Python: [BREAKING] PR2 — Wire context provider pipeline, remove old types, update all consumers (#3850)

* PR2: Wire context provider pipeline and update all internal consumers

- Replace AgentThread with AgentSession across all packages
- Replace ContextProvider with BaseContextProvider across all packages
- Replace context_provider param with context_providers (Sequence)
- Replace thread= with session= in run() signatures
- Replace get_new_thread() with create_session()
- Add get_session(service_session_id) to agent interface
- DurableAgentThread -> DurableAgentSession
- Remove _notify_thread_of_new_messages from WorkflowAgent
- Wire before_run/after_run context provider pipeline in RawAgent
- Auto-inject InMemoryHistoryProvider when no providers configured

* fix: update all tests for context provider pipeline, fix lazy-loaders, remove old test files

* refactor: update all sample files for context provider pipeline (AgentThread→AgentSession, ContextProvider→BaseContextProvider)

* fix: update remaining ag-ui references (client docstring, getting_started sample)

* fix: make get_session service_session_id keyword-only to avoid confusion with session_id

* refactor: rename _RunContext.thread_messages to session_messages

* refactor: remove _threads.py, _memory.py, and old provider files; migrate devui to use plain message lists

* rename: remove _new_ prefix from test files

* refactor: rewrite SlidingWindowChatMessageStore as SlidingWindowHistoryProvider(InMemoryHistoryProvider)

* fix: read full history from session state directly instead of reaching into provider internals

* fix: update stale .pyi stubs, sample imports, and README references for new provider types

* fix: remove stale message_store, _notify_thread_of_new_messages, and session_id.key references in samples

* refactor: merge context_providers and sessions sample folders into sessions, remove aggregate_context_provider

* refactor: UserInfoMemory stores state in session.state instead of instance attributes

* feat: add Pydantic BaseModel support to session state serialization

Pydantic models stored in session.state are now automatically serialized
via model_dump() and restored via model_validate() during to_dict()/from_dict()
round-trips. Models are auto-registered on first serialization; use
register_state_type() for cold-start deserialization.

Also export register_state_type as a public API.

* fix mem0

* Update sample README links and descriptions for session terminology

- Replace 'thread' with 'session' in sample descriptions across all READMEs
- Update file links for renamed samples (mem0_sessions, redis_sessions, etc.)
- Fix Threads section → Sessions section in main samples/README.md
- Update tools, middleware, workflows, durabletask, azure_functions READMEs
- Update architecture diagrams in concepts/tools/README.md
- Update migration guides (autogen, semantic-kernel)

* Fix broken Redis README link to renamed sample

* Fix Mem0 OSS client search: pass scoping params as direct kwargs

AsyncMemory (OSS) expects user_id/agent_id/run_id as direct kwargs,
while AsyncMemoryClient (Platform) expects them in a filters dict.
Adds tests for both client types.

Port of fix from #3844 to new Mem0ContextProvider.

* Fix rebase issues: restore missing _conversation_state.py and checkpoint decode logic

- Add back _conversation_state.py (encode/decode_chat_messages) lost in rebase
- Fix on_checkpoint_restore to decode cache/conversation with decode_chat_messages
- Fix on_checkpoint_restore to use decode_checkpoint_value for pending requests
- Add tests/workflow/__init__.py for relative import support
- Fix test_agent_executor checkpoint selection (checkpoints[1] not superstep)

* Add STORES_BY_DEFAULT ClassVar to skip redundant InMemoryHistoryProvider injection

Chat clients that store history server-side by default (OpenAI Responses API,
Azure AI Agent) now declare STORES_BY_DEFAULT = True. The agent checks this
during auto-injection and skips InMemoryHistoryProvider unless the user
explicitly sets store=False.

* Fix broken markdown links in azure_ai and redis READMEs

* Fix getting-started samples to use session API instead of removed thread/ContextProvider API

* updates to workflow as agent

* fix group chat import

* Rename Thread→Session throughout, fix service_session_id propagation, remove stale AGUIThread

- Fix: Propagate conversation_id from ChatResponse back to session.service_session_id
  in both streaming and non-streaming paths in _agents.py
- Rename AgentThreadException → AgentSessionException
- Remove stale AGUIThread from ag_ui lazy-loader
- Rename use_service_thread → use_service_session in ag-ui package
- Rename test functions from *_thread_* to *_session_*
- Rename sample files from *_thread* to *_session*
- Update docstrings and comments: thread → session
- Update _mcp.py kwargs filter: add 'session' alongside 'thread'
- Fix ContinuationToken docstring example: thread=thread → session=session
- Fix _clients.py docstring: 'Agent threads' → 'Agent sessions'

* Fix broken markdown links after thread→session file renames

* fix azure ai test

python/samples/getting_started/sessions/mem0/mem0_basic.py

@@ -0,0 +1,82 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+import uuid
+
+from agent_framework import tool
+from agent_framework.azure import AzureAIAgentClient
+from agent_framework.mem0 import Mem0ContextProvider
+from azure.identity.aio import AzureCliCredential
+
+
+# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_sessions.py.
+@tool(approval_mode="never_require")
+def retrieve_company_report(company_code: str, detailed: bool) -> str:
+    if company_code != "CNTS":
+        raise ValueError("Company code not found")
+    if not detailed:
+        return "CNTS is a company that specializes in technology."
+    return (
+        "CNTS is a company that specializes in technology. "
+        "It had a revenue of $10 million in 2022. It has 100 employees."
+    )
+
+
+async def main() -> None:
+    """Example of memory usage with Mem0 context provider."""
+    print("=== Mem0 Context Provider Example ===")
+
+    # Each record in Mem0 should be associated with agent_id or user_id or application_id or thread_id.
+    # In this example, we associate Mem0 records with user_id.
+    user_id = str(uuid.uuid4())
+
+    # For Azure authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
+    # authentication option.
+    # For Mem0 authentication, set Mem0 API key via "api_key" parameter or MEM0_API_KEY environment variable.
+    async with (
+        AzureCliCredential() as credential,
+        AzureAIAgentClient(credential=credential).as_agent(
+            name="FriendlyAssistant",
+            instructions="You are a friendly assistant.",
+            tools=retrieve_company_report,
+            context_providers=[Mem0ContextProvider(user_id=user_id)],
+        ) as agent,
+    ):
+        # First ask the agent to retrieve a company report with no previous context.
+        # The agent will not be able to invoke the tool, since it doesn't know
+        # the company code or the report format, so it should ask for clarification.
+        query = "Please retrieve my company report"
+        print(f"User: {query}")
+        result = await agent.run(query)
+        print(f"Agent: {result}\n")
+
+        # Now tell the agent the company code and the report format that you want to use
+        # and it should be able to invoke the tool and return the report.
+        query = "I always work with CNTS and I always want a detailed report format. Please remember and retrieve it."
+        print(f"User: {query}")
+        result = await agent.run(query)
+        print(f"Agent: {result}\n")
+
+        # Mem0 processes and indexes memories asynchronously.
+        # Wait for memories to be indexed before querying in a new thread.
+        # In production, consider implementing retry logic or using Mem0's
+        # eventual consistency handling instead of a fixed delay.
+        print("Waiting for memories to be processed...")
+        await asyncio.sleep(12)  # Empirically determined delay for Mem0 indexing
+
+        print("\nRequest within a new session:")
+        # Create a new session for the agent.
+        # The new session has no context of the previous conversation.
+        session = agent.create_session()
+
+        # Since we have the mem0 component in the session, the agent should be able to
+        # retrieve the company report without asking for clarification, as it will
+        # be able to remember the user preferences from Mem0 component.
+        query = "Please retrieve my company report"
+        print(f"User: {query}")
+        result = await agent.run(query, session=session)
+        print(f"Agent: {result}\n")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())