sync from container_agent repo

Author: lusu-msft

sdk/agentserver/azure-ai-agentserver-agentframework/azure/ai/agentserver/agentframework/agent_framework.py

@@ -14,7 +14,7 @@
 
 from azure.ai.agentserver.core import AgentRunContext, FoundryCBAgent
 from azure.ai.agentserver.core.constants import Constants as AdapterConstants
-from azure.ai.agentserver.core.logger import get_logger
+from azure.ai.agentserver.core.logger import APPINSIGHT_CONNSTR_ENV_NAME, get_logger
 from azure.ai.agentserver.core.models import (
     CreateResponse,
     Response as OpenAIResponse,
@@ -77,7 +77,7 @@ def _resolve_stream_timeout(self, request_body: CreateResponse) -> float:
 
     def init_tracing(self):
         exporter = os.environ.get(AdapterConstants.OTEL_EXPORTER_ENDPOINT)
-        app_insights_conn_str = os.environ.get(AdapterConstants.APPLICATION_INSIGHTS_CONNECTION_STRING)
+        app_insights_conn_str = os.environ.get(APPINSIGHT_CONNSTR_ENV_NAME)
         project_endpoint = os.environ.get(AdapterConstants.AZURE_AI_PROJECT_ENDPOINT)
 
         if project_endpoint:

sdk/agentserver/azure-ai-agentserver-agentframework/azure/ai/agentserver/agentframework/models/agent_framework_output_non_streaming_converter.py

@@ -169,7 +169,7 @@ def _append_function_result_content(self, content: FunctionResultContent, sink:
             result = [raw]
         elif isinstance(raw, list):
             for item in raw:
-                result.append(self._coerce_result_text(item))   # type: ignore
+                result.append(self._coerce_result_text(item))  # type: ignore
         call_id = getattr(content, "call_id", None) or ""
         func_out_id = self._context.id_generator.generate_function_output_id()
         sink.append(

sdk/agentserver/azure-ai-agentserver-agentframework/azure/ai/agentserver/agentframework/models/agent_framework_output_streaming_converter.py

@@ -545,6 +545,7 @@ def build_response(self, status: str) -> OpenAIResponse:
             "id": self._response_id,
             "status": status,
             "created_at": self._response_created_at,
+            "conversation": self._context.get_conversation_object(),
         }
         if status == "completed" and self._completed_output_items:
             response_data["output"] = self._completed_output_items

sdk/agentserver/azure-ai-agentserver-core/azure/ai/agentserver/core/constants.py

@@ -3,12 +3,11 @@
 # ---------------------------------------------------------
 class Constants:
     # well-known environment variables
-    APPLICATION_INSIGHTS_CONNECTION_STRING = "_AGENT_RUNTIME_APP_INSIGHTS_CONNECTION_STRING"
     AZURE_AI_PROJECT_ENDPOINT = "AZURE_AI_PROJECT_ENDPOINT"
     AGENT_ID = "AGENT_ID"
     AGENT_NAME = "AGENT_NAME"
     AGENT_PROJECT_RESOURCE_ID = "AGENT_PROJECT_NAME"
     OTEL_EXPORTER_ENDPOINT = "OTEL_EXPORTER_ENDPOINT"
     AGENT_LOG_LEVEL = "AGENT_LOG_LEVEL"
     AGENT_DEBUG_ERRORS = "AGENT_DEBUG_ERRORS"
-    ENABLE_APPLICATION_INSIGHTS_LOGGER = "ENABLE_APPLICATION_INSIGHTS_LOGGER"
+    ENABLE_APPLICATION_INSIGHTS_LOGGER = "AGENT_APP_INSIGHTS_ENABLED"

sdk/agentserver/azure-ai-agentserver-core/azure/ai/agentserver/core/logger.py

@@ -28,6 +28,8 @@
 
 request_context = contextvars.ContextVar("request_context", default=None)
 
+APPINSIGHT_CONNSTR_ENV_NAME = "APPLICATIONINSIGHTS_CONNECTION_STRING"
+
 
 def get_dimensions():
     env_values = {name: value for name, value in vars(Constants).items() if not name.startswith("_")}
@@ -58,9 +60,9 @@ def get_project_endpoint():
 
 def get_application_insights_connstr():
     try:
-        conn_str = os.environ.get(Constants.APPLICATION_INSIGHTS_CONNECTION_STRING)
+        conn_str = os.environ.get(APPINSIGHT_CONNSTR_ENV_NAME)
         if not conn_str:
-            print("environment variable APPLICATION_INSIGHTS_CONNECTION_STRING not set.")
+            print(f"environment variable {APPINSIGHT_CONNSTR_ENV_NAME} not set.")
             project_endpoint = get_project_endpoint()
             if project_endpoint:
                 # try to get the project connected application insights
@@ -72,7 +74,7 @@ def get_application_insights_connstr():
                 if not conn_str:
                     print(f"no connected application insights found for project:{project_endpoint}")
                 else:
-                    os.environ[Constants.APPLICATION_INSIGHTS_CONNECTION_STRING] = conn_str
+                    os.environ[APPINSIGHT_CONNSTR_ENV_NAME] = conn_str
         return conn_str
     except Exception as e:
         print(f"failed to get application insights with error: {e}")

sdk/agentserver/azure-ai-agentserver-core/azure/ai/agentserver/core/server/base.py

@@ -21,7 +21,7 @@
 from starlette.types import ASGIApp
 
 from ..constants import Constants
-from ..logger import get_logger, request_context
+from ..logger import APPINSIGHT_CONNSTR_ENV_NAME, get_logger, request_context
 from ..models import (
     Response as OpenAIResponse,
     ResponseStreamEvent,
@@ -93,7 +93,7 @@ async def runs_endpoint(request):
                 kind=trace.SpanKind.SERVER,
             ):
                 try:
-                    logger.info("Start processing CreateResponse request:")
+                    logger.info("Start processing CreateResponse request.")
 
                     context_carrier = {}
                     TraceContextTextMapPropagator().inject(context_carrier)
@@ -126,7 +126,7 @@ def gen():
                                 yield "data: [DONE]\n\n"
                                 error_sent = True
                             finally:
-                                logger.info("End of processing CreateResponse request:")
+                                logger.info("End of processing CreateResponse request.")
                                 otel_context.detach(token)
                                 if not error_sent:
                                     yield "data: [DONE]\n\n"
@@ -261,7 +261,7 @@ def run(self, port: int = int(os.environ.get("DEFAULT_AD_PORT", 8088))) -> None:
 
     def init_tracing(self):
         exporter = os.environ.get(Constants.OTEL_EXPORTER_ENDPOINT)
-        app_insights_conn_str = os.environ.get(Constants.APPLICATION_INSIGHTS_CONNECTION_STRING)
+        app_insights_conn_str = os.environ.get(APPINSIGHT_CONNSTR_ENV_NAME)
         if exporter or app_insights_conn_str:
             from opentelemetry.sdk.resources import Resource
             from opentelemetry.sdk.trace import TracerProvider

sdk/agentserver/azure-ai-agentserver-core/azure/ai/agentserver/core/server/common/agent_run_context.py

@@ -46,7 +46,7 @@ def stream(self) -> bool:
     def get_agent_id_object(self) -> AgentId:
         agent = self.request.get("agent")
         if not agent:
-            return None   # type: ignore
+            return None  # type: ignore
         return AgentId(
             {
                 "type": agent.type,
@@ -57,7 +57,7 @@ def get_agent_id_object(self) -> AgentId:
 
     def get_conversation_object(self) -> ResponseConversation1:
         if not self._conversation_id:
-            return None   # type: ignore
+            return None  # type: ignore
         return ResponseConversation1(id=self._conversation_id)
 
 
@@ -72,5 +72,5 @@ def _deserialize_create_response(payload: dict) -> CreateResponse:
 
 def _deserialize_agent_reference(payload: dict) -> AgentReference:
     if not payload:
-        return None   # type: ignore
+        return None  # type: ignore
     return AgentReference(**payload)

sdk/agentserver/azure-ai-agentserver-core/azure/ai/agentserver/core/server/common/id_generator/foundry_id_generator.py

@@ -88,7 +88,7 @@ def _new_id(
 
         infix = infix or ""
         prefix_part = f"{prefix}{delimiter}" if prefix else ""
-        return f"{prefix_part}{entropy}{infix}{pkey}"
+        return f"{prefix_part}{infix}{pkey}{entropy}"
 
     @staticmethod
     def _secure_entropy(string_length: int) -> str:

sdk/agentserver/azure-ai-agentserver-langgraph/azure/ai/agentserver/langgraph/models/response_event_generators/response_content_part_event_generator.py

@@ -63,7 +63,7 @@ def try_process_message(
 
         return is_processed, next_processor, events
 
-    def on_start(   # mypy: ignore[override]
+    def on_start(  # mypy: ignore[override]
         self, event, run_details, stream_state: StreamEventState
     ) -> tuple[bool, List[project_models.ResponseStreamEvent]]:
         if self.started:
@@ -81,8 +81,9 @@ def on_start(   # mypy: ignore[override]
 
         return True, [start_event]
 
-    def on_end(self, message, context, stream_state: StreamEventState
-            ) -> List[project_models.ResponseStreamEvent]:   # mypy: ignore[override]
+    def on_end(
+        self, message, context, stream_state: StreamEventState
+    ) -> List[project_models.ResponseStreamEvent]:  # mypy: ignore[override]
         aggregated_content = self.item_content_helper.create_item_content()
         done_event = project_models.ResponseContentPartDoneEvent(
             item_id=self.item_id,

sdk/agentserver/azure-ai-agentserver-langgraph/azure/ai/agentserver/langgraph/models/response_event_generators/response_event_generator.py

@@ -33,11 +33,11 @@ def __init__(self, logger, parent):
         self.parent = parent  # parent generator
 
     def try_process_message(
-            self,
-            message: AnyMessage,   # mypy: ignore[valid-type]
-            context: AgentRunContext,
-            stream_state: StreamEventState
-        ):    # mypy: ignore[empty-body]
+        self,
+        message: AnyMessage,  # mypy: ignore[valid-type]
+        context: AgentRunContext,
+        stream_state: StreamEventState,
+    ):  # mypy: ignore[empty-body]
         """
         Try to process the incoming message.
 
@@ -63,8 +63,8 @@ def on_start(self) -> tuple[bool, List[project_models.ResponseStreamEvent]]:
         return False, []
 
     def on_end(
-            self, message: AnyMessage, context: AgentRunContext, stream_state: StreamEventState
-        ) -> tuple[bool, List[project_models.ResponseStreamEvent]]:
+        self, message: AnyMessage, context: AgentRunContext, stream_state: StreamEventState
+    ) -> tuple[bool, List[project_models.ResponseStreamEvent]]:
         """
         Generate the ending events for this layer.
         TODO: handle different end conditions, e.g. normal end, error end, etc.