Python: Fix tool normalization and provider sample consolidation (#3953)

* Fix tool normalization and provider samples

- restore callable/single-tool normalization paths and unset tool-choice behavior\n- consolidate and expand chat/provider samples (OpenAI/Azure/Anthropic/Ollama/Bedrock)\n- migrate Bedrock lazy import surface to agent_framework.amazon and move provider samples

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* small fix in sample

* Finalize provider, samples, and core cleanup

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix CopilotTool passthrough in agent

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* fix link

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Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

python/samples/02-agents/chat_client/README.md

@@ -1,41 +1,74 @@
 # Chat Client Examples
 
-This folder contains simple examples demonstrating direct usage of various chat clients.
+This folder contains examples for direct chat client usage patterns.
 
 ## Examples
 
 | File | Description |
 |------|-------------|
-| [`azure_assistants_client.py`](azure_assistants_client.py) | Direct usage of Azure Assistants Client for basic chat interactions with Azure OpenAI assistants. |
-| [`azure_chat_client.py`](azure_chat_client.py) | Direct usage of Azure Chat Client for chat interactions with Azure OpenAI models. |
-| [`azure_responses_client.py`](azure_responses_client.py) | Direct usage of Azure Responses Client for structured response generation with Azure OpenAI models. |
+| [`built_in_chat_clients.py`](built_in_chat_clients.py) | Consolidated sample for built-in chat clients. Uses `get_client()` to create the selected client and pass it to `main()`. |
 | [`chat_response_cancellation.py`](chat_response_cancellation.py) | Demonstrates how to cancel chat responses during streaming, showing proper cancellation handling and cleanup. |
-| [`azure_ai_chat_client.py`](azure_ai_chat_client.py) | Direct usage of Azure AI Chat Client for chat interactions with Azure AI models. |
-| [`openai_assistants_client.py`](openai_assistants_client.py) | Direct usage of OpenAI Assistants Client for basic chat interactions with OpenAI assistants. |
-| [`openai_chat_client.py`](openai_chat_client.py) | Direct usage of OpenAI Chat Client for chat interactions with OpenAI models. |
-| [`openai_responses_client.py`](openai_responses_client.py) | Direct usage of OpenAI Responses Client for structured response generation with OpenAI models. |
 | [`custom_chat_client.py`](custom_chat_client.py) | Demonstrates how to create custom chat clients by extending the `BaseChatClient` class. Shows a `EchoingChatClient` implementation and how to integrate it with `Agent` using the `as_agent()` method. |
 
+## Selecting a built-in client
+
+`built_in_chat_clients.py` starts with:
+
+```python
+asyncio.run(main("openai_chat"))
+```
+
+Change the argument to pick a client:
+
+- `openai_chat`
+- `openai_responses`
+- `openai_assistants`
+- `anthropic`
+- `ollama`
+- `bedrock`
+- `azure_openai_chat`
+- `azure_openai_responses`
+- `azure_openai_responses_foundry`
+- `azure_openai_assistants`
+- `azure_ai_agent`
+
+Example:
+
+```bash
+uv run samples/02-agents/chat_client/built_in_chat_clients.py
+```
+
 ## Environment Variables
 
-Depending on which client you're using, set the appropriate environment variables:
+Depending on the selected client, set the appropriate environment variables:
 
 **For Azure clients:**
 - `AZURE_OPENAI_ENDPOINT`: Your Azure OpenAI endpoint
 - `AZURE_OPENAI_CHAT_DEPLOYMENT_NAME`: The name of your Azure OpenAI chat deployment
 - `AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME`: The name of your Azure OpenAI responses deployment
 
-**For Azure AI client:**
+**For Azure OpenAI Foundry responses client (`azure_openai_responses_foundry`):**
 - `AZURE_AI_PROJECT_ENDPOINT`: Your Azure AI project endpoint
-- `AZURE_AI_MODEL_DEPLOYMENT_NAME`: The name of your model deployment
+- `AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME`: The name of your Azure OpenAI responses deployment
+
+**For Azure AI agent client (`azure_ai_agent`):**
+- `AZURE_AI_PROJECT_ENDPOINT`: Your Azure AI project endpoint
+- `AZURE_AI_MODEL_DEPLOYMENT_NAME`: The name of your model deployment (used by `azure_ai_agent`)
 
 **For OpenAI clients:**
 - `OPENAI_API_KEY`: Your OpenAI API key
-- `OPENAI_CHAT_MODEL_ID`: The OpenAI model to use for chat clients (e.g., `gpt-4o`, `gpt-4o-mini`, `gpt-3.5-turbo`)
-- `OPENAI_RESPONSES_MODEL_ID`: The OpenAI model to use for responses clients (e.g., `gpt-4o`, `gpt-4o-mini`, `gpt-3.5-turbo`)
+- `OPENAI_CHAT_MODEL_ID`: The OpenAI model for `openai_chat` and `openai_assistants`
+- `OPENAI_RESPONSES_MODEL_ID`: The OpenAI model for `openai_responses`
 
-**For Ollama client:**
-- `OLLAMA_HOST`: Your Ollama server URL (defaults to `http://localhost:11434` if not set)
-- `OLLAMA_MODEL_ID`: The Ollama model to use for chat (e.g., `llama3.2`, `llama2`, `codellama`)
+**For Anthropic client (`anthropic`):**
+- `ANTHROPIC_API_KEY`: Your Anthropic API key
+- `ANTHROPIC_CHAT_MODEL_ID`: The Anthropic model ID (for example, `claude-sonnet-4-5`)
 
-> **Note**: For Ollama, ensure you have Ollama installed and running locally with at least one model downloaded. Visit [https://ollama.com/](https://ollama.com/) for installation instructions.
+**For Ollama client (`ollama`):**
+- `OLLAMA_HOST`: Ollama server URL (defaults to `http://localhost:11434` if unset)
+- `OLLAMA_MODEL_ID`: Ollama model name (for example, `mistral`, `qwen2.5:8b`)
+
+**For Bedrock client (`bedrock`):**
+- `BEDROCK_CHAT_MODEL_ID`: Bedrock model ID (for example, `anthropic.claude-3-5-sonnet-20240620-v1:0`)
+- `BEDROCK_REGION`: AWS region (defaults to `us-east-1` if unset)
+- AWS credentials via standard environment variables (for example, `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`)