Merge pull request #486 from microsoft/macae-v3-dev-marktayl

Macae v3 dev marktayl

Author: Fr4nc3

data/agent_teams/marketing.json

@@ -43,7 +43,7 @@
       "input_key": "",
       "type": "",
       "name": "ProxyAgent",
-      "deployment_name": "gpt-4.1-mini",
+      "deployment_name": "",
       "icon": "",
       "system_message": "",
       "description": "",

data/agent_teams/retail.json

@@ -29,8 +29,8 @@
       "name": "OrderDataAgent",
       "deployment_name": "gpt-4.1-mini",
       "icon": "",
-      "system_message": "You have access to internal order, inventory, product, and fulfilment data through a secure index. Use this data to answer questions about products, shipping delays, customer orders, warehouse management, etc. Be mindful of privacy and compliance regulations when handling customer data.",
-      "description": "An agent that has access to internal order, inventory, product, and fulfilment data. Ask this agent if you have questions about products, shipping delays, customerr orders, warehouse management, etc.",
+      "system_message": "You have access to internal order, inventory, product, and fulfillment data through a secure index. Use this data to answer questions about products, shipping delays, customer orders, warehouse management, etc. Be mindful of privacy and compliance regulations when handling customer data.",
+      "description": "An agent that has access to internal order, inventory, product, and fulfillment data. Ask this agent if you have questions about products, shipping delays, customer orders, warehouse management, etc.",
       "use_rag": true,
       "use_mcp": false,
       "use_bing": false,
@@ -42,7 +42,7 @@
     {
       "input_key": "",
       "type": "",
-      "name": "AnalysisRecomendationAgent",
+      "name": "AnalysisRecommendationAgent",
       "deployment_name": "o4-mini",
       "icon": "",
       "system_message": "You are a reasoning agent that can analyze customer data and provide recommendations for improving customer satisfaction and retention. You do not have access to any data sources, but you can reason based on the information provided to you by other agents. Use your reasoning skills to identify patterns, trends, and insights that can help improve customer satisfaction and retention. Provide actionable recommendations based on your analysis. You have access to other agents that can answer questions and provide data about customers, products, orders, inventory, and fulfilment. Use these agents to gather information as needed.",
@@ -54,6 +54,22 @@
       "index_name": "",
       "index_foundry_name": "",
       "coding_tools": false
+    },
+    {
+      "input_key": "",
+      "type": "",
+      "name": "ProxyAgent",
+      "deployment_name": "",
+      "icon": "",
+      "system_message": "",
+      "description": "",
+      "use_rag": false,
+      "use_mcp": false,
+      "use_bing": false,
+      "use_reasoning": false,
+      "index_name": "",
+      "index_foundry_name": "",
+      "coding_tools": false
     }
   ],
   "protected": false,
@@ -64,7 +80,7 @@
     {
       "id": "task-1",
       "name": "Satisfaction Plan",
-      "prompt": "Create a  plan to improve Emily Thompson's satisfaction.​",
+      "prompt": "Analyze the satisfaction of Emily Thompson with Contoso.  If needed, provide a plan to increase her satisfaction.",
       "created": "",
       "creator": "",
       "logo": ""

src/backend/.env.sample

@@ -17,7 +17,7 @@ APPLICATIONINSIGHTS_CONNECTION_STRING=
 AZURE_AI_AGENT_MODEL_DEPLOYMENT_NAME=gpt-4o
 AZURE_COGNITIVE_SERVICES="https://cognitiveservices.azure.com/.default"
 AZURE_AI_AGENT_ENDPOINT=
-AZURE_BING_CONNECTION_NAME=
+# AZURE_BING_CONNECTION_NAME=
 REASONING_MODEL_NAME=o3
 APP_ENV=dev
 MCP_SERVER_ENDPOINT=http://localhost:8080/mcp

src/backend/common/config/app_config.py

@@ -4,8 +4,10 @@
 from typing import Optional
 
 from azure.ai.projects.aio import AIProjectClient
+from azure.cosmos import CosmosClient
 from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
 from dotenv import load_dotenv
+from semantic_kernel import Kernel
 
 # Load environment variables from .env file
 load_dotenv()
@@ -52,9 +54,9 @@ def __init__(self):
         )
         self.AZURE_OPENAI_ENDPOINT = self._get_required("AZURE_OPENAI_ENDPOINT")
         self.REASONING_MODEL_NAME = self._get_optional("REASONING_MODEL_NAME", "o3")
-        self.AZURE_BING_CONNECTION_NAME = self._get_optional(
-            "AZURE_BING_CONNECTION_NAME"
-        )
+        # self.AZURE_BING_CONNECTION_NAME = self._get_optional(
+        #     "AZURE_BING_CONNECTION_NAME"
+        # )
         self.SUPPORTED_MODELS = self._get_optional("SUPPORTED_MODELS")
         # Frontend settings
         self.FRONTEND_SITE_NAME = self._get_optional(
@@ -82,7 +84,7 @@ def __init__(self):
         self.AZURE_AI_SEARCH_INDEX_NAME = self._get_optional("AZURE_AI_SEARCH_INDEX_NAME")
         self.AZURE_AI_SEARCH_ENDPOINT = self._get_optional("AZURE_AI_SEARCH_ENDPOINT")
         self.AZURE_AI_SEARCH_API_KEY = self._get_optional("AZURE_AI_SEARCH_API_KEY")
-        self.BING_CONNECTION_NAME = self._get_optional("BING_CONNECTION_NAME")  
+        # self.BING_CONNECTION_NAME = self._get_optional("BING_CONNECTION_NAME")  
 
         test_team_json = self._get_optional("TEST_TEAM_JSON")
 
@@ -125,7 +127,7 @@ def get_azure_credentials(self):
     async def get_access_token(self) -> str:
         """Get Azure access token for API calls."""
         try:
-            credential = self.get_azure_credentials(self.AZURE_CLIENT_ID)
+            credential = self.get_azure_credentials()
             token = credential.get_token(self.AZURE_COGNITIVE_SERVICES)
             return token.token
         except Exception as e:
@@ -190,7 +192,7 @@ def get_cosmos_database_client(self):
         try:
             if self._cosmos_client is None:
                 self._cosmos_client = CosmosClient(
-                    self.COSMOSDB_ENDPOINT, credential=get_azure_credential(self.AZURE_CLIENT_ID)
+                    self.COSMOSDB_ENDPOINT, credential=self.get_azure_credential(self.AZURE_CLIENT_ID)
                 )
 
             if self._cosmos_database is None:
@@ -227,7 +229,7 @@ def get_ai_project_client(self):
             return self._ai_project_client
 
         try:
-            credential = get_azure_credential(self.AZURE_CLIENT_ID)
+            credential = self.get_azure_credential(self.AZURE_CLIENT_ID)
             if credential is None:
                 raise RuntimeError(
                     "Unable to acquire Azure credentials; ensure Managed Identity is configured"

src/backend/common/utils/utils_kernel.py

@@ -40,7 +40,7 @@ async def create_RAI_agent() -> FoundryAgentTemplate:
         model_deployment_name=model_deployment_name,
         enable_code_interpreter=False,
         mcp_config=None,
-        bing_config=None,
+        #bing_config=None,
         search_config=None
     )
 

src/backend/v3/config/settings.py

@@ -14,10 +14,7 @@
 from fastapi import WebSocket
 from semantic_kernel.agents.orchestration.magentic import MagenticOrchestration
 from semantic_kernel.connectors.ai.open_ai import (
-    AzureChatCompletion,
-    OpenAIChatPromptExecutionSettings,
-)
-
+    AzureChatCompletion, OpenAIChatPromptExecutionSettings)
 from v3.models.messages import WebsocketMessageType
 
 logger = logging.getLogger(__name__)
@@ -35,7 +32,7 @@ def __init__(self):
         self.endpoint = config.AZURE_OPENAI_ENDPOINT
         self.reasoning_model = config.REASONING_MODEL_NAME
         self.standard_model = config.AZURE_OPENAI_DEPLOYMENT_NAME
-        self.bing_connection_name = config.AZURE_BING_CONNECTION_NAME
+        #self.bing_connection_name = config.AZURE_BING_CONNECTION_NAME
 
         # Create credential
         self.credential = config.get_azure_credentials()
@@ -89,6 +86,7 @@ def __init__(self):
         self.approvals: Dict[str, bool] = {}  # m_plan_id -> approval status
         self.sockets: Dict[str, WebSocket] = {}  # user_id -> WebSocket
         self.clarifications: Dict[str, str] = {}  # m_plan_id -> clarification response
+        self.max_rounds: int = 20  # Maximum number of replanning rounds 20 needed to accommodate complex tasks
 
     def get_current_orchestration(self, user_id: str) -> MagenticOrchestration:
         """get existing orchestration instance."""
@@ -199,16 +197,36 @@ async def send_status_update_async(
             )
             return
 
-        print(f" websocket {message}")
+        print(f" websocket original message: {message}")
+        print(f" websocket message type: {type(message)}")
+        
+        # Convert message to proper format for frontend
         try:
-            if hasattr(message, "data") and hasattr(message, "type"):
-                message = message.data
+            if hasattr(message, "to_dict"):
+                # Use the custom to_dict method if available
+                message_data = message.to_dict()
+                print(f" websocket used to_dict(): {message_data}")
+            elif hasattr(message, "data") and hasattr(message, "type"):
+                # Handle structured messages with data property
+                message_data = message.data
+                print(f" websocket used message.data: {message_data}")
+            elif isinstance(message, dict):
+                # Already a dictionary
+                message_data = message
+                print(f" websocket already dict: {message_data}")
+            else:
+                # Convert to string if it's a simple type
+                message_data = str(message)
+                print(f" websocket converted to string: {message_data}")
         except Exception as e:
-                print(f"Error loading message data: {e}")
-        print(f" websocket after {message}")
+            print(f"Error processing message data: {e}")
+            message_data = str(message)
+            
+        print(f" websocket final message_data: {message_data}")
+        
         standard_message = {
             "type": message_type,
-            "data": message
+            "data": message_data
         }
         connection = self.get_connection(process_id)
         if connection:

src/backend/v3/magentic_agents/foundry_agent.py

@@ -7,8 +7,10 @@
                                     CodeInterpreterToolDefinition)
 from semantic_kernel.agents import AzureAIAgent  # pylint: disable=E0611
 from v3.magentic_agents.common.lifecycle import AzureAgentBase
-from v3.magentic_agents.models.agent_models import (BingConfig, MCPConfig,
-                                                    SearchConfig)
+from v3.magentic_agents.models.agent_models import MCPConfig, SearchConfig
+
+# from v3.magentic_agents.models.agent_models import (BingConfig, MCPConfig,
+#                                                     SearchConfig)
 
 # exception too broad warning
 # pylint: disable=w0718 
@@ -22,15 +24,15 @@ def __init__(self, agent_name: str,
                  model_deployment_name: str,
                  enable_code_interpreter: bool = False, 
                  mcp_config: MCPConfig | None = None,
-                 bing_config: BingConfig | None = None,
+                 #bing_config: BingConfig | None = None,
                  search_config: SearchConfig | None = None) -> None:
         super().__init__(mcp=mcp_config)
         self.agent_name = agent_name
         self.agent_description = agent_description
         self.agent_instructions = agent_instructions
         self.model_deployment_name = model_deployment_name
         self.enable_code_interpreter = enable_code_interpreter
-        self.bing = bing_config
+        #self.bing = bing_config
         self.mcp = mcp_config
         self.search = search_config
         self._search_connection = None
@@ -40,19 +42,19 @@ def __init__(self, agent_name: str,
         if self.model_deployment_name is any(["o3", "o4-mini"]):
             raise ValueError("The current version of Foundry agents do not support reasoning models.")
 
-    async def _make_bing_tool(self) -> Optional[BingGroundingTool]:
-        """Create Bing search tool for web search."""
-        if not all([self.client, self.bing.connection_name]):
-            self.logger.info("Bing tool not enabled")
-            return None
-        try:
-            self._bing_connection = await self.client.connections.get(name=self.bing.connection_name)
-            bing_tool = BingGroundingTool(connection_id=self._bing_connection.id)
-            self.logger.info("Bing tool created with connection %s", self._bing_connection.id)
-            return bing_tool
-        except Exception as ex:
-            self.logger.error("Bing tool creation failed: %s", ex)
-            return None
+    # async def _make_bing_tool(self) -> Optional[BingGroundingTool]:
+    #     """Create Bing search tool for web search."""
+    #     if not all([self.client, self.bing.connection_name]):
+    #         self.logger.info("Bing tool not enabled")
+    #         return None
+    #     try:
+    #         self._bing_connection = await self.client.connections.get(name=self.bing.connection_name)
+    #         bing_tool = BingGroundingTool(connection_id=self._bing_connection.id)
+    #         self.logger.info("Bing tool created with connection %s", self._bing_connection.id)
+    #         return bing_tool
+    #     except Exception as ex:
+    #         self.logger.error("Bing tool creation failed: %s", ex)
+    #         return None
 
     async def _make_azure_search_tool(self) -> Optional[AzureAISearchTool]:
         """Create Azure AI Search tool for RAG capabilities."""
@@ -95,13 +97,13 @@ async def _collect_tools_and_resources(self) -> tuple[List, dict]:
                 self.logger.error("Something went wrong, Azure AI Search tool not configured")
 
         # Add Bing search tool
-        if self.bing and self.bing.connection_name:
-            bing_tool = await self._make_bing_tool()
-            if bing_tool:
-                tools.extend(bing_tool.definitions)
-                self.logger.info("Added Bing search tools: %d tools", len(bing_tool.definitions))
-            else:
-                self.logger.error("Something went wrong, Bing tool not configured")
+        # if self.bing and self.bing.connection_name:
+        #     bing_tool = await self._make_bing_tool()
+        #     if bing_tool:
+        #         tools.extend(bing_tool.definitions)
+        #         self.logger.info("Added Bing search tools: %d tools", len(bing_tool.definitions))
+        #     else:
+        #         self.logger.error("Something went wrong, Bing tool not configured")
 
         if self.enable_code_interpreter:
             try:
@@ -145,7 +147,7 @@ async def create_foundry_agent(agent_name:str,
                                agent_instructions:str,
                                model_deployment_name:str, 
                                mcp_config:MCPConfig, 
-                               bing_config:BingConfig, 
+                               #bing_config:BingConfig, 
                                search_config:SearchConfig) -> FoundryAgentTemplate:
 
     """Factory function to create and open a ResearcherAgent."""
@@ -155,7 +157,7 @@ async def create_foundry_agent(agent_name:str,
                                  model_deployment_name=model_deployment_name,
                                  enable_code_interpreter=True,
                                  mcp_config=mcp_config,
-                                 bing_config=bing_config,
+                                 #bing_config=bing_config,
                                  search_config=search_config)
     await agent.open()
     return agent

src/backend/v3/magentic_agents/magentic_agent_factory.py

@@ -8,14 +8,16 @@
 from types import SimpleNamespace
 from typing import List, Union
 
+from common.config.app_config import config
 from common.models.messages_kernel import TeamConfiguration
 from v3.config.settings import current_user_id
 from v3.magentic_agents.foundry_agent import FoundryAgentTemplate
-from v3.magentic_agents.models.agent_models import (BingConfig, MCPConfig,
-                                                    SearchConfig)
+from v3.magentic_agents.models.agent_models import MCPConfig, SearchConfig
+# from v3.magentic_agents.models.agent_models import (BingConfig, MCPConfig,
+#                                                     SearchConfig)
 from v3.magentic_agents.proxy_agent import ProxyAgent
 from v3.magentic_agents.reasoning_agent import ReasoningAgentTemplate
-from common.config.app_config import config
+
 
 class UnsupportedModelError(Exception):
     """Raised when an unsupported model is specified."""
@@ -87,7 +89,7 @@ async def create_agent_from_config(self, agent_obj: SimpleNamespace) -> Union[Fo
         # Only create configs for explicitly requested capabilities
         search_config = SearchConfig.from_env() if getattr(agent_obj, 'use_rag', False) else None
         mcp_config = MCPConfig.from_env() if getattr(agent_obj, 'use_mcp', False) else None
-        bing_config = BingConfig.from_env() if getattr(agent_obj, 'use_bing', False) else None
+        # bing_config = BingConfig.from_env() if getattr(agent_obj, 'use_bing', False) else None
 
         self.logger.info(f"Creating agent '{agent_obj.name}' with model '{deployment_name}' "
                         f"(Template: {'Reasoning' if use_reasoning else 'Foundry'})")
@@ -114,7 +116,7 @@ async def create_agent_from_config(self, agent_obj: SimpleNamespace) -> Union[Fo
                 model_deployment_name=deployment_name,
                 enable_code_interpreter=getattr(agent_obj, 'coding_tools', False),
                 mcp_config=mcp_config,
-                bing_config=bing_config,
+                #bing_config=bing_config,
                 search_config=search_config
             )
 

src/backend/v3/magentic_agents/models/agent_models.py

@@ -35,22 +35,22 @@ def from_env(cls) -> "MCPConfig":
             client_id=client_id,
         )
 
-@dataclass(slots=True)
-class BingConfig:
-    """Configuration for connecting to Bing Search."""
-    connection_name: str = "Bing"
+# @dataclass(slots=True)
+# class BingConfig:
+#     """Configuration for connecting to Bing Search."""
+#     connection_name: str = "Bing"
 
-    @classmethod
-    def from_env(cls) -> "BingConfig":
-        connection_name = config.BING_CONNECTION_NAME
+#     @classmethod
+#     def from_env(cls) -> "BingConfig":
+#         connection_name = config.BING_CONNECTION_NAME
 
-        # Raise exception if required environment variable is missing
-        if not connection_name:
-            raise ValueError(f"{cls.__name__} Missing required environment variables")
+#         # Raise exception if required environment variable is missing
+#         if not connection_name:
+#             raise ValueError(f"{cls.__name__} Missing required environment variables")
 
-        return cls(
-            connection_name=connection_name,
-        )
+#         return cls(
+#             connection_name=connection_name,
+#         )
 
 @dataclass(slots=True)
 class SearchConfig: