embeddings via Azure AI Inference, supporting Content | str input with separate model IDs for text (AZURE_AI_INFERENCE_EMBEDDING_MODEL_ID) and image (AZURE_AI_INFERENCE_IMAGE_EMBEDDING_MODEL_ID) endpoints Additional changes: - Rename EmbeddingCoT -> EmbeddingT, EmbeddingOptionsCoT -> EmbeddingOptionsT - Add otel_provider_name passthrough to all embedding clients - Register integration pytest marker in all packages - Add lazy-loading namespace exports for Ollama and Bedrock embeddings - Add image embedding sample using Cohere-embed-v3-english - Add azure-ai-inference dependency to azure-ai package Part of #1188 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix mypy duplicate name and ruff lint issues - Rename second 'vector' variable to 'img_vector' in image embedding loop - Combine nested with statements in tests - Remove unused result assignments in tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updates from feedback * Fix CI failures in embedding usage handling - Fix Azure AI embedding mypy issues by normalizing vectors to list[float], safely accumulating optional usage token fields, and filtering None entries before constructing GeneratedEmbeddings - Avoid Bandit false positive by initializing usage details as an empty dict - Update OpenAI embedding tests to assert canonical usage keys (input_token_count/total_token_count) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-02-25 17:45:08 +00:00 -
Python: updated integration tests and guidance (#4181)
* updated integration tests and guidance * fixed merge test * updated integration tests * fix: remove duplicate --dist loadfile flag from pytest-xdist config Only one --dist mode can be active at a time; the second value silently overrides the first. Keep --dist worksteal (dynamic load balancing) and remove the redundant --dist loadfile from all workflow files and pyproject.toml configs. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: add keep-in-sync notes for merge and integration test workflows Both python-merge-tests.yml and python-integration-tests.yml share the same parallel job structure. Added sync reminders in workflow file comments, the python-testing SKILL.md, and CODING_STANDARD.md. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refactor: remove RUN_INTEGRATION_TESTS flag Integration test gating now uses two mechanisms: - `@pytest.mark.integration` for test selection via `-m` filtering - `skip_if_*_disabled` for credential/service availability checks The RUN_INTEGRATION_TESTS env var was redundant since the marker handles selection and the skip decorators already check for actual credentials. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: sync missing env vars from merge-tests to integration-tests Add OPENAI_EMBEDDINGS_MODEL_ID and AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME to python-integration-tests.yml to match python-merge-tests.yml. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: remove remaining RUN_INTEGRATION_TESTS from embedding tests and docs Missed test_openai_embedding_client.py and vector-stores README in the earlier cleanup. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * set functions tests to 3.10 --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-02-24 09:35:46 +00:00 -
Python: feat(python): Add embedding abstractions and OpenAI implementation (Phase 1) (#4153)
* feat(python): Add embedding abstractions and OpenAI implementation (Phase 1) This PR contains two parts: 1. **Overall migration plan** for porting vector stores and embeddings from Semantic Kernel to Agent Framework (docs/features/vector-stores-and-embeddings/README.md) covering all 10 phases from core abstractions through connectors and TextSearch. 2. **Phase 1 implementation** — core embedding abstractions and OpenAI/Azure OpenAI embedding clients: Core types (_types.py): - EmbeddingGenerationOptions TypedDict (total=False) - Embedding[EmbeddingT] generic class with model_id, dimensions, created_at - GeneratedEmbeddings[EmbeddingT, EmbeddingOptionsT] list container with options, usage - EmbeddingInputT (default str) and EmbeddingT (default list[float]) TypeVars Protocol + base class (_clients.py): - SupportsGetEmbeddings protocol — Generic[EmbeddingInputT, EmbeddingT, OptionsContraT] - BaseEmbeddingClient ABC — Generic[EmbeddingInputT, EmbeddingT, OptionsCoT] Telemetry (observability.py): - EmbeddingTelemetryLayer with gen_ai.operation.name = "embeddings" OpenAI implementation (openai/_embedding_client.py): - RawOpenAIEmbeddingClient, OpenAIEmbeddingClient, OpenAIEmbeddingOptions - Uses _ensure_client() factory pattern Azure OpenAI implementation (azure/_embedding_client.py): - AzureOpenAIEmbeddingClient following AzureOpenAIChatClient pattern - Supports API key, Entra ID credentials, env var configuration Tests: - 47 unit tests for types, protocol, base class, OpenAI, and Azure clients - 6 integration tests (gated behind RUN_INTEGRATION_TESTS + credentials) Samples: - samples/02-agents/embeddings/openai_embeddings.py - samples/02-agents/embeddings/azure_openai_embeddings.py Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Add AzureOpenAIEmbeddingClient to azure __init__.pyi stub Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * ci: Add embedding env vars to Python integration tests Map OPENAI_EMBEDDING_MODEL_ID and AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME from GitHub vars to the integration test environment. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Handle base64 encoding_format in OpenAI embedding client When encoding_format='base64' is used, the OpenAI API returns base64-encoded floats instead of a JSON array. Decode these automatically to list[float] so the return type stays consistent regardless of encoding format. Also adds a unit test for base64 decoding and fixes minor docstring/import issues. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Only record INPUT_TOKENS for embedding telemetry Embeddings have no output/completion tokens. Remove OUTPUT_TOKENS recording which was double-counting prompt_tokens via the total_tokens fallback. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Resolve mypy variance error and lint warning Use contravariant/covariant TypeVars for SupportsGetEmbeddings Protocol. Combine nested if into single statement in telemetry layer. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Make EmbeddingCoT invariant for mypy compatibility GeneratedEmbeddings is invariant in its type param, so the Protocol TypeVar cannot be covariant. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Address PR review - empty values guard, service_url for telemetry - Add early return for empty values in get_embeddings to avoid unnecessary API calls - Add service_url() method to RawOpenAIEmbeddingClient for proper telemetry endpoint reporting - Add test for empty values behavior Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Fix OpenAI chat client compatibility with third-party endpoints and OTel 0.4.14 (#4161) * Fix system message content sent as list instead of string Some OpenAI-compatible endpoints (e.g. NVIDIA NIM) reject system messages when content is a list of content parts. This change flattens system and developer message content to a plain string in the Chat Completions client. Fixes https://github.com/microsoft/agent-framework/issues/1407 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix compatibility with opentelemetry-semantic-conventions-ai 0.4.14 Version 0.4.14 removed several LLM_* attributes from SpanAttributes (LLM_SYSTEM, LLM_REQUEST_MODEL, LLM_RESPONSE_MODEL, LLM_REQUEST_MAX_TOKENS, LLM_REQUEST_TEMPERATURE, LLM_REQUEST_TOP_P, LLM_TOKEN_TYPE). Move these to the OtelAttr enum with their well-known gen_ai.* string values and update all references in observability.py and tests. Fixes https://github.com/microsoft/agent-framework/issues/4160 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Flatten text-only message content to string for all roles Extend the system/developer fix to all message roles. Text-only content lists are now post-processed into plain strings, while multimodal content (text + images/audio) remains as a list. This fixes compatibility with OpenAI-like endpoints that cannot deserialize list content (e.g. Foundry Local's Neutron backend). Partially fixes https://github.com/microsoft/agent-framework/issues/4084 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix streaming text lost when usage data in same chunk Some providers (e.g. Gemini) include both usage data and text content in the same streaming chunk. The early return on chunk.usage caused text and tool call parsing to be skipped entirely. Remove the early return and process usage alongside text/tool calls. Fixes https://github.com/microsoft/agent-framework/issues/3434 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix mypy errors in _chat_client.py Rename shadowed variable 'args' in system/developer branch to 'sys_args' and rename loop variable 'content' to 'msg_content' to avoid type conflict. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * reorder imports * fix: Use OtelAttr.REQUEST_MODEL instead of removed SpanAttributes.LLM_REQUEST_MODEL Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: Add score_threshold to vector store plan Reference SK .NET PR #13501 for score threshold filtering semantics. Include score_threshold in SearchOptions from Phase 3. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: Add reference to roji's SK .NET MEVD work for SQL connectors Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Clear env vars in construction tests to avoid CI leakage Tests for missing API key / model ID now use monkeypatch.delenv to ensure env vars from the integration test environment don't prevent the expected ValueError from being raised. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-02-24 07:40:20 +00:00