Usage
To use Google Cloud Vertex AI Vector Search with zentry
, you need to configure the vector_store
in your zentry
config:
import os
from zentry import Memory
os.environ["GEMINI_API_KEY"] = = "sk-xx"
config = {
"vector_store": {
"provider": "vertex_ai_vector_search",
"config": {
"endpoint_id": "YOUR_ENDPOINT_ID", # Required: Vector Search endpoint ID
"index_id": "YOUR_INDEX_ID", # Required: Vector Search index ID
"deployment_index_id": "YOUR_DEPLOYMENT_INDEX_ID", # Required: Deployment-specific ID
"project_id": "YOUR_PROJECT_ID", # Required: Google Cloud project ID
"project_number": "YOUR_PROJECT_NUMBER", # Required: Google Cloud project number
"region": "YOUR_REGION", # Optional: Defaults to GOOGLE_CLOUD_REGION
"credentials_path": "path/to/credentials.json", # Optional: Defaults to GOOGLE_APPLICATION_CREDENTIALS
"vector_search_api_endpoint": "YOUR_API_ENDPOINT" # Required for get operations
}
}
}
m = Memory.from_config(config)
m.add("Your text here", user_id="user", metadata={"category": "example"})
Required Parameters
Parameter | Description | Required |
---|
endpoint_id | Vector Search endpoint ID | Yes |
index_id | Vector Search index ID | Yes |
deployment_index_id | Deployment-specific index ID | Yes |
project_id | Google Cloud project ID | Yes |
project_number | Google Cloud project number | Yes |
vector_search_api_endpoint | Vector search API endpoint | Yes (for get operations) |
region | Google Cloud region | No (defaults to GOOGLE_CLOUD_REGION) |
credentials_path | Path to service account credentials | No (defaults to GOOGLE_APPLICATION_CREDENTIALS) |