Python: adr for python client constructors

python/.env.example

@@ -19,16 +19,41 @@ OPENAI_RESPONSES_MODEL_ID=""
 AZURE_OPENAI_ENDPOINT=""
 AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=""
 AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME=""
+# Use API key authentication (alternative to Azure CLI/DefaultAzureCredential)
+# AZURE_OPENAI_API_KEY=""
+# Optional: Explicit backend selection (openai, azure)
+# OPENAI_CHAT_CLIENT_BACKEND=
 # Mem0
 MEM0_API_KEY=""
 # Copilot Studio
 COPILOTSTUDIOAGENT__ENVIRONMENTID=""
 COPILOTSTUDIOAGENT__SCHEMANAME=""
 COPILOTSTUDIOAGENT__TENANTID=""
 COPILOTSTUDIOAGENT__AGENTAPPID=""
-# Anthropic
+# Anthropic (common)
+ANTHROPIC_CHAT_MODEL_ID=""
+# Optional: Explicit backend selection (anthropic, foundry, vertex, bedrock)
+# ANTHROPIC_CHAT_CLIENT_BACKEND=
+
+# Anthropic API (Direct)
 ANTHROPIC_API_KEY=""
-ANTHROPIC_MODEL=""
+# ANTHROPIC_BASE_URL=
+
+# Anthropic via Azure AI Foundry
+# ANTHROPIC_FOUNDRY_API_KEY=
+# ANTHROPIC_FOUNDRY_RESOURCE=
+# ANTHROPIC_FOUNDRY_BASE_URL=
+
+# Anthropic via Google Vertex AI
+# ANTHROPIC_VERTEX_ACCESS_TOKEN=
+# ANTHROPIC_VERTEX_PROJECT_ID=
+# CLOUD_ML_REGION=
+
+# Anthropic via AWS Bedrock
+# ANTHROPIC_AWS_ACCESS_KEY_ID=
+# ANTHROPIC_AWS_SECRET_ACCESS_KEY=
+# ANTHROPIC_AWS_PROFILE=
+# ANTHROPIC_AWS_REGION=
 # Ollama
 OLLAMA_ENDPOINT=""
 OLLAMA_MODEL=""

python/packages/ag-ui/agent_framework_ag_ui_examples/server/api/backend_tool_rendering.py

@@ -3,7 +3,7 @@
 """Backend tool rendering endpoint."""
 
 from agent_framework.ag_ui import add_agent_framework_fastapi_endpoint
-from agent_framework.azure import AzureOpenAIChatClient
+from agent_framework.openai import OpenAIChatClient
 from fastapi import FastAPI
 
 from ...agents.weather_agent import weather_agent
@@ -16,7 +16,7 @@ def register_backend_tool_rendering(app: FastAPI) -> None:
         app: The FastAPI application.
     """
     # Create a chat client and call the factory function
-    chat_client = AzureOpenAIChatClient()
+    chat_client = OpenAIChatClient(backend="azure")
 
     add_agent_framework_fastapi_endpoint(
         app,

python/packages/ag-ui/agent_framework_ag_ui_examples/server/main.py

@@ -10,7 +10,7 @@
 from agent_framework._clients import BaseChatClient
 from agent_framework.ag_ui import add_agent_framework_fastapi_endpoint
 from agent_framework.anthropic import AnthropicClient
-from agent_framework.azure import AzureOpenAIChatClient
+from agent_framework.openai import OpenAIChatClient
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 
@@ -65,7 +65,7 @@
 # You can use different chat clients for different agents if needed
 # Set CHAT_CLIENT=anthropic to use Anthropic, defaults to Azure OpenAI
 chat_client: BaseChatClient[ChatOptions] = (
-    AnthropicClient() if os.getenv("CHAT_CLIENT", "").lower() == "anthropic" else AzureOpenAIChatClient()
+    AnthropicClient() if os.getenv("CHAT_CLIENT", "").lower() == "anthropic" else OpenAIChatClient(backend="azure")
 )
 
 # Agentic Chat - basic chat agent

python/packages/ag-ui/getting_started/server.py

@@ -7,7 +7,7 @@
 
 from agent_framework import ChatAgent, tool
 from agent_framework.ag_ui import add_agent_framework_fastapi_endpoint
-from agent_framework.azure import AzureOpenAIChatClient
+from agent_framework.openai import OpenAIChatClient
 from dotenv import load_dotenv
 from fastapi import Depends, FastAPI, HTTPException, Security
 from fastapi.security import APIKeyHeader
@@ -117,9 +117,10 @@ def get_time_zone(location: str) -> str:
 agent = ChatAgent(
     name="AGUIAssistant",
     instructions="You are a helpful assistant. Use get_weather for weather and get_time_zone for time zones.",
-    chat_client=AzureOpenAIChatClient(
+    chat_client=OpenAIChatClient(
+        backend="azure",
         endpoint=endpoint,
-        deployment_name=deployment_name,
+        model_id=deployment_name,
     ),
     tools=[get_time_zone],  # ONLY server-side tools
 )

python/packages/anthropic/README.md

@@ -8,11 +8,87 @@ pip install agent-framework-anthropic --pre
 
 ## Anthropic Integration
 
-The Anthropic integration enables communication with the Anthropic API, allowing your Agent Framework applications to leverage Anthropic's capabilities.
+The Anthropic integration enables communication with Anthropic's Claude models through multiple backends:
+
+- **Anthropic API** (direct) - Default, highest precedence
+- **Azure AI Foundry** - Claude models via Azure
+- **Google Vertex AI** - Claude models via Google Cloud
+- **AWS Bedrock** - Claude models via AWS
 
 ### Basic Usage Example
 
+```python
+from agent_framework_anthropic import AnthropicClient
+
+# Using environment variables (ANTHROPIC_API_KEY, ANTHROPIC_CHAT_MODEL_ID)
+client = AnthropicClient()
+
+# Or with explicit parameters
+client = AnthropicClient(
+    api_key="sk-...",
+    model_id="claude-sonnet-4-5-20250929",
+)
+```
+
+### Multi-Backend Support
+
+The client automatically detects which backend to use based on available credentials, or you can explicitly specify the backend:
+
+```python
+# Explicit backend selection
+client = AnthropicClient(backend="anthropic")  # Direct Anthropic API
+client = AnthropicClient(backend="foundry")    # Azure AI Foundry
+client = AnthropicClient(backend="vertex")     # Google Vertex AI
+client = AnthropicClient(backend="bedrock")    # AWS Bedrock
+```
+
+### Environment Variables
+
+#### Anthropic API (Direct)
+| Variable | Description |
+|----------|-------------|
+| `ANTHROPIC_API_KEY` | Anthropic API key |
+| `ANTHROPIC_CHAT_MODEL_ID` | Model ID (e.g., `claude-sonnet-4-5-20250929`) |
+| `ANTHROPIC_BASE_URL` | Optional custom base URL |
+
+#### Azure AI Foundry
+| Variable | Description |
+|----------|-------------|
+| `ANTHROPIC_FOUNDRY_API_KEY` | Foundry API key (or use `ad_token_provider`) |
+| `ANTHROPIC_FOUNDRY_RESOURCE` | Azure resource name |
+| `ANTHROPIC_FOUNDRY_BASE_URL` | Optional custom endpoint URL |
+| `ANTHROPIC_CHAT_MODEL_ID` | Model ID |
+
+#### Google Vertex AI
+| Variable | Description |
+|----------|-------------|
+| `ANTHROPIC_VERTEX_ACCESS_TOKEN` | Google access token (or use `google_credentials`) |
+| `ANTHROPIC_VERTEX_PROJECT_ID` | GCP project ID |
+| `CLOUD_ML_REGION` | GCP region (e.g., `us-central1`) |
+| `ANTHROPIC_VERTEX_BASE_URL` | Optional custom endpoint URL |
+| `ANTHROPIC_CHAT_MODEL_ID` | Model ID |
+
+#### AWS Bedrock
+| Variable | Description |
+|----------|-------------|
+| `ANTHROPIC_AWS_ACCESS_KEY_ID` | AWS access key |
+| `ANTHROPIC_AWS_SECRET_ACCESS_KEY` | AWS secret key |
+| `ANTHROPIC_AWS_SESSION_TOKEN` | Optional session token |
+| `ANTHROPIC_AWS_PROFILE` | AWS profile name (alternative to access keys) |
+| `ANTHROPIC_AWS_REGION` | AWS region |
+| `ANTHROPIC_BEDROCK_BASE_URL` | Optional custom endpoint URL |
+| `ANTHROPIC_CHAT_MODEL_ID` | Model ID |
+
+#### Backend Selection
+| Variable | Description |
+|----------|-------------|
+| `ANTHROPIC_CHAT_CLIENT_BACKEND` | Explicit backend: `anthropic`, `foundry`, `vertex`, or `bedrock` |
+
+### Examples
+
 See the [Anthropic agent examples](https://github.com/microsoft/agent-framework/tree/main/python/samples/getting_started/agents/anthropic/) which demonstrate:
 
-- Connecting to a Anthropic endpoint with an agent
+- Connecting to Anthropic with an agent
 - Streaming and non-streaming responses
+- Using different backends (Foundry, Vertex, Bedrock)
+- Advanced features like hosted tools and thinking

python/packages/anthropic/agent_framework_anthropic/__init__.py

@@ -3,14 +3,17 @@
 import importlib.metadata
 
 from ._chat_client import AnthropicChatOptions, AnthropicClient
+from ._shared import AnthropicBackend, AnthropicSettings
 
 try:
     __version__ = importlib.metadata.version(__name__)
 except importlib.metadata.PackageNotFoundError:
     __version__ = "0.0.0"  # Fallback for development mode
 
 __all__ = [
+    "AnthropicBackend",
     "AnthropicChatOptions",
     "AnthropicClient",
+    "AnthropicSettings",
     "__version__",
 ]