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>

python/packages/core/tests/openai/test_openai_embedding_client.py

@@ -100,8 +100,8 @@ async def test_openai_get_embeddings_usage(openai_unit_test_env: None) -> None:
     result = await client.get_embeddings(["test"])
 
     assert result.usage is not None
-    assert result.usage["prompt_tokens"] == 10
-    assert result.usage["total_tokens"] == 10
+    assert result.usage["input_token_count"] == 10
+    assert result.usage["total_token_count"] == 10
 
 
 async def test_openai_options_passthrough_dimensions(openai_unit_test_env: None) -> None:
@@ -284,7 +284,7 @@ async def test_integration_openai_get_embeddings() -> None:
     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["prompt_tokens"] > 0
+    assert result.usage["input_token_count"] > 0
 
 
 @skip_if_openai_integration_tests_disabled
@@ -327,7 +327,7 @@ async def test_integration_azure_openai_get_embeddings() -> None:
     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["prompt_tokens"] > 0
+    assert result.usage["input_token_count"] > 0
 
 
 @skip_if_azure_openai_integration_tests_disabled