Agent Platform Tuning Management

Safety & Confirmation Tiers (CRITICAL)

1. Tier R: Read-only (

   list

   ,

   get

   )
   • Rule: No confirmation needed. You may execute these commands immediately to gather information for the user.
2. Tier D: Destructive & Interruptive (

   cancel

   )
   • Rule: This requires explicit typed confirmation. You MUST output a text message to the user explaining that this will stop the tuning process and any progress will be lost, and asking them to type "I confirm" or "Yes, cancel it". You MUST ask for this confirmation IMMEDIATELY, before executing the cancel command.

Phase 0: Environment Setup

1. Virtual Environment: Create and activate a virtual environment:
   bash

   python3 -m venv ~/tuning_mgr_venv
   source ~/tuning_mgr_venv/bin/activate

2. Google Cloud Authentication: Authenticate with your Google Cloud account and configure active Application Default Credentials (ADC) for Agent Platform access:
   bash

   gcloud auth login
   gcloud auth application-default login

3. Install Dependencies: Install the required Agent Platform SDK:
   bash

   pip install google-cloud-aiplatform

4. Execution: Advise the user that every time they execute a Python snippet, they must ensure this virtual environment is activated first.

Workflow Decision Tree

1. Information Gathering: Do you have a Project ID and Region?
   • No -> You MUST ask the user for the missing Project ID and Region in plain text, or advise them to check their gcloud configuration. If neither location has this information, then ask the user to provide it. Do not attempt to search random regions on your own.
   • Yes -> Proceed to Step 2.
2. Task Type: What does the user want to do?
   • Find or List Jobs -> Use the Python SDK to list tuning jobs. (Tier R)
   • Check Status / Inspect a Specific Job -> Use the Python SDK to get tuning job details. (Tier R)
   • Cancel a Job -> Ask for confirmation, then use the Python SDK to cancel the tuning job. (Tier D)

Using the Python SDK

[!NOTE] Resource Verification & Missing Projects/Jobs: If the execution of the Python snippet fails with an error (such as

403 Permission Denied

,

404 Not Found

,

INVALID_ARGUMENT

, or indicating a dummy/missing project or job ID), you MUST inform the user that the project or tuning job does not exist or cannot be accessed. You MUST prompt the user to provide a valid Project ID or Job ID, and stop tool execution immediately to wait for their response. Do NOT retry or loop, do NOT assume the resource is valid, and do NOT execute further scripts before receiving valid details from the user.

1. Listing Tuning Jobs (Tier R)

from google.cloud import aiplatform_v1

project_id = "YOUR_PROJECT_ID"
region = "YOUR_REGION"
parent = f"projects/{project_id}/locations/{region}"

client = aiplatform_v1.GenAiTuningServiceClient(
    client_options={"api_endpoint": f"{region}-aiplatform.googleapis.com"}
)

jobs = client.list_tuning_jobs(parent=parent)
for job in jobs:
    print(f"Name: {job.name}")
    print(f"Base Model: {job.base_model}")
    print(f"State: {job.state}")

2. Getting Details for a Specific Job (Tier R)

from google.cloud import aiplatform_v1

project_id = "YOUR_PROJECT_ID"
region = "YOUR_REGION"
job_id = "YOUR_JOB_ID"  # 19-digit ID
name = f"projects/{project_id}/locations/{region}/tuningJobs/{job_id}"

client = aiplatform_v1.GenAiTuningServiceClient(
    client_options={"api_endpoint": f"{region}-aiplatform.googleapis.com"}
)

job = client.get_tuning_job(name=name)
print(f"Name: {job.name}")
print(f"Base Model: {job.base_model}")
print(f"State: {job.state}")
print(f"Tuning Model: {job.tuned_model_display_name}")

3. Canceling a Job (Tier D)

[!IMPORTANT] NEVER pre-emptively provide or execute any cancellation code before receiving the user's response in a new turn. You must never speculate or assume that confirmation will be given. Asking for confirmation and providing the code in a single parallel turn is a severe safety violation.

from google.cloud import aiplatform_v1

project_id = "YOUR_PROJECT_ID"
region = "YOUR_REGION"
job_id = "YOUR_JOB_ID"  # 19-digit ID
name = f"projects/{project_id}/locations/{region}/tuningJobs/{job_id}"

client = aiplatform_v1.GenAiTuningServiceClient(
    client_options={"api_endpoint": f"{region}-aiplatform.googleapis.com"}
)

client.cancel_tuning_job(name=name)
print(f"Successfully requested cancellation for {name}")