Python: added inline yaml sample (#2582)

* added inline yaml sample

* fixed some typos and added intro comment

* added description params and pass through to client

* add azure assistants

* fix tests

* observabiltiy mypy fix

* for some reason mypy doesn't accept a subclass

---------

Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>

python/samples/getting_started/declarative/README.md

@@ -47,7 +47,17 @@ Shows how to create an agent that can search and retrieve information from Micro
 
 **Key concepts**: Azure AI Foundry integration, MCP server usage, async patterns, resource management
 
-### 3. **Azure OpenAI Responses Agent** ([`azure_openai_responses_agent.py`](./azure_openai_responses_agent.py))
+### 3. **Inline YAML Agent** ([`inline_yaml.py`](./inline_yaml.py))
+
+Shows how to create an agent using an inline YAML string rather than a file.
+
+- Uses Azure AI Foundry v2 Client with instructions.
+
+**Requirements**: `pip install agent-framework-azure-ai --pre`
+
+**Key concepts**: Inline YAML definition.
+
+### 4. **Azure OpenAI Responses Agent** ([`azure_openai_responses_agent.py`](./azure_openai_responses_agent.py))
 
 Illustrates a basic agent using Azure OpenAI with structured responses.
 
@@ -58,7 +68,7 @@ Illustrates a basic agent using Azure OpenAI with structured responses.
 
 **Key concepts**: Azure OpenAI integration, credential management, structured outputs
 
-### 4. **OpenAI Responses Agent** ([`openai_responses_agent.py`](./openai_responses_agent.py))
+### 5. **OpenAI Responses Agent** ([`openai_responses_agent.py`](./openai_responses_agent.py))
 
 Demonstrates the simplest possible agent using OpenAI directly.
 
@@ -243,6 +253,7 @@ Each sample can be run independently. Make sure you have the required environmen
 # Run a specific sample
 python get_weather_agent.py
 python microsoft_learn_agent.py
+python inline_yaml.py
 python azure_openai_responses_agent.py
 python openai_responses_agent.py
 ```

python/samples/getting_started/declarative/get_weather_agent.py

@@ -26,7 +26,7 @@ async def main():
 
     # create the AgentFactory with a chat client and bindings
     agent_factory = AgentFactory(
-        AzureOpenAIResponsesClient(credential=AzureCliCredential()),
+        chat_client=AzureOpenAIResponsesClient(credential=AzureCliCredential()),
         bindings={"get_weather": get_weather},
     )
     # create the agent from the yaml

python/samples/getting_started/declarative/inline_yaml.py

@@ -0,0 +1,44 @@
+# Copyright (c) Microsoft. All rights reserved.
+import asyncio
+
+from agent_framework.declarative import AgentFactory
+from azure.identity.aio import AzureCliCredential
+
+"""
+This sample shows how to create an agent using an inline YAML string rather than a file.
+
+It uses a Azure AI Client so it needs the credential to be passed into the AgentFactory.
+
+Prerequisites:
+- `pip install agent-framework-azure-ai agent-framework-declarative --pre`
+- Set the following environment variables in a .env file or your environment:
+    - AZURE_AI_PROJECT_ENDPOINT
+    - AZURE_OPENAI_MODEL
+"""
+
+
+async def main():
+    """Create an agent from a declarative YAML specification and run it."""
+    yaml_definition = """kind: Prompt
+name: DiagnosticAgent
+displayName: Diagnostic Assistant
+instructions: Specialized diagnostic and issue detection agent for systems with critical error protocol and automatic handoff capabilities
+description: A agent that performs diagnostics on systems and can escalate issues when critical errors are detected.
+
+model:
+  id: =Env.AZURE_OPENAI_MODEL
+  connection:
+    kind: remote
+    endpoint: =Env.AZURE_AI_PROJECT_ENDPOINT
+"""
+    # create the agent from the yaml
+    async with (
+        AzureCliCredential() as credential,
+        AgentFactory(client_kwargs={"async_credential": credential}).create_agent_from_yaml(yaml_definition) as agent,
+    ):
+        response = await agent.run("What can you do for me?")
+        print("Agent response:", response.text)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())