Python: Reorganize A2A samples and use package A2AExecutor (#6165)

* Reorganize A2A samples: client demos in 02-agents, use package A2AExecutor

- Move client samples (agent_with_a2a, a2a_agent_as_function_tools) to samples/02-agents/a2a/
- Add new concept samples: polling, stream reconnection, protocol selection
- Replace sample agent_executor.py with package-level A2AExecutor (stream=True)
- Update 04-hosting/a2a to focus on server-side, point to 02-agents for clients
- Add README.md for the new 02-agents/a2a/ sample collection

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

* Fix streaming artifact coalescing and address PR review feedback

A2AExecutor fix:
- Generate a stable artifact_id per stream in _run_stream so all streaming
  chunks share the same ID, enabling proper append=True coalescing per the
  A2A spec (TaskArtifactUpdateEvent with same artifactId).
- Previously, item.message_id was None for OpenAI/Foundry streaming updates,
  causing the SDK to generate a new random UUID per token (100+ separate
  artifacts instead of 1 appended artifact).

Sample improvements:
- Replace join workaround with response.text now that coalescing works
- Add background=True to stream reconnection resume call (required for
  continuation token emission on in-progress tasks)
- Fix type ignore specificity in polling sample

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

---------

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

python/samples/04-hosting/a2a/README.md

@@ -1,39 +1,30 @@
-# A2A Agent Examples
+# A2A Server Hosting Examples
 
-This sample demonstrates how to host and consume agents using the [A2A (Agent2Agent) protocol](https://a2a-protocol.org/latest/) with the `agent_framework` package. There are three runnable entry points:
+This sample demonstrates how to **host** Agent Framework agents as A2A-compliant servers using the [A2A (Agent2Agent) protocol](https://a2a-protocol.org/latest/).
+
+> **Looking for client samples?** See [`samples/02-agents/a2a/`](../../02-agents/a2a/) for consuming remote A2A agents.
+
+## Server Samples
 
 | Run this file | To... |
 |---------------|-------|
-| **[`a2a_server.py`](a2a_server.py)** | Host an Agent Framework agent as an A2A-compliant server. |
-| **[`agent_with_a2a.py`](agent_with_a2a.py)** | Connect to an A2A server and send requests (non-streaming and streaming). |
-| **[`a2a_agent_as_function_tools.py`](a2a_agent_as_function_tools.py)** | Convert A2A agent skills into function tools for a host agent. |
+| **[`a2a_server.py`](a2a_server.py)** | Host an Agent Framework agent as an A2A-compliant server (multi-agent). |
+| **[`agent_framework_to_a2a.py`](agent_framework_to_a2a.py)** | Minimal example: expose a single agent as an A2A server. |
 
-The remaining files are supporting modules used by the server:
+## Supporting Modules
 
 | File | Description |
 |------|-------------|
-| [`agent_framework_to_a2a.py`](agent_framework_to_a2a.py) | Exposes an agent_framework agent as an A2A-compliant server. Demonstrates how to wrap an agent_framework agent and expose it as an A2A service that other A2A clients can discover and communicate with. |
 | [`agent_definitions.py`](agent_definitions.py) | Agent and AgentCard factory definitions for invoice, policy, and logistics agents. |
-| [`agent_executor.py`](agent_executor.py) | Bridges the a2a-sdk `AgentExecutor` interface to Agent Framework agents. |
 | [`invoice_data.py`](invoice_data.py) | Mock invoice data and tool functions for the invoice agent. |
 | [`a2a_server.http`](a2a_server.http) | REST Client requests for testing the server directly from VS Code. |
 
 ## Environment Variables
 
-Make sure to set the following environment variables before running the examples:
-
 ### Required (Server)
 - `FOUNDRY_PROJECT_ENDPOINT` — Your Azure AI Foundry project endpoint
 - `FOUNDRY_MODEL` — Model deployment name (e.g. `gpt-4o`)
 
-### Required (Client)
-- `A2A_AGENT_HOST` — URL of the A2A server (e.g. `http://localhost:5001/`)
-
-### Required (Function Tools Sample)
-- `A2A_AGENT_HOST` — URL of the A2A server (e.g. `http://localhost:5000/`)
-- `FOUNDRY_PROJECT_ENDPOINT` — Your Azure AI Foundry project endpoint
-- `FOUNDRY_MODEL` — Model deployment name (e.g. `gpt-4o`)
-
 ## Quick Start
 
 All commands below should be run from this directory:
@@ -67,7 +58,7 @@ uv run python a2a_server.py --agent-type policy
 
 ### 1. Start the A2A Server
 
-> **Note (Option A — pip users):** Replace `uv run python` with `python` in all `uv run` commands below (e.g. `python a2a_server.py ...`). `uv` is not required once the virtual environment is activated.
+> **Note (Option A — pip users):** Replace `uv run python` with `python` in all `uv run` commands below. `uv` is not required once the virtual environment is activated.
 
 Pick an agent type and start the server (each in its own terminal):
 
@@ -79,25 +70,12 @@ uv run python a2a_server.py --agent-type logistics --port 5002
 
 You can run one agent or all three — each listens on its own port.
 
-### 2. Run the A2A Client
+### 2. Run a Client
 
-In a separate terminal (from the same directory), point the client at a running server:
+Once a server is running, use any of the client samples in [`samples/02-agents/a2a/`](../../02-agents/a2a/):
 
 ```powershell
+cd python/samples/02-agents/a2a
 $env:A2A_AGENT_HOST = "http://localhost:5001/"
 uv run python agent_with_a2a.py
-
-# A2A server exposing an agent_framework agent
-uv run python agent_framework_to_a2a.py
-```
-
-### 3. Run the Function Tools Sample
-
-This sample resolves the remote agent's skills and registers each one as a function tool
-on a host Foundry-backed agent. The host agent then autonomously selects the right skill
-to handle the user's request.
-
-```powershell
-$env:A2A_AGENT_HOST = "http://localhost:5000/"
-uv run python a2a_agent_as_function_tools.py
 ```