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/autogen-migration/README.md

@@ -8,7 +8,7 @@ This gallery helps AutoGen developers move to the Microsoft Agent Framework (AF)
 
 - [01_basic_assistant_agent.py](single_agent/01_basic_assistant_agent.py) — Minimal AutoGen `AssistantAgent` and AF `Agent` comparison.
 - [02_assistant_agent_with_tool.py](single_agent/02_assistant_agent_with_tool.py) — Function tool integration in both SDKs.
-- [03_assistant_agent_thread_and_stream.py](single_agent/03_assistant_agent_thread_and_stream.py) — Thread management and streaming responses.
+- [03_assistant_agent_thread_and_stream.py](single_agent/03_assistant_agent_thread_and_stream.py) — Session management and streaming responses.
 - [04_agent_as_tool.py](single_agent/04_agent_as_tool.py) — Using agents as tools (hierarchical agent pattern) and streaming with tools.
 
 ### Multi-Agent Orchestration
@@ -52,7 +52,7 @@ python samples/autogen-migration/orchestrations/04_magentic_one.py
 ## Tips for Migration
 
 - **Default behavior differences**: AutoGen's `AssistantAgent` is single-turn by default (`max_tool_iterations=1`), while AF's `Agent` is multi-turn and continues tool execution automatically.
-- **Thread management**: AF agents are stateless by default. Use `agent.get_new_thread()` and pass it to `run()` to maintain conversation state, similar to AutoGen's conversation context.
+- **Thread management**: AF agents are stateless by default. Use `agent.create_session()` and pass it to `run()` to maintain conversation state, similar to AutoGen's conversation context.
 - **Tools**: AutoGen uses `FunctionTool` wrappers; AF uses `@tool` decorators with automatic schema inference.
 - **Orchestration patterns**:
   - `RoundRobinGroupChat` → `SequentialBuilder` or `WorkflowBuilder`

python/samples/autogen-migration/single_agent/02_assistant_agent_with_tool.py

@@ -62,7 +62,7 @@ async def run_agent_framework() -> None:
     from agent_framework.openai import OpenAIChatClient
 
     # Define tool with @tool decorator (automatic schema inference)
-    # 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_threads.py.
+    # 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 get_weather(location: str) -> str:
         """Get the weather for a location.

python/samples/autogen-migration/single_agent/03_assistant_agent_thread_and_stream.py

@@ -46,7 +46,7 @@ async def run_autogen() -> None:
 
 
 async def run_agent_framework() -> None:
-    """Agent Framework agent with explicit thread and streaming."""
+    """Agent Framework agent with explicit session and streaming."""
     from agent_framework.openai import OpenAIChatClient
 
     client = OpenAIChatClient(model_id="gpt-4.1-mini")
@@ -55,22 +55,22 @@ async def run_agent_framework() -> None:
         instructions="You are a helpful math tutor.",
     )
 
-    print("[Agent Framework] Conversation with thread:")
-    # Create a thread to maintain state
-    thread = agent.get_new_thread()
+    print("[Agent Framework] Conversation with session:")
+    # Create a session to maintain state
+    session = agent.create_session()
 
-    # First turn - pass thread to maintain history
-    result1 = await agent.run("What is 15 + 27?", thread=thread)
+    # First turn - pass session to maintain history
+    result1 = await agent.run("What is 15 + 27?", session=session)
     print(f"  Q1: {result1.text}")
 
-    # Second turn - agent remembers context via thread
-    result2 = await agent.run("What about that number times 2?", thread=thread)
+    # Second turn - agent remembers context via session
+    result2 = await agent.run("What about that number times 2?", session=session)
     print(f"  Q2: {result2.text}")
 
     print("\n[Agent Framework] Streaming response:")
     # Stream response
     print("  ", end="")
-    async for chunk in agent.run("Count from 1 to 5", thread=thread, stream=True):
+    async for chunk in agent.run("Count from 1 to 5", session=session, stream=True):
         if chunk.text:
             print(chunk.text, end="", flush=True)
     print()