Fix: align crew ai sample with A365 Observability SDK breaking changes

python/crewai/sample_agent/agent.py

@@ -56,7 +56,7 @@
     create_agent_details,
     create_invoke_agent_details,
     create_caller_details,
-    create_tenant_details,
+    create_user_details,
     create_request,
     build_baggage_builder,
 )
@@ -66,7 +66,8 @@
 # These are used by MCP tool wrappers to access the current request's context
 # without risk of concurrent request interference
 _current_agent_details: contextvars.ContextVar = contextvars.ContextVar('agent_details', default=None)
-_current_tenant_details: contextvars.ContextVar = contextvars.ContextVar('tenant_details', default=None)
+_current_user_details: contextvars.ContextVar = contextvars.ContextVar('user_details', default=None)
+_current_conversation_id: contextvars.ContextVar = contextvars.ContextVar('conversation_id', default=None)
 
 
 class CrewAIAgent(AgentInterface):
@@ -140,7 +141,8 @@ def _create_observable_tools(self) -> list:
             mcp_tools=self.mcp_tools,
             tool_executor=self.mcp_tool_executor,
             get_agent_details=lambda: _current_agent_details.get(),
-            get_tenant_details=lambda: _current_tenant_details.get(),
+            get_user_details=lambda: _current_user_details.get(),
+            get_conversation_id=lambda: _current_conversation_id.get(),
         )
 
     # =========================================================================
@@ -171,18 +173,18 @@ async def process_user_message(
         try:
             logger.info(f"Processing message: {message[:100]}...")
 
-            with build_baggage_builder(context, ctx_details.correlation_id).build():
+            with build_baggage_builder(context, ctx_details.conversation_id).build():
                 # Create observability details
                 agent_details = create_agent_details(ctx_details, "AI agent powered by CrewAI framework")
                 caller_details = create_caller_details(ctx_details)
-                tenant_details = create_tenant_details(ctx_details)
+                user_details = create_user_details(ctx_details)
                 request = create_request(ctx_details, message)
-                invoke_details = create_invoke_agent_details(ctx_details, "AI agent powered by CrewAI framework")
+                invoke_details = create_invoke_agent_details()
 
                 with InvokeAgentScope.start(
-                    invoke_agent_details=invoke_details,
-                    tenant_details=tenant_details,
                     request=request,
+                    scope_details=invoke_details,
+                    agent_details=agent_details,
                     caller_details=caller_details,
                 ) as invoke_scope:
                     if hasattr(invoke_scope, 'record_input_messages'):
@@ -194,7 +196,8 @@ async def process_user_message(
                     # Store context for observable MCP tool wrappers using context variables
                     # This is thread/async-safe for concurrent request handling
                     agent_details_token = _current_agent_details.set(agent_details)
-                    tenant_details_token = _current_tenant_details.set(tenant_details)
+                    user_details_token = _current_user_details.set(user_details)
+                    conversation_id_token = _current_conversation_id.set(ctx_details.conversation_id)
 
                     try:
                         # Create observable MCP tool wrappers
@@ -206,15 +209,16 @@ async def process_user_message(
 
                         # Run CrewAI with InferenceScope
                         full_response = await self._run_crew_with_inference_scope(
-                            message, observable_mcp_tools, agent_details, tenant_details, request, display_name
+                            message, observable_mcp_tools, agent_details, user_details, request, display_name
                         )
 
                         if hasattr(invoke_scope, 'record_output_messages'):
                             invoke_scope.record_output_messages([full_response])
                     finally:
                         # Reset context variables to previous values
                         _current_agent_details.reset(agent_details_token)
-                        _current_tenant_details.reset(tenant_details_token)
+                        _current_user_details.reset(user_details_token)
+                        _current_conversation_id.reset(conversation_id_token)
 
                 logger.info("✅ Observability scopes closed successfully")
                 return full_response
@@ -225,7 +229,7 @@ async def process_user_message(
             return f"Sorry, I encountered an error: {str(e)}"
 
     async def _run_crew_with_inference_scope(
-        self, message: str, observable_mcp_tools: list, agent_details, tenant_details, request, user_name: str = "unknown"
+        self, message: str, observable_mcp_tools: list, agent_details, user_details, request, user_name: str = "unknown"
     ) -> str:
         """Run CrewAI with InferenceScope for LLM call tracking."""
         inference_details = InferenceCallDetails(
@@ -235,10 +239,10 @@ async def _run_crew_with_inference_scope(
         )
 
         with InferenceScope.start(
+            request=request,
             details=inference_details,
             agent_details=agent_details,
-            tenant_details=tenant_details,
-            request=request,
+            user_details=user_details,
         ) as inference_scope:
             from crew_agent.agent_runner import run_crew
 

python/crewai/sample_agent/docs/design.md

@@ -101,15 +101,33 @@ class CrewAIAgent(AgentInterface):
 ```bash
 # LLM Configuration (used by CrewAI)
 OPENAI_API_KEY=sk-...
+AZURE_API_KEY=...
+AZURE_API_BASE=https://your-resource.openai.azure.com/
+AZURE_API_VERSION=2025-01-01-preview
+AZURE_OPENAI_DEPLOYMENT=azure/gpt-4.1
+OPENAI_MODEL_NAME=azure/gpt-4.1
 
 # Authentication
 BEARER_TOKEN=...
+USE_AGENTIC_AUTH=false
 AUTH_HANDLER_NAME=AGENTIC
-CLIENT_ID=...
-TENANT_ID=...
+AGENTIC_AUTH_SCOPE=https://api.powerplatform.com/.default
+AGENT_ID=...
+AGENTIC_APP_ID=crewai-agent
+
+# Weather Search
+TAVILY_API_KEY=tvly-...
 
 # Observability
-OBSERVABILITY_SERVICE_NAME=crewai-sample-agent
+OBSERVABILITY_SERVICE_NAME=crewai-agent-sample
+OBSERVABILITY_SERVICE_NAMESPACE=agent365-samples
+ENABLE_OBSERVABILITY=true
+ENABLE_A365_OBSERVABILITY_EXPORTER=false
+PYTHON_ENVIRONMENT=development
+
+# Server
+PORT=3978
+LOG_LEVEL=INFO
 ```
 
 ## Message Flow
@@ -127,12 +145,19 @@ OBSERVABILITY_SERVICE_NAME=crewai-sample-agent
 ```toml
 [project]
 dependencies = [
-    "crewai>=0.30.0",
-    "microsoft-agents-hosting-aiohttp>=0.0.1",
-    "microsoft-agents-hosting-core>=0.0.1",
-    "microsoft_agents_a365_observability_core>=0.0.1",
-    "microsoft_agents_a365_tooling_core>=0.0.1",
+    "crewai[azure-ai-inference,tools]==1.4.1",
+    "tavily-python>=0.3.0",
     "python-dotenv>=1.0.0",
+    "microsoft-agents-hosting-aiohttp>=0.9.0",
+    "microsoft-agents-hosting-core>=0.9.0",
+    "microsoft-agents-authentication-msal>=0.9.0",
+    "microsoft-agents-activity>=0.9.0",
+    "aiohttp",
+    "microsoft_agents_a365_tooling>=0.1.0",
+    "microsoft_agents_a365_observability_core>=0.1.0",
+    "microsoft_agents_a365_observability_hosting>=0.1.0",
+    "microsoft_agents_a365_notifications>=0.1.0",
+    "microsoft_agents_a365_runtime>=0.1.0",
 ]
 ```
 

python/crewai/sample_agent/host_agent_server.py

@@ -55,9 +55,10 @@
 
 from turn_context_utils import (
     extract_turn_context_details,
+    create_agent_details,
     create_invoke_agent_details,
     create_caller_details,
-    create_tenant_details,
+    create_user_details,
     create_request,
 )
 from token_cache import cache_agentic_token, get_cached_agentic_token
@@ -73,7 +74,6 @@
 # Enable observability SDK logging to see exporter warnings
 observability_logger = logging.getLogger("microsoft_agents_a365.observability")
 observability_logger.setLevel(logging.INFO)
-
 logger = logging.getLogger(__name__)
 
 # Load configuration
@@ -206,7 +206,7 @@ async def on_message(context: TurnContext, _: TurnState):
                 # Extract context from turn using shared utility
                 ctx_details = extract_turn_context_details(context)
 
-                with BaggageBuilder().tenant_id(ctx_details.tenant_id).agent_id(ctx_details.agent_id).correlation_id(ctx_details.correlation_id).build():
+                with BaggageBuilder().tenant_id(ctx_details.tenant_id).agent_id(ctx_details.agent_id).session_id(ctx_details.conversation_id).build():
                     if not self.agent_instance:
                         error_msg = "ERROR Sorry, the agent is not available."
                         logger.error(error_msg)
@@ -262,16 +262,17 @@ async def _typing_loop():
                     typing_task = asyncio.create_task(_typing_loop())
                     try:
                         # Create observability details using shared utility
-                        invoke_details = create_invoke_agent_details(ctx_details, "AI agent powered by CrewAI framework")
+                        invoke_details = create_invoke_agent_details()
                         caller_details = create_caller_details(ctx_details)
-                        tenant_details = create_tenant_details(ctx_details)
+                        user_details = create_user_details(ctx_details)
                         request = create_request(ctx_details, user_message)
+                        agent_details = create_agent_details(ctx_details, "AI agent powered by CrewAI framework")
 
                         # Wrap the agent invocation with InvokeAgentScope
                         with InvokeAgentScope.start(
-                            invoke_agent_details=invoke_details,
-                            tenant_details=tenant_details,
                             request=request,
+                            scope_details=invoke_details,
+                            agent_details=agent_details,
                             caller_details=caller_details,
                         ) as invoke_scope:
                             if hasattr(invoke_scope, 'record_input_messages'):

python/crewai/sample_agent/mcp_observable_tools.py

@@ -18,7 +18,7 @@
 from crewai.tools import BaseTool
 from pydantic import BaseModel, Field, create_model
 
-from microsoft_agents_a365.observability.core import ExecuteToolScope, ToolCallDetails
+from microsoft_agents_a365.observability.core import ExecuteToolScope, ToolCallDetails, Request
 from mcp_tool_registration_service import MCPToolDefinition
 
 if TYPE_CHECKING:
@@ -49,7 +49,8 @@ async def call_tool(
         tool_name: str,
         arguments: dict,
         agent_details: Any,
-        tenant_details: Any,
+        user_details: Any,
+        conversation_id: str | None = None,
     ) -> str:
         """
         Call an MCP tool by name with ExecuteToolScope observability.
@@ -58,7 +59,8 @@ async def call_tool(
             tool_name: Name of the tool to call
             arguments: Tool arguments as a dictionary
             agent_details: AgentDetails for observability
-            tenant_details: TenantDetails for observability
+            user_details: UserDetails for observability
+            conversation_id: Optional conversation ID for telemetry correlation
 
         Returns:
             The tool result as a string
@@ -86,11 +88,19 @@ async def call_tool(
             endpoint=endpoint,
         )
 
+        # Create a Request for the tool scope
+        tool_request = Request(
+            content=args_str,
+            session_id=conversation_id,
+            conversation_id=conversation_id,
+        )
+
         # Execute with ExecuteToolScope for observability
         with ExecuteToolScope.start(
+            request=tool_request,
             details=tool_call_details,
             agent_details=agent_details,
-            tenant_details=tenant_details,
+            user_details=user_details,
         ) as tool_scope:
             try:
                 logger.info(f"🔧 Calling MCP tool: {tool_name}")
@@ -112,7 +122,8 @@ def create_observable_mcp_tools(
     mcp_tools: list[MCPToolDefinition],
     tool_executor: MCPToolExecutor,
     get_agent_details: callable,
-    get_tenant_details: callable,
+    get_user_details: callable,
+    get_conversation_id: callable = None,
 ) -> list[BaseTool]:
     """
     Create CrewAI-compatible tool wrappers for MCP tools with ExecuteToolScope observability.
@@ -125,7 +136,8 @@ def create_observable_mcp_tools(
         mcp_tools: List of MCP tool definitions from the registration service
         tool_executor: MCPToolExecutor instance for executing tools with observability
         get_agent_details: Callable that returns current agent details for observability
-        get_tenant_details: Callable that returns current tenant details for observability
+        get_user_details: Callable that returns current user details for observability
+        get_conversation_id: Optional callable that returns current conversation ID for telemetry
 
     Returns:
         List of CrewAI BaseTool instances that wrap MCP tools with observability
@@ -141,7 +153,7 @@ def create_observable_mcp_tools(
 
         # Create a closure to capture the tool definition and executor reference
         tool_class = _create_tool_class(
-            mcp_tool, InputModel, tool_executor, get_agent_details, get_tenant_details
+            mcp_tool, InputModel, tool_executor, get_agent_details, get_user_details, get_conversation_id
         )
 
         observable_tools.append(tool_class)
@@ -205,7 +217,8 @@ def _create_tool_class(
     input_model: Type[BaseModel],
     tool_executor: MCPToolExecutor,
     get_agent_details: callable,
-    get_tenant_details: callable,
+    get_user_details: callable,
+    get_conversation_id: callable = None,
 ) -> BaseTool:
     """
     Create a CrewAI BaseTool class for an MCP tool with observability.
@@ -215,7 +228,8 @@ def _create_tool_class(
         input_model: Pydantic model for input validation
         tool_executor: MCPToolExecutor for executing the tool
         get_agent_details: Callable to get current agent details
-        get_tenant_details: Callable to get current tenant details
+        get_user_details: Callable to get current user details
+        get_conversation_id: Optional callable to get current conversation ID
 
     Returns:
         Instance of the created tool class
@@ -240,7 +254,8 @@ def _run(self, **kwargs) -> str:
                         tool_name=tool_def.name,
                         arguments=kwargs,
                         agent_details=get_agent_details(),
-                        tenant_details=get_tenant_details(),
+                        user_details=get_user_details(),
+                        conversation_id=get_conversation_id() if get_conversation_id else None,
                     ),
                     loop
                 )
@@ -253,7 +268,8 @@ def _run(self, **kwargs) -> str:
                         tool_name=tool_def.name,
                         arguments=kwargs,
                         agent_details=get_agent_details(),
-                        tenant_details=get_tenant_details(),
+                        user_details=get_user_details(),
+                        conversation_id=get_conversation_id() if get_conversation_id else None,
                     )
                 )
                 return result

python/crewai/sample_agent/pyproject.toml

@@ -11,10 +11,10 @@ dependencies = [
     "python-dotenv>=1.0.0",
 
     # Microsoft 365 Agents SDK - hosting and auth
-    "microsoft-agents-hosting-aiohttp>=0.7.0",
-    "microsoft-agents-hosting-core>=0.7.0",
-    "microsoft-agents-authentication-msal>=0.7.0",
-    "microsoft-agents-activity>=0.7.0",
+    "microsoft-agents-hosting-aiohttp>=0.9.0",
+    "microsoft-agents-hosting-core>=0.9.0",
+    "microsoft-agents-authentication-msal>=0.9.0",
+    "microsoft-agents-activity>=0.9.0",
 
     # Core hosting deps
     "aiohttp",

python/crewai/sample_agent/src/crew_agent/config/agents.yaml

@@ -8,7 +8,6 @@ weather_checker:
     and forecasting tools. You excel at gathering comprehensive weather information
     including temperature, precipitation, wind conditions, and visibility to help
     people make informed decisions about outdoor activities and driving conditions.
-  llm: azure/gpt-4o
 
 driving_safety_advisor:
   role: >
@@ -21,5 +20,4 @@ driving_safety_advisor:
     their performance characteristics, and safety considerations. You understand that
     summer tires have reduced grip in cold temperatures (below 7°C/45°F), on wet roads,
     and especially on snow or ice. You provide clear, safety-focused recommendations
-    based on weather data.
-  llm: azure/gpt-4o
+    based on weather data.