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Eduard van Valkenburg 6138487888 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>

6138487888 · 2026-02-25 17:45:08 +00:00

History

agent_framework_a2a

Python: [BREAKING] Fix #3613 chat/agent message typing alignment (#3920 )

2026-02-16 15:27:25 +00:00

tests

Python: [BREAKING] Simplify API: ChatAgent -> Agent, ChatMessage -> Message (#3747 )

2026-02-10 23:04:32 +00:00

AGENTS.md

.NET: Python: Add AGENTS.md files and update coding standards (#3644 )

2026-02-05 10:27:46 +00:00

LICENSE

Python: basic python a2a support (#906 )

2025-09-29 17:53:45 +00:00

pyproject.toml

Python: Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference (#4207 )

2026-02-25 17:45:08 +00:00

README.md

Python: restructure: Python samples into progressive 01-05 layout (#3862 )

2026-02-12 17:36:36 +00:00

README.md

Get Started with Microsoft Agent Framework A2A

Please install this package via pip:

pip install agent-framework-a2a --pre

A2A Agent Integration

The A2A agent integration enables communication with remote A2A-compliant agents using the standardized A2A protocol. This allows your Agent Framework applications to connect to agents running on different platforms, languages, or services.

Basic Usage Example

See the A2A agent examples which demonstrate:

Connecting to remote A2A agents
Sending messages and receiving responses
Handling different content types (text, files, data)
Streaming responses and real-time interaction