Testcases

Author: UtkarshMishra-Microsoft

src/backend/agents/agentutils.py

@@ -5,7 +5,7 @@
 from pydantic import BaseModel
 
 from src.backend.context.cosmos_memory import CosmosBufferedChatCompletionContext
-from models.messages import InputTask, PlanStatus, Step, StepStatus
+from src.backend.models.messages import InputTask, PlanStatus, Step, StepStatus
 
 common_agent_system_message = "If you do not have the information for the arguments of the function you need to call, do not call the function. Instead, respond back to the user requesting further information. You must not hallucinate or invent any of the information used as arguments in the function. For example, if you need to call a function that requires a delivery address, you must not generate 123 Example St. You must skip calling functions and return a clarification message along the lines of: Sorry, I'm missing some information I need to help you with that. Could you please provide the delivery address so I can do that for you?"
 

src/backend/agents/base_agent.py

@@ -10,8 +10,8 @@
 from autogen_core.components.tool_agent import tool_agent_caller_loop
 from autogen_core.components.tools import Tool
 
-from context.cosmos_memory import CosmosBufferedChatCompletionContext
-from models.messages import (ActionRequest, ActionResponse,
+from src.backend.context.cosmos_memory import CosmosBufferedChatCompletionContext
+from src.backend.models.messages import (ActionRequest, ActionResponse,
                              AgentMessage, Step, StepStatus)
 from azure.monitor.events.extension import track_event
 

src/backend/agents/generic.py

@@ -5,8 +5,8 @@
 from autogen_core.components.models import AzureOpenAIChatCompletionClient
 from autogen_core.components.tools import FunctionTool, Tool
 
-from agents.base_agent import BaseAgent
-from context.cosmos_memory import CosmosBufferedChatCompletionContext
+from src.backend.agents.base_agent import BaseAgent
+from src.backend.context.cosmos_memory import CosmosBufferedChatCompletionContext
 
 async def dummy_function() -> str:
     # This is a placeholder function, for a proper Azure AI Search RAG process.

src/backend/agents/hr.py

@@ -6,8 +6,8 @@
 from autogen_core.components.tools import FunctionTool, Tool
 from typing_extensions import Annotated
 
-from agents.base_agent import BaseAgent
-from context.cosmos_memory import CosmosBufferedChatCompletionContext
+from src.backend.agents.base_agent import BaseAgent
+from src.backend.context.cosmos_memory import CosmosBufferedChatCompletionContext
 
 formatting_instructions = "Instructions: returning the output of this function call verbatim to the user in markdown. Then write AGENT SUMMARY: and then include a summary of what you did."
 

src/backend/agents/human.py

@@ -5,8 +5,8 @@
 from autogen_core.components import (RoutedAgent, default_subscription,
                                      message_handler)
 
-from context.cosmos_memory import CosmosBufferedChatCompletionContext
-from models.messages import (
+from src.backend.context.cosmos_memory import CosmosBufferedChatCompletionContext
+from src.backend.models.messages import (
     ApprovalRequest,
     HumanFeedback,
     HumanClarification,

src/backend/agents/marketing.py

@@ -5,8 +5,8 @@
 from autogen_core.components.models import AzureOpenAIChatCompletionClient
 from autogen_core.components.tools import FunctionTool, Tool
 
-from agents.base_agent import BaseAgent
-from context.cosmos_memory import CosmosBufferedChatCompletionContext
+from src.backend.agents.base_agent import BaseAgent
+from src.backend.context.cosmos_memory import CosmosBufferedChatCompletionContext
 
 
 # Define new Marketing tools (functions)

src/backend/agents/planner.py

@@ -11,8 +11,8 @@
                                             LLMMessage, UserMessage)
 from pydantic import BaseModel
 
-from context.cosmos_memory import CosmosBufferedChatCompletionContext
-from models.messages import (
+from src.backend.context.cosmos_memory import CosmosBufferedChatCompletionContext
+from src.backend.models.messages import (
     ActionRequest,
     AgentMessage,
     HumanClarification,

src/backend/agents/procurement.py

@@ -6,8 +6,8 @@
 from autogen_core.components.tools import FunctionTool, Tool
 from typing_extensions import Annotated
 
-from agents.base_agent import BaseAgent
-from context.cosmos_memory import CosmosBufferedChatCompletionContext
+from src.backend.agents.base_agent import BaseAgent
+from src.backend.context.cosmos_memory import CosmosBufferedChatCompletionContext
 
 
 # Define new Procurement tools (functions)

src/backend/agents/product.py

@@ -8,8 +8,8 @@
 from autogen_core.components.tools import FunctionTool, Tool
 from typing_extensions import Annotated
 
-from agents.base_agent import BaseAgent
-from context.cosmos_memory import CosmosBufferedChatCompletionContext
+from src.backend.agents.base_agent import BaseAgent
+from src.backend.context.cosmos_memory import CosmosBufferedChatCompletionContext
 from datetime import datetime
 
 formatting_instructions = "Instructions: returning the output of this function call verbatim to the user in markdown. Then write AGENT SUMMARY: and then include a summary of what you did."