from google.cloud import aiplatform
from vertexai.agent_engines import Agent, AgentEngine, create
from vertexai.agent_engines import AgentLibrary

# Basic initialization
aiplatform.init(project='example-project-123456', location='europe-southwest1')

# Create a basic agent
root_agent = Agent()

# Create a library reference


# Working version (without env_vars)
remote_app = agent_engines.create(
    display_name="data_science",
    agent_engine=root_agent,
    requirements=["google-cloud-aiplatform[adk,agent_engines]"],
)

# Version that FAILS with 500 error
env_vars = {
    "GOOGLE_GENAI_USE_VERTEXAI": "1",
    "GOOGLE_CLOUD_PROJECT": "example-project-123456",
    "GOOGLE_CLOUD_LOCATION": "us-central1",
    "BQML_RAG_CORPUS_NAME": "default_corpus",
    "BQ_PROJECT_ID": "example-project-123456",
    "BQ_DATASET_ID": "cuvo_platform"
}

remote_app_with_env = agent_engines.create(
    display_name="data_science_with_env",
    agent_engine=root_agent,
    requirements=["google-cloud-aiplatform[adk,agent_engines]"],
    env_vars=env_vars
)