Antigravity × Vertex AI / Firebase Integration Errors: Complete Production Fix Guide

Combining Antigravity agents with Vertex AI models and Firebase's real-time infrastructure unlocks powerful intelligent applications — but production deployments surface errors that never appear in local development: authentication failures, IAM permission gaps, Firestore security rule violations, Cloud Functions timeouts, and real-time sync disconnects.

Antigravity × Vertex AI Authentication Errors

Error Pattern 1: DefaultCredentialsError

google.auth.exceptions.DefaultCredentialsError:
Could not automatically determine credentials.

This appears when Google Cloud credentials aren't available in the current environment.

Production environments (Cloud Run, GKE, Compute Engine):

On managed Google Cloud infrastructure, attach a service account to the resource and Application Default Credentials (ADC) work automatically — no credential code needed.

import vertexai
from vertexai.generative_models import GenerativeModel
from antigravity import AgentBuilder  # hypothetical SDK
 
# ✅ Works automatically on Cloud Run / GKE with an attached service account
vertexai.init(project="YOUR_PROJECT_ID", location="us-central1")
 
class AntigravityVertexAgent:
    def __init__(self):
        self.vertex_model = GenerativeModel("gemini-2.0-flash-001")
        self.agent = AgentBuilder().with_llm(self.vertex_model).build()
 
    async def run(self, task: str) -> str:
        return await self.agent.execute(task)

Local development:

# Set up ADC with your personal credentials
gcloud auth application-default login
 
# Or impersonate a service account to test production permissions
gcloud auth application-default login \
  --impersonate-service-account=antigravity-agent@YOUR_PROJECT_ID.iam.gserviceaccount.com

Error Pattern 2: Insufficient IAM Permissions

google.api_core.exceptions.PermissionDenied: 403
Permission 'aiplatform.endpoints.predict' denied on resource

The service account running your agent doesn't have the required Vertex AI role.

Grant the required roles:

# Required for inference requests to Vertex AI
gcloud projects add-iam-policy-binding YOUR_PROJECT_ID \
  --member="serviceAccount:antigravity-agent@YOUR_PROJECT_ID.iam.gserviceaccount.com" \
  --role="roles/aiplatform.user"
 
# Required for custom model endpoints
gcloud projects add-iam-policy-binding YOUR_PROJECT_ID \
  --member="serviceAccount:antigravity-agent@YOUR_PROJECT_ID.iam.gserviceaccount.com" \
  --role="roles/ml.developer"

Minimum permissions for a custom IAM role:

custom_role_permissions = [
    "aiplatform.endpoints.predict",
    "aiplatform.models.get",
    "storage.objects.get",  # Only if reading from GCS
]

Error Pattern 3: Region Mismatch for Vertex AI Endpoints

google.api_core.exceptions.NotFound: 404
Endpoint not found: projects/xxx/locations/us-east1/endpoints/yyy

Vertex AI custom endpoints are region-specific. Your vertexai.init() location must match the endpoint's region.

# ❌ Region mismatch — endpoint is in us-east1 but init uses us-central1
vertexai.init(project="YOUR_PROJECT_ID", location="us-central1")
 
# ✅ Match the endpoint's region exactly
VERTEX_AI_REGION = "us-east1"
vertexai.init(project="YOUR_PROJECT_ID", location=VERTEX_AI_REGION)

Firebase Integration Errors

Firestore Access Errors

Security Rule Violations

FirebaseError: PERMISSION_DENIED: Missing or insufficient permissions.

Firestore's security rules are blocking the agent's request. In server-side agent code, use the Admin SDK, which bypasses security rules entirely.

import firebase_admin
from firebase_admin import credentials, firestore
import uuid
 
# ✅ Admin SDK bypasses security rules
cred = credentials.ApplicationDefault()
firebase_admin.initialize_app(cred, {'projectId': 'YOUR_PROJECT_ID'})
db = firestore.client()
 
async def save_agent_result(agent_id: str, result: dict) -> str:
    """Save agent execution results to Firestore"""
    try:
        doc_ref = db.collection('agent_results').document()
        await doc_ref.set({
            **result,
            'agent_id': agent_id,
            'created_at': firestore.SERVER_TIMESTAMP,
            'status': 'completed'
        })
        return doc_ref.id
    except Exception as e:
        print(f"Firestore write error: {e}")
        raise

Security rules for client-side access (web/mobile apps):

// firestore.rules
rules_version = '2';
service cloud.firestore {
  match /databases/{database}/documents {
    // Agent results — read only by the owning user
    match /agent_results/{resultId} {
      allow read: if request.auth != null && request.auth.uid == resource.data.user_id;
      allow create: if false;   // Only Admin SDK can write
      allow update, delete: if false;
    }
 
    // Task queue — users can submit tasks for themselves
    match /agent_tasks/{taskId} {
      allow create: if request.auth != null
        && request.resource.data.user_id == request.auth.uid
        && request.resource.data.status == 'pending';
      allow read: if request.auth != null && request.auth.uid == resource.data.user_id;
      allow update, delete: if false;  // Admin SDK only
    }
  }
}

Field Type Errors on Write

ValueError: A document must have an even number of segments
google.api_core.exceptions.InvalidArgument: Document path must be a string

These occur when document IDs or field values have incorrect types.

from google.cloud.firestore_v1 import AsyncClient
import uuid
 
async def safe_firestore_write(db: AsyncClient, collection: str, data: dict) -> str:
    """Type-safe Firestore write with sanitization"""
    sanitized = {}
    for key, value in data.items():
        str_key = str(key)  # Keys must be strings
 
        if value is None:
            sanitized[str_key] = ""  # No null values
        elif isinstance(value, (dict, list)):
            sanitized[str_key] = value
        elif isinstance(value, (int, float, bool)):
            sanitized[str_key] = value
        else:
            sanitized[str_key] = str(value)
 
    doc_id = str(uuid.uuid4())
    doc_ref = db.collection(collection).document(doc_id)
    await doc_ref.set(sanitized)
    return doc_id

Cloud Functions Integration Errors

Timeout Errors

Antigravity agent processing often exceeds Cloud Functions' default 60-second timeout.

# Use async task queuing instead of synchronous processing
from google.cloud import tasks_v2
import json
 
tasks_client = tasks_v2.CloudTasksClient()
 
def handle_agent_request(request):
    """Accept immediately, process asynchronously"""
    task_data = request.get_json()
    if not task_data:
        return {'error': 'Invalid request'}, 400
 
    parent = tasks_client.queue_path('YOUR_PROJECT_ID', 'us-central1', 'antigravity-tasks')
    task = {
        'http_request': {
            'http_method': tasks_v2.HttpMethod.POST,
            'url': 'https://REGION-PROJECT_ID.cloudfunctions.net/process_agent_task',
            'body': json.dumps(task_data).encode(),
            'headers': {'Content-Type': 'application/json'},
        }
    }
 
    response = tasks_client.create_task(parent=parent, task=task)
    return {'task_name': response.name, 'status': 'queued'}, 202

Pub/Sub async pattern (recommended for high volume):

from google.cloud import pubsub_v1
import json, uuid
 
publisher = pubsub_v1.PublisherClient()
topic_path = publisher.topic_path('YOUR_PROJECT_ID', 'antigravity-agent-tasks')
 
async def submit_agent_task(task_data: dict) -> str:
    message_data = json.dumps(task_data).encode('utf-8')
    future = publisher.publish(
        topic_path,
        message_data,
        task_id=task_data.get('task_id', str(uuid.uuid4())),
    )
    return future.result()
 
# Pub/Sub subscriber (in a separate Cloud Function)
import functions_framework
from cloudevents.http import CloudEvent
import base64
 
@functions_framework.cloud_event
def process_agent_task(cloud_event: CloudEvent):
    data = base64.b64decode(cloud_event.data["message"]["data"])
    task_data = json.loads(data.decode('utf-8'))
    result = run_antigravity_agent(task_data)
    save_to_firestore(task_data['task_id'], result)

Real-Time Sync Error Handling

Firestore Listener Disconnections

Real-time listeners can disconnect due to network issues or Firestore maintenance.

from google.cloud.firestore_v1 import AsyncClient
import asyncio
 
class AgentStatusWatcher:
    def __init__(self, db: AsyncClient, agent_id: str):
        self.db = db
        self.agent_id = agent_id
        self._reconnect_delay = 1.0
        self._max_reconnect_delay = 60.0
 
    async def start_watching(self, on_status_change):
        """Start real-time listener with automatic reconnection"""
        while True:
            try:
                await self._watch(on_status_change)
            except Exception as e:
                print(f"Listener disconnected: {e}. Reconnecting in {self._reconnect_delay}s")
                await asyncio.sleep(self._reconnect_delay)
                self._reconnect_delay = min(self._reconnect_delay * 2, self._max_reconnect_delay)
 
    async def _watch(self, on_status_change):
        query = (
            self.db.collection('agent_results')
            .where('agent_id', '==', self.agent_id)
            .order_by('created_at', direction='DESCENDING')
            .limit(1)
        )
 
        from google.cloud.firestore_v1.watch import DocumentChange
        async for changes in query.watch():
            self._reconnect_delay = 1.0  # Reset on successful connection
            for change in changes:
                if change.type in (DocumentChange.ADDED, DocumentChange.MODIFIED):
                    await on_status_change(change.document.to_dict())

Cross-Database Consistency (Firestore + Realtime Database)

When using both databases, maintain consistency with careful error handling:

async def update_agent_status_atomic(firestore_db, rtdb_ref, agent_id: str, status: str, result: dict = None):
    """Best-effort atomic update across Firestore and Realtime Database"""
    firestore_success = False
 
    try:
        await firestore_db.collection('agents').document(agent_id).update({
            'status': status,
            'updated_at': firestore.SERVER_TIMESTAMP,
            'result': result
        })
        firestore_success = True
    except Exception as e:
        print(f"Firestore update failed: {e}")
 
    try:
        rtdb_ref.child(f'agent_status/{agent_id}').set({
            'status': status,
            'updated_at': {'.sv': 'timestamp'}
        })
    except Exception as e:
        print(f"RTDB update failed: {e}")
        if not firestore_success:
            raise Exception("Both databases failed to update")
 
    if not firestore_success:
        # Roll back RTDB if Firestore failed
        try:
            rtdb_ref.child(f'agent_status/{agent_id}').delete()
        except:
            pass
        raise Exception("Firestore update failed")

End-to-End Error Monitoring

import google.cloud.error_reporting as error_reporting
import google.cloud.logging as cloud_logging
import logging, traceback
 
logging_client = cloud_logging.Client()
logging_client.setup_logging()
logger = logging.getLogger('antigravity-agent')
error_client = error_reporting.Client()
 
class MonitoredAntigravityAgent:
    def __init__(self, agent_id: str):
        self.agent_id = agent_id
 
    async def execute_with_monitoring(self, task: dict) -> dict:
        task_id = task.get('task_id', 'unknown')
 
        logger.info(f"Task started: {task_id}", extra={
            'agent_id': self.agent_id,
            'task_type': task.get('type'),
        })
 
        try:
            result = await self._execute(task)
            logger.info(f"Task completed: {task_id}", extra={'agent_id': self.agent_id})
            return result
 
        except PermissionError as e:
            logger.error(f"Permission error: {task_id} - {e}", extra={'error_type': 'permission_error'})
            error_client.report_exception()
            raise
 
        except Exception as e:
            logger.exception(f"Unexpected error: {task_id}", extra={'agent_id': self.agent_id})
            error_client.report_exception()
            return {'task_id': task_id, 'status': 'error', 'error': str(e)}
 
    async def _execute(self, task: dict) -> dict:
        raise NotImplementedError

Production Diagnosis Flow

When an Antigravity × Vertex AI / Firebase integration error occurs, follow this sequence.

Step 1: Authentication error? DefaultCredentialsError → verify ADC setup. PermissionDenied → check IAM roles (roles/aiplatform.user required).

Step 2: Firestore error? PERMISSION_DENIED → use Admin SDK or fix security rules. InvalidArgument → check field types and document path format.

Step 3: Cloud Functions error? Timeout → switch to async pattern (Pub/Sub or Cloud Tasks). Cold start delay → set minimum instance count.

Step 4: Real-time sync error? Listener disconnect → implement auto-reconnect with exponential backoff. Consistency failure → use best-effort updates with rollback on critical paths.

Working through these steps in order resolves the vast majority of production integration issues. We hope this guide helps you ship reliable Antigravity-powered applications with confidence.