Set agent name as env variable (#16)

* set agent name as env variable, defaults to agents-template-assistant
* renames template azd-agents-starter instead of azd-aistudio-starter

Author: sophia-ramsey

azure.yaml

@@ -2,9 +2,9 @@
 # TODO: do we need hooks? 
 # TODO: do we need all of the variables?
 
-name: azd-aistudio-starter
+name: azd-agents-starter
 metadata:
-  template: azd-aistudio[email protected]
+  template: azd-agents[email protected]
 
 services:
   api:
@@ -42,6 +42,7 @@ pipeline:
     - USE_CONTAINER_REGISTRY
     - USE_APPLICATION_INSIGHTS
     - USE_SEARCH_SERVICE
+    - AZURE_AI_AGENT_NAME
     - AZURE_AI_AGENT_DEPLOYMENT_NAME
     - AZURE_AI_AGENT_DEPLOYMENT_SKU
     - AZURE_AI_AGENT_DEPLOYMENT_CAPACITY

infra/main.bicep

@@ -73,7 +73,8 @@ param principalId string = ''
 @description('Format of the chat model to deploy')
 @allowed(['Microsoft', 'OpenAI'])
 param agentModelFormat string
-
+@description('Name of agent to deploy')
+param agentName string
 @description('Name of the chat model to deploy')
 param agentModelName string
 @description('Name of the model deployment')
@@ -339,6 +340,7 @@ output AZURE_RESOURCE_GROUP string = rg.name
 output AZURE_TENANT_ID string = tenant().tenantId
 output AZURE_AIPROJECT_CONNECTION_STRING string = projectConnectionString
 output AZURE_AI_AGENT_DEPLOYMENT_NAME string = agentDeploymentName
+output AZURE_AI_AGENT_NAME string = agentName
 
 // Outputs required by azd for ACA
 output AZURE_CONTAINER_ENVIRONMENT_NAME string = containerApps.outputs.environmentName

infra/main.parameters.json

@@ -50,6 +50,9 @@
     "useSearchService": {
       "value": "${USE_SEARCH_SERVICE=true}"
     },
+    "agentName": {
+      "value": "${AZURE_AI_AGENT_NAME=agent-template-assistant}"
+    },
     "agentDeploymentName": {
       "value": "${AZURE_AI_AGENT_MODEL_NAME=gpt-4o-mini}"
     },

scripts/write_env.ps1

@@ -8,9 +8,11 @@ Set-Content -Path $envFilePath -Value ""
 $azureAiProjectConnectionString = azd env get-value AZURE_AIPROJECT_CONNECTION_STRING
 $azureAiagentDeploymentName = azd env get-value AZURE_AI_AGENT_DEPLOYMENT_NAME
 $azureAiAgentId = azd env get-value AZURE_AI_AGENT_ID
+$azureAiAgentName = azd env get-value AZURE_AI_AGENT_NAME
 $azureTenantId = azd env get-value AZURE_TENANT_ID
 
 Add-Content -Path $envFilePath -Value "AZURE_AIPROJECT_CONNECTION_STRING=$azureAiProjectConnectionString"
 Add-Content -Path $envFilePath -Value "AZURE_AI_AGENT_DEPLOYMENT_NAME=$azureAiagentDeploymentName"
 Add-Content -Path $envFilePath -Value "AZURE_AI_AGENT_ID=$azureAiAgentId"
+Add-Content -Path $envFilePath -Value "AZURE_AI_AGENT_NAME=$azureAiAgentName"
 Add-Content -Path $envFilePath -Value "AZURE_TENANT_ID=$azureTenantId"

scripts/write_env.sh

@@ -9,4 +9,5 @@ ENV_FILE_PATH="src/.env"
 echo "AZURE_AIPROJECT_CONNECTION_STRING=$(azd env get-value AZURE_AIPROJECT_CONNECTION_STRING)" >> $ENV_FILE_PATH
 echo "AZURE_AI_AGENT_DEPLOYMENT_NAME=$(azd env get-value AZURE_AI_AGENT_DEPLOYMENT_NAME)" >> $ENV_FILE_PATH
 echo "AZURE_AI_AGENT_ID=$(azd env get-value AZURE_AI_AGENT_ID)" >> $ENV_FILE_PATH
+echo "AZURE_AI_AGENT_NAME=$(azd env get-value AZURE_AI_AGENT_NAME)" >> $ENV_FILE_PATH
 echo "AZURE_TENANT_ID=$(azd env get-value AZURE_TENANT_ID)" >> $ENV_FILE_PATH

src/api/main.py

@@ -101,7 +101,7 @@ async def lifespan(app: fastapi.FastAPI):
             agent_list = await ai_client.agents.list_agents()
             if agent_list.data:
                 for agent_object in agent_list.data:
-                    if agent_object.name == "agent-template-assistant":
+                    if agent_object.name == os.environ["AZURE_AI_AGENT_NAME"]:
                         agent = agent_object
         if agent == None:
             raise Exception("Agent not found")

src/gunicorn.conf.py

@@ -1,7 +1,9 @@
 import multiprocessing
 import os
+import sys
 from typing import Dict
 import asyncio
+import logging
 from azure.ai.projects.aio import AIProjectClient
 from azure.ai.projects.models import FilePurpose, FileSearchTool, AsyncToolSet
 from azure.identity import DefaultAzureCredential
@@ -10,6 +12,26 @@
 
 load_dotenv()
 
+# Create a central logger for the application
+logger = logging.getLogger("azureaiapp")
+logger.setLevel(logging.INFO)
+
+# Configure the stream handler (stdout)
+stream_handler = logging.StreamHandler(sys.stdout)
+stream_handler.setLevel(logging.INFO)
+stream_formatter = logging.Formatter("%(asctime)s [%(levelname)s] %(name)s: %(message)s")
+stream_handler.setFormatter(stream_formatter)
+logger.addHandler(stream_handler)
+
+# Configure logging to file, if log file name is provided
+log_file_name = os.getenv("APP_LOG_FILE", "")
+if log_file_name != "":
+    file_handler = logging.FileHandler(log_file_name)
+    file_handler.setLevel(logging.INFO)
+    file_formatter = logging.Formatter("%(asctime)s [%(levelname)s] %(name)s: %(message)s")
+    file_handler.setFormatter(file_formatter)
+    logger.addHandler(file_handler)
+
 async def list_or_create_agent():
     files: Dict[str, Dict[str, str]] = {}  # File name -> {"id": file_id, "path": file_path}
     vector_store = None
@@ -26,17 +48,17 @@ async def list_or_create_agent():
                 agent = await ai_client.agents.get_agent(os.environ["AZURE_AI_AGENT_ID"])
                 return
             except Exception as e:
-                print(f"Error fetching agent: {e}")
+                logger.info("Error with agent ID")
 
         # Check if a previous agent created by the template exists
         agent_list = await ai_client.agents.list_agents()
         if agent_list.data:
             for agent_object in agent_list.data:
-                if agent_object.name == "agent-template-assistant":
+                if agent_object.name == os.environ["AZURE_AI_AGENT_NAME"]:
                     return 
 
         # Create a new agent with the required resources
-        print(f"Creating new agent with resources")
+        logger.info("Creating new agent with resources")
         file_names = ["product_info_1.md", "product_info_2.md"]
         for file_name in file_names:
             file_path = os.path.abspath(os.path.join(os.path.dirname(__file__), 'files', file_name))
@@ -49,22 +71,22 @@ async def list_or_create_agent():
             file_ids=[info["id"] for info in files.values()],
             name="sample_store"
         )
-        print(f"agent: file store and vector store success")
+        logger.info("agent: file store and vector store success")
 
         file_search_tool = FileSearchTool(vector_store_ids=[vector_store.id])
         toolset = AsyncToolSet()
         toolset.add(file_search_tool)
 
         agent = await ai_client.agents.create_agent(
             model=os.environ["AZURE_AI_AGENT_DEPLOYMENT_NAME"],
-            name="agent-template-assistant", 
+            name=os.environ["AZURE_AI_AGENT_NAME"], 
             instructions="You are helpful assistant",
             toolset=toolset
         )
-        print(f"Created agent, agent ID: {agent.id}")
+        logger.info("Created agent, agent ID: {agent.id}")
 
     except Exception as e:
-        print(f"Error creating agent: {e}", exc_info=True)
+        logger.info("Error creating agent: {e}", exc_info=True)
         raise RuntimeError(f"Failed to create the agent: {e}")
 
 def on_starting(server):