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Python: [BREAKING] Python: Provider-leading client design & OpenAI package extraction (#4818)
* Python: Provider-leading client design & OpenAI package extraction Major refactoring of the Python Agent Framework client architecture: - Extract OpenAI clients into new `agent-framework-openai` package - Core package no longer depends on openai, azure-identity, azure-ai-projects - Rename clients for discoverability: OpenAIResponsesClient → OpenAIChatClient, OpenAIChatClient → OpenAIChatCompletionClient - Unify `model_id`/`deployment_name`/`model_deployment_name` → `model` param - New FoundryChatClient for Azure AI Foundry Responses API - New FoundryAgent/FoundryAgentClient for connecting to pre-configured Foundry agents - Remove OpenAIBase/OpenAIConfigMixin from non-deprecated client MRO - Deprecate AzureOpenAI* clients, AzureAIClient, OpenAIAssistantsClient - Reorganize samples: azure_openai+azure_ai+azure_ai_agent → azure/ - ADR-0020: Provider-Leading Client Design Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: missing Agent imports in samples, .model_id → .model in foundry_local sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: CI failures — mypy errors, coverage targets, sample imports - azure-ai mypy: add type ignores for TypedDict total=, model arg, forward ref - Coverage: replace core.azure/openai targets with openai package target - project_provider: add type annotation for opts dict Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: populate openai .pyi stub, fix broken README links, coverage targets Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixes * updated observabilitty * reset azure init.pyi * fix errors * updated adr number * fix foundry local * fixed not renamed docstrings and comments, and added deprecated markers to old classes * fix tests and pyprojects * fix test vars * updated function tests * update durable * updated test setup for functions * Fix Foundry auth in workflow samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize Python integration workflows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update hosting samples for Foundry Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger full CI rerun Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger CI rerun again Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * trigger rerun * trigger rerun * fix for litellm * undo durabletask changes * Move Foundry APIs into foundry namespace Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Foundry pyproject formatting Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Split provider samples by Foundry surface Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Restore hosting sample requirements Also fix the Foundry Local sample link after the provider sample move. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated tests * udpated foundry integration tests * removed dist from azurefunctions tests * Use separate Foundry clients for concurrent agents Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix client setup in azfunc and durable * disabled two tests * updated setup for some function and durable tests * improved azure openai setup with new clients * ignore deprecated * fixes * skip 11 * remove openai assistants int tests --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Eduard van Valkenburg ·
2026-03-25 09:56:29 +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: 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