Model Alias

The model name you show an end-user might be different from the one you pass to LiteLLM - e.g. Displaying GPT-3.5 while calling gpt-3.5-turbo-16k on the backend.

LiteLLM simplifies this by letting you pass in a model alias mapping.

expected format

litellm.model_alias_map = {
    # a dictionary containing a mapping of the alias string to the actual litellm model name string
    "model_alias": "litellm_model_name"
}

usage

Relevant Code

model_alias_map = {
    "GPT-3.5": "gpt-3.5-turbo-16k",
    "llama2": "replicate/llama-2-70b-chat:2796ee9483c3fd7aa2e171d38f4ca12251a30609463dcfd4cd76703f22e96cdf"
}

litellm.model_alias_map = model_alias_map

Complete Code

import litellm 
from litellm import completion 


## set ENV variables
os.environ["OPENAI_API_KEY"] = "openai key"
os.environ["REPLICATE_API_KEY"] = "cohere key"

## set model alias map
model_alias_map = {
    "GPT-3.5": "gpt-3.5-turbo-16k",
    "llama2": "replicate/llama-2-70b-chat:2796ee9483c3fd7aa2e171d38f4ca12251a30609463dcfd4cd76703f22e96cdf"
}

litellm.model_alias_map = model_alias_map

messages = [{ "content": "Hello, how are you?","role": "user"}]

# openai call
response = completion(model="GPT-3.5", messages=messages)

# replicate call
response = completion("llama2", messages)

no-code

If you use litellm client, you can also do this without going into code. Learn more