from portkey_ai import Portkey
# Initialize the Portkey client
portkey = Portkey(
api_key="PORTKEY_API_KEY",
)
# Get a specific virtual key
virtual_key = portkey.virtual_keys.retrieve(
slug='VIRTUAL_KEY_SLUG'
)
print(virtual_key){
"id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"organisation_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"ai_provider_id": "<string>",
"name": "<string>",
"created_at": "2023-11-07T05:31:56Z",
"last_updated_at": "2023-11-07T05:31:56Z",
"slug": "<string>",
"description": "<string>",
"masked_key": "<string>",
"configurations": {
"openai_organization": "<string>",
"openai_project": "<string>"
},
"global_workspace_access_settings": {
"enabled": true,
"usage_limits": [
{
"credit_limit": 10,
"periodic_reset": "monthly",
"alert_threshold": 8
}
],
"rate_limits": [
{
"value": 123
}
]
},
"allow_all_models": true,
"workspace_count": 123,
"secret_mappings": [
{
"target_field": "key",
"secret_reference_id": "my-aws-secret",
"secret_key": "<string>"
}
]
}Retrieve Integration
GET
/
integrations
/
{slug}
from portkey_ai import Portkey
# Initialize the Portkey client
portkey = Portkey(
api_key="PORTKEY_API_KEY",
)
# Get a specific virtual key
virtual_key = portkey.virtual_keys.retrieve(
slug='VIRTUAL_KEY_SLUG'
)
print(virtual_key){
"id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"organisation_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"ai_provider_id": "<string>",
"name": "<string>",
"created_at": "2023-11-07T05:31:56Z",
"last_updated_at": "2023-11-07T05:31:56Z",
"slug": "<string>",
"description": "<string>",
"masked_key": "<string>",
"configurations": {
"openai_organization": "<string>",
"openai_project": "<string>"
},
"global_workspace_access_settings": {
"enabled": true,
"usage_limits": [
{
"credit_limit": 10,
"periodic_reset": "monthly",
"alert_threshold": 8
}
],
"rate_limits": [
{
"value": 123
}
]
},
"allow_all_models": true,
"workspace_count": 123,
"secret_mappings": [
{
"target_field": "key",
"secret_reference_id": "my-aws-secret",
"secret_key": "<string>"
}
]
}Documentation Index
Fetch the complete documentation index at: https://portkey-docs-small-fix-agent-registry.mintlify.app/llms.txt
Use this file to discover all available pages before exploring further.
Authorizations
Path Parameters
Response
200 - application/json
Successful response
Available options:
active, archived Available options:
integration Masked API key
Provider-specific configuration object
⚠️ Security Note - Response Masking: When retrieving integration details, sensitive fields are automatically masked:
- Sensitive fields get a
masked_prefix (e.g.,client_secret→masked_client_secret) - Non-sensitive fields (IDs, URLs, regions, etc.) remain unchanged
- OpenAI
- Azure OpenAI
- AWS Bedrock
- Vertex AI
- Azure AI
- Workers AI
- AWS Sagemaker
- Hugginface
- Cortex
- Custom Base URL
Show child attributes
Show child attributes
Global workspace access configuration
Show child attributes
Show child attributes
Whether new models will be enabled by default
Number of workspaces with access to this integration
Secret reference mappings for this integration. Valid target_field values are "key" or "configurations.".
Show child attributes
Show child attributes
Last modified on April 8, 2026
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