Together AI | liteLLM (original) (raw)

LiteLLM supports all models on Together AI.

API Keys

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

Sample Usage

from litellm import completion 

os.environ["TOGETHERAI_API_KEY"] = "your-api-key"

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

completion(model="together_ai/togethercomputer/Llama-2-7B-32K-Instruct", messages=messages)

Together AI Models

liteLLM supports non-streaming and streaming requests to all models on https://api.together.xyz/

Example TogetherAI Usage - Note: liteLLM supports all models deployed on TogetherAI

Llama LLMs - Chat

Model Name Function Call Required OS Variables
togethercomputer/llama-2-70b-chat completion('together_ai/togethercomputer/llama-2-70b-chat', messages) os.environ['TOGETHERAI_API_KEY']

Llama LLMs - Language / Instruct

Model Name Function Call Required OS Variables
togethercomputer/llama-2-70b completion('together_ai/togethercomputer/llama-2-70b', messages) os.environ['TOGETHERAI_API_KEY']
togethercomputer/LLaMA-2-7B-32K completion('together_ai/togethercomputer/LLaMA-2-7B-32K', messages) os.environ['TOGETHERAI_API_KEY']
togethercomputer/Llama-2-7B-32K-Instruct completion('together_ai/togethercomputer/Llama-2-7B-32K-Instruct', messages) os.environ['TOGETHERAI_API_KEY']
togethercomputer/llama-2-7b completion('together_ai/togethercomputer/llama-2-7b', messages) os.environ['TOGETHERAI_API_KEY']

Falcon LLMs

Model Name Function Call Required OS Variables
togethercomputer/falcon-40b-instruct completion('together_ai/togethercomputer/falcon-40b-instruct', messages) os.environ['TOGETHERAI_API_KEY']
togethercomputer/falcon-7b-instruct completion('together_ai/togethercomputer/falcon-7b-instruct', messages) os.environ['TOGETHERAI_API_KEY']

Alpaca LLMs

Model Name Function Call Required OS Variables
togethercomputer/alpaca-7b completion('together_ai/togethercomputer/alpaca-7b', messages) os.environ['TOGETHERAI_API_KEY']

Other Chat LLMs

Model Name Function Call Required OS Variables
HuggingFaceH4/starchat-alpha completion('together_ai/HuggingFaceH4/starchat-alpha', messages) os.environ['TOGETHERAI_API_KEY']

Code LLMs

Model Name Function Call Required OS Variables
togethercomputer/CodeLlama-34b completion('together_ai/togethercomputer/CodeLlama-34b', messages) os.environ['TOGETHERAI_API_KEY']
togethercomputer/CodeLlama-34b-Instruct completion('together_ai/togethercomputer/CodeLlama-34b-Instruct', messages) os.environ['TOGETHERAI_API_KEY']
togethercomputer/CodeLlama-34b-Python completion('together_ai/togethercomputer/CodeLlama-34b-Python', messages) os.environ['TOGETHERAI_API_KEY']
defog/sqlcoder completion('together_ai/defog/sqlcoder', messages) os.environ['TOGETHERAI_API_KEY']
NumbersStation/nsql-llama-2-7B completion('together_ai/NumbersStation/nsql-llama-2-7B', messages) os.environ['TOGETHERAI_API_KEY']
WizardLM/WizardCoder-15B-V1.0 completion('together_ai/WizardLM/WizardCoder-15B-V1.0', messages) os.environ['TOGETHERAI_API_KEY']
WizardLM/WizardCoder-Python-34B-V1.0 completion('together_ai/WizardLM/WizardCoder-Python-34B-V1.0', messages) os.environ['TOGETHERAI_API_KEY']

Language LLMs

Model Name Function Call Required OS Variables
NousResearch/Nous-Hermes-Llama2-13b completion('together_ai/NousResearch/Nous-Hermes-Llama2-13b', messages) os.environ['TOGETHERAI_API_KEY']
Austism/chronos-hermes-13b completion('together_ai/Austism/chronos-hermes-13b', messages) os.environ['TOGETHERAI_API_KEY']
upstage/SOLAR-0-70b-16bit completion('together_ai/upstage/SOLAR-0-70b-16bit', messages) os.environ['TOGETHERAI_API_KEY']
WizardLM/WizardLM-70B-V1.0 completion('together_ai/WizardLM/WizardLM-70B-V1.0', messages) os.environ['TOGETHERAI_API_KEY']

Prompt Templates

Using a chat model on Together AI with it's own prompt format?

Using Llama2 Instruct models

If you're using Together AI's Llama2 variants( model=togethercomputer/llama-2..-instruct), LiteLLM can automatically translate between the OpenAI prompt format and the TogetherAI Llama2 one ([INST]..[/INST]).

from litellm import completion 

# set env variable 
os.environ["TOGETHERAI_API_KEY"] = ""

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

completion(model="together_ai/togethercomputer/Llama-2-7B-32K-Instruct", messages=messages)

Using another model

You can create a custom prompt template on LiteLLM (and we welcome PRs to add them to the main repo 🤗)

Let's make one for OpenAssistant/llama2-70b-oasst-sft-v10!

The accepted template format is: Reference

"""
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
"""

Let's register our custom prompt template: Implementation Code

import litellm 

litellm.register_prompt_template(
        model="OpenAssistant/llama2-70b-oasst-sft-v10",
        roles={
            "system": {
                "pre_message": "[<|im_start|>system",
                "post_message": "\n"
            },
            "user": {
                "pre_message": "<|im_start|>user",
                "post_message": "\n"
            }, 
            "assistant": {
                "pre_message": "<|im_start|>assistant",
                "post_message": "\n"
            }
        }
    )

Let's use it!

from litellm import completion 

# set env variable 
os.environ["TOGETHERAI_API_KEY"] = ""

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

completion(model="together_ai/OpenAssistant/llama2-70b-oasst-sft-v10", messages=messages)

Complete Code

import litellm 
from litellm import completion

# set env variable 
os.environ["TOGETHERAI_API_KEY"] = ""

litellm.register_prompt_template(
        model="OpenAssistant/llama2-70b-oasst-sft-v10",
        roles={
            "system": {
                "pre_message": "[<|im_start|>system",
                "post_message": "\n"
            },
            "user": {
                "pre_message": "<|im_start|>user",
                "post_message": "\n"
            }, 
            "assistant": {
                "pre_message": "<|im_start|>assistant",
                "post_message": "\n"
            }
        }
    )

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

response = completion(model="together_ai/OpenAssistant/llama2-70b-oasst-sft-v10", messages=messages)

print(response)

Output

{
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": ".\n\nThe sky is a canvas of blue,\nWith clouds that drift and move,",
        "role": "assistant",
        "logprobs": null
      }
    }
  ],
  "created": 1693941410.482018,
  "model": "OpenAssistant/llama2-70b-oasst-sft-v10",
  "usage": {
    "prompt_tokens": 7,
    "completion_tokens": 16,
    "total_tokens": 23
  },
  "litellm_call_id": "f21315db-afd6-4c1e-b43a-0b5682de4b06"
}

Rerank

Usage

from litellm import rerank
import os

os.environ["TOGETHERAI_API_KEY"] = "sk-.."

query = "What is the capital of the United States?"
documents = [
    "Carson City is the capital city of the American state of Nevada.",
    "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean. Its capital is Saipan.",
    "Washington, D.C. is the capital of the United States.",
    "Capital punishment has existed in the United States since before it was a country.",
]

response = rerank(
    model="together_ai/rerank-english-v3.0",
    query=query,
    documents=documents,
    top_n=3,
)
print(response)