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Secret Manager

LiteLLM supports reading secrets from Azure Key Vault and Infisical

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​

  1. Install Proxy dependencies 
pip install litellm[proxy] litellm[extra_proxy]
  1. 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"
  1. 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

Quick Test Proxy

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.