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Multiple Instances

Load balance multiple instances of the same model

The proxy will handle routing requests (using LiteLLM's Router). Set rpm in the config if you want maximize throughput

info

For more details on routing strategies / params, see Routing

Load Balancing using multiple litellm instances (Kubernetes, Auto Scaling)

LiteLLM Proxy supports sharing rpm/tpm shared across multiple litellm instances, pass redis_host, redis_password and redis_port to enable this. (LiteLLM will use Redis to track rpm/tpm usage )

Example config

model_list:
- model_name: gpt-3.5-turbo
litellm_params:
model: azure/<your-deployment-name>
api_base: <your-azure-endpoint>
api_key: <your-azure-api-key>
rpm: 6 # Rate limit for this deployment: in requests per minute (rpm)
- model_name: gpt-3.5-turbo
litellm_params:
model: azure/gpt-turbo-small-ca
api_base: https://my-endpoint-canada-berri992.openai.azure.com/
api_key: <your-azure-api-key>
rpm: 6
router_settings:
redis_host: <your redis host>
redis_password: <your redis password>
redis_port: 1992

Router settings on config - routing_strategy, model_group_alias

Expose an 'alias' for a 'model_name' on the proxy server.

model_group_alias: {
"gpt-4": "gpt-3.5-turbo"
}

These aliases are shown on /v1/models, /v1/model/info, and /v1/model_group/info by default.

litellm.Router() settings can be set under router_settings. You can set model_group_alias, routing_strategy, num_retries,timeout . See all Router supported params here

Usage

Example config with router_settings

model_list:
- model_name: gpt-3.5-turbo
litellm_params:
model: azure/<your-deployment-name>
api_base: <your-azure-endpoint>
api_key: <your-azure-api-key>

router_settings:
model_group_alias: {"gpt-4": "gpt-3.5-turbo"} # all requests with `gpt-4` will be routed to models

Hide Alias Models

Use this if you want to set-up aliases for:

  1. typos
  2. minor model version changes
  3. case sensitive changes between updates
model_list:
- model_name: gpt-3.5-turbo
litellm_params:
model: azure/<your-deployment-name>
api_base: <your-azure-endpoint>
api_key: <your-azure-api-key>

router_settings:
model_group_alias:
"GPT-3.5-turbo": # alias
model: "gpt-3.5-turbo" # Actual model name in 'model_list'
hidden: true # Exclude from `/v1/models`, `/v1/model/info`, `/v1/model_group/info`

Complete Spec

model_group_alias: Optional[Dict[str, Union[str, RouterModelGroupAliasItem]]] = {}


class RouterModelGroupAliasItem(TypedDict):
model: str
hidden: bool # if 'True', don't return on `/v1/models`, `/v1/model/info`, `/v1/model_group/info`