AI21

LiteLLM supports the following AI21 models:

• jamba-1.5-mini
• jamba-1.5-large
• j2-light
• j2-mid
• j2-ultra

tip

We support ALL AI21 models, just set model=ai21/<any-model-on-ai21> as a prefix when sending litellm requests. See all litellm supported AI21 models here

API KEYS

import os 
os.environ["AI21_API_KEY"] = "your-api-key"

LiteLLM Python SDK Usage

Sample Usage

from litellm import completion 

# set env variable 
os.environ["AI21_API_KEY"] = "your-api-key"

messages = [{"role": "user", "content": "Write me a poem about the blue sky"}]

completion(model="ai21/jamba-1.5-mini", messages=messages)

LiteLLM Proxy Server Usage

Here's how to call a ai21 model with the LiteLLM Proxy Server

1. Modify the config.yaml

   model_list:
     - model_name: my-model
       litellm_params:
         model: ai21/<your-model-name>  # add ai21/ prefix to route as ai21 provider
         api_key: api-key                 # api key to send your model

2. Start the proxy

   $ litellm --config /path/to/config.yaml

3. Send Request to LiteLLM Proxy Server

   OpenAI Python v1.0.0+

   import openai
   client = openai.OpenAI(
       api_key="sk-1234",             # pass litellm proxy key, if you're using virtual keys
       base_url="http://0.0.0.0:4000" # litellm-proxy-base url
   )
   
   response = client.chat.completions.create(
       model="my-model",
       messages = [
           {
               "role": "user",
               "content": "what llm are you"
           }
       ],
   )
   
   print(response)

   curl

   curl --location 'http://0.0.0.0:4000/chat/completions' \
       --header 'Authorization: Bearer sk-1234' \
       --header 'Content-Type: application/json' \
       --data '{
       "model": "my-model",
       "messages": [
           {
           "role": "user",
           "content": "what llm are you"
           }
       ],
   }'

Supported OpenAI Parameters

param	type	AI21 equivalent
tools	Optional[list]	tools
response_format	Optional[dict]	response_format
max_tokens	Optional[int]	max_tokens
temperature	Optional[float]	temperature
top_p	Optional[float]	top_p
stop	Optional[Union[str, list]]	stop
n	Optional[int]	n
stream	Optional[bool]	stream
seed	Optional[int]	seed
tool_choice	Optional[str]	tool_choice
user	Optional[str]	user

Supported AI21 Parameters

param	type	AI21 equivalent
documents	Optional[List[Dict]]	documents

Passing AI21 Specific Parameters - documents

LiteLLM allows you to pass all AI21 specific parameters to the litellm.completion function. Here is an example of how to pass the documents parameter to the litellm.completion function.

LiteLLM Python SDK

response = await litellm.acompletion(
    model="jamba-1.5-large",
    messages=[{"role": "user", "content": "what does the document say"}],
    documents = [
        {
            "content": "hello world",
            "metadata": {
                "source": "google",
                "author": "ishaan"
            }
        }
    ]
)

LiteLLM Proxy Server

import openai
client = openai.OpenAI(
    api_key="sk-1234",             # pass litellm proxy key, if you're using virtual keys
    base_url="http://0.0.0.0:4000" # litellm-proxy-base url
)

response = client.chat.completions.create(
    model="my-model",
    messages = [
        {
            "role": "user",
            "content": "what llm are you"
        }
    ],
    extra_body = {
        "documents": [
            {
                "content": "hello world",
                "metadata": {
                    "source": "google",
                    "author": "ishaan"
                }
            }
        ]
    }
)

print(response)

tip

We support ALL AI21 models, just set model=ai21/<any-model-on-ai21> as a prefix when sending litellm requests See all litellm supported AI21 models here

AI21 Models

Model Name	Function Call	Required OS Variables
jamba-1.5-mini	completion('jamba-1.5-mini', messages)	os.environ['AI21_API_KEY']
jamba-1.5-large	completion('jamba-1.5-large', messages)	os.environ['AI21_API_KEY']
j2-light	completion('j2-light', messages)	os.environ['AI21_API_KEY']
j2-mid	completion('j2-mid', messages)	os.environ['AI21_API_KEY']
j2-ultra	completion('j2-ultra', messages)	os.environ['AI21_API_KEY']