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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Banana\n",
"This example goes over how to use LangChain to interact with Banana models"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"from langchain.llms import Banana\n",
"from langchain import PromptTemplate, LLMChain\n",
"os.environ[\"BANANA_API_KEY\"] = \"YOUR_API_KEY\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"template = \"\"\"Question: {question}\n",
"\n",
"Answer: Let's think step by step.\"\"\"\n",
"\n",
"prompt = PromptTemplate(template=template, input_variables=[\"question\"])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"llm = Banana(model_key=\"YOUR_MODEL_KEY\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"llm_chain = LLMChain(prompt=prompt, llm=llm)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"question = \"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\n",
"\n",
"llm_chain.run(question)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.9.12 ('palm')",
"language": "python",
"name": "python3"
},
"language_info": {
"name": "python",
"version": "3.9.12"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "a0a0263b650d907a3bfe41c0f8d6a63a071b884df3cfdc1579f00cdc1aed6b03"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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