Merge pull request #6560 from dargilco/dargilco/update-python-agents-quickstart

Updates to Agents Python quickstart code

Author: prmerger-automator[bot]

articles/ai-foundry/agents/includes/quickstart-csharp.md

@@ -92,7 +92,7 @@ client.Messages.CreateMessage(
     MessageRole.User,
     "Hi, Agent! Draw a graph for a line with a slope of 4 and y-intercept of 9.");
 
-//Have Agent beging processing user's question with some additional instructions associated with the ThreadRun.
+//Have Agent begin processing user's question with some additional instructions associated with the ThreadRun.
 ThreadRun run = client.Runs.CreateRun(
     thread.Id,
     agent.Id,

articles/ai-foundry/agents/includes/quickstart-python.md

@@ -51,15 +51,16 @@ Set this endpoint as an environment variable named `PROJECT_ENDPOINT`.
 
 [!INCLUDE [model-name-portal](model-name-portal.md)]
 
-Save the name of your model deployment name as an environment variable named `MODEL_DEPLOYMENT_NAME`. 
+Save the name of your model deployment name as an environment variable named `MODEL_DEPLOYMENT_NAME`.
 
 ```python
 import os
+from pathlib import Path
 from azure.ai.projects import AIProjectClient
 from azure.identity import DefaultAzureCredential
 from azure.ai.agents.models import CodeInterpreterTool
 
-# Create an Azure AI Client from an endpoint, copied from your Azure AI Foundry project.
+# Create an AIProjectClient from an endpoint, copied from your Azure AI Foundry project.
 # You need to login to Azure subscription via Azure CLI and set the environment variables
 project_endpoint = os.environ["PROJECT_ENDPOINT"]  # Ensure the PROJECT_ENDPOINT environment variable is set
 
@@ -71,40 +72,51 @@ project_client = AIProjectClient(
 
 code_interpreter = CodeInterpreterTool()
 with project_client:
-    # Create an agent with the Bing Grounding tool
+    # Create an agent with the Code Interpreter tool
     agent = project_client.agents.create_agent(
         model=os.environ["MODEL_DEPLOYMENT_NAME"],  # Model deployment name
         name="my-agent",  # Name of the agent
-        instructions="You are a helpful agent",  # Instructions for the agent
+        instructions="You politely help with math questions. Use the Code Interpreter tool when asked to visualize numbers.",  # Instructions for the agent
         tools=code_interpreter.definitions,  # Attach the tool
     )
     print(f"Created agent, ID: {agent.id}")
 
     # Create a thread for communication
     thread = project_client.agents.threads.create()
     print(f"Created thread, ID: {thread.id}")
-    
+
     # Add a message to the thread
     message = project_client.agents.messages.create(
         thread_id=thread.id,
         role="user",  # Role of the message sender
-        content="What is the weather in Seattle today?",  # Message content
+        content="Hi, Agent! Draw a graph for a line with a slope of 4 and y-intercept of 9.",  # Message content
     )
     print(f"Created message, ID: {message['id']}")
-    
+
     # Create and process an agent run
-    run = project_client.agents.runs.create_and_process(thread_id=thread.id, agent_id=agent.id)
+    run = project_client.agents.runs.create_and_process(
+        thread_id=thread.id,
+        agent_id=agent.id,
+        additional_instructions="Please address the user as Jane Doe. The user has a premium account",
+    )
     print(f"Run finished with status: {run.status}")
-    
+
     # Check if the run failed
     if run.status == "failed":
         print(f"Run failed: {run.last_error}")
-    
+
     # Fetch and log all messages
     messages = project_client.agents.messages.list(thread_id=thread.id)
     for message in messages:
         print(f"Role: {message.role}, Content: {message.content}")
-    
+
+        # Save every image file in the message
+        for img in message.image_contents:
+            file_id = img.image_file.file_id
+            file_name = f"{file_id}_image_file.png"
+            project_client.agents.files.save(file_id=file_id, file_name=file_name)
+            print(f"Saved image file to: {Path.cwd() / file_name}")
+
     # Delete the agent when done
     project_client.agents.delete_agent(agent.id)
     print("Deleted agent")