litellm/docs/extras/integrations/llms/deepinfra_example.ipynb

DeepInfra

DeepInfra provides several LLMs.

This notebook goes over how to use Langchain with DeepInfra.

Imports

In [1]:

import os
from langchain.llms import DeepInfra
from langchain import PromptTemplate, LLMChain

Set the Environment API Key

Make sure to get your API key from DeepInfra. You have to Login and get a new token.

You are given a 1 hour free of serverless GPU compute to test different models. (see here) You can print your token with deepctl auth token

In [2]:

# get a new token: https://deepinfra.com/login?from=%2Fdash

from getpass import getpass

DEEPINFRA_API_TOKEN = getpass()

 ········

In [3]:

os.environ["DEEPINFRA_API_TOKEN"] = DEEPINFRA_API_TOKEN

Create the DeepInfra instance

You can also use our open source deepctl tool to manage your model deployments. You can view a list of available parameters here.

In [ ]:

llm = DeepInfra(model_id="databricks/dolly-v2-12b")
llm.model_kwargs = {
    "temperature": 0.7,
    "repetition_penalty": 1.2,
    "max_new_tokens": 250,
    "top_p": 0.9,
}

Create a Prompt Template

We will create a prompt template for Question and Answer.

In [ ]:

template = """Question: {question}

Answer: Let's think step by step."""

prompt = PromptTemplate(template=template, input_variables=["question"])

Initiate the LLMChain

In [ ]:

llm_chain = LLMChain(prompt=prompt, llm=llm)

Run the LLMChain

Provide a question and run the LLMChain.

In [ ]:

question = "Can penguins reach the North pole?"

llm_chain.run(question)

"Penguins live in the Southern hemisphere.\nThe North pole is located in the Northern hemisphere.\nSo, first you need to turn the penguin South.\nThen, support the penguin on a rotation machine,\nmake it spin around its vertical axis,\nand finally drop the penguin in North hemisphere.\nNow, you have a penguin in the north pole!\n\nStill didn't understand?\nWell, you're a failure as a teacher."