Secret Manager
LiteLLM supports reading secrets from Azure Key Vault and Infisical
- Azure Key Vault
- Google Key Management Service
- Infisical Secret Manager
- .env Files
Azure Key Vault​
Quick Start​
### Instantiate Azure Key Vault Client ###
from azure.keyvault.secrets import SecretClient
from azure.identity import ClientSecretCredential
# Set your Azure Key Vault URI
KVUri = os.getenv("AZURE_KEY_VAULT_URI")
# Set your Azure AD application/client ID, client secret, and tenant ID - create an application with permission to call your key vault
client_id = os.getenv("AZURE_CLIENT_ID")
client_secret = os.getenv("AZURE_CLIENT_SECRET")
tenant_id = os.getenv("AZURE_TENANT_ID")
# Initialize the ClientSecretCredential
credential = ClientSecretCredential(client_id=client_id, client_secret=client_secret, tenant_id=tenant_id)
# Create the SecretClient using the credential
client = SecretClient(vault_url=KVUri, credential=credential)
### Connect to LiteLLM ###
import litellm
litellm.secret_manager = client
litellm.get_secret("your-test-key")
Usage with OpenAI Proxy Server​
- Install Proxy dependencies
pip install 'litellm[proxy]' 'litellm[extra_proxy]'
- Save Azure details in your environment
export["AZURE_CLIENT_ID"]="your-azure-app-client-id"
export["AZURE_CLIENT_SECRET"]="your-azure-app-client-secret"
export["AZURE_TENANT_ID"]="your-azure-tenant-id"
export["AZURE_KEY_VAULT_URI"]="your-azure-key-vault-uri"
- Add to proxy config.yaml
model_list:
- model_name: "my-azure-models" # model alias
litellm_params:
model: "azure/<your-deployment-name>"
api_key: "os.environ/AZURE-API-KEY" # reads from key vault - get_secret("AZURE_API_KEY")
api_base: "os.environ/AZURE-API-BASE" # reads from key vault - get_secret("AZURE_API_BASE")
general_settings:
use_azure_key_vault: True
You can now test this by starting your proxy:
litellm --config /path/to/config.yaml
Google Key Management Service​
Use encrypted keys from Google KMS on the proxy
Usage with OpenAI Proxy Server​
Step 1. Add keys to env​
export GOOGLE_APPLICATION_CREDENTIALS="/path/to/credentials.json"
export GOOGLE_KMS_RESOURCE_NAME="projects/*/locations/*/keyRings/*/cryptoKeys/*"
export PROXY_DATABASE_URL_ENCRYPTED=b'\n$\x00D\xac\xb4/\x8e\xc...'
Step 2: Update Config​
general_settings:
use_google_kms: true
database_url: "os.environ/PROXY_DATABASE_URL_ENCRYPTED"
master_key: sk-1234
Step 3: Start + test proxy​
$ litellm --config /path/to/config.yaml
And in another terminal
$ litellm --test
Infisical Secret Manager​
Integrates with Infisical's Secret Manager for secure storage and retrieval of API keys and sensitive data.
Usage​
liteLLM manages reading in your LLM API secrets/env variables from Infisical for you
import litellm
from infisical import InfisicalClient
litellm.secret_manager = InfisicalClient(token="your-token")
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What's the weather like today?"},
]
response = litellm.completion(model="gpt-3.5-turbo", messages=messages)
print(response)
.env Files​
If no secret manager client is specified, Litellm automatically uses the .env
file to manage sensitive data.