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Documentation Index

Fetch the complete documentation index at: https://docs.langchain.com/llms.txt

Use this file to discover all available pages before exploring further.

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 -qU  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_classic.chains import LLMChain
from langchain_community.llms import Banana
from langchain_core.prompts import 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)