I am facing above runtime error when trying to deploy an agent using google.cloud.aiplatform'.
aiplatform version: 1.82.0, Python 3.12.3. my python script is below.
from google.cloud import aiplatform
import google.auth
import json
import os
def create_vertex_agent(project_id, location, agent_name, display_name, description😞
"""
Creates a Vertex AI Agent based on the provided configuration.
Args:
project_id: The ID of your Google Cloud project.
location: The location for the Agent.
agent_name: The name of the Agent.
display_name: The display name of the Agent.
description: A description of the Agent.
Returns:
The created Agent object.
"""
try:
# Authenticate with Google Cloud
credentials, project = google.auth.default()
except Exception as e:
print(f"Error getting credentials: {e}")
return None
# Initialize Vertex AI SDK
aiplatform.init(project=project_id, location=location, credentials=credentials)
# Agent Configuration
agent_config = {
"default_language_code": "en",
"time_zone": "UTC",
# Add other agent configuration settings here
}
# Knowledge Resources
knowledge_resources = [
{
"display_name": "SysML2 Knowledge",
"source": "URL Removed by Staff" ,
}
]
# Tool Configuration
tool_config = {
"type": "function_calling",
"function_calling_config": {
"function_calling_model": "gemini-pro"
}
}
# Intent Configuration
intent_config = {
"training_phrases": [
"Create a new element",
"Display the model",
"Add a child element"
]
}
# Action Configuration
action_config = {
"actions": [
{
"name": "create_element",
"handler": "create_element_handler"
},
{
"name": "display_model",
"handler": "display_model_handler"
},
{
"name": "add_child_element",
"handler": "add_child_element_handler"
}
]
}
# Function Calling Configuration
function_calling_config = {
"function_calling_definitions": [
{
"name": "call_agent_2",
"description": "Calls Agent 2 to collect data for a specific SysML element type.",
"parameters": [
{
"name": "element_type",
"type": "string",
"description": "The type of SysML element to create.",
"required": True
}
],
"return_type": "string"
},
{
"name": "call_agent_3",
"description": "Calls Agent 3 to query the requirement database.",
"parameters": [
{
"name": "query",
"type": "string",
"description": "The query to execute against the requirement database.",
"required": True
}
],
"return_type": "string"
}
]
}
try:
# Create the Agent
agent = aiplatform.Agent.create(
display_name=display_name,
#name=agent_name, # Agent name is autogenerated, do not provide
description=description,
agent_config=agent_config,
knowledge_resources=knowledge_resources,
tool_config=tool_config,
intent_config=intent_config,
action_config=action_config,
function_calling_config=function_calling_config
)
print(f"Agent created: {agent.name}")
return agent
except Exception as e:
print(f"Error creating agent: {e}")
return None
if __name__ == "__main__":
credentials_path = os.environ.get("GOOGLE_APPLICATION_CREDENTIALS")
if credentials_path:
print(f"GOOGLE_APPLICATION_CREDENTIALS is set to: {credentials_path}")
else:
print("GOOGLE_APPLICATION_CREDENTIALS is not set.")
# Replace with your actual project ID and location
print("aiplatform version: ", aiplatform.__version__)
PROJECT_ID = "sysengcopilot"
LOCATION = "europe-west6"
# Agent details from Terraform
AGENT_NAME = "agent-mbse-autosar-model-orchestrator" # Needs to be lowercase and hyphenated
DISPLAY_NAME = "Agent MBSE Autosar Model Orchestrator"
DESCRIPTION = "Orchestrates the MBSE design process using SysML2 and Autosar."
# Create the Vertex AI Agent
agent = create_vertex_agent(PROJECT_ID, LOCATION, AGENT_NAME, DISPLAY_NAME, DESCRIPTION)
if agent:
print(f"Agent Name: {agent.name}")
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