Banana

Banana is focused on building the machine learning infrastructure.

This example goes over how to use LangChain to interact with Banana models

##Installing the langchain packages needed to use the integration
%pip install -qU  langchain-community

# Install the package  https://docs.banana.dev/banana-docs/core-concepts/sdks/python
%pip install --upgrade --quiet  banana-dev

# get new tokens: https://app.banana.dev/
# We need three parameters to make a Banana.dev API call:
# * a team api key
# * the model's unique key
# * the model's url slug

import os

# You can get this from the main dashboard
# at https://app.banana.dev
os.environ["BANANA_API_KEY"] = "YOUR_API_KEY"
# OR
# BANANA_API_KEY = getpass()

from langchain.chains import LLMChain
from langchain_community.llms import Banana
from langchain_core.prompts import PromptTemplate

API Reference:LLMChain | Banana | PromptTemplate

template = """Question: {question}

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

prompt = PromptTemplate.from_template(template)

# Both of these are found in your model's
# detail page in https://app.banana.dev
llm = Banana(model_key="YOUR_MODEL_KEY", model_url_slug="YOUR_MODEL_URL_SLUG")

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

question = "What NFL team won the Super Bowl in the year Justin Beiber was born?"

llm_chain.run(question)

Related

• LLM conceptual guide
• LLM how-to guides