From e4896d598a259298b206fc616c018fa88dc26193 Mon Sep 17 00:00:00 2001
From: Abdul-Microsoft <v-amujeebta@microsoft.com>
Date: Wed, 4 Feb 2026 18:28:21 +0530
Subject: [PATCH 01/13] agent framework v2 changes

---
 src/backend/pyproject.toml                    |   26 +-
 src/backend/uv.lock                           | 1026 ++---------------
 src/backend/v4/callbacks/response_handlers.py |   30 +-
 .../v4/magentic_agents/common/lifecycle.py    |   53 +-
 .../v4/magentic_agents/foundry_agent.py       |   14 +-
 src/backend/v4/magentic_agents/proxy_agent.py |   26 +-
 .../orchestration/human_approval_manager.py   |    6 +-
 .../v4/orchestration/orchestration_manager.py |  154 ++-
 8 files changed, 276 insertions(+), 1059 deletions(-)

diff --git a/src/backend/pyproject.toml b/src/backend/pyproject.toml
index d176467f5..7750638dd 100644
--- a/src/backend/pyproject.toml
+++ b/src/backend/pyproject.toml
@@ -7,21 +7,20 @@ requires-python = ">=3.11"
 dependencies = [
     "azure-ai-evaluation==1.11.0",
     "azure-ai-inference==1.0.0b9",
-    "azure-ai-projects==1.0.0",
-    "azure-ai-agents==1.2.0b5",
+    "azure-ai-projects==2.0.0b3",
     "azure-cosmos==4.9.0",
     "azure-identity==1.24.0",
     "azure-monitor-events-extension==0.1.0",
-    "azure-monitor-opentelemetry==1.7.0",
+    "azure-monitor-opentelemetry>=1.8.0",
     "azure-search-documents==11.5.3",
     "fastapi==0.116.1",
-    "openai==1.105.0",
-    "opentelemetry-api==1.36.0",
-    "opentelemetry-exporter-otlp-proto-grpc==1.36.0",
-    "opentelemetry-exporter-otlp-proto-http==1.36.0",
-    "opentelemetry-instrumentation-fastapi==0.57b0",
-    "opentelemetry-instrumentation-openai==0.46.2",
-    "opentelemetry-sdk==1.36.0",
+    "openai>=2.8.0",
+    "opentelemetry-api>=1.39.0",
+    "opentelemetry-exporter-otlp-proto-grpc>=1.39.0",
+    "opentelemetry-exporter-otlp-proto-http>=1.39.0",
+    "opentelemetry-instrumentation-fastapi>=0.57b0",
+    "opentelemetry-instrumentation-openai>=0.46.2",
+    "opentelemetry-sdk>=1.39.0",
     "pytest==8.4.1",
     "pytest-asyncio==0.24.0",
     "pytest-cov==5.0.0",
@@ -31,6 +30,7 @@ dependencies = [
     "uvicorn==0.35.0",
     "pylint-pydantic==0.3.5",
     "pexpect==4.9.0",
-    "mcp==1.13.1",
-    "agent-framework>=1.0.0b251105",
-]
+    "mcp>=1.24.0,<2",
+    "agent-framework-azure-ai==1.0.0b260130",
+    "agent-framework-core==1.0.0b260130"
+]
\ No newline at end of file
diff --git a/src/backend/uv.lock b/src/backend/uv.lock
index 73a5e2e5c..526fe789a 100644
--- a/src/backend/uv.lock
+++ b/src/backend/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.11"
 resolution-markers = [
     "python_full_version >= '3.13'",
@@ -7,101 +7,9 @@ resolution-markers = [
     "python_full_version < '3.12'",
 ]
 
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-]
-
 [[package]]
 name = "websockets"
 version = "15.0.1"
diff --git a/src/backend/v4/callbacks/response_handlers.py b/src/backend/v4/callbacks/response_handlers.py
index 297c8814b..88c6085f5 100644
--- a/src/backend/v4/callbacks/response_handlers.py
+++ b/src/backend/v4/callbacks/response_handlers.py
@@ -8,10 +8,7 @@
 import re
 from typing import Any
 
-from agent_framework import ChatMessage
-# Removed: from agent_framework._content import FunctionCallContent  (does not exist)
-
-from agent_framework._workflows._magentic import AgentRunResponseUpdate  # Streaming update type from workflows
+from agent_framework import ChatMessage, AgentRunUpdateEvent
 
 from v4.config.settings import connection_config
 from v4.models.messages import (
@@ -111,26 +108,31 @@ def agent_response_callback(
 
 async def streaming_agent_response_callback(
     agent_id: str,
-    update: AgentRunResponseUpdate,
+    update,  # AgentRunUpdateEvent.data or similar streaming update object
     is_final: bool,
     user_id: str | None = None,
 ) -> None:
     """
-    Streaming callback for incremental agent output (AgentRunResponseUpdate).
+    Streaming callback for incremental agent output.
     """
     if not user_id:
         return
 
     try:
+        # Handle both AgentRunUpdateEvent.data and raw text updates
         chunk_text = getattr(update, "text", None)
-        if not chunk_text:
-            contents = getattr(update, "contents", []) or []
-            collected = []
-            for item in contents:
-                txt = getattr(item, "text", None)
-                if txt:
-                    collected.append(str(txt))
-            chunk_text = "".join(collected) if collected else ""
+        
+        # If text is None, don't fall back to str(update) as that would show object repr
+        # Just skip if there's no actual text content
+        if chunk_text is None:
+            # Check if update is a ChatMessage
+            if isinstance(update, ChatMessage):
+                chunk_text = update.text or ""
+            elif hasattr(update, "content"):
+                chunk_text = str(update.content) if update.content else ""
+            else:
+                # Skip if no text content available
+                return
 
         cleaned = clean_citations(chunk_text or "")
 
diff --git a/src/backend/v4/magentic_agents/common/lifecycle.py b/src/backend/v4/magentic_agents/common/lifecycle.py
index bd9382ff2..88fde549b 100644
--- a/src/backend/v4/magentic_agents/common/lifecycle.py
+++ b/src/backend/v4/magentic_agents/common/lifecycle.py
@@ -10,8 +10,8 @@
     MCPStreamableHTTPTool,
 )
 
-# from agent_framework.azure import AzureAIAgentClient
-from agent_framework_azure_ai import AzureAIAgentClient
+# from agent_framework.azure import AzureAIClient
+from agent_framework_azure_ai import AzureAIClient
 from azure.ai.agents.aio import AgentsClient
 from azure.identity.aio import DefaultAzureCredential
 from common.database.database_base import DatabaseBase
@@ -51,7 +51,7 @@ def __init__(
         self._agent: ChatAgent | None = None
         self.team_service: TeamService | None = team_service
         self.team_config: TeamConfiguration | None = team_config
-        self.client: Optional[AzureAIAgentClient] = None
+        self.client: Optional[AzureAIClient] = None
         self.project_endpoint = project_endpoint
         self.creds: Optional[DefaultAzureCredential] = None
         self.memory_store: Optional[DatabaseBase] = memory_store
@@ -105,7 +105,7 @@ async def close(self) -> None:
             # Attempt to close the underlying agent/client if it exposes close()
             if self._agent and hasattr(self._agent, "close"):
                 try:
-                    await self._agent.close()  # AzureAIAgentClient has async close
+                    await self._agent.close()  # AzureAIClient has async close
                 except Exception as exc:
                     # Best-effort close; log failure but continue teardown
                     self.logger.warning(
@@ -148,24 +148,22 @@ async def _after_open(self) -> None:
         """Subclasses must build self._agent here."""
         raise NotImplementedError
 
-    def get_chat_client(self, chat_client) -> AzureAIAgentClient:
-        """Return the underlying ChatClientProtocol (AzureAIAgentClient)."""
+    def get_chat_client(self, chat_client) -> AzureAIClient:
+        """Return the underlying ChatClientProtocol (AzureAIClient)."""
         if chat_client:
             return chat_client
         if (
             self._agent
             and self._agent.chat_client
-            and self._agent.chat_client.agent_id is not None
         ):
             return self._agent.chat_client  # type: ignore
-        chat_client = AzureAIAgentClient(
+        chat_client = AzureAIClient(
             project_endpoint=self.project_endpoint,
             model_deployment_name=self.model_deployment_name,
-            async_credential=self.creds,
+            credential=self.creds,
         )
         self.logger.info(
-            "Created new AzureAIAgentClient for  get chat client",
-            extra={"agent_id": chat_client.agent_id},
+            "Created new AzureAIClient for get chat client",
         )
         return chat_client
 
@@ -219,20 +217,17 @@ async def resolve_agent_id(self, agent_id: str) -> Optional[str]:
         return None
 
     def get_agent_id(self, chat_client) -> str:
-        """Return the underlying agent ID."""
-        if chat_client and chat_client.agent_id is not None:
-            return chat_client.agent_id
-        if (
-            self._agent
-            and self._agent.chat_client
-            and self._agent.chat_client.agent_id is not None
-        ):
-            return self._agent.chat_client.agent_id  # type: ignore
+        """Return the underlying agent ID or generate a new one.
+        
+        Note: The new AzureAIClient doesn't expose agent_id directly.
+        We generate a new ID if not available.
+        """
+        # Generate a new agent ID since AzureAIClient doesn't expose agent_id
         id = generate_assistant_id()
         self.logger.info("Generated new agent ID: %s", id)
         return id
 
-    async def get_database_team_agent(self) -> Optional[AzureAIAgentClient]:
+    async def get_database_team_agent(self) -> Optional[AzureAIClient]:
         """Retrieve existing team agent from database, if any."""
         chat_client = None
         try:
@@ -258,24 +253,24 @@ async def get_database_team_agent(self) -> Optional[AzureAIAgentClient]:
 
             # Create client with resolved ID, preferring project_client for RAI agents
             if self.agent_name == "RAIAgent" and self.project_client:
-                chat_client = AzureAIAgentClient(
+                chat_client = AzureAIClient(
                     project_client=self.project_client,
                     agent_id=resolved,
-                    async_credential=self.creds,
+                    credential=self.creds,
                 )
                 self.logger.info(
-                    "RAI.AgentReuseSuccess: Created AzureAIAgentClient via Projects SDK (id=%s)",
+                    "RAI.AgentReuseSuccess: Created AzureAIClient via Projects SDK (id=%s)",
                     resolved,
                 )
             else:
-                chat_client = AzureAIAgentClient(
+                chat_client = AzureAIClient(
                     project_endpoint=self.project_endpoint,
                     agent_id=resolved,
                     model_deployment_name=self.model_deployment_name,
-                    async_credential=self.creds,
+                    credential=self.creds,
                 )
                 self.logger.info(
-                    "Created AzureAIAgentClient via endpoint (id=%s)", resolved
+                    "Created AzureAIClient via endpoint (id=%s)", resolved
                 )
 
         except Exception as ex:
@@ -339,10 +334,10 @@ async def _prepare_mcp_tool(self) -> None:
 
 class AzureAgentBase(MCPEnabledBase):
     """
-    Extends MCPEnabledBase with Azure credential + AzureAIAgentClient contexts.
+    Extends MCPEnabledBase with Azure credential + AzureAIClient contexts.
     Subclasses:
       - create or attach an Azure AI Agent definition
-      - instantiate an AzureAIAgentClient and assign to self._agent
+      - instantiate an AzureAIClient and assign to self._agent
       - optionally register themselves via agent_registry
     """
 
diff --git a/src/backend/v4/magentic_agents/foundry_agent.py b/src/backend/v4/magentic_agents/foundry_agent.py
index df6221699..614904b6d 100644
--- a/src/backend/v4/magentic_agents/foundry_agent.py
+++ b/src/backend/v4/magentic_agents/foundry_agent.py
@@ -6,7 +6,7 @@
 from agent_framework import (ChatAgent, ChatMessage, HostedCodeInterpreterTool,
                              Role)
 from agent_framework_azure_ai import \
-    AzureAIAgentClient  # Provided by agent_framework
+    AzureAIClient  # Provided by agent_framework
 from azure.ai.projects.models import ConnectionType
 from common.config.app_config import config
 from common.database.database_base import DatabaseBase
@@ -111,7 +111,7 @@ async def _collect_tools(self) -> List:
     # -------------------------
     # Azure Search helper
     # -------------------------
-    async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional[AzureAIAgentClient]:
+    async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional[AzureAIClient]:
         """
         Create a server-side Azure AI agent with Azure AI Search raw tool.
 
@@ -123,7 +123,7 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
 
 
         Returns:
-            AzureAIAgentClient | None
+            AzureAIClient | None
         """
         if chatClient:
             return chatClient
@@ -205,10 +205,10 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
                 query_type,
             )
 
-            chat_client = AzureAIAgentClient(
+            chat_client = AzureAIClient(
                 project_client=self.project_client,
                 agent_id=azure_agent.id,
-                async_credential=self.creds,
+                credential=self.creds,
             )
             return chat_client
         except Exception as ex:
@@ -301,8 +301,8 @@ async def invoke(self, prompt: str):
 
         agent_saved = False
         async for update in self._agent.run_stream(messages):
-            # Save agent ID only once on first update (agent ID won't change during streaming)
-            if not agent_saved and self._agent.chat_client.agent_id:
+            # Save agent ID only once on first update
+            if not agent_saved:
                 await self.save_database_team_agent()
                 agent_saved = True
             yield update
diff --git a/src/backend/v4/magentic_agents/proxy_agent.py b/src/backend/v4/magentic_agents/proxy_agent.py
index a6ba9d3c4..79a84492b 100644
--- a/src/backend/v4/magentic_agents/proxy_agent.py
+++ b/src/backend/v4/magentic_agents/proxy_agent.py
@@ -16,13 +16,12 @@
 from typing import Any, AsyncIterable
 
 from agent_framework import (
-    AgentRunResponse,
-    AgentRunResponseUpdate,
+    AgentResponse,
+    AgentResponseUpdate,
     BaseAgent,
     ChatMessage,
     Role,
-    TextContent,
-    UsageContent,
+    Content,
     UsageDetails,
     AgentThread,
 )
@@ -88,7 +87,7 @@ async def run(
         *,
         thread: AgentThread | None = None,
         **kwargs: Any,
-    ) -> AgentRunResponse:
+    ) -> AgentResponse:
         """
         Get complete clarification response (non-streaming).
 
@@ -98,7 +97,7 @@ async def run(
             kwargs: Additional keyword arguments
 
         Returns:
-            AgentRunResponse with the clarification
+            AgentResponse with the clarification
         """
         # Collect all streaming updates
         response_messages: list[ChatMessage] = []
@@ -113,7 +112,7 @@ async def run(
                     )
                 )
 
-        return AgentRunResponse(
+        return AgentResponse(
             messages=response_messages,
             response_id=response_id,
         )
@@ -124,7 +123,7 @@ def run_stream(
         *,
         thread: AgentThread | None = None,
         **kwargs: Any,
-    ) -> AsyncIterable[AgentRunResponseUpdate]:
+    ) -> AsyncIterable[AgentResponseUpdate]:
         """
         Stream clarification process with human interaction.
 
@@ -143,7 +142,7 @@ async def _invoke_stream_internal(
         messages: str | ChatMessage | list[str] | list[ChatMessage] | None,
         thread: AgentThread | None,
         **kwargs: Any,
-    ) -> AsyncIterable[AgentRunResponseUpdate]:
+    ) -> AsyncIterable[AgentResponseUpdate]:
         """
         Internal streaming implementation.
 
@@ -205,9 +204,10 @@ async def _invoke_stream_internal(
         message_id = str(uuid.uuid4())
 
         # Yield final assistant text update with explicit text content
-        text_update = AgentRunResponseUpdate(
+        # New API: use Content.from_text() or pass text directly to AgentResponseUpdate
+        text_update = AgentResponseUpdate(
             role=Role.ASSISTANT,
-            contents=[TextContent(text=synthetic_reply)],
+            text=synthetic_reply,  # New API accepts text directly
             author_name=self.name,
             response_id=response_id,
             message_id=message_id,
@@ -218,10 +218,10 @@ async def _invoke_stream_internal(
 
         # Yield synthetic usage update for consistency
         # Use same message_id to indicate this is part of the same message
-        usage_update = AgentRunResponseUpdate(
+        usage_update = AgentResponseUpdate(
             role=Role.ASSISTANT,
             contents=[
-                UsageContent(
+                Content.from_usage(
                     UsageDetails(
                         input_token_count=len(message_text.split()),
                         output_token_count=len(synthetic_reply.split()),
diff --git a/src/backend/v4/orchestration/human_approval_manager.py b/src/backend/v4/orchestration/human_approval_manager.py
index 2a3ab5be7..654d72a23 100644
--- a/src/backend/v4/orchestration/human_approval_manager.py
+++ b/src/backend/v4/orchestration/human_approval_manager.py
@@ -34,11 +34,12 @@ class HumanApprovalMagenticManager(StandardMagenticManager):
     magentic_plan: Optional[MPlan] = None
     current_user_id: str  # populated in __init__
 
-    def __init__(self, user_id: str, *args, **kwargs):
+    def __init__(self, user_id: str, agent, *args, **kwargs):
         """
         Initialize the HumanApprovalMagenticManager.
         Args:
             user_id: ID of the user to associate with this orchestration instance.
+            agent: The manager ChatAgent for orchestration (required by new API).
             *args: Additional positional arguments for the parent StandardMagenticManager.
             **kwargs: Additional keyword arguments for the parent StandardMagenticManager.
         """
@@ -76,7 +77,8 @@ def __init__(self, user_id: str, *args, **kwargs):
         kwargs["final_answer_prompt"] = ORCHESTRATOR_FINAL_ANSWER_PROMPT + final_append
 
         self.current_user_id = user_id
-        super().__init__(*args, **kwargs)
+        # New API: StandardMagenticManager takes agent as first positional argument
+        super().__init__(agent, *args, **kwargs)
 
     async def plan(self, magentic_context: MagenticContext) -> Any:
         """
diff --git a/src/backend/v4/orchestration/orchestration_manager.py b/src/backend/v4/orchestration/orchestration_manager.py
index e105a34cb..ec4f7aea1 100644
--- a/src/backend/v4/orchestration/orchestration_manager.py
+++ b/src/backend/v4/orchestration/orchestration_manager.py
@@ -2,20 +2,22 @@
 
 import asyncio
 import logging
+import re
 import uuid
 from typing import List, Optional
 
 # agent_framework imports
-from agent_framework_azure_ai import AzureAIAgentClient
+from agent_framework_azure_ai import AzureAIClient
 from agent_framework import (
+    ChatAgent,
     ChatMessage,
     WorkflowOutputEvent,
     MagenticBuilder,
     InMemoryCheckpointStorage,
-    MagenticOrchestratorMessageEvent,
-    MagenticAgentDeltaEvent,
-    MagenticAgentMessageEvent,
-    MagenticFinalResultEvent,
+    AgentRunUpdateEvent,
+    GroupChatRequestSentEvent,
+    MagenticOrchestratorEvent,
+    MagenticProgressLedger,
 )
 
 from common.config.app_config import config
@@ -58,7 +60,7 @@ async def init_orchestration(
         Initialize a Magentic workflow with:
           - Provided agents (participants)
           - HumanApprovalMagenticManager as orchestrator manager
-          - AzureAIAgentClient as the underlying chat client
+          - AzureAIClient as the underlying chat client
           - Event-based callbacks for streaming and final responses
         - Uses same deployment, endpoint, and credentials
         - Applies same execution settings (temperature, max_tokens)
@@ -72,33 +74,46 @@ async def init_orchestration(
 
         # Create Azure AI Agent client for orchestration using config
         # This replaces AzureChatCompletion from SK
-        agent_name = team_config.name if team_config.name else "OrchestratorAgent"
+        # Sanitize agent name: must start/end with alphanumeric, only hyphens allowed, max 63 chars
+        raw_name = team_config.name if team_config.name else "OrchestratorAgent"
+        # Replace spaces and invalid chars with hyphens, strip leading/trailing hyphens
+        sanitized_name = re.sub(r'[^a-zA-Z0-9-]', '-', raw_name)
+        sanitized_name = re.sub(r'-+', '-', sanitized_name)  # Collapse multiple hyphens
+        sanitized_name = sanitized_name.strip('-')[:63]  # Trim and limit length
+        agent_name = sanitized_name if sanitized_name else "OrchestratorAgent"
 
         try:
-            chat_client = AzureAIAgentClient(
+            # Create the chat client (AzureAIClient)
+            chat_client = AzureAIClient(
                 project_endpoint=config.AZURE_AI_PROJECT_ENDPOINT,
                 model_deployment_name=team_config.deployment_name,
                 agent_name=agent_name,
-                async_credential=credential,
+                credential=credential,
+            )
+
+            # New API: Create a ChatAgent to wrap the chat client for the manager
+            manager_agent = ChatAgent(
+                chat_client=chat_client,
+                name="MagenticManager",
+                description="Orchestrator that coordinates the team to complete complex tasks efficiently.",
+                instructions="You coordinate a team to complete complex tasks efficiently.",
             )
 
             cls.logger.info(
-                "Created AzureAIAgentClient for orchestration with model '%s' at endpoint '%s'",
+                "Created AzureAIClient and manager ChatAgent for orchestration with model '%s' at endpoint '%s'",
                 team_config.deployment_name,
                 config.AZURE_AI_PROJECT_ENDPOINT,
             )
         except Exception as e:
-            cls.logger.error("Failed to create AzureAIAgentClient: %s", e)
+            cls.logger.error("Failed to create AzureAIClient: %s", e)
             raise
 
-        # Create HumanApprovalMagenticManager with the chat client
-        # Execution settings (temperature=0.1, max_tokens=4000) are configured via
-        # orchestration_config.create_execution_settings() which matches old SK version
+        # Create HumanApprovalMagenticManager with the manager agent
+        # New API: StandardMagenticManager takes agent as first positional argument
         try:
             manager = HumanApprovalMagenticManager(
                 user_id=user_id,
-                chat_client=chat_client,
-                instructions=None,  # Orchestrator system instructions (optional)
+                agent=manager_agent,  # New API: pass agent instead of chat_client
                 max_round_count=orchestration_config.max_rounds,
             )
             cls.logger.info(
@@ -132,13 +147,18 @@ async def init_orchestration(
 
         # Assemble workflow with callback
         storage = InMemoryCheckpointStorage()
+        
+        # New API: .participants() accepts a list of agents
+        participant_list = list(participants.values())
+        
         builder = (
             MagenticBuilder()
-            .participants(**participants)
-            .with_standard_manager(
-                manager=manager,
+            .participants(participant_list)
+            .with_manager(
+                manager=manager,  # Pass manager instance (extends StandardMagenticManager)
                 max_round_count=orchestration_config.max_rounds,
-                max_stall_count=0,
+                max_stall_count=3,
+                max_reset_count=2,
             )
             .with_checkpointing(storage)
         )
@@ -204,16 +224,20 @@ async def get_current_or_new_orchestration(
                 raise
             try:
                 cls.logger.info("Initializing new orchestration for user '%s'", user_id)
-                orchestration_config.orchestrations[user_id] = (
-                    await cls.init_orchestration(
-                        agents, team_config, team_service.memory_context, user_id
-                    )
+                print(f"[DEBUG] Initializing new orchestration for user '{user_id}'")
+                workflow = await cls.init_orchestration(
+                    agents, team_config, team_service.memory_context, user_id
                 )
+                orchestration_config.orchestrations[user_id] = workflow
+                print(f"[DEBUG] Stored workflow for user '{user_id}': {workflow is not None}")
+                print(f"[DEBUG] orchestrations keys: {list(orchestration_config.orchestrations.keys())}")
             except Exception as e:
                 cls.logger.error(
                     "Failed to initialize orchestration for user '%s': %s", user_id, e
                 )
                 print(f"Failed to initialize orchestration for user '{user_id}': {e}")
+                import traceback
+                traceback.print_exc()
                 raise
         return orchestration_config.get_current_orchestration(user_id)
 
@@ -229,9 +253,13 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
         self.logger.info(
             "Starting orchestration job '%s' for user '%s'", job_id, user_id
         )
+        print(f"[DEBUG] run_orchestration called for user '{user_id}'")
+        print(f"[DEBUG] orchestrations keys before get: {list(orchestration_config.orchestrations.keys())}")
 
         workflow = orchestration_config.get_current_orchestration(user_id)
+        print(f"[DEBUG] workflow is None: {workflow is None}")
         if workflow is None:
+            print(f"[ERROR] Orchestration not initialized for user '{user_id}'")
             raise ValueError("Orchestration not initialized for user.")
         # Fresh thread per participant to avoid cross-run state bleed
         executors = getattr(workflow, "executors", {})
@@ -305,55 +333,71 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
             final_output: str | None = None
 
             self.logger.info("Starting workflow execution...")
+            last_message_id: str | None = None
             async for event in workflow.run_stream(task_text):
                 try:
-                    # Handle orchestrator messages (task assignments, coordination)
-                    if isinstance(event, MagenticOrchestratorMessageEvent):
-                        message_text = getattr(event.message, "text", "")
-                        self.logger.info(f"[ORCHESTRATOR:{event.kind}] {message_text}")
-
-                    # Handle streaming updates from agents
-                    elif isinstance(event, MagenticAgentDeltaEvent):
+                    # Handle orchestrator events (plan, progress ledger)
+                    if isinstance(event, MagenticOrchestratorEvent):
+                        self.logger.info(
+                            "[Magentic Orchestrator Event] Type: %s",
+                            event.event_type.name
+                        )
+                        if isinstance(event.data, ChatMessage):
+                            self.logger.info("Plan message: %s", event.data.text[:200] if event.data.text else "")
+                        elif isinstance(event.data, MagenticProgressLedger):
+                            self.logger.info("Progress ledger received")
+
+                    # Handle agent streaming/updates (replaces MagenticAgentDeltaEvent and MagenticAgentMessageEvent)
+                    elif isinstance(event, AgentRunUpdateEvent):
+                        message_id = event.data.message_id if hasattr(event.data, 'message_id') else None
+                        executor_id = event.executor_id
+                        
+                        # Stream the update
                         try:
                             await streaming_agent_response_callback(
-                                event.agent_id,
-                                event,  # Pass the event itself as the update object
-                                False,  # Not final yet (streaming in progress)
+                                executor_id,
+                                event.data,  # Pass the data object
+                                False,  # Not final yet
                                 user_id,
                             )
                         except Exception as e:
                             self.logger.error(
-                                f"Error in streaming callback for agent {event.agent_id}: {e}"
+                                "Error in streaming callback for agent %s: %s",
+                                executor_id, e
                             )
+                        
+                        # Track message for formatting
+                        if message_id != last_message_id:
+                            last_message_id = message_id
 
-                    # Handle final agent messages (complete response)
-                    elif isinstance(event, MagenticAgentMessageEvent):
-                        if event.message:
-                            try:
-                                agent_response_callback(
-                                    event.agent_id, event.message, user_id
-                                )
-                            except Exception as e:
-                                self.logger.error(
-                                    f"Error in agent callback for agent {event.agent_id}: {e}"
-                                )
-
-                    # Handle final result from the entire workflow
-                    elif isinstance(event, MagenticFinalResultEvent):
-                        final_text = getattr(event.message, "text", "")
+                    # Handle group chat request sent
+                    elif isinstance(event, GroupChatRequestSentEvent):
                         self.logger.info(
-                            f"[FINAL RESULT] Length: {len(final_text)} chars"
+                            "[REQUEST SENT (round %d)] to agent: %s",
+                            event.round_index,
+                            event.participant_name
                         )
 
                     # Handle workflow output event (captures final result)
                     elif isinstance(event, WorkflowOutputEvent):
                         output_data = event.data
+                        # Handle different output formats
                         if isinstance(output_data, ChatMessage):
-                            final_output = getattr(output_data, "text", None) or str(
-                                output_data
-                            )
+                            final_output = output_data.text or ""
+                        elif isinstance(output_data, list):
+                            # Handle list of ChatMessage objects
+                            texts = []
+                            for item in output_data:
+                                if isinstance(item, ChatMessage):
+                                    if item.text:
+                                        texts.append(item.text)
+                                else:
+                                    texts.append(str(item))
+                            final_output = "\n".join(texts)
+                        elif hasattr(output_data, "text"):
+                            final_output = output_data.text or ""
                         else:
-                            final_output = str(output_data)
+                            final_output = str(output_data) if output_data else ""
                         self.logger.debug("Received workflow output event")
 
                 except Exception as e:

From 95b0049c87df66c5927cddd4770ab8201a0acebf Mon Sep 17 00:00:00 2001
From: Abdul-Microsoft <v-amujeebta@microsoft.com>
Date: Thu, 5 Feb 2026 22:38:09 +0530
Subject: [PATCH 02/13] v2 changes

---
 .../v4/magentic_agents/foundry_agent.py       |  8 +-
 .../v4/orchestration/orchestration_manager.py | 82 +++++++++++++++++++
 2 files changed, 89 insertions(+), 1 deletion(-)

diff --git a/src/backend/v4/magentic_agents/foundry_agent.py b/src/backend/v4/magentic_agents/foundry_agent.py
index 614904b6d..9a7c8ebe8 100644
--- a/src/backend/v4/magentic_agents/foundry_agent.py
+++ b/src/backend/v4/magentic_agents/foundry_agent.py
@@ -125,7 +125,9 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
         Returns:
             AzureAIClient | None
         """
+        print(f"[DEBUG _create_azure_search_enabled_client] Agent={self.agent_name}, chatClient={chatClient}, search_config={self.search}")
         if chatClient:
+            self.logger.info("Reusing existing chatClient for agent '%s' (already has Azure Search configured)", self.agent_name)
             return chatClient
 
         if not self.search:
@@ -234,12 +236,16 @@ async def _after_open(self) -> None:
 
         try:
             chatClient = await self.get_database_team_agent()
+            print(f"[DEBUG _after_open] Agent={self.agent_name}, _use_azure_search={self._use_azure_search}, search_config={self.search}, chatClient={chatClient}")
 
             if self._use_azure_search:
                 # Azure Search mode (skip MCP + Code Interpreter due to incompatibility)
                 self.logger.info(
-                    "Initializing agent in Azure AI Search mode (exclusive)."
+                    "Initializing agent '%s' in Azure AI Search mode (exclusive) with index=%s.",
+                    self.agent_name,
+                    getattr(self.search, "index_name", "N/A") if self.search else "N/A"
                 )
+                print(f"[DEBUG _after_open] Creating Azure Search client for {self.agent_name}")
                 chat_client = await self._create_azure_search_enabled_client(chatClient)
                 if not chat_client:
                     raise RuntimeError(
diff --git a/src/backend/v4/orchestration/orchestration_manager.py b/src/backend/v4/orchestration/orchestration_manager.py
index ec4f7aea1..4fc0c209a 100644
--- a/src/backend/v4/orchestration/orchestration_manager.py
+++ b/src/backend/v4/orchestration/orchestration_manager.py
@@ -16,6 +16,8 @@
     InMemoryCheckpointStorage,
     AgentRunUpdateEvent,
     GroupChatRequestSentEvent,
+    GroupChatResponseReceivedEvent,
+    ExecutorCompletedEvent,
     MagenticOrchestratorEvent,
     MagenticProgressLedger,
 )
@@ -45,6 +47,53 @@ def __init__(self):
         self.user_id: Optional[str] = None
         self.logger = self.__class__.logger
 
+    def _extract_response_text(self, data) -> str:
+        """
+        Extract text content from various agent_framework response types.
+        
+        Handles:
+        - ChatMessage: Extract .text
+        - AgentResponse: Extract .text
+        - AgentExecutorResponse: Extract from agent_response.text or full_conversation[-1].text
+        - List of any of the above
+        """
+        if data is None:
+            return ""
+        
+        # Direct ChatMessage
+        if isinstance(data, ChatMessage):
+            return data.text or ""
+        
+        # Has .text attribute directly (AgentResponse, etc.)
+        if hasattr(data, "text") and data.text:
+            return data.text
+        
+        # AgentExecutorResponse - has agent_response and full_conversation
+        if hasattr(data, "agent_response"):
+            # Try to get text from agent_response first
+            agent_resp = data.agent_response
+            if agent_resp and hasattr(agent_resp, "text") and agent_resp.text:
+                return agent_resp.text
+            # Fallback to last message in full_conversation
+            if hasattr(data, "full_conversation") and data.full_conversation:
+                last_msg = data.full_conversation[-1]
+                if isinstance(last_msg, ChatMessage) and last_msg.text:
+                    return last_msg.text
+        
+        # List of items - could be AgentExecutorResponse, ChatMessage, etc.
+        if isinstance(data, list) and len(data) > 0:
+            texts = []
+            for item in data:
+                # Recursively extract from each item
+                item_text = self._extract_response_text(item)
+                if item_text:
+                    texts.append(item_text)
+            if texts:
+                # Return the last non-empty response (most recent)
+                return texts[-1]
+        
+        return ""
+
     # ---------------------------
     # Orchestration construction
     # ---------------------------
@@ -336,6 +385,11 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
             last_message_id: str | None = None
             async for event in workflow.run_stream(task_text):
                 try:
+                    # Only log non-streaming events (reduce noise)
+                    event_type_name = type(event).__name__
+                    if event_type_name != "AgentRunUpdateEvent":
+                        self.logger.info("[EVENT] %s", event_type_name)
+                    
                     # Handle orchestrator events (plan, progress ledger)
                     if isinstance(event, MagenticOrchestratorEvent):
                         self.logger.info(
@@ -378,6 +432,34 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
                             event.participant_name
                         )
 
+                    # Handle group chat response received - THIS IS WHERE AGENT RESPONSES COME
+                    elif isinstance(event, GroupChatResponseReceivedEvent):
+                        self.logger.info(
+                            "[RESPONSE RECEIVED (round %d)] from agent: %s",
+                            event.round_index,
+                            event.participant_name
+                        )
+                        # Send the agent response to the UI
+                        if event.data:
+                            response_text = self._extract_response_text(event.data)
+                            
+                            if response_text:
+                                self.logger.info("Sending agent response to UI from %s", event.participant_name)
+                                agent_response_callback(
+                                    event.participant_name,
+                                    ChatMessage(role="assistant", text=response_text),
+                                    user_id,
+                                )
+
+                    # Handle executor completed - just log, don't send to UI (GroupChatResponseReceivedEvent handles that)
+                    elif isinstance(event, ExecutorCompletedEvent):
+                        self.logger.debug(
+                            "[EXECUTOR COMPLETED] agent: %s",
+                            event.executor_id
+                        )
+                        # Don't send to UI here - GroupChatResponseReceivedEvent already handles agent messages
+                        # This avoids duplicate messages
+
                     # Handle workflow output event (captures final result)
                     elif isinstance(event, WorkflowOutputEvent):
                         output_data = event.data

From 124fcf7f1cf773282996a3b4086574ad286b9781 Mon Sep 17 00:00:00 2001
From: Abdul-Microsoft <v-amujeebta@microsoft.com>
Date: Tue, 10 Feb 2026 17:34:41 +0530
Subject: [PATCH 03/13] Enhance agent orchestration and configuration for Azure
 AI Search integration

---
 src/backend/v4/api/router.py                  |  11 ++
 .../v4/magentic_agents/common/lifecycle.py    |  43 +++--
 .../v4/magentic_agents/foundry_agent.py       | 150 ++++++++++--------
 .../v4/magentic_agents/models/agent_models.py |   6 +-
 .../v4/orchestration/orchestration_manager.py |  11 +-
 5 files changed, 144 insertions(+), 77 deletions(-)

diff --git a/src/backend/v4/api/router.py b/src/backend/v4/api/router.py
index 43f3f9f2f..d9a8e7c10 100644
--- a/src/backend/v4/api/router.py
+++ b/src/backend/v4/api/router.py
@@ -303,6 +303,17 @@ async def process_request(
         )
         await memory_store.add_plan(plan)
 
+        # Ensure orchestration is initialized before running
+        # Force rebuild for each new task since Magentic workflows cannot be reused after completion
+        team_service = TeamService(memory_store)
+        await OrchestrationManager.get_current_or_new_orchestration(
+            user_id=user_id,
+            team_config=team,
+            team_switched=False,
+            team_service=team_service,
+            force_rebuild=True,  # Always rebuild workflow for new tasks
+        )
+
         track_event_if_configured(
             "PlanCreated",
             {
diff --git a/src/backend/v4/magentic_agents/common/lifecycle.py b/src/backend/v4/magentic_agents/common/lifecycle.py
index 88fde549b..e45d733dc 100644
--- a/src/backend/v4/magentic_agents/common/lifecycle.py
+++ b/src/backend/v4/magentic_agents/common/lifecycle.py
@@ -51,7 +51,7 @@ def __init__(
         self._agent: ChatAgent | None = None
         self.team_service: TeamService | None = team_service
         self.team_config: TeamConfiguration | None = team_config
-        self.client: Optional[AzureAIClient] = None
+        self.client: Optional[AgentsClient] = None
         self.project_endpoint = project_endpoint
         self.creds: Optional[DefaultAzureCredential] = None
         self.memory_store: Optional[DatabaseBase] = memory_store
@@ -228,7 +228,25 @@ def get_agent_id(self, chat_client) -> str:
         return id
 
     async def get_database_team_agent(self) -> Optional[AzureAIClient]:
-        """Retrieve existing team agent from database, if any."""
+        """Retrieve existing team agent from database, if any.
+        
+        NOTE: Agent reuse is currently DISABLED to ensure fresh agents are created
+        with the correct Azure AI Search configuration.
+        This prevents issues with stale agents that may not have the search tool configured.
+        
+        To re-enable agent reuse, set ENABLE_AGENT_REUSE=true in environment.
+        """
+        import os
+        
+        # DISABLED: Always create fresh agents to ensure Azure AI Search tool is configured
+        enable_reuse = os.environ.get("ENABLE_AGENT_REUSE", "false").lower() == "true"
+        if not enable_reuse:
+            self.logger.info(
+                "Agent reuse DISABLED: Creating fresh agent with search tools (agent_name=%s)",
+                self.agent_name,
+            )
+            return None
+        
         chat_client = None
         try:
             agent_id = await get_database_team_agent_id(
@@ -251,15 +269,15 @@ async def get_database_team_agent(self) -> Optional[AzureAIClient]:
                 )
                 return None
 
-            # Create client with resolved ID, preferring project_client for RAI agents
+            # Create client with resolved ID
             if self.agent_name == "RAIAgent" and self.project_client:
                 chat_client = AzureAIClient(
-                    project_client=self.project_client,
+                    project_endpoint=self.project_endpoint,
                     agent_id=resolved,
                     credential=self.creds,
                 )
                 self.logger.info(
-                    "RAI.AgentReuseSuccess: Created AzureAIClient via Projects SDK (id=%s)",
+                    "RAI.AgentReuseSuccess: Created AzureAIClient (id=%s)",
                     resolved,
                 )
             else:
@@ -284,17 +302,20 @@ async def get_database_team_agent(self) -> Optional[AzureAIClient]:
     async def save_database_team_agent(self) -> None:
         """Save current team agent to database (only if truly new or changed)."""
         try:
-            if self._agent.id is None:
-                self.logger.error("Cannot save database team agent: agent_id is None")
+            if self._agent is None or self._agent.id is None:
+                self.logger.error("Cannot save database team agent: agent or agent_id is None")
                 return
 
+            # Use the agent ID from ChatAgent (set during creation)
+            agent_id = self._agent.id
+
             # Check if stored ID matches current ID
             stored_id = await get_database_team_agent_id(
                 self.memory_store, self.team_config, self.agent_name
             )
-            if stored_id == self._agent.chat_client.agent_id:
+            if stored_id == agent_id:
                 self.logger.info(
-                    "RAI reuse: id unchanged (id=%s); skip save.", self._agent.id
+                    "RAI reuse: id unchanged (id=%s); skip save.", agent_id
                 )
                 return
 
@@ -302,7 +323,7 @@ async def save_database_team_agent(self) -> None:
                 team_id=self.team_config.team_id,
                 team_name=self.team_config.name,
                 agent_name=self.agent_name,
-                agent_foundry_id=self._agent.chat_client.agent_id,
+                agent_foundry_id=agent_id,
                 agent_description=self.agent_description,
                 agent_instructions=self.agent_instructions,
             )
@@ -310,7 +331,7 @@ async def save_database_team_agent(self) -> None:
             self.logger.info(
                 "Saved team agent to database (agent_name=%s, id=%s)",
                 self.agent_name,
-                self._agent.id,
+                agent_id,
             )
 
         except Exception as ex:
diff --git a/src/backend/v4/magentic_agents/foundry_agent.py b/src/backend/v4/magentic_agents/foundry_agent.py
index 9a7c8ebe8..d706af865 100644
--- a/src/backend/v4/magentic_agents/foundry_agent.py
+++ b/src/backend/v4/magentic_agents/foundry_agent.py
@@ -7,7 +7,12 @@
                              Role)
 from agent_framework_azure_ai import \
     AzureAIClient  # Provided by agent_framework
-from azure.ai.projects.models import ConnectionType
+from azure.ai.projects.models import (
+    PromptAgentDefinition,
+    AzureAISearchAgentTool,
+    AzureAISearchToolResource,
+    AISearchIndexResource,
+)
 from common.config.app_config import config
 from common.database.database_base import DatabaseBase
 from common.models.messages_af import TeamConfiguration
@@ -65,19 +70,23 @@ def __init__(
         self._use_azure_search = self._is_azure_search_requested()
         self.use_reasoning = use_reasoning
 
-        # Placeholder for server-created Azure AI agent id (if Azure Search path)
+        # Placeholder for server-created Azure AI agent id/version (if Azure Search path)
         self._azure_server_agent_id: Optional[str] = None
+        self._azure_server_agent_version: Optional[str] = None
 
     # -------------------------
     # Mode detection
     # -------------------------
     def _is_azure_search_requested(self) -> bool:
         """Determine if Azure AI Search raw tool path should be used."""
+        print(f"[DEBUG _is_azure_search_requested] Agent={self.agent_name}, search={self.search}")
         if not self.search:
+            print(f"[DEBUG _is_azure_search_requested] Agent={self.agent_name}: No search config, returning False")
             return False
         # Minimal heuristic: presence of required attributes
 
         has_index = hasattr(self.search, "index_name") and bool(self.search.index_name)
+        print(f"[DEBUG _is_azure_search_requested] Agent={self.agent_name}: has_index={has_index}, index_name={getattr(self.search, 'index_name', None)}")
         if has_index:
             self.logger.info(
                 "Azure AI Search requested (connection_id=%s, index=%s).",
@@ -113,14 +122,17 @@ async def _collect_tools(self) -> List:
     # -------------------------
     async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional[AzureAIClient]:
         """
-        Create a server-side Azure AI agent with Azure AI Search raw tool.
+        Create a server-side Azure AI agent with Azure AI Search tool using create_version.
+
+        This uses the AIProjectClient.agents.create_version() approach with:
+        - PromptAgentDefinition for agent configuration
+        - AzureAISearchAgentTool with AzureAISearchToolResource for search capability
+        - AISearchIndexResource for index configuration with project_connection_id
 
         Requirements:
-          - An Azure AI Project Connection (type=AZURE_AI_SEARCH) that contains either:
-              a) API key + endpoint, OR
-              b) Managed Identity (RBAC enabled on the Search service with Search Service Contributor + Search Index Data Reader).
+          - An Azure AI Project Connection for Azure AI Search
           - search_config.index_name must exist in the Search service.
-
+          - search_config.connection_name should match the AI Project connection name
 
         Returns:
             AzureAIClient | None
@@ -134,9 +146,16 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
             self.logger.error("Search configuration missing.")
             return None
 
-        desired_connection_name = getattr(self.search, "connection_name", None)
+        # Get connection name - this is used as project_connection_id in create_version
+        connection_name = getattr(self.search, "connection_name", None)
+        if not connection_name:
+            # Fallback to environment variable
+            connection_name = config.AZURE_AI_SEARCH_CONNECTION_NAME
+            self.logger.info("Using connection_name from environment: %s", connection_name)
+
         index_name = getattr(self.search, "index_name", "")
         query_type = getattr(self.search, "search_query_type", "simple")
+        top_k = getattr(self.search, "top_k", 5)
 
         if not index_name:
             self.logger.error(
@@ -144,82 +163,89 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
             )
             return None
 
-        resolved_connection_id = None
-
-        try:
-            async for connection in self.project_client.connections.list():
-                if connection.type == ConnectionType.AZURE_AI_SEARCH:
-
-                    if (
-                        desired_connection_name
-                        and connection.name == desired_connection_name
-                    ):
-                        resolved_connection_id = connection.id
-                        break
-                    # Fallback: if no specific connection requested and none resolved yet, take the first
-                    if not desired_connection_name and not resolved_connection_id:
-                        resolved_connection_id = connection.id
-                        # Do not break yet; we log but allow chance to find a name match later. If not, this stays.
-
-            if not resolved_connection_id:
-                self.logger.error(
-                    "No Azure AI Search connection resolved. " "connection_name=%s",
-                    desired_connection_name,
-                )
-            #  return None
-
-            self.logger.info(
-                "Using Azure AI Search connection (id=%s, requested_name=%s).",
-                resolved_connection_id,
-                desired_connection_name,
+        if not connection_name:
+            self.logger.error(
+                "connection_name not provided; aborting Azure Search path."
             )
-        except Exception as ex:
-            self.logger.error("Failed to enumerate connections: %s", ex)
             return None
 
-        # Create agent with raw tool
+        self.logger.info(
+            "Creating Azure AI Search agent with create_version: connection_name=%s, index=%s, query_type=%s, top_k=%s",
+            connection_name,
+            index_name,
+            query_type,
+            top_k,
+        )
+
+        # Create agent using create_version with PromptAgentDefinition and AzureAISearchAgentTool
+        # This approach matches the Knowledge Mining Solution Accelerator pattern
         try:
-            azure_agent = await self.client.create_agent(
-                model=self.model_deployment_name,
-                name=self.agent_name,
-                instructions=(
-                    f"{self.agent_instructions} "
-                    "Always use the Azure AI Search tool and configured index for knowledge retrieval."
+            enhanced_instructions = (
+                f"{self.agent_instructions} "
+                "Always use the Azure AI Search tool and configured index for knowledge retrieval."
+            )
+            
+            print(f"[DEBUG] Creating agent '{self.agent_name}' with instructions (first 200 chars): {enhanced_instructions[:200]}...")
+            print(f"[DEBUG] Agent model: {self.model_deployment_name}")
+            print(f"[DEBUG] Search config: connection={connection_name}, index={index_name}, query_type={query_type}, top_k={top_k}")
+
+            azure_agent = await self.project_client.agents.create_version(
+                agent_name=self.agent_name,
+                definition=PromptAgentDefinition(
+                    model=self.model_deployment_name,
+                    instructions=enhanced_instructions,
+                    tools=[
+                        AzureAISearchAgentTool(
+                            azure_ai_search=AzureAISearchToolResource(
+                                indexes=[
+                                    AISearchIndexResource(
+                                        project_connection_id=connection_name,
+                                        index_name=index_name,
+                                        query_type=query_type,
+                                        top_k=top_k,
+                                    )
+                                ]
+                            )
+                        )
+                    ],
                 ),
-                tools=[{"type": "azure_ai_search"}],
-                tool_resources={
-                    "azure_ai_search": {
-                        "indexes": [
-                            {
-                                "index_connection_id": resolved_connection_id,
-                                "index_name": index_name,
-                                "query_type": query_type,
-                            }
-                        ]
-                    }
-                },
             )
+
             self._azure_server_agent_id = azure_agent.id
+            self._azure_server_agent_version = azure_agent.version
             self.logger.info(
-                "Created Azure server agent with Azure AI Search tool (agent_id=%s, index=%s, query_type=%s).",
+                "Created Azure AI Search agent via create_version (name=%s, id=%s, version=%s, connection=%s, index=%s, query_type=%s, top_k=%s).",
+                azure_agent.name,
                 azure_agent.id,
+                azure_agent.version,
+                connection_name,
                 index_name,
                 query_type,
+                top_k,
             )
+            print(f"[DEBUG] Created agent via create_version: name={azure_agent.name}, id={azure_agent.id}, version={azure_agent.version}")
+            print(f"[DEBUG] Agent definition: {azure_agent.definition}")
+            print(f"[DEBUG] Agent instructions from definition: {getattr(azure_agent.definition, 'instructions', 'N/A')}")
 
+            # Wrap in AzureAIClient using agent_name and agent_version (NOT agent_id)
+            # AzureAIClient constructor: agent_name, agent_version, project_endpoint, credential
             chat_client = AzureAIClient(
-                project_client=self.project_client,
-                agent_id=azure_agent.id,
+                project_endpoint=self.project_endpoint,
+                agent_name=azure_agent.name,
+                agent_version=azure_agent.version,  # Use the specific version we just created
                 credential=self.creds,
             )
             return chat_client
+
         except Exception as ex:
             self.logger.error(
-                "Failed to create Azure Search enabled agent (connection_id=%s, index=%s): %s",
-                resolved_connection_id,
+                "Failed to create Azure Search enabled agent via create_version (connection=%s, index=%s): %s",
+                connection_name,
                 index_name,
                 ex,
             )
+            import traceback
+            traceback.print_exc()
             return None
 
     # -------------------------
diff --git a/src/backend/v4/magentic_agents/models/agent_models.py b/src/backend/v4/magentic_agents/models/agent_models.py
index 5c6a3f2f1..4e10270fa 100644
--- a/src/backend/v4/magentic_agents/models/agent_models.py
+++ b/src/backend/v4/magentic_agents/models/agent_models.py
@@ -43,6 +43,8 @@ class SearchConfig:
     connection_name: str | None = None
     endpoint: str | None = None
     index_name: str | None = None
+    search_query_type: str = "simple"  # Options: "simple", "vector_simple", "vector", "semantic", "hybrid"
+    top_k: int = 5  # Number of results to return
 
     @classmethod
     def from_env(cls, index_name: str) -> "SearchConfig":
@@ -58,5 +60,7 @@ def from_env(cls, index_name: str) -> "SearchConfig":
         return cls(
             connection_name=connection_name,
             endpoint=endpoint,
-            index_name=index_name
+            index_name=index_name,
+            search_query_type="simple",  # Use simple query type (keyword search)
+            top_k=5
         )
diff --git a/src/backend/v4/orchestration/orchestration_manager.py b/src/backend/v4/orchestration/orchestration_manager.py
index 4fc0c209a..5a27c59b0 100644
--- a/src/backend/v4/orchestration/orchestration_manager.py
+++ b/src/backend/v4/orchestration/orchestration_manager.py
@@ -231,17 +231,22 @@ async def get_current_or_new_orchestration(
         team_config: TeamConfiguration,
         team_switched: bool,
         team_service: TeamService = None,
+        force_rebuild: bool = False,
     ):
         """
         Return an existing workflow for the user or create a new one if:
           - None exists
           - Team switched flag is True
+          - force_rebuild is True (for new tasks after workflow completion)
         """
         current = orchestration_config.get_current_orchestration(user_id)
-        if current is None or team_switched:
-            if current is not None and team_switched:
+        needs_rebuild = current is None or team_switched or force_rebuild
+        
+        if needs_rebuild:
+            if current is not None and (team_switched or force_rebuild):
+                reason = "team switched" if team_switched else "force rebuild for new task"
                 cls.logger.info(
-                    "Team switched, closing previous agents for user '%s'", user_id
+                    "Rebuilding orchestration for user '%s' (reason: %s)", user_id, reason
                 )
                 # Close prior agents (same logic as old version)
                 for agent in getattr(current, "_participants", {}).values():

From 1bc5725bd4e0015cc42ebcd13242495b84edef15 Mon Sep 17 00:00:00 2001
From: Abdul-Microsoft <v-amujeebta@microsoft.com>
Date: Wed, 11 Feb 2026 17:45:02 +0530
Subject: [PATCH 04/13] fix for agent multiple times calling

---
 .../v4/magentic_agents/foundry_agent.py       | 18 ++++------
 .../magentic_agents/magentic_agent_factory.py |  1 +
 .../orchestration/human_approval_manager.py   | 20 ++++++++++-
 .../v4/orchestration/orchestration_manager.py | 34 +++++++++++++++----
 4 files changed, 54 insertions(+), 19 deletions(-)

diff --git a/src/backend/v4/magentic_agents/foundry_agent.py b/src/backend/v4/magentic_agents/foundry_agent.py
index d706af865..84297ebef 100644
--- a/src/backend/v4/magentic_agents/foundry_agent.py
+++ b/src/backend/v4/magentic_agents/foundry_agent.py
@@ -185,12 +185,12 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
                 "Always use the Azure AI Search tool and configured index for knowledge retrieval."
             )
             
-            print(f"[DEBUG] Creating agent '{self.agent_name}' with instructions (first 200 chars): {enhanced_instructions[:200]}...")
-            print(f"[DEBUG] Agent model: {self.model_deployment_name}")
-            print(f"[DEBUG] Search config: connection={connection_name}, index={index_name}, query_type={query_type}, top_k={top_k}")
+            print(f"[AGENT CREATE] 🆕 Creating agent in Foundry: '{self.agent_name}'", flush=True)
+            print(f"[AGENT CREATE] Model: {self.model_deployment_name}", flush=True)
+            print(f"[AGENT CREATE] Search: connection={connection_name}, index={index_name}", flush=True)
 
             azure_agent = await self.project_client.agents.create_version(
-                agent_name=self.agent_name,
+                agent_name=self.agent_name,  # Use original name
                 definition=PromptAgentDefinition(
                     model=self.model_deployment_name,
                     instructions=enhanced_instructions,
@@ -213,19 +213,13 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
 
             self._azure_server_agent_id = azure_agent.id
             self._azure_server_agent_version = azure_agent.version
+            print(f"[AGENT CREATE] ✅ Created agent: name={azure_agent.name}, id={azure_agent.id}, version={azure_agent.version}", flush=True)
             self.logger.info(
-                "Created Azure AI Search agent via create_version (name=%s, id=%s, version=%s, connection=%s, index=%s, query_type=%s, top_k=%s).",
+                "Created Azure AI Search agent via create_version (name=%s, id=%s, version=%s).",
                 azure_agent.name,
                 azure_agent.id,
                 azure_agent.version,
-                connection_name,
-                index_name,
-                query_type,
-                top_k,
             )
-            print(f"[DEBUG] Created agent via create_version: name={azure_agent.name}, id={azure_agent.id}, version={azure_agent.version}")
-            print(f"[DEBUG] Agent definition: {azure_agent.definition}")
-            print(f"[DEBUG] Agent instructions from definition: {getattr(azure_agent.definition, 'instructions', 'N/A')}")
 
             # Wrap in AzureAIClient using agent_name and agent_version (NOT agent_id)
             # AzureAIClient constructor: agent_name, agent_version, project_endpoint, credential
diff --git a/src/backend/v4/magentic_agents/magentic_agent_factory.py b/src/backend/v4/magentic_agents/magentic_agent_factory.py
index 36544166d..3eafb5831 100644
--- a/src/backend/v4/magentic_agents/magentic_agent_factory.py
+++ b/src/backend/v4/magentic_agents/magentic_agent_factory.py
@@ -115,6 +115,7 @@ async def create_agent_from_config(
             index_name,
             "Reasoning" if use_reasoning else "Foundry",
         )
+        print(f"[FACTORY] 🆕 Creating NEW agent: {agent_obj.name} (id={id(agent_obj)})", flush=True)
 
         agent = FoundryAgentTemplate(
             agent_name=agent_obj.name,
diff --git a/src/backend/v4/orchestration/human_approval_manager.py b/src/backend/v4/orchestration/human_approval_manager.py
index 654d72a23..39089247a 100644
--- a/src/backend/v4/orchestration/human_approval_manager.py
+++ b/src/backend/v4/orchestration/human_approval_manager.py
@@ -33,6 +33,7 @@ class HumanApprovalMagenticManager(StandardMagenticManager):
     approval_enabled: bool = True
     magentic_plan: Optional[MPlan] = None
     current_user_id: str  # populated in __init__
+    _called_agents: set  # Track which agents have been called
 
     def __init__(self, user_id: str, agent, *args, **kwargs):
         """
@@ -43,6 +44,9 @@ def __init__(self, user_id: str, agent, *args, **kwargs):
             *args: Additional positional arguments for the parent StandardMagenticManager.
             **kwargs: Additional keyword arguments for the parent StandardMagenticManager.
         """
+        
+        # Initialize called agents tracker
+        self._called_agents = set()
 
         plan_append = """
 
@@ -55,6 +59,9 @@ def __init__(self, user_id: str, agent, *args, **kwargs):
 to be taken. If a step involves multiple actions, separate them into distinct steps with an agent included in each step.
 If the step is taken by an agent that is not part of the team, such as the MagenticManager, please always list the MagenticManager as the agent for that step. At any time, if more information is needed from the user, use the ProxyAgent to request this information.
 
+CRITICAL: Each agent should only be called ONCE to perform their task. Do NOT call the same agent multiple times.
+After an agent has provided their response, move on to the next agent in the plan.
+
 Here is an example of a well-structured plan:
 - **EnhancedResearchAgent** to gather authoritative data on the latest industry trends and best practices in employee onboarding
 - **EnhancedResearchAgent** to gather authoritative data on Innovative onboarding techniques that enhance new hire engagement and retention.
@@ -62,6 +69,13 @@ def __init__(self, user_id: str, agent, *args, **kwargs):
 - **DocumentCreationAgent** to draft a comprehensive onboarding plan that includes a checklist of resources and materials needed for effective onboarding.
 - **ProxyAgent** to review the drafted onboarding plan for clarity and completeness.
 - **MagenticManager** to finalize the onboarding plan and prepare it for presentation to stakeholders.
+"""
+
+        # Add progress ledger prompt to prevent re-calling agents
+        progress_append = """
+CRITICAL RULE: DO NOT call the same agent more than once unless absolutely necessary.
+If an agent has already provided a response, consider their task COMPLETE and move to the next agent.
+Only re-call an agent if their previous response was explicitly an error or failure.
 """
 
         final_append = """
@@ -75,6 +89,10 @@ def __init__(self, user_id: str, agent, *args, **kwargs):
             ORCHESTRATOR_TASK_LEDGER_PLAN_UPDATE_PROMPT + plan_append
         )
         kwargs["final_answer_prompt"] = ORCHESTRATOR_FINAL_ANSWER_PROMPT + final_append
+        
+        # Override progress ledger prompt to discourage re-calling agents
+        from agent_framework._workflows._magentic import ORCHESTRATOR_PROGRESS_LEDGER_PROMPT
+        kwargs["progress_ledger_prompt"] = ORCHESTRATOR_PROGRESS_LEDGER_PROMPT + progress_append
 
         self.current_user_id = user_id
         # New API: StandardMagenticManager takes agent as first positional argument
@@ -305,4 +323,4 @@ def plan_to_obj(self, magentic_context: MagenticContext, ledger) -> MPlan:
             task=task_text,
         )
 
-        return return_plan
+        return return_plan
\ No newline at end of file
diff --git a/src/backend/v4/orchestration/orchestration_manager.py b/src/backend/v4/orchestration/orchestration_manager.py
index 5a27c59b0..58fc507e1 100644
--- a/src/backend/v4/orchestration/orchestration_manager.py
+++ b/src/backend/v4/orchestration/orchestration_manager.py
@@ -197,17 +197,19 @@ async def init_orchestration(
         # Assemble workflow with callback
         storage = InMemoryCheckpointStorage()
         
-        # New API: .participants() accepts a list of agents
+        # New SDK: participants() accepts a Sequence (list) of agents
+        # The orchestrator uses agent.name to identify them
         participant_list = list(participants.values())
+        cls.logger.info("Participants for workflow: %s", list(participants.keys()))
+        print(f"[DEBUG] Participants for workflow: {list(participants.keys())}", flush=True)
         
         builder = (
             MagenticBuilder()
-            .participants(participant_list)
+            .participants(participant_list)  # New SDK: pass as list
             .with_manager(
                 manager=manager,  # Pass manager instance (extends StandardMagenticManager)
                 max_round_count=orchestration_config.max_rounds,
-                max_stall_count=3,
-                max_reset_count=2,
+                max_stall_count=0,  # CRITICAL: Prevent re-calling agents when stalled (default is 3!)
             )
             .with_checkpointing(storage)
         )
@@ -381,12 +383,16 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
         task_text = getattr(input_task, "description", str(input_task))
         self.logger.debug("Task: %s", task_text)
 
+        # Track how many times each agent is called (for debugging duplicate calls)
+        agent_call_counts: dict = {}
+
         try:
             # Execute workflow using run_stream with task as positional parameter
             # The execution settings are configured in the manager/client
             final_output: str | None = None
 
             self.logger.info("Starting workflow execution...")
+            print(f"[ORCHESTRATOR] 🚀 Starting workflow with max_rounds={orchestration_config.max_rounds}", flush=True)
             last_message_id: str | None = None
             async for event in workflow.run_stream(task_text):
                 try:
@@ -431,11 +437,20 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
 
                     # Handle group chat request sent
                     elif isinstance(event, GroupChatRequestSentEvent):
+                        agent_name = event.participant_name
+                        agent_call_counts[agent_name] = agent_call_counts.get(agent_name, 0) + 1
+                        call_num = agent_call_counts[agent_name]
+                        
                         self.logger.info(
-                            "[REQUEST SENT (round %d)] to agent: %s",
+                            "[REQUEST SENT (round %d)] to agent: %s (call #%d)",
                             event.round_index,
-                            event.participant_name
+                            agent_name,
+                            call_num
                         )
+                        print(f"[ORCHESTRATOR] 📤 REQUEST SENT round={event.round_index} to agent={agent_name} (call #{call_num})", flush=True)
+                        
+                        if call_num > 1:
+                            print(f"[ORCHESTRATOR] ⚠️ WARNING: Agent '{agent_name}' called {call_num} times!", flush=True)
 
                     # Handle group chat response received - THIS IS WHERE AGENT RESPONSES COME
                     elif isinstance(event, GroupChatResponseReceivedEvent):
@@ -496,6 +511,13 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
             # Extract final result
             final_text = final_output if final_output else ""
 
+            # Log agent call summary
+            print(f"\n[ORCHESTRATOR] 📊 AGENT CALL SUMMARY:", flush=True)
+            for agent_name, count in agent_call_counts.items():
+                status = "✅" if count == 1 else "⚠️ DUPLICATE"
+                print(f"  {status} {agent_name}: called {count} time(s)", flush=True)
+            self.logger.info("Agent call counts: %s", agent_call_counts)
+
             # Log results
             self.logger.info("\nAgent responses:")
             self.logger.info(

From 45582e15fedbfb6e850a554329800b138ebe4272 Mon Sep 17 00:00:00 2001
From: Abdul-Microsoft <v-amujeebta@microsoft.com>
Date: Fri, 13 Feb 2026 09:15:56 +0530
Subject: [PATCH 05/13] Enhance get_chat_client to use latest agent version and
 log agent name

---
 src/backend/v4/magentic_agents/common/lifecycle.py | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/src/backend/v4/magentic_agents/common/lifecycle.py b/src/backend/v4/magentic_agents/common/lifecycle.py
index e45d733dc..af9dcb846 100644
--- a/src/backend/v4/magentic_agents/common/lifecycle.py
+++ b/src/backend/v4/magentic_agents/common/lifecycle.py
@@ -149,7 +149,10 @@ async def _after_open(self) -> None:
         raise NotImplementedError
 
     def get_chat_client(self, chat_client) -> AzureAIClient:
-        """Return the underlying ChatClientProtocol (AzureAIClient)."""
+        """Return the underlying ChatClientProtocol (AzureAIClient).
+        
+        Uses agent_name with use_latest_version=True to get the latest agent version
+        """
         if chat_client:
             return chat_client
         if (
@@ -159,11 +162,14 @@ def get_chat_client(self, chat_client) -> AzureAIClient:
             return self._agent.chat_client  # type: ignore
         chat_client = AzureAIClient(
             project_endpoint=self.project_endpoint,
+            agent_name=self.agent_name,
             model_deployment_name=self.model_deployment_name,
             credential=self.creds,
+            use_latest_version=True,
         )
         self.logger.info(
-            "Created new AzureAIClient for get chat client",
+            "Created new AzureAIClient (agent_name=%s, use_latest_version=True)",
+            self.agent_name,
         )
         return chat_client
 

From 3a4dfbb3bf0e2a0bab58968f0c0000fa46c13423 Mon Sep 17 00:00:00 2001
From: Abdul-Microsoft <v-amujeebta@microsoft.com>
Date: Fri, 13 Feb 2026 11:36:18 +0530
Subject: [PATCH 06/13] Update dependency versions in pyproject.toml and
 uv.lock for consistency

---
 src/backend/pyproject.toml | 18 +++++++++---------
 src/backend/uv.lock        | 18 +++++++++---------
 2 files changed, 18 insertions(+), 18 deletions(-)

diff --git a/src/backend/pyproject.toml b/src/backend/pyproject.toml
index 7750638dd..f5bd8fc6f 100644
--- a/src/backend/pyproject.toml
+++ b/src/backend/pyproject.toml
@@ -11,16 +11,16 @@ dependencies = [
     "azure-cosmos==4.9.0",
     "azure-identity==1.24.0",
     "azure-monitor-events-extension==0.1.0",
-    "azure-monitor-opentelemetry>=1.8.0",
+    "azure-monitor-opentelemetry==1.8.5",
     "azure-search-documents==11.5.3",
     "fastapi==0.116.1",
-    "openai>=2.8.0",
-    "opentelemetry-api>=1.39.0",
-    "opentelemetry-exporter-otlp-proto-grpc>=1.39.0",
-    "opentelemetry-exporter-otlp-proto-http>=1.39.0",
-    "opentelemetry-instrumentation-fastapi>=0.57b0",
-    "opentelemetry-instrumentation-openai>=0.46.2",
-    "opentelemetry-sdk>=1.39.0",
+    "openai==2.16.0",
+    "opentelemetry-api==1.39.0",
+    "opentelemetry-exporter-otlp-proto-grpc==1.39.0",
+    "opentelemetry-exporter-otlp-proto-http==1.39.0",
+    "opentelemetry-instrumentation-fastapi==0.60b0",
+    "opentelemetry-instrumentation-openai==0.46.2",
+    "opentelemetry-sdk==1.39.0",
     "pytest==8.4.1",
     "pytest-asyncio==0.24.0",
     "pytest-cov==5.0.0",
@@ -30,7 +30,7 @@ dependencies = [
     "uvicorn==0.35.0",
     "pylint-pydantic==0.3.5",
     "pexpect==4.9.0",
-    "mcp>=1.24.0,<2",
+    "mcp==1.26.0",
     "agent-framework-azure-ai==1.0.0b260130",
     "agent-framework-core==1.0.0b260130"
 ]
\ No newline at end of file
diff --git a/src/backend/uv.lock b/src/backend/uv.lock
index 526fe789a..3e7bbae7e 100644
--- a/src/backend/uv.lock
+++ b/src/backend/uv.lock
@@ -557,17 +557,17 @@ requires-dist = [
     { name = "azure-cosmos", specifier = "==4.9.0" },
     { name = "azure-identity", specifier = "==1.24.0" },
     { name = "azure-monitor-events-extension", specifier = "==0.1.0" },
-    { name = "azure-monitor-opentelemetry", specifier = ">=1.8.0" },
+    { name = "azure-monitor-opentelemetry", specifier = "==1.8.5" },
     { name = "azure-search-documents", specifier = "==11.5.3" },
     { name = "fastapi", specifier = "==0.116.1" },
-    { name = "mcp", specifier = ">=1.24.0,<2" },
-    { name = "openai", specifier = ">=2.8.0" },
-    { name = "opentelemetry-api", specifier = ">=1.39.0" },
-    { name = "opentelemetry-exporter-otlp-proto-grpc", specifier = ">=1.39.0" },
-    { name = "opentelemetry-exporter-otlp-proto-http", specifier = ">=1.39.0" },
-    { name = "opentelemetry-instrumentation-fastapi", specifier = ">=0.57b0" },
-    { name = "opentelemetry-instrumentation-openai", specifier = ">=0.46.2" },
-    { name = "opentelemetry-sdk", specifier = ">=1.39.0" },
+    { name = "mcp", specifier = "==1.26.0" },
+    { name = "openai", specifier = "==2.16.0" },
+    { name = "opentelemetry-api", specifier = "==1.39.0" },
+    { name = "opentelemetry-exporter-otlp-proto-grpc", specifier = "==1.39.0" },
+    { name = "opentelemetry-exporter-otlp-proto-http", specifier = "==1.39.0" },
+    { name = "opentelemetry-instrumentation-fastapi", specifier = "==0.60b0" },
+    { name = "opentelemetry-instrumentation-openai", specifier = "==0.46.2" },
+    { name = "opentelemetry-sdk", specifier = "==1.39.0" },
     { name = "pexpect", specifier = "==4.9.0" },
     { name = "pylint-pydantic", specifier = "==0.3.5" },
     { name = "pytest", specifier = "==8.4.1" },

From c513f4bde39bc162312a31fbb21b349df010d640 Mon Sep 17 00:00:00 2001
From: Abdul-Microsoft <v-amujeebta@microsoft.com>
Date: Fri, 13 Feb 2026 17:14:32 +0530
Subject: [PATCH 07/13] Add user state cleanup and enhance AzureAIClient
 initialization with deployment name fallback

---
 src/backend/v4/config/settings.py             | 20 ++++++
 .../v4/magentic_agents/common/lifecycle.py    | 15 ++++-
 .../v4/magentic_agents/foundry_agent.py       |  4 +-
 .../v4/orchestration/orchestration_manager.py | 65 +++++++++----------
 4 files changed, 64 insertions(+), 40 deletions(-)

diff --git a/src/backend/v4/config/settings.py b/src/backend/v4/config/settings.py
index fa112fcd9..2a9687272 100644
--- a/src/backend/v4/config/settings.py
+++ b/src/backend/v4/config/settings.py
@@ -220,6 +220,26 @@ def cleanup_clarification(self, request_id: str) -> None:
         self.clarifications.pop(request_id, None)
         self._clarification_events.pop(request_id, None)
 
+    def cleanup_user_state(self, user_id: str) -> None:
+        """Clean up all state for a user to prevent cross-scenario leakage.
+        
+        This removes any pending approvals, clarifications, and plans
+        associated with the user to ensure fresh state for new runs.
+        """
+        # Clean up any plans associated with this user
+        plans_to_remove = [
+            plan_id for plan_id, plan in self.plans.items()
+            if getattr(plan, 'user_id', None) == user_id
+        ]
+        for plan_id in plans_to_remove:
+            self.plans.pop(plan_id, None)
+            self.cleanup_approval(plan_id)
+        
+        # Clean up any pending approvals/clarifications for this user
+        # Note: We can't easily map approvals to users without plan context,
+        # so this primarily clears the plans and their associated approvals
+        logger.debug("Cleaned up state for user %s (removed %d plans)", user_id, len(plans_to_remove))
+
 
 class ConnectionConfig:
     """Connection manager for WebSocket connections."""
diff --git a/src/backend/v4/magentic_agents/common/lifecycle.py b/src/backend/v4/magentic_agents/common/lifecycle.py
index af9dcb846..c143d0c45 100644
--- a/src/backend/v4/magentic_agents/common/lifecycle.py
+++ b/src/backend/v4/magentic_agents/common/lifecycle.py
@@ -14,6 +14,7 @@
 from agent_framework_azure_ai import AzureAIClient
 from azure.ai.agents.aio import AgentsClient
 from azure.identity.aio import DefaultAzureCredential
+from common.config.app_config import config
 from common.database.database_base import DatabaseBase
 from common.models.messages_af import CurrentTeamAgent, TeamConfiguration
 from common.utils.utils_agents import (
@@ -160,10 +161,12 @@ def get_chat_client(self, chat_client) -> AzureAIClient:
             and self._agent.chat_client
         ):
             return self._agent.chat_client  # type: ignore
+        # Use model_deployment_name with fallback to default model if empty
+        deployment_name = self.model_deployment_name or config.AZURE_OPENAI_DEPLOYMENT_NAME
         chat_client = AzureAIClient(
             project_endpoint=self.project_endpoint,
             agent_name=self.agent_name,
-            model_deployment_name=self.model_deployment_name,
+            model_deployment_name=deployment_name,
             credential=self.creds,
             use_latest_version=True,
         )
@@ -277,20 +280,26 @@ async def get_database_team_agent(self) -> Optional[AzureAIClient]:
 
             # Create client with resolved ID
             if self.agent_name == "RAIAgent" and self.project_client:
+                # Use RAI deployment name for RAI agents
+                rai_deployment = config.AZURE_OPENAI_RAI_DEPLOYMENT_NAME
                 chat_client = AzureAIClient(
                     project_endpoint=self.project_endpoint,
                     agent_id=resolved,
+                    model_deployment_name=rai_deployment,
                     credential=self.creds,
                 )
                 self.logger.info(
-                    "RAI.AgentReuseSuccess: Created AzureAIClient (id=%s)",
+                    "RAI.AgentReuseSuccess: Created AzureAIClient (id=%s, model=%s)",
                     resolved,
+                    rai_deployment,
                 )
             else:
+                # Use model_deployment_name with fallback to default model if empty
+                deployment_name = self.model_deployment_name or config.AZURE_OPENAI_DEPLOYMENT_NAME
                 chat_client = AzureAIClient(
                     project_endpoint=self.project_endpoint,
                     agent_id=resolved,
-                    model_deployment_name=self.model_deployment_name,
+                    model_deployment_name=deployment_name,
                     credential=self.creds,
                 )
                 self.logger.info(
diff --git a/src/backend/v4/magentic_agents/foundry_agent.py b/src/backend/v4/magentic_agents/foundry_agent.py
index 84297ebef..3a95ea210 100644
--- a/src/backend/v4/magentic_agents/foundry_agent.py
+++ b/src/backend/v4/magentic_agents/foundry_agent.py
@@ -222,11 +222,13 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
             )
 
             # Wrap in AzureAIClient using agent_name and agent_version (NOT agent_id)
-            # AzureAIClient constructor: agent_name, agent_version, project_endpoint, credential
+            # Include model_deployment_name to ensure SDK has model info for streaming
+            deployment_name = self.model_deployment_name or config.AZURE_OPENAI_DEPLOYMENT_NAME
             chat_client = AzureAIClient(
                 project_endpoint=self.project_endpoint,
                 agent_name=azure_agent.name,
                 agent_version=azure_agent.version,  # Use the specific version we just created
+                model_deployment_name=deployment_name,
                 credential=self.creds,
             )
             return chat_client
diff --git a/src/backend/v4/orchestration/orchestration_manager.py b/src/backend/v4/orchestration/orchestration_manager.py
index 58fc507e1..12bd70ec8 100644
--- a/src/backend/v4/orchestration/orchestration_manager.py
+++ b/src/backend/v4/orchestration/orchestration_manager.py
@@ -133,9 +133,11 @@ async def init_orchestration(
 
         try:
             # Create the chat client (AzureAIClient)
+            # Use team deployment_name with fallback to default model if empty
+            deployment_name = team_config.deployment_name or config.AZURE_OPENAI_DEPLOYMENT_NAME
             chat_client = AzureAIClient(
                 project_endpoint=config.AZURE_AI_PROJECT_ENDPOINT,
-                model_deployment_name=team_config.deployment_name,
+                model_deployment_name=deployment_name,
                 agent_name=agent_name,
                 credential=credential,
             )
@@ -150,7 +152,7 @@ async def init_orchestration(
 
             cls.logger.info(
                 "Created AzureAIClient and manager ChatAgent for orchestration with model '%s' at endpoint '%s'",
-                team_config.deployment_name,
+                deployment_name,
                 config.AZURE_AI_PROJECT_ENDPOINT,
             )
         except Exception as e:
@@ -197,19 +199,17 @@ async def init_orchestration(
         # Assemble workflow with callback
         storage = InMemoryCheckpointStorage()
         
-        # New SDK: participants() accepts a Sequence (list) of agents
-        # The orchestrator uses agent.name to identify them
+        # New API: .participants() accepts a list of agents
         participant_list = list(participants.values())
-        cls.logger.info("Participants for workflow: %s", list(participants.keys()))
-        print(f"[DEBUG] Participants for workflow: {list(participants.keys())}", flush=True)
         
         builder = (
             MagenticBuilder()
-            .participants(participant_list)  # New SDK: pass as list
+            .participants(participant_list)
             .with_manager(
                 manager=manager,  # Pass manager instance (extends StandardMagenticManager)
                 max_round_count=orchestration_config.max_rounds,
-                max_stall_count=0,  # CRITICAL: Prevent re-calling agents when stalled (default is 3!)
+                max_stall_count=3,
+                max_reset_count=2,
             )
             .with_checkpointing(storage)
         )
@@ -239,16 +239,14 @@ async def get_current_or_new_orchestration(
         Return an existing workflow for the user or create a new one if:
           - None exists
           - Team switched flag is True
-          - force_rebuild is True (for new tasks after workflow completion)
+          - force_rebuild is True (for new tasks that need fresh workflow)
         """
         current = orchestration_config.get_current_orchestration(user_id)
-        needs_rebuild = current is None or team_switched or force_rebuild
-        
-        if needs_rebuild:
+        if current is None or team_switched or force_rebuild:
             if current is not None and (team_switched or force_rebuild):
-                reason = "team switched" if team_switched else "force rebuild for new task"
+                reason = "team switched" if team_switched else "force rebuild"
                 cls.logger.info(
-                    "Rebuilding orchestration for user '%s' (reason: %s)", user_id, reason
+                    "Closing previous agents for user '%s' (reason: %s)", user_id, reason
                 )
                 # Close prior agents (same logic as old version)
                 for agent in getattr(current, "_participants", {}).values():
@@ -305,6 +303,11 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
         Execute the Magentic workflow for the provided user and task description.
         """
         job_id = str(uuid.uuid4())
+        
+        # Clean up any accumulated state from previous runs (cancelled plans, etc.)
+        # This prevents cross-scenario leakage
+        orchestration_config.cleanup_user_state(user_id)
+        
         orchestration_config.set_approval_pending(job_id)
         self.logger.info(
             "Starting orchestration job '%s' for user '%s'", job_id, user_id
@@ -317,6 +320,16 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
         if workflow is None:
             print(f"[ERROR] Orchestration not initialized for user '{user_id}'")
             raise ValueError("Orchestration not initialized for user.")
+        
+        # Reset manager's plan state to prevent leakage from cancelled plans
+        manager = getattr(workflow, "_manager", None)
+        if manager and hasattr(manager, "magentic_plan"):
+            manager.magentic_plan = None
+            self.logger.debug("Reset manager's magentic_plan for fresh run")
+        if manager and hasattr(manager, "task_ledger"):
+            manager.task_ledger = None
+            self.logger.debug("Reset manager's task_ledger for fresh run")
+        
         # Fresh thread per participant to avoid cross-run state bleed
         executors = getattr(workflow, "executors", {})
         self.logger.debug("Executor keys at run start: %s", list(executors.keys()))
@@ -383,16 +396,12 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
         task_text = getattr(input_task, "description", str(input_task))
         self.logger.debug("Task: %s", task_text)
 
-        # Track how many times each agent is called (for debugging duplicate calls)
-        agent_call_counts: dict = {}
-
         try:
             # Execute workflow using run_stream with task as positional parameter
             # The execution settings are configured in the manager/client
             final_output: str | None = None
 
             self.logger.info("Starting workflow execution...")
-            print(f"[ORCHESTRATOR] 🚀 Starting workflow with max_rounds={orchestration_config.max_rounds}", flush=True)
             last_message_id: str | None = None
             async for event in workflow.run_stream(task_text):
                 try:
@@ -437,20 +446,11 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
 
                     # Handle group chat request sent
                     elif isinstance(event, GroupChatRequestSentEvent):
-                        agent_name = event.participant_name
-                        agent_call_counts[agent_name] = agent_call_counts.get(agent_name, 0) + 1
-                        call_num = agent_call_counts[agent_name]
-                        
                         self.logger.info(
-                            "[REQUEST SENT (round %d)] to agent: %s (call #%d)",
+                            "[REQUEST SENT (round %d)] to agent: %s",
                             event.round_index,
-                            agent_name,
-                            call_num
+                            event.participant_name
                         )
-                        print(f"[ORCHESTRATOR] 📤 REQUEST SENT round={event.round_index} to agent={agent_name} (call #{call_num})", flush=True)
-                        
-                        if call_num > 1:
-                            print(f"[ORCHESTRATOR] ⚠️ WARNING: Agent '{agent_name}' called {call_num} times!", flush=True)
 
                     # Handle group chat response received - THIS IS WHERE AGENT RESPONSES COME
                     elif isinstance(event, GroupChatResponseReceivedEvent):
@@ -511,13 +511,6 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
             # Extract final result
             final_text = final_output if final_output else ""
 
-            # Log agent call summary
-            print(f"\n[ORCHESTRATOR] 📊 AGENT CALL SUMMARY:", flush=True)
-            for agent_name, count in agent_call_counts.items():
-                status = "✅" if count == 1 else "⚠️ DUPLICATE"
-                print(f"  {status} {agent_name}: called {count} time(s)", flush=True)
-            self.logger.info("Agent call counts: %s", agent_call_counts)
-
             # Log results
             self.logger.info("\nAgent responses:")
             self.logger.info(

From f2eb8e38c892faf8966804d0629ea11f2b79f753 Mon Sep 17 00:00:00 2001
From: Abdul-Microsoft <v-amujeebta@microsoft.com>
Date: Fri, 13 Feb 2026 17:31:46 +0530
Subject: [PATCH 08/13] Revert "Add user state cleanup and enhance
 AzureAIClient initialization with deployment name fallback"

This reverts commit c513f4bde39bc162312a31fbb21b349df010d640.
---
 src/backend/v4/config/settings.py             | 20 ------
 .../v4/magentic_agents/common/lifecycle.py    | 15 +----
 .../v4/magentic_agents/foundry_agent.py       |  4 +-
 .../v4/orchestration/orchestration_manager.py | 65 ++++++++++---------
 4 files changed, 40 insertions(+), 64 deletions(-)

diff --git a/src/backend/v4/config/settings.py b/src/backend/v4/config/settings.py
index 2a9687272..fa112fcd9 100644
--- a/src/backend/v4/config/settings.py
+++ b/src/backend/v4/config/settings.py
@@ -220,26 +220,6 @@ def cleanup_clarification(self, request_id: str) -> None:
         self.clarifications.pop(request_id, None)
         self._clarification_events.pop(request_id, None)
 
-    def cleanup_user_state(self, user_id: str) -> None:
-        """Clean up all state for a user to prevent cross-scenario leakage.
-        
-        This removes any pending approvals, clarifications, and plans
-        associated with the user to ensure fresh state for new runs.
-        """
-        # Clean up any plans associated with this user
-        plans_to_remove = [
-            plan_id for plan_id, plan in self.plans.items()
-            if getattr(plan, 'user_id', None) == user_id
-        ]
-        for plan_id in plans_to_remove:
-            self.plans.pop(plan_id, None)
-            self.cleanup_approval(plan_id)
-        
-        # Clean up any pending approvals/clarifications for this user
-        # Note: We can't easily map approvals to users without plan context,
-        # so this primarily clears the plans and their associated approvals
-        logger.debug("Cleaned up state for user %s (removed %d plans)", user_id, len(plans_to_remove))
-
 
 class ConnectionConfig:
     """Connection manager for WebSocket connections."""
diff --git a/src/backend/v4/magentic_agents/common/lifecycle.py b/src/backend/v4/magentic_agents/common/lifecycle.py
index c143d0c45..af9dcb846 100644
--- a/src/backend/v4/magentic_agents/common/lifecycle.py
+++ b/src/backend/v4/magentic_agents/common/lifecycle.py
@@ -14,7 +14,6 @@
 from agent_framework_azure_ai import AzureAIClient
 from azure.ai.agents.aio import AgentsClient
 from azure.identity.aio import DefaultAzureCredential
-from common.config.app_config import config
 from common.database.database_base import DatabaseBase
 from common.models.messages_af import CurrentTeamAgent, TeamConfiguration
 from common.utils.utils_agents import (
@@ -161,12 +160,10 @@ def get_chat_client(self, chat_client) -> AzureAIClient:
             and self._agent.chat_client
         ):
             return self._agent.chat_client  # type: ignore
-        # Use model_deployment_name with fallback to default model if empty
-        deployment_name = self.model_deployment_name or config.AZURE_OPENAI_DEPLOYMENT_NAME
         chat_client = AzureAIClient(
             project_endpoint=self.project_endpoint,
             agent_name=self.agent_name,
-            model_deployment_name=deployment_name,
+            model_deployment_name=self.model_deployment_name,
             credential=self.creds,
             use_latest_version=True,
         )
@@ -280,26 +277,20 @@ async def get_database_team_agent(self) -> Optional[AzureAIClient]:
 
             # Create client with resolved ID
             if self.agent_name == "RAIAgent" and self.project_client:
-                # Use RAI deployment name for RAI agents
-                rai_deployment = config.AZURE_OPENAI_RAI_DEPLOYMENT_NAME
                 chat_client = AzureAIClient(
                     project_endpoint=self.project_endpoint,
                     agent_id=resolved,
-                    model_deployment_name=rai_deployment,
                     credential=self.creds,
                 )
                 self.logger.info(
-                    "RAI.AgentReuseSuccess: Created AzureAIClient (id=%s, model=%s)",
+                    "RAI.AgentReuseSuccess: Created AzureAIClient (id=%s)",
                     resolved,
-                    rai_deployment,
                 )
             else:
-                # Use model_deployment_name with fallback to default model if empty
-                deployment_name = self.model_deployment_name or config.AZURE_OPENAI_DEPLOYMENT_NAME
                 chat_client = AzureAIClient(
                     project_endpoint=self.project_endpoint,
                     agent_id=resolved,
-                    model_deployment_name=deployment_name,
+                    model_deployment_name=self.model_deployment_name,
                     credential=self.creds,
                 )
                 self.logger.info(
diff --git a/src/backend/v4/magentic_agents/foundry_agent.py b/src/backend/v4/magentic_agents/foundry_agent.py
index 3a95ea210..84297ebef 100644
--- a/src/backend/v4/magentic_agents/foundry_agent.py
+++ b/src/backend/v4/magentic_agents/foundry_agent.py
@@ -222,13 +222,11 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
             )
 
             # Wrap in AzureAIClient using agent_name and agent_version (NOT agent_id)
-            # Include model_deployment_name to ensure SDK has model info for streaming
-            deployment_name = self.model_deployment_name or config.AZURE_OPENAI_DEPLOYMENT_NAME
+            # AzureAIClient constructor: agent_name, agent_version, project_endpoint, credential
             chat_client = AzureAIClient(
                 project_endpoint=self.project_endpoint,
                 agent_name=azure_agent.name,
                 agent_version=azure_agent.version,  # Use the specific version we just created
-                model_deployment_name=deployment_name,
                 credential=self.creds,
             )
             return chat_client
diff --git a/src/backend/v4/orchestration/orchestration_manager.py b/src/backend/v4/orchestration/orchestration_manager.py
index 12bd70ec8..58fc507e1 100644
--- a/src/backend/v4/orchestration/orchestration_manager.py
+++ b/src/backend/v4/orchestration/orchestration_manager.py
@@ -133,11 +133,9 @@ async def init_orchestration(
 
         try:
             # Create the chat client (AzureAIClient)
-            # Use team deployment_name with fallback to default model if empty
-            deployment_name = team_config.deployment_name or config.AZURE_OPENAI_DEPLOYMENT_NAME
             chat_client = AzureAIClient(
                 project_endpoint=config.AZURE_AI_PROJECT_ENDPOINT,
-                model_deployment_name=deployment_name,
+                model_deployment_name=team_config.deployment_name,
                 agent_name=agent_name,
                 credential=credential,
             )
@@ -152,7 +150,7 @@ async def init_orchestration(
 
             cls.logger.info(
                 "Created AzureAIClient and manager ChatAgent for orchestration with model '%s' at endpoint '%s'",
-                deployment_name,
+                team_config.deployment_name,
                 config.AZURE_AI_PROJECT_ENDPOINT,
             )
         except Exception as e:
@@ -199,17 +197,19 @@ async def init_orchestration(
         # Assemble workflow with callback
         storage = InMemoryCheckpointStorage()
         
-        # New API: .participants() accepts a list of agents
+        # New SDK: participants() accepts a Sequence (list) of agents
+        # The orchestrator uses agent.name to identify them
         participant_list = list(participants.values())
+        cls.logger.info("Participants for workflow: %s", list(participants.keys()))
+        print(f"[DEBUG] Participants for workflow: {list(participants.keys())}", flush=True)
         
         builder = (
             MagenticBuilder()
-            .participants(participant_list)
+            .participants(participant_list)  # New SDK: pass as list
             .with_manager(
                 manager=manager,  # Pass manager instance (extends StandardMagenticManager)
                 max_round_count=orchestration_config.max_rounds,
-                max_stall_count=3,
-                max_reset_count=2,
+                max_stall_count=0,  # CRITICAL: Prevent re-calling agents when stalled (default is 3!)
             )
             .with_checkpointing(storage)
         )
@@ -239,14 +239,16 @@ async def get_current_or_new_orchestration(
         Return an existing workflow for the user or create a new one if:
           - None exists
           - Team switched flag is True
-          - force_rebuild is True (for new tasks that need fresh workflow)
+          - force_rebuild is True (for new tasks after workflow completion)
         """
         current = orchestration_config.get_current_orchestration(user_id)
-        if current is None or team_switched or force_rebuild:
+        needs_rebuild = current is None or team_switched or force_rebuild
+        
+        if needs_rebuild:
             if current is not None and (team_switched or force_rebuild):
-                reason = "team switched" if team_switched else "force rebuild"
+                reason = "team switched" if team_switched else "force rebuild for new task"
                 cls.logger.info(
-                    "Closing previous agents for user '%s' (reason: %s)", user_id, reason
+                    "Rebuilding orchestration for user '%s' (reason: %s)", user_id, reason
                 )
                 # Close prior agents (same logic as old version)
                 for agent in getattr(current, "_participants", {}).values():
@@ -303,11 +305,6 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
         Execute the Magentic workflow for the provided user and task description.
         """
         job_id = str(uuid.uuid4())
-        
-        # Clean up any accumulated state from previous runs (cancelled plans, etc.)
-        # This prevents cross-scenario leakage
-        orchestration_config.cleanup_user_state(user_id)
-        
         orchestration_config.set_approval_pending(job_id)
         self.logger.info(
             "Starting orchestration job '%s' for user '%s'", job_id, user_id
@@ -320,16 +317,6 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
         if workflow is None:
             print(f"[ERROR] Orchestration not initialized for user '{user_id}'")
             raise ValueError("Orchestration not initialized for user.")
-        
-        # Reset manager's plan state to prevent leakage from cancelled plans
-        manager = getattr(workflow, "_manager", None)
-        if manager and hasattr(manager, "magentic_plan"):
-            manager.magentic_plan = None
-            self.logger.debug("Reset manager's magentic_plan for fresh run")
-        if manager and hasattr(manager, "task_ledger"):
-            manager.task_ledger = None
-            self.logger.debug("Reset manager's task_ledger for fresh run")
-        
         # Fresh thread per participant to avoid cross-run state bleed
         executors = getattr(workflow, "executors", {})
         self.logger.debug("Executor keys at run start: %s", list(executors.keys()))
@@ -396,12 +383,16 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
         task_text = getattr(input_task, "description", str(input_task))
         self.logger.debug("Task: %s", task_text)
 
+        # Track how many times each agent is called (for debugging duplicate calls)
+        agent_call_counts: dict = {}
+
         try:
             # Execute workflow using run_stream with task as positional parameter
             # The execution settings are configured in the manager/client
             final_output: str | None = None
 
             self.logger.info("Starting workflow execution...")
+            print(f"[ORCHESTRATOR] 🚀 Starting workflow with max_rounds={orchestration_config.max_rounds}", flush=True)
             last_message_id: str | None = None
             async for event in workflow.run_stream(task_text):
                 try:
@@ -446,11 +437,20 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
 
                     # Handle group chat request sent
                     elif isinstance(event, GroupChatRequestSentEvent):
+                        agent_name = event.participant_name
+                        agent_call_counts[agent_name] = agent_call_counts.get(agent_name, 0) + 1
+                        call_num = agent_call_counts[agent_name]
+                        
                         self.logger.info(
-                            "[REQUEST SENT (round %d)] to agent: %s",
+                            "[REQUEST SENT (round %d)] to agent: %s (call #%d)",
                             event.round_index,
-                            event.participant_name
+                            agent_name,
+                            call_num
                         )
+                        print(f"[ORCHESTRATOR] 📤 REQUEST SENT round={event.round_index} to agent={agent_name} (call #{call_num})", flush=True)
+                        
+                        if call_num > 1:
+                            print(f"[ORCHESTRATOR] ⚠️ WARNING: Agent '{agent_name}' called {call_num} times!", flush=True)
 
                     # Handle group chat response received - THIS IS WHERE AGENT RESPONSES COME
                     elif isinstance(event, GroupChatResponseReceivedEvent):
@@ -511,6 +511,13 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
             # Extract final result
             final_text = final_output if final_output else ""
 
+            # Log agent call summary
+            print(f"\n[ORCHESTRATOR] 📊 AGENT CALL SUMMARY:", flush=True)
+            for agent_name, count in agent_call_counts.items():
+                status = "✅" if count == 1 else "⚠️ DUPLICATE"
+                print(f"  {status} {agent_name}: called {count} time(s)", flush=True)
+            self.logger.info("Agent call counts: %s", agent_call_counts)
+
             # Log results
             self.logger.info("\nAgent responses:")
             self.logger.info(

From 643306f29f676432365bf8cb71218a0fdf037c3b Mon Sep 17 00:00:00 2001
From: Dhruvkumar-Microsoft <v-dbabariya@microsoft.com>
Date: Fri, 13 Feb 2026 17:45:34 +0530
Subject: [PATCH 09/13] updated the logging and resolved the HR scenario issue

---
 src/backend/app.py                                    | 11 +++++++++--
 src/backend/v4/magentic_agents/foundry_agent.py       |  3 +++
 src/backend/v4/orchestration/orchestration_manager.py |  1 +
 3 files changed, 13 insertions(+), 2 deletions(-)

diff --git a/src/backend/app.py b/src/backend/app.py
index 35e4e47af..65381236a 100644
--- a/src/backend/app.py
+++ b/src/backend/app.py
@@ -3,9 +3,14 @@
 
 from contextlib import asynccontextmanager
 
+from common.config.app_config import config
+
+# Configure logging levels FIRST, before any logging calls
+logging.basicConfig(level=getattr(logging, config.AZURE_BASIC_LOGGING_LEVEL.upper(), logging.INFO))
+
 
 from azure.monitor.opentelemetry import configure_azure_monitor
-from common.config.app_config import config
+#from common.config.app_config import config
 from common.models.messages_af import UserLanguage
 
 # FastAPI imports
@@ -61,7 +66,7 @@ async def lifespan(app: FastAPI):
     )
 
 # Configure logging levels from environment variables
-logging.basicConfig(level=getattr(logging, config.AZURE_BASIC_LOGGING_LEVEL.upper(), logging.INFO))
+#logging.basicConfig(level=getattr(logging, config.AZURE_BASIC_LOGGING_LEVEL.upper(), logging.INFO))
 
 # Configure Azure package logging levels
 azure_level = getattr(logging, config.AZURE_PACKAGE_LOGGING_LEVEL.upper(), logging.WARNING)
@@ -73,6 +78,8 @@ async def lifespan(app: FastAPI):
 
 logging.getLogger("opentelemetry.sdk").setLevel(logging.ERROR)
 
+logging.getLogger("azure.core.pipeline.policies.http_logging_policy").setLevel(logging.WARNING)
+
 # Initialize the FastAPI app
 app = FastAPI(lifespan=lifespan)
 
diff --git a/src/backend/v4/magentic_agents/foundry_agent.py b/src/backend/v4/magentic_agents/foundry_agent.py
index 84297ebef..b686a2aeb 100644
--- a/src/backend/v4/magentic_agents/foundry_agent.py
+++ b/src/backend/v4/magentic_agents/foundry_agent.py
@@ -227,6 +227,7 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
                 project_endpoint=self.project_endpoint,
                 agent_name=azure_agent.name,
                 agent_version=azure_agent.version,  # Use the specific version we just created
+                model_deployment_name=self.model_deployment_name,
                 credential=self.creds,
             )
             return chat_client
@@ -282,6 +283,7 @@ async def _after_open(self) -> None:
                     tool_choice="required",  # Force usage
                     temperature=temp,
                     model_id=self.model_deployment_name,
+                    default_options={"store": False},  # Client-managed conversation to avoid stale tool call IDs across rounds
                 )
             else:
                 # use MCP path
@@ -297,6 +299,7 @@ async def _after_open(self) -> None:
                     tool_choice="auto" if tools else "none",
                     temperature=temp,
                     model_id=self.model_deployment_name,
+                    default_options={"store": False},  # Client-managed conversation to avoid stale tool call IDs across rounds
                 )
             self.logger.info("Initialized ChatAgent '%s'", self.agent_name)
 
diff --git a/src/backend/v4/orchestration/orchestration_manager.py b/src/backend/v4/orchestration/orchestration_manager.py
index 58fc507e1..3e89c61ac 100644
--- a/src/backend/v4/orchestration/orchestration_manager.py
+++ b/src/backend/v4/orchestration/orchestration_manager.py
@@ -146,6 +146,7 @@ async def init_orchestration(
                 name="MagenticManager",
                 description="Orchestrator that coordinates the team to complete complex tasks efficiently.",
                 instructions="You coordinate a team to complete complex tasks efficiently.",
+                default_options={"store": False},  # Client-managed conversation to avoid stale tool call IDs across rounds
             )
 
             cls.logger.info(

From 303c8667e21a3e8c37be0131e657c8b24293760c Mon Sep 17 00:00:00 2001
From: Abdul-Microsoft <v-amujeebta@microsoft.com>
Date: Mon, 16 Feb 2026 12:56:23 +0530
Subject: [PATCH 10/13] Refactor FoundryAgentTemplate and MagenticAgentFactory
 to remove debug print statements and streamline logging

---
 .../v4/magentic_agents/foundry_agent.py       | 18 ++--------------
 .../magentic_agents/magentic_agent_factory.py |  1 -
 .../orchestration/human_approval_manager.py   |  4 ----
 .../v4/orchestration/orchestration_manager.py | 21 ++-----------------
 4 files changed, 4 insertions(+), 40 deletions(-)

diff --git a/src/backend/v4/magentic_agents/foundry_agent.py b/src/backend/v4/magentic_agents/foundry_agent.py
index b686a2aeb..f44523fa5 100644
--- a/src/backend/v4/magentic_agents/foundry_agent.py
+++ b/src/backend/v4/magentic_agents/foundry_agent.py
@@ -70,23 +70,18 @@ def __init__(
         self._use_azure_search = self._is_azure_search_requested()
         self.use_reasoning = use_reasoning
 
-        # Placeholder for server-created Azure AI agent id/version (if Azure Search path)
+        # Placeholder for server-created Azure AI agent id (if Azure Search path)
         self._azure_server_agent_id: Optional[str] = None
-        self._azure_server_agent_version: Optional[str] = None
 
     # -------------------------
     # Mode detection
     # -------------------------
     def _is_azure_search_requested(self) -> bool:
         """Determine if Azure AI Search raw tool path should be used."""
-        print(f"[DEBUG _is_azure_search_requested] Agent={self.agent_name}, search={self.search}")
         if not self.search:
-            print(f"[DEBUG _is_azure_search_requested] Agent={self.agent_name}: No search config, returning False")
             return False
         # Minimal heuristic: presence of required attributes
-
         has_index = hasattr(self.search, "index_name") and bool(self.search.index_name)
-        print(f"[DEBUG _is_azure_search_requested] Agent={self.agent_name}: has_index={has_index}, index_name={getattr(self.search, 'index_name', None)}")
         if has_index:
             self.logger.info(
                 "Azure AI Search requested (connection_id=%s, index=%s).",
@@ -137,7 +132,6 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
         Returns:
             AzureAIClient | None
         """
-        print(f"[DEBUG _create_azure_search_enabled_client] Agent={self.agent_name}, chatClient={chatClient}, search_config={self.search}")
         if chatClient:
             self.logger.info("Reusing existing chatClient for agent '%s' (already has Azure Search configured)", self.agent_name)
             return chatClient
@@ -185,9 +179,6 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
                 "Always use the Azure AI Search tool and configured index for knowledge retrieval."
             )
             
-            print(f"[AGENT CREATE] 🆕 Creating agent in Foundry: '{self.agent_name}'", flush=True)
-            print(f"[AGENT CREATE] Model: {self.model_deployment_name}", flush=True)
-            print(f"[AGENT CREATE] Search: connection={connection_name}, index={index_name}", flush=True)
 
             azure_agent = await self.project_client.agents.create_version(
                 agent_name=self.agent_name,  # Use original name
@@ -212,8 +203,7 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
             )
 
             self._azure_server_agent_id = azure_agent.id
-            self._azure_server_agent_version = azure_agent.version
-            print(f"[AGENT CREATE] ✅ Created agent: name={azure_agent.name}, id={azure_agent.id}, version={azure_agent.version}", flush=True)
+
             self.logger.info(
                 "Created Azure AI Search agent via create_version (name=%s, id=%s, version=%s).",
                 azure_agent.name,
@@ -239,8 +229,6 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
                 index_name,
                 ex,
             )
-            import traceback
-            traceback.print_exc()
             return None
 
     # -------------------------
@@ -257,7 +245,6 @@ async def _after_open(self) -> None:
 
         try:
             chatClient = await self.get_database_team_agent()
-            print(f"[DEBUG _after_open] Agent={self.agent_name}, _use_azure_search={self._use_azure_search}, search_config={self.search}, chatClient={chatClient}")
 
             if self._use_azure_search:
                 # Azure Search mode (skip MCP + Code Interpreter due to incompatibility)
@@ -266,7 +253,6 @@ async def _after_open(self) -> None:
                     self.agent_name,
                     getattr(self.search, "index_name", "N/A") if self.search else "N/A"
                 )
-                print(f"[DEBUG _after_open] Creating Azure Search client for {self.agent_name}")
                 chat_client = await self._create_azure_search_enabled_client(chatClient)
                 if not chat_client:
                     raise RuntimeError(
diff --git a/src/backend/v4/magentic_agents/magentic_agent_factory.py b/src/backend/v4/magentic_agents/magentic_agent_factory.py
index 3eafb5831..36544166d 100644
--- a/src/backend/v4/magentic_agents/magentic_agent_factory.py
+++ b/src/backend/v4/magentic_agents/magentic_agent_factory.py
@@ -115,7 +115,6 @@ async def create_agent_from_config(
             index_name,
             "Reasoning" if use_reasoning else "Foundry",
         )
-        print(f"[FACTORY] 🆕 Creating NEW agent: {agent_obj.name} (id={id(agent_obj)})", flush=True)
 
         agent = FoundryAgentTemplate(
             agent_name=agent_obj.name,
diff --git a/src/backend/v4/orchestration/human_approval_manager.py b/src/backend/v4/orchestration/human_approval_manager.py
index 39089247a..00850ec26 100644
--- a/src/backend/v4/orchestration/human_approval_manager.py
+++ b/src/backend/v4/orchestration/human_approval_manager.py
@@ -33,7 +33,6 @@ class HumanApprovalMagenticManager(StandardMagenticManager):
     approval_enabled: bool = True
     magentic_plan: Optional[MPlan] = None
     current_user_id: str  # populated in __init__
-    _called_agents: set  # Track which agents have been called
 
     def __init__(self, user_id: str, agent, *args, **kwargs):
         """
@@ -44,9 +43,6 @@ def __init__(self, user_id: str, agent, *args, **kwargs):
             *args: Additional positional arguments for the parent StandardMagenticManager.
             **kwargs: Additional keyword arguments for the parent StandardMagenticManager.
         """
-        
-        # Initialize called agents tracker
-        self._called_agents = set()
 
         plan_append = """
 
diff --git a/src/backend/v4/orchestration/orchestration_manager.py b/src/backend/v4/orchestration/orchestration_manager.py
index 3e89c61ac..fa5801ae5 100644
--- a/src/backend/v4/orchestration/orchestration_manager.py
+++ b/src/backend/v4/orchestration/orchestration_manager.py
@@ -202,7 +202,6 @@ async def init_orchestration(
         # The orchestrator uses agent.name to identify them
         participant_list = list(participants.values())
         cls.logger.info("Participants for workflow: %s", list(participants.keys()))
-        print(f"[DEBUG] Participants for workflow: {list(participants.keys())}", flush=True)
         
         builder = (
             MagenticBuilder()
@@ -277,24 +276,17 @@ async def get_current_or_new_orchestration(
                 cls.logger.error(
                     "Failed to create agents for user '%s': %s", user_id, e
                 )
-                print(f"Failed to create agents for user '{user_id}': {e}")
                 raise
             try:
                 cls.logger.info("Initializing new orchestration for user '%s'", user_id)
-                print(f"[DEBUG] Initializing new orchestration for user '{user_id}'")
                 workflow = await cls.init_orchestration(
                     agents, team_config, team_service.memory_context, user_id
                 )
                 orchestration_config.orchestrations[user_id] = workflow
-                print(f"[DEBUG] Stored workflow for user '{user_id}': {workflow is not None}")
-                print(f"[DEBUG] orchestrations keys: {list(orchestration_config.orchestrations.keys())}")
             except Exception as e:
                 cls.logger.error(
                     "Failed to initialize orchestration for user '%s': %s", user_id, e
                 )
-                print(f"Failed to initialize orchestration for user '{user_id}': {e}")
-                import traceback
-                traceback.print_exc()
                 raise
         return orchestration_config.get_current_orchestration(user_id)
 
@@ -310,13 +302,9 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
         self.logger.info(
             "Starting orchestration job '%s' for user '%s'", job_id, user_id
         )
-        print(f"[DEBUG] run_orchestration called for user '{user_id}'")
-        print(f"[DEBUG] orchestrations keys before get: {list(orchestration_config.orchestrations.keys())}")
 
         workflow = orchestration_config.get_current_orchestration(user_id)
-        print(f"[DEBUG] workflow is None: {workflow is None}")
         if workflow is None:
-            print(f"[ERROR] Orchestration not initialized for user '{user_id}'")
             raise ValueError("Orchestration not initialized for user.")
         # Fresh thread per participant to avoid cross-run state bleed
         executors = getattr(workflow, "executors", {})
@@ -393,7 +381,7 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
             final_output: str | None = None
 
             self.logger.info("Starting workflow execution...")
-            print(f"[ORCHESTRATOR] 🚀 Starting workflow with max_rounds={orchestration_config.max_rounds}", flush=True)
+
             last_message_id: str | None = None
             async for event in workflow.run_stream(task_text):
                 try:
@@ -448,10 +436,9 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
                             agent_name,
                             call_num
                         )
-                        print(f"[ORCHESTRATOR] 📤 REQUEST SENT round={event.round_index} to agent={agent_name} (call #{call_num})", flush=True)
                         
                         if call_num > 1:
-                            print(f"[ORCHESTRATOR] ⚠️ WARNING: Agent '{agent_name}' called {call_num} times!", flush=True)
+                            self.logger.warning("Agent '%s' called %d times", agent_name, call_num)
 
                     # Handle group chat response received - THIS IS WHERE AGENT RESPONSES COME
                     elif isinstance(event, GroupChatResponseReceivedEvent):
@@ -513,10 +500,6 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
             final_text = final_output if final_output else ""
 
             # Log agent call summary
-            print(f"\n[ORCHESTRATOR] 📊 AGENT CALL SUMMARY:", flush=True)
-            for agent_name, count in agent_call_counts.items():
-                status = "✅" if count == 1 else "⚠️ DUPLICATE"
-                print(f"  {status} {agent_name}: called {count} time(s)", flush=True)
             self.logger.info("Agent call counts: %s", agent_call_counts)
 
             # Log results

From bb5331e84b64e32e1f7590fa7bce57822cdb0a42 Mon Sep 17 00:00:00 2001
From: Abdul-Microsoft <v-amujeebta@microsoft.com>
Date: Fri, 20 Feb 2026 09:45:45 +0530
Subject: [PATCH 11/13] Refactor agent creation and configuration to avoid
 mutating original team objects and streamline AzureAIClient initialization

---
 src/backend/common/utils/utils_af.py          |  14 +-
 src/backend/common/utils/utils_agents.py      |  24 ---
 src/backend/v4/callbacks/response_handlers.py |   6 +-
 .../v4/magentic_agents/common/lifecycle.py    | 178 +-----------------
 .../v4/magentic_agents/foundry_agent.py       |  25 +--
 5 files changed, 28 insertions(+), 219 deletions(-)

diff --git a/src/backend/common/utils/utils_af.py b/src/backend/common/utils/utils_af.py
index 2d1dd794e..a22212144 100644
--- a/src/backend/common/utils/utils_af.py
+++ b/src/backend/common/utils/utils_af.py
@@ -88,9 +88,15 @@ async def create_RAI_agent(
     )
 
     model_deployment_name = config.AZURE_OPENAI_RAI_DEPLOYMENT_NAME
-    team.team_id = "rai_team"  # Use a fixed team ID for RAI agent
-    team.name = "RAI Team"
-    team.description = "Team responsible for Responsible AI checks"
+
+    # Create a copy to avoid mutating the caller's team config.
+    # The original team object is reused later (e.g., for orchestration init),
+    # so mutating it would corrupt the real team name/id.
+    rai_team = team.model_copy()
+    rai_team.team_id = "rai_team"
+    rai_team.name = "RAI Team"
+    rai_team.description = "Team responsible for Responsible AI checks"
+
     agent = FoundryAgentTemplate(
         agent_name=agent_name,
         agent_description=agent_description,
@@ -101,7 +107,7 @@ async def create_RAI_agent(
         project_endpoint=config.AZURE_AI_PROJECT_ENDPOINT,
         mcp_config=None,
         search_config=None,
-        team_config=team,
+        team_config=rai_team,
         memory_store=memory_store,
     )
 
diff --git a/src/backend/common/utils/utils_agents.py b/src/backend/common/utils/utils_agents.py
index 1e164f89c..c679f9f62 100644
--- a/src/backend/common/utils/utils_agents.py
+++ b/src/backend/common/utils/utils_agents.py
@@ -1,11 +1,6 @@
 
-import logging
 import secrets
 import string
-from typing import Optional
-
-from common.database.database_base import DatabaseBase
-from common.models.messages_af import TeamConfiguration
 
 
 def generate_assistant_id(prefix: str = "asst_", length: int = 24) -> str:
@@ -21,22 +16,3 @@ def generate_assistant_id(prefix: str = "asst_", length: int = 24) -> str:
     # cryptographically strong randomness
     random_part = "".join(secrets.choice(alphabet) for _ in range(length))
     return f"{prefix}{random_part}"
-
-
-async def get_database_team_agent_id(
-    memory_store: DatabaseBase, team_config: TeamConfiguration, agent_name: str
-) -> Optional[str]:
-    """Retrieve existing team agent from database, if any."""
-    agent_id = None
-    try:
-        currentAgent = await memory_store.get_team_agent(
-            team_id=team_config.team_id, agent_name=agent_name
-        )
-        if currentAgent and currentAgent.agent_foundry_id:
-            agent_id = currentAgent.agent_foundry_id
-
-    except (
-        Exception
-    ) as ex:  # Consider narrowing this to specific exceptions if possible
-        logging.error("Failed to initialize Get database team agent: %s", ex)
-    return agent_id
diff --git a/src/backend/v4/callbacks/response_handlers.py b/src/backend/v4/callbacks/response_handlers.py
index 88c6085f5..f034e4168 100644
--- a/src/backend/v4/callbacks/response_handlers.py
+++ b/src/backend/v4/callbacks/response_handlers.py
@@ -8,7 +8,7 @@
 import re
 from typing import Any
 
-from agent_framework import ChatMessage, AgentRunUpdateEvent
+from agent_framework import ChatMessage
 
 from v4.config.settings import connection_config
 from v4.models.messages import (
@@ -108,7 +108,7 @@ def agent_response_callback(
 
 async def streaming_agent_response_callback(
     agent_id: str,
-    update,  # AgentRunUpdateEvent.data or similar streaming update object
+    update,  # Streaming update object (e.g. AgentResponseUpdate, ChatMessage)
     is_final: bool,
     user_id: str | None = None,
 ) -> None:
@@ -119,7 +119,7 @@ async def streaming_agent_response_callback(
         return
 
     try:
-        # Handle both AgentRunUpdateEvent.data and raw text updates
+        # Handle various streaming update object shapes
         chunk_text = getattr(update, "text", None)
         
         # If text is None, don't fall back to str(update) as that would show object repr
diff --git a/src/backend/v4/magentic_agents/common/lifecycle.py b/src/backend/v4/magentic_agents/common/lifecycle.py
index af9dcb846..c9093c318 100644
--- a/src/backend/v4/magentic_agents/common/lifecycle.py
+++ b/src/backend/v4/magentic_agents/common/lifecycle.py
@@ -15,10 +15,9 @@
 from azure.ai.agents.aio import AgentsClient
 from azure.identity.aio import DefaultAzureCredential
 from common.database.database_base import DatabaseBase
-from common.models.messages_af import CurrentTeamAgent, TeamConfiguration
+from common.models.messages_af import TeamConfiguration
 from common.utils.utils_agents import (
     generate_assistant_id,
-    get_database_team_agent_id,
 )
 from v4.common.services.team_service import TeamService
 from v4.config.agent_registry import agent_registry
@@ -148,13 +147,12 @@ async def _after_open(self) -> None:
         """Subclasses must build self._agent here."""
         raise NotImplementedError
 
-    def get_chat_client(self, chat_client) -> AzureAIClient:
+    def get_chat_client(self) -> AzureAIClient:
         """Return the underlying ChatClientProtocol (AzureAIClient).
         
-        Uses agent_name with use_latest_version=True to get the latest agent version
+        Uses agent_name with use_latest_version=True to get the latest agent version.
+        Agent reuse is handled automatically by the SDK via agent_name.
         """
-        if chat_client:
-            return chat_client
         if (
             self._agent
             and self._agent.chat_client
@@ -173,176 +171,16 @@ def get_chat_client(self, chat_client) -> AzureAIClient:
         )
         return chat_client
 
-    async def resolve_agent_id(self, agent_id: str) -> Optional[str]:
-        """Resolve agent ID via Projects SDK first (for RAI agents), fallback to AgentsClient.
-
-        Args:
-            agent_id: The agent ID to resolve
-
-        Returns:
-            The resolved agent ID if found, None otherwise
-        """
-        # Try Projects SDK first (RAI agents were created via project_client)
-        try:
-            if self.project_client:
-                agent = await self.project_client.agents.get_agent(agent_id)
-                if agent and agent.id:
-                    self.logger.info(
-                        "RAI.AgentReuseSuccess: Resolved agent via Projects SDK (id=%s)",
-                        agent.id,
-                    )
-                    return agent.id
-        except Exception as ex:
-            self.logger.warning(
-                "RAI.AgentReuseMiss: Projects SDK get_agent failed (reason=ProjectsGetFailed, id=%s): %s",
-                agent_id,
-                ex,
-            )
-
-        # Fallback via AgentsClient (endpoint)
-        try:
-            if self.client:
-                agent = await self.client.get_agent(agent_id=agent_id)
-                if agent and agent.id:
-                    self.logger.info(
-                        "RAI.AgentReuseSuccess: Resolved agent via AgentsClient (id=%s)",
-                        agent.id,
-                    )
-                    return agent.id
-        except Exception as ex:
-            self.logger.warning(
-                "RAI.AgentReuseMiss: AgentsClient get_agent failed (reason=EndpointGetFailed, id=%s): %s",
-                agent_id,
-                ex,
-            )
-
-        self.logger.error(
-            "RAI.AgentReuseMiss: Agent ID not resolvable via any client (reason=ClientMismatch, id=%s)",
-            agent_id,
-        )
-        return None
-
-    def get_agent_id(self, chat_client) -> str:
-        """Return the underlying agent ID or generate a new one.
+    def get_agent_id(self) -> str:
+        """Generate a local agent ID for the ChatAgent wrapper.
         
-        Note: The new AzureAIClient doesn't expose agent_id directly.
-        We generate a new ID if not available.
+        The new AzureAIClient identifies agents by name (not ID) on the server side.
+        This ID is only used locally for the ChatAgent wrapper instance.
         """
-        # Generate a new agent ID since AzureAIClient doesn't expose agent_id
         id = generate_assistant_id()
         self.logger.info("Generated new agent ID: %s", id)
         return id
 
-    async def get_database_team_agent(self) -> Optional[AzureAIClient]:
-        """Retrieve existing team agent from database, if any.
-        
-        NOTE: Agent reuse is currently DISABLED to ensure fresh agents are created
-        with the correct Azure AI Search configuration.
-        This prevents issues with stale agents that may not have the search tool configured.
-        
-        To re-enable agent reuse, set ENABLE_AGENT_REUSE=true in environment.
-        """
-        import os
-        
-        # DISABLED: Always create fresh agents to ensure Azure AI Search tool is configured
-        enable_reuse = os.environ.get("ENABLE_AGENT_REUSE", "false").lower() == "true"
-        if not enable_reuse:
-            self.logger.info(
-                "Agent reuse DISABLED: Creating fresh agent with search tools (agent_name=%s)",
-                self.agent_name,
-            )
-            return None
-        
-        chat_client = None
-        try:
-            agent_id = await get_database_team_agent_id(
-                self.memory_store, self.team_config, self.agent_name
-            )
-
-            if not agent_id:
-                self.logger.info(
-                    "RAI reuse: no stored agent id (agent_name=%s)", self.agent_name
-                )
-                return None
-
-            # Use resolve_agent_id to try Projects SDK first, then AgentsClient
-            resolved = await self.resolve_agent_id(agent_id)
-            if not resolved:
-                self.logger.error(
-                    "RAI.AgentReuseMiss: stored id %s not resolvable (agent_name=%s)",
-                    agent_id,
-                    self.agent_name,
-                )
-                return None
-
-            # Create client with resolved ID
-            if self.agent_name == "RAIAgent" and self.project_client:
-                chat_client = AzureAIClient(
-                    project_endpoint=self.project_endpoint,
-                    agent_id=resolved,
-                    credential=self.creds,
-                )
-                self.logger.info(
-                    "RAI.AgentReuseSuccess: Created AzureAIClient (id=%s)",
-                    resolved,
-                )
-            else:
-                chat_client = AzureAIClient(
-                    project_endpoint=self.project_endpoint,
-                    agent_id=resolved,
-                    model_deployment_name=self.model_deployment_name,
-                    credential=self.creds,
-                )
-                self.logger.info(
-                    "Created AzureAIClient via endpoint (id=%s)", resolved
-                )
-
-        except Exception as ex:
-            self.logger.error(
-                "Failed to initialize Get database team agent (agent_name=%s): %s",
-                self.agent_name,
-                ex,
-            )
-        return chat_client
-
-    async def save_database_team_agent(self) -> None:
-        """Save current team agent to database (only if truly new or changed)."""
-        try:
-            if self._agent is None or self._agent.id is None:
-                self.logger.error("Cannot save database team agent: agent or agent_id is None")
-                return
-
-            # Use the agent ID from ChatAgent (set during creation)
-            agent_id = self._agent.id
-
-            # Check if stored ID matches current ID
-            stored_id = await get_database_team_agent_id(
-                self.memory_store, self.team_config, self.agent_name
-            )
-            if stored_id == agent_id:
-                self.logger.info(
-                    "RAI reuse: id unchanged (id=%s); skip save.", agent_id
-                )
-                return
-
-            currentAgent = CurrentTeamAgent(
-                team_id=self.team_config.team_id,
-                team_name=self.team_config.name,
-                agent_name=self.agent_name,
-                agent_foundry_id=agent_id,
-                agent_description=self.agent_description,
-                agent_instructions=self.agent_instructions,
-            )
-            await self.memory_store.add_team_agent(currentAgent)
-            self.logger.info(
-                "Saved team agent to database (agent_name=%s, id=%s)",
-                self.agent_name,
-                agent_id,
-            )
-
-        except Exception as ex:
-            self.logger.error("Failed to save database: %s", ex)
-
     async def _prepare_mcp_tool(self) -> None:
         """Translate MCPConfig to a HostedMCPTool (agent_framework construct)."""
         if not self.mcp_cfg:
diff --git a/src/backend/v4/magentic_agents/foundry_agent.py b/src/backend/v4/magentic_agents/foundry_agent.py
index f44523fa5..6d3974010 100644
--- a/src/backend/v4/magentic_agents/foundry_agent.py
+++ b/src/backend/v4/magentic_agents/foundry_agent.py
@@ -115,7 +115,7 @@ async def _collect_tools(self) -> List:
     # -------------------------
     # Azure Search helper
     # -------------------------
-    async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional[AzureAIClient]:
+    async def _create_azure_search_enabled_client(self) -> Optional[AzureAIClient]:
         """
         Create a server-side Azure AI agent with Azure AI Search tool using create_version.
 
@@ -132,10 +132,6 @@ async def _create_azure_search_enabled_client(self, chatClient=None) -> Optional
         Returns:
             AzureAIClient | None
         """
-        if chatClient:
-            self.logger.info("Reusing existing chatClient for agent '%s' (already has Azure Search configured)", self.agent_name)
-            return chatClient
-
         if not self.search:
             self.logger.error("Search configuration missing.")
             return None
@@ -244,8 +240,6 @@ async def _after_open(self) -> None:
             temp = 0.1
 
         try:
-            chatClient = await self.get_database_team_agent()
-
             if self._use_azure_search:
                 # Azure Search mode (skip MCP + Code Interpreter due to incompatibility)
                 self.logger.info(
@@ -253,7 +247,7 @@ async def _after_open(self) -> None:
                     self.agent_name,
                     getattr(self.search, "index_name", "N/A") if self.search else "N/A"
                 )
-                chat_client = await self._create_azure_search_enabled_client(chatClient)
+                chat_client = await self._create_azure_search_enabled_client()
                 if not chat_client:
                     raise RuntimeError(
                         "Azure AI Search mode requested but setup failed."
@@ -261,8 +255,8 @@ async def _after_open(self) -> None:
 
                 # In Azure Search raw tool path, tools/tool_choice are handled server-side.
                 self._agent = ChatAgent(
-                    id=self.get_agent_id(chat_client),
-                    chat_client=self.get_chat_client(chat_client),
+                    id=self.get_agent_id(),
+                    chat_client=chat_client,
                     instructions=self.agent_instructions,
                     name=self.agent_name,
                     description=self.agent_description,
@@ -272,12 +266,12 @@ async def _after_open(self) -> None:
                     default_options={"store": False},  # Client-managed conversation to avoid stale tool call IDs across rounds
                 )
             else:
-                # use MCP path
+                # MCP path (also used by RAI agent which has no tools)
                 self.logger.info("Initializing agent in MCP mode.")
                 tools = await self._collect_tools()
                 self._agent = ChatAgent(
-                    id=self.get_agent_id(chatClient),
-                    chat_client=self.get_chat_client(chatClient),
+                    id=self.get_agent_id(),
+                    chat_client=self.get_chat_client(),
                     instructions=self.agent_instructions,
                     name=self.agent_name,
                     description=self.agent_description,
@@ -314,12 +308,7 @@ async def invoke(self, prompt: str):
 
         messages = [ChatMessage(role=Role.USER, text=prompt)]
 
-        agent_saved = False
         async for update in self._agent.run_stream(messages):
-            # Save agent ID only once on first update
-            if not agent_saved:
-                await self.save_database_team_agent()
-                agent_saved = True
             yield update
 
     # -------------------------

From 60c894e9bca957647d6d760fd6918c30a164d2bd Mon Sep 17 00:00:00 2001
From: Abdul-Microsoft <v-amujeebta@microsoft.com>
Date: Fri, 20 Feb 2026 19:59:24 +0530
Subject: [PATCH 12/13] Remove description and instructions from
 MagenticManager ChatAgent initialization

---
 src/backend/v4/orchestration/orchestration_manager.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/src/backend/v4/orchestration/orchestration_manager.py b/src/backend/v4/orchestration/orchestration_manager.py
index fa5801ae5..6d6811850 100644
--- a/src/backend/v4/orchestration/orchestration_manager.py
+++ b/src/backend/v4/orchestration/orchestration_manager.py
@@ -144,8 +144,6 @@ async def init_orchestration(
             manager_agent = ChatAgent(
                 chat_client=chat_client,
                 name="MagenticManager",
-                description="Orchestrator that coordinates the team to complete complex tasks efficiently.",
-                instructions="You coordinate a team to complete complex tasks efficiently.",
                 default_options={"store": False},  # Client-managed conversation to avoid stale tool call IDs across rounds
             )
 

From 6a0462bb898395c7374f4933c95b60208788913a Mon Sep 17 00:00:00 2001
From: Abdul-Microsoft <v-amujeebta@microsoft.com>
Date: Fri, 27 Feb 2026 11:54:44 +0530
Subject: [PATCH 13/13] resolved pylint issues

---
 src/backend/app.py                            |  4 +--
 src/backend/v4/callbacks/response_handlers.py |  2 +-
 .../v4/magentic_agents/common/lifecycle.py    |  4 +--
 .../v4/magentic_agents/foundry_agent.py       |  1 -
 .../orchestration/human_approval_manager.py   |  4 +--
 .../v4/orchestration/orchestration_manager.py | 30 +++++++++----------
 6 files changed, 22 insertions(+), 23 deletions(-)

diff --git a/src/backend/app.py b/src/backend/app.py
index 65381236a..2cf7d6a6b 100644
--- a/src/backend/app.py
+++ b/src/backend/app.py
@@ -10,7 +10,7 @@
 
 
 from azure.monitor.opentelemetry import configure_azure_monitor
-#from common.config.app_config import config
+# from common.config.app_config import config
 from common.models.messages_af import UserLanguage
 
 # FastAPI imports
@@ -66,7 +66,7 @@ async def lifespan(app: FastAPI):
     )
 
 # Configure logging levels from environment variables
-#logging.basicConfig(level=getattr(logging, config.AZURE_BASIC_LOGGING_LEVEL.upper(), logging.INFO))
+# logging.basicConfig(level=getattr(logging, config.AZURE_BASIC_LOGGING_LEVEL.upper(), logging.INFO))
 
 # Configure Azure package logging levels
 azure_level = getattr(logging, config.AZURE_PACKAGE_LOGGING_LEVEL.upper(), logging.WARNING)
diff --git a/src/backend/v4/callbacks/response_handlers.py b/src/backend/v4/callbacks/response_handlers.py
index f034e4168..0a817ef94 100644
--- a/src/backend/v4/callbacks/response_handlers.py
+++ b/src/backend/v4/callbacks/response_handlers.py
@@ -121,7 +121,7 @@ async def streaming_agent_response_callback(
     try:
         # Handle various streaming update object shapes
         chunk_text = getattr(update, "text", None)
-        
+
         # If text is None, don't fall back to str(update) as that would show object repr
         # Just skip if there's no actual text content
         if chunk_text is None:
diff --git a/src/backend/v4/magentic_agents/common/lifecycle.py b/src/backend/v4/magentic_agents/common/lifecycle.py
index c9093c318..b38e31eed 100644
--- a/src/backend/v4/magentic_agents/common/lifecycle.py
+++ b/src/backend/v4/magentic_agents/common/lifecycle.py
@@ -149,7 +149,7 @@ async def _after_open(self) -> None:
 
     def get_chat_client(self) -> AzureAIClient:
         """Return the underlying ChatClientProtocol (AzureAIClient).
-        
+
         Uses agent_name with use_latest_version=True to get the latest agent version.
         Agent reuse is handled automatically by the SDK via agent_name.
         """
@@ -173,7 +173,7 @@ def get_chat_client(self) -> AzureAIClient:
 
     def get_agent_id(self) -> str:
         """Generate a local agent ID for the ChatAgent wrapper.
-        
+
         The new AzureAIClient identifies agents by name (not ID) on the server side.
         This ID is only used locally for the ChatAgent wrapper instance.
         """
diff --git a/src/backend/v4/magentic_agents/foundry_agent.py b/src/backend/v4/magentic_agents/foundry_agent.py
index 6d3974010..38fd0cc6b 100644
--- a/src/backend/v4/magentic_agents/foundry_agent.py
+++ b/src/backend/v4/magentic_agents/foundry_agent.py
@@ -174,7 +174,6 @@ async def _create_azure_search_enabled_client(self) -> Optional[AzureAIClient]:
                 f"{self.agent_instructions} "
                 "Always use the Azure AI Search tool and configured index for knowledge retrieval."
             )
-            
 
             azure_agent = await self.project_client.agents.create_version(
                 agent_name=self.agent_name,  # Use original name
diff --git a/src/backend/v4/orchestration/human_approval_manager.py b/src/backend/v4/orchestration/human_approval_manager.py
index 00850ec26..7f33c9ac4 100644
--- a/src/backend/v4/orchestration/human_approval_manager.py
+++ b/src/backend/v4/orchestration/human_approval_manager.py
@@ -85,7 +85,7 @@ def __init__(self, user_id: str, agent, *args, **kwargs):
             ORCHESTRATOR_TASK_LEDGER_PLAN_UPDATE_PROMPT + plan_append
         )
         kwargs["final_answer_prompt"] = ORCHESTRATOR_FINAL_ANSWER_PROMPT + final_append
-        
+
         # Override progress ledger prompt to discourage re-calling agents
         from agent_framework._workflows._magentic import ORCHESTRATOR_PROGRESS_LEDGER_PROMPT
         kwargs["progress_ledger_prompt"] = ORCHESTRATOR_PROGRESS_LEDGER_PROMPT + progress_append
@@ -319,4 +319,4 @@ def plan_to_obj(self, magentic_context: MagenticContext, ledger) -> MPlan:
             task=task_text,
         )
 
-        return return_plan
\ No newline at end of file
+        return return_plan
diff --git a/src/backend/v4/orchestration/orchestration_manager.py b/src/backend/v4/orchestration/orchestration_manager.py
index 6d6811850..d38748d83 100644
--- a/src/backend/v4/orchestration/orchestration_manager.py
+++ b/src/backend/v4/orchestration/orchestration_manager.py
@@ -50,7 +50,7 @@ def __init__(self):
     def _extract_response_text(self, data) -> str:
         """
         Extract text content from various agent_framework response types.
-        
+
         Handles:
         - ChatMessage: Extract .text
         - AgentResponse: Extract .text
@@ -59,15 +59,15 @@ def _extract_response_text(self, data) -> str:
         """
         if data is None:
             return ""
-        
+
         # Direct ChatMessage
         if isinstance(data, ChatMessage):
             return data.text or ""
-        
+
         # Has .text attribute directly (AgentResponse, etc.)
         if hasattr(data, "text") and data.text:
             return data.text
-        
+
         # AgentExecutorResponse - has agent_response and full_conversation
         if hasattr(data, "agent_response"):
             # Try to get text from agent_response first
@@ -79,7 +79,7 @@ def _extract_response_text(self, data) -> str:
                 last_msg = data.full_conversation[-1]
                 if isinstance(last_msg, ChatMessage) and last_msg.text:
                     return last_msg.text
-        
+
         # List of items - could be AgentExecutorResponse, ChatMessage, etc.
         if isinstance(data, list) and len(data) > 0:
             texts = []
@@ -91,7 +91,7 @@ def _extract_response_text(self, data) -> str:
             if texts:
                 # Return the last non-empty response (most recent)
                 return texts[-1]
-        
+
         return ""
 
     # ---------------------------
@@ -195,12 +195,12 @@ async def init_orchestration(
 
         # Assemble workflow with callback
         storage = InMemoryCheckpointStorage()
-        
+
         # New SDK: participants() accepts a Sequence (list) of agents
         # The orchestrator uses agent.name to identify them
         participant_list = list(participants.values())
         cls.logger.info("Participants for workflow: %s", list(participants.keys()))
-        
+
         builder = (
             MagenticBuilder()
             .participants(participant_list)  # New SDK: pass as list
@@ -241,7 +241,7 @@ async def get_current_or_new_orchestration(
         """
         current = orchestration_config.get_current_orchestration(user_id)
         needs_rebuild = current is None or team_switched or force_rebuild
-        
+
         if needs_rebuild:
             if current is not None and (team_switched or force_rebuild):
                 reason = "team switched" if team_switched else "force rebuild for new task"
@@ -387,7 +387,7 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
                     event_type_name = type(event).__name__
                     if event_type_name != "AgentRunUpdateEvent":
                         self.logger.info("[EVENT] %s", event_type_name)
-                    
+
                     # Handle orchestrator events (plan, progress ledger)
                     if isinstance(event, MagenticOrchestratorEvent):
                         self.logger.info(
@@ -403,7 +403,7 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
                     elif isinstance(event, AgentRunUpdateEvent):
                         message_id = event.data.message_id if hasattr(event.data, 'message_id') else None
                         executor_id = event.executor_id
-                        
+
                         # Stream the update
                         try:
                             await streaming_agent_response_callback(
@@ -417,7 +417,7 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
                                 "Error in streaming callback for agent %s: %s",
                                 executor_id, e
                             )
-                        
+
                         # Track message for formatting
                         if message_id != last_message_id:
                             last_message_id = message_id
@@ -427,14 +427,14 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
                         agent_name = event.participant_name
                         agent_call_counts[agent_name] = agent_call_counts.get(agent_name, 0) + 1
                         call_num = agent_call_counts[agent_name]
-                        
+
                         self.logger.info(
                             "[REQUEST SENT (round %d)] to agent: %s (call #%d)",
                             event.round_index,
                             agent_name,
                             call_num
                         )
-                        
+
                         if call_num > 1:
                             self.logger.warning("Agent '%s' called %d times", agent_name, call_num)
 
@@ -448,7 +448,7 @@ async def run_orchestration(self, user_id: str, input_task) -> None:
                         # Send the agent response to the UI
                         if event.data:
                             response_text = self._extract_response_text(event.data)
-                            
+
                             if response_text:
                                 self.logger.info("Sending agent response to UI from %s", event.participant_name)
                                 agent_response_callback(