feat: Agent framework - Upgrading to new Foundry Agents changes

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)
 

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,
     )
 

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

src/backend/pyproject.toml

@@ -7,38 +7,37 @@ 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==1.8.5",
     "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",
+    "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==1.36.0",
+    "opentelemetry-sdk==1.39.0",
     "pytest==8.4.1",
     "pytest-asyncio==0.24.0",
     "pytest-cov==5.0.0",
     "python-dotenv==1.1.1",
     "python-multipart==0.0.22",
-    "semantic-kernel==1.39.4",
     "uvicorn==0.35.0",
     "pylint-pydantic==0.3.5",
     "pexpect==4.9.0",
     "mcp==1.26.0",
     "werkzeug==3.1.5",
     "azure-core==1.38.0",
-    "agent-framework>=1.0.0b251105",
+    "agent-framework-azure-ai==1.0.0b260130",
+    "agent-framework-core==1.0.0b260130",
     "urllib3==2.6.3",
     "protobuf==5.29.6",
     "cryptography==46.0.5",
     "aiohttp==3.13.3",
     "pyasn1==0.6.2",
     "nltk==3.9.3",
-]
+]