Llama API

This notebook shows how to use LangChain with LlamaAPI - a hosted version of Llama2 that adds in support for function calling.

!pip install -U llamaapi

In [2]:

from llamaapi import LlamaAPI

# Replace 'Your_API_Token' with your actual API token
llama = LlamaAPI('Your_API_Token')

In [4]:

from langchain_experimental.llms import ChatLlamaAPI

/Users/harrisonchase/.pyenv/versions/3.9.1/envs/langchain/lib/python3.9/site-packages/deeplake/util/check_latest_version.py:32: UserWarning: A newer version of deeplake (3.6.12) is available. It's recommended that you update to the latest version using `pip install -U deeplake`.
  warnings.warn(

In [5]:

model = ChatLlamaAPI(client=llama)

In [6]:

from langchain.chains import create_tagging_chain

schema = {
    "properties": {
        "sentiment": {"type": "string", 'description': 'the sentiment encountered in the passage'},
        "aggressiveness": {"type": "integer", 'description': 'a 0-10 score of how aggressive the passage is'},
        "language": {"type": "string", 'description': 'the language of the passage'},
    }
}

chain = create_tagging_chain(schema, model)

In [7]:

chain.run("give me your money")

Out [7]:

{'sentiment': 'aggressive', 'aggressiveness': 8}

In [ ]:

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Llama API

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