Mock behavior of extension as test baseline

COBO-INTEGRATION-TEST.md

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+## COBO Agent E2E Test
+
+
+1. Get the bicep
+```powershell
+azd init --template https://github.com/Azure-Samples/azd-ai-starter-basic
+```
+
+2. Install the required azd version and extension
+
+Install azd daily build
+```powershell
+powershell -ex AllSigned -c "Invoke-RestMethod 'https://aka.ms/install-azd.ps1' -OutFile 'install-azd.ps1'; ./install-azd.ps1 -Version 'daily'"
+```
+Open a new powershell then
+```
+azd version
+```
+It should give you the expected commit number, most recently, you should see
+```
+azd version 1.20.2 (commit 2063759a9d972b4b4b8d9a5052bc4b5fa664d7e7)
+```
+
+Install extension
+```powershell
+azd extension install azure.foundry.ai.agents  
+```
+Then
+```
+azd ext list
+```
+You should see
+```
+Id                        Name                                  Version   Installed Version  Source
+azure.coding-agent        Coding agent configuration extension  0.5.1                        azd
+azure.foundry.ai.agents   AI Foundry Agents                     0.0.2     0.0.2              azd
+microsoft.azd.demo        Demo Extension                        0.3.0                        azd
+microsoft.azd.extensions  AZD Extensions Developer Kit          0.6.0                        azd
+```
+
+3. Init Agent sample
+```
+azd ai agent init -m https://github.com/coreai-microsoft/foundry-golden-path/tree/main/idea-to-proto/01-build-agent-in-code/agent-catalog-code-samples/cobo-calculator-agent
+```
+
+Your folder structure should look like this now:
+```
+cobo-calculator-agent/
+├── .azure/
+├── infra/
+├── agent.yaml
+├── azure.yaml
+├── Dockerfile
+├── langraph_agent_calculator.py
+└── requirements.txt
+```
+
+
+4. Test
+```
+azd up
+```
+Use the following parameters if you don't have a test subscription:
+```
+? Select an Azure Subscription to use: 87. azure-openai-agents-exp-nonprod-01 (921496dc-987f-410f-bd57-426eb2611356)
+? Enter a value for the 'aiDeploymentsLocation' infrastructure parameter: 24. (US) West US 2 (westus2)
+? Enter a value for the 'enableCoboAgent' infrastructure parameter: True
+```
+Please contact migu@microsoft to get permission to the subscription
+
+
+When it finishes, you should see console output like:
+```
+--- Testing Agent with Data Plane Call ---
+Data Plane POST URL: https://ai-account-kply6uaglbh5u.services.ai.azure.com/api/projects/migu-cobo-int-1602/openai/responses?api-version=2025-05-15-preview
+Data Plane Payload: {
+  "stream": false,
+  "agent": {
+    "version": "2",
+    "name": "Cobo Calculator Agent",
+    "type": "agent_reference"
+  },
+  "input": "Tell me a joke."
+}
+Data Plane POST completed. Response:
+{
+  "metadata": {},
+  "temperature": null,
+  "top_p": null,
+  "user": null,
+  "model": "",
+  "background": false,
+  "tools": [],
+  "id": "caresp_33443885792eaac0004iX4VWbkLbS4rTYxSKosWlyE6h1DZeFF",
+  "object": "response",
+  "status": "completed",
+  "created_at": 1761349040,
+  "error": null,
+  "incomplete_details": null,
+  "output": [
+    {
+      "type": "message",
+      "id": "msg_33443885792eaac0009lEaLBx6qSEMnII3pakiMz10q6ZnlBVI",
+      "status": "completed",
+      "role": "assistant",
+      "content": [
+        {
+          "type": "output_text",
+          "text": "Why don't skeletons fight each other?\n\nBecause they don't have the guts!",
+          "annotations": []
+        }
+      ]
+    }
+  ],
+  "instructions": null,
+  "parallel_tool_calls": false,
+  "conversation": null,
+  "agent": {
+    "type": "agent_id",
+    "name": "Cobo Calculator Agent",
+    "version": "2"
+  }
+}
+
+======================================
+Azure Portal Links
+======================================
+Container App: https://portal.azure.com/#@/resource/subscriptions/921496dc-987f-410f-bd57-426eb2611356/resourceGroups/rg-migu-cobo-int-1602/providers/Microsoft.App/containerApps/ca-migu-cobo-int-1602-kply6uaglb  
+```

Dockerfile

@@ -0,0 +1,16 @@
+# syntax=docker/dockerfile:1
+
+FROM mcr.microsoft.com/devcontainers/python:3.11
+
+WORKDIR /app
+
+# Copy package sources (new_app project)
+COPY . .
+
+# Install the package with the langgraph extras
+RUN pip install -r requirements.txt
+
+# Expose the port that the agent server uses
+EXPOSE 8088
+
+CMD ["python", "langgraph_agent_calculator.py"]

agent.yaml

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+agent:
+  kind: container
+  name: Cobo Calculator Agent
+  description: This Agent can perform basic arithmetic calculations such as addition, subtraction, multiplication, and division.
+  metadata:
+    example:
+      - role: user
+        content: |-
+          What's 3 / 1.5 + 2?
+    tags:
+      - example
+      - learning
+    authors:
+      - migu
+
+  models:
+    - id: gpt-4o-mini
+      provider: azure
+      deployment: {{model_deployment_name}}
+
+parameters:
+  model_deployment_name:
+    schema:
+      type: string
+      default: gpt-4o-mini
+    description: the name of your model deployment
+    required: true

azure.yaml

@@ -9,3 +9,24 @@ requiredVersions:
   extensions:
     # the azd ai agent extension is required for this template
     "azure.foundry.ai.agents": ">=0.0.1"
+
+services:
+  cobo-agent:
+    project: .
+    language: py
+    host: containerapp
+    docker:
+      remoteBuild: true
+
+hooks:
+  postdeploy:
+    windows:
+      shell: pwsh
+      run: ./scripts/postdeploy.ps1
+      continueOnError: true
+      interactive: true
+    posix:
+      shell: sh
+      run: ./scripts/postdeploy.sh
+      continueOnError: true
+      interactive: true

infra/main.bicep

@@ -149,3 +149,5 @@ output AI_FOUNDRY_PROJECT_PRINCIPAL_ID string = enableCoboAgent ? coboAgent!.out
 output AI_FOUNDRY_PROJECT_TENANT_ID string = enableCoboAgent ? coboAgent!.outputs.AI_FOUNDRY_PROJECT_TENANT_ID : ''
 output AI_FOUNDRY_RESOURCE_ID string = '/subscriptions/${subscription().subscriptionId}/resourceGroups/${resourceGroupName}/providers/Microsoft.CognitiveServices/accounts/${aiProject.outputs.aiServicesAccountName}'
 output AI_FOUNDRY_PROJECT_RESOURCE_ID string = aiProject.outputs.projectId
+// Mock output of AGENT_NAME which should be populated by azd extension by reading from agent.yaml
+output AGENT_NAME string = 'Cobo Calculator Agent'

infra/main.parameters.json

@@ -24,7 +24,7 @@
         "value": "${AZURE_PRINCIPAL_TYPE}"
       },
       "aiProjectDeploymentsJson": {
-        "value": "${AI_PROJECT_DEPLOYMENTS:=[]}"
+        "value": "[{\"name\":\"gpt-4o-mini\",\"model\":{\"name\":\"gpt-4o-mini\",\"format\":\"OpenAI\",\"version\":\"2024-07-18\"},\"sku\":{\"name\":\"GlobalStandard\",\"capacity\":50}}]"
       },
       "aiProjectConnectionsJson": {
         "value": "${AI_PROJECT_CONNECTIONS:=[]}"

langgraph_agent_calculator.py

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+import os
+
+from dotenv import load_dotenv
+from langchain.chat_models import init_chat_model
+from langchain_core.messages import SystemMessage, ToolMessage
+from langchain_core.tools import tool
+from langgraph.graph import (
+    END,
+    START,
+    MessagesState,
+    StateGraph,
+)
+from typing_extensions import Literal
+from azure.identity import DefaultAzureCredential, get_bearer_token_provider
+
+from azure.ai.agentshosting import from_langgraph
+
+load_dotenv()
+
+deployment_name = os.getenv("AZURE_OPENAI_CHAT_DEPLOYMENT_NAME", "gpt-4o-mini")
+api_key = os.getenv("AZURE_OPENAI_API_KEY", "")
+
+if api_key:
+    llm = init_chat_model(f"azure_openai:{deployment_name}")
+else:
+    credential = DefaultAzureCredential()
+    token_provider = get_bearer_token_provider(
+        credential, "https://cognitiveservices.azure.com/.default"
+    )
+    llm = init_chat_model(
+        f"azure_openai:{deployment_name}",
+        azure_ad_token_provider=token_provider,
+    )
+
+
+# Define tools
+@tool
+def multiply(a: int, b: int) -> int:
+    """Multiply a and b.
+
+    Args:
+        a: first int
+        b: second int
+    """
+    return a * b
+
+
+@tool
+def add(a: int, b: int) -> int:
+    """Adds a and b.
+
+    Args:
+        a: first int
+        b: second int
+    """
+    return a + b
+
+
+@tool
+def divide(a: int, b: int) -> float:
+    """Divide a and b.
+
+    Args:
+        a: first int
+        b: second int
+    """
+    return a / b
+
+
+# Augment the LLM with tools
+tools = [add, multiply, divide]
+tools_by_name = {tool.name: tool for tool in tools}
+llm_with_tools = llm.bind_tools(tools)
+
+
+# Nodes
+def llm_call(state: MessagesState):
+    """LLM decides whether to call a tool or not"""
+
+    return {
+        "messages": [
+            llm_with_tools.invoke(
+                [
+                    SystemMessage(
+                        content="You are a helpful assistant tasked with performing arithmetic on a set of inputs."
+                    )
+                ]
+                + state["messages"]
+            )
+        ]
+    }
+
+
+def tool_node(state: dict):
+    """Performs the tool call"""
+
+    result = []
+    for tool_call in state["messages"][-1].tool_calls:
+        tool = tools_by_name[tool_call["name"]]
+        observation = tool.invoke(tool_call["args"])
+        result.append(ToolMessage(content=observation, tool_call_id=tool_call["id"]))
+    return {"messages": result}
+
+
+# Conditional edge function to route to the tool node or end based upon whether the LLM made a tool call
+def should_continue(state: MessagesState) -> Literal["environment", END]:
+    """Decide if we should continue the loop or stop based upon whether the LLM made a tool call"""
+
+    messages = state["messages"]
+    last_message = messages[-1]
+    # If the LLM makes a tool call, then perform an action
+    if last_message.tool_calls:
+        return "Action"
+    # Otherwise, we stop (reply to the user)
+    return END
+
+
+# Build workflow
+agent_builder = StateGraph(MessagesState)
+
+# Add nodes
+agent_builder.add_node("llm_call", llm_call)
+agent_builder.add_node("environment", tool_node)
+
+# Add edges to connect nodes
+agent_builder.add_edge(START, "llm_call")
+agent_builder.add_conditional_edges(
+    "llm_call",
+    should_continue,
+    {
+        "Action": "environment",
+        END: END,
+    },
+)
+agent_builder.add_edge("environment", "llm_call")
+
+# Compile the agent
+agent = agent_builder.compile()
+
+if __name__ == "__main__":
+    adapter = from_langgraph(agent)
+    adapter.run()

requirements.txt

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+python-dotenv
+my-agents-adapter[langgraph]==0.0.7
+azure-identity