Python: restructure: Python samples into progressive 01-05 layout (#3862)

* restructure: Python samples into progressive 01-05 layout

- 01-get-started/: 6 numbered steps (hello agent → hosting)
- 02-agents/: all agent concept samples (tools, middleware, providers, etc.)
- 03-workflows/: ALL existing workflow samples preserved as-is
- 04-hosting/: azure-functions, durabletask, a2a
- 05-end-to-end/: demos, evaluation, hosted agents
- Old files moved to _to_delete/ for review
- Added AGENTS.md with structure documentation
- autogen-migration/ and semantic-kernel-migration/ preserved at root

* fix: switch to AzureOpenAI Foundry, fix CI failures

- Switch all 01-get-started samples to AzureOpenAIResponsesClient with
  Azure AI Foundry project endpoint (AZURE_AI_PROJECT_ENDPOINT +
  AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME + AzureCliCredential)
- Add _to_delete/ and 05-end-to-end/ to pyrightconfig.samples.json excludes
- Fix test paths in packages/ that referenced old getting_started/ dirs:
  durabletask conftest + streaming test, azurefunctions conftest,
  devui conftest + capture_messages + openai_sdk_integration
- Fix workflow_as_agent_human_in_the_loop.py import (sibling import)
- Update hosting READMEs and tool comment paths
- Replace root README.md with new structure overview
- Update AGENTS.md to document Azure OpenAI Foundry as default provider

* cleanup: remove _to_delete folder, copy resource files to active dirs

All files in _to_delete/ were either:
- Exact duplicates of files in the new structure (240 files)
- Same file with only comment path updates (100 files)
- One import-fix diff (workflow_as_agent_human_in_the_loop.py)
- One superseded minimal_sample.py

Resource files (sample.pdf, countries.json, employees.pdf, weather.json)
copied to 02-agents/sample_assets/ and 02-agents/resources/ since active
samples reference them.

* fix: address PR review comments, centralize resources, remove root duplicates

- Fix type annotation in 04_memory.py (string union -> proper types)
- Fix old sample paths in observability files
- Fix grammar/spelling in observability samples
- Move sample_assets/ and resources/ to shared/ folder
- Remove 8 duplicate observability files from 02-agents root
- Update resource path references in multimodal_input and provider samples

* fix: update broken links from old getting_started paths to new structure

- Update relative paths in READMEs: getting_started/ → 01-get-started/,
  02-agents/, 03-workflows/, 04-hosting/, 05-end-to-end/
- Fix absolute GitHub URLs in package READMEs
- Fix broken link in ollama package README

* fix: convert absolute GitHub URLs to relative paths for link checker

Absolute URLs to python/samples/ on main branch 404 until PR merges.
Converted to relative paths that linkspector can verify locally.

* fix: update link for handoff sample moved to orchestrations/

* fix: update chatkit-integration README path from demos/ to 05-end-to-end/

* fix: update broken links in orchestrations README to match flat directory structure

python/samples/01-get-started/04_memory.py

@@ -0,0 +1,91 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+import os
+from collections.abc import MutableSequence
+from typing import Any
+
+from agent_framework import Context, ContextProvider, Message
+from agent_framework.azure import AzureOpenAIResponsesClient
+from azure.identity import AzureCliCredential
+
+"""
+Agent Memory with Context Providers
+
+Context providers let you inject dynamic instructions and context into each
+agent invocation. This sample defines a simple provider that tracks the user's
+name and enriches every request with personalization instructions.
+
+Environment variables:
+  AZURE_AI_PROJECT_ENDPOINT        — Your Azure AI Foundry project endpoint
+  AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME — Model deployment name (e.g. gpt-4o)
+"""
+
+
+# <context_provider>
+class UserNameProvider(ContextProvider):
+    """A simple context provider that remembers the user's name."""
+
+    def __init__(self) -> None:
+        self.user_name: str | None = None
+
+    async def invoking(self, messages: Message | MutableSequence[Message], **kwargs: Any) -> Context:
+        """Called before each agent invocation — add extra instructions."""
+        if self.user_name:
+            return Context(instructions=f"The user's name is {self.user_name}. Always address them by name.")
+        return Context(instructions="You don't know the user's name yet. Ask for it politely.")
+
+    async def invoked(
+        self,
+        request_messages: Message | list[Message] | None = None,
+        response_messages: "Message | list[Message] | None" = None,
+        invoke_exception: Exception | None = None,
+        **kwargs: Any,
+    ) -> None:
+        """Called after each agent invocation — extract information."""
+        msgs = [request_messages] if isinstance(request_messages, Message) else list(request_messages or [])
+        for msg in msgs:
+            text = msg.text if hasattr(msg, "text") else ""
+            if isinstance(text, str) and "my name is" in text.lower():
+                # Simple extraction — production code should use structured extraction
+                self.user_name = text.lower().split("my name is")[-1].strip().split()[0].capitalize()
+# </context_provider>
+
+
+async def main() -> None:
+    # <create_agent>
+    credential = AzureCliCredential()
+    client = AzureOpenAIResponsesClient(
+        project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
+        deployment_name=os.environ["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"],
+        credential=credential,
+    )
+
+    memory = UserNameProvider()
+
+    agent = client.as_agent(
+        name="MemoryAgent",
+        instructions="You are a friendly assistant.",
+        context_provider=memory,
+    )
+    # </create_agent>
+
+    thread = agent.get_new_thread()
+
+    # The provider doesn't know the user yet — it will ask for a name
+    result = await agent.run("Hello! What's the square root of 9?", thread=thread)
+    print(f"Agent: {result}\n")
+
+    # Now provide the name — the provider extracts and stores it
+    result = await agent.run("My name is Alice", thread=thread)
+    print(f"Agent: {result}\n")
+
+    # Subsequent calls are personalized
+    result = await agent.run("What is 2 + 2?", thread=thread)
+    print(f"Agent: {result}\n")
+
+    print(f"[Memory] Stored user name: {memory.user_name}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())