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{
"cells": [
{
"cell_type": "code",
"execution_count": 6,
"id": "1a305246-59d9-453e-9903-ca462611f1eb",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Product</th>\n",
" <th>Review</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Queen Size sheet Set</td>\n",
" <td>I ordered a king size set.</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Waterproof Phone Pcuch</td>\n",
" <td>I loved the waterproof sac</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Luxury Air Mattress</td>\n",
" <td>This mattress had a small hole in the top</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Pillows Insert</td>\n",
" <td>this is the best pillow filters on amazon</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Milk Frother Handheld\\nm</td>\n",
" <td>I loved this product But they only seem to I</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Product Review\n",
"0 Queen Size sheet Set I ordered a king size set.\n",
"1 Waterproof Phone Pcuch I loved the waterproof sac\n",
"2 Luxury Air Mattress This mattress had a small hole in the top\n",
"3 Pillows Insert this is the best pillow filters on amazon\n",
"4 Milk Frother Handheld\\nm I loved this product But they only seem to I"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import openai\n",
"import os\n",
"\n",
"from dotenv import load_dotenv, find_dotenv\n",
"_ = load_dotenv(find_dotenv())\n",
"import pandas as pd\n",
"\n",
"df = pd.read_csv('Data.csv')\n",
"df.head()\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "8f75bedd-2b00-466a-a00f-bc7c47f2f7a8",
"metadata": {},
"outputs": [],
"source": [
"from langchain.chat_models import ChatOpenAI\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain.chains import LLMChain"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "edc76aa3-1d1f-41d2-93a9-8297268817ea",
"metadata": {},
"outputs": [],
"source": [
"llm = ChatOpenAI(temperature=0.9)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "27f2d3c9-9601-4b31-8d35-bae9538ee2a0",
"metadata": {},
"outputs": [],
"source": [
"prompt = ChatPromptTemplate.from_template(\"what is the best name to describe a company that make {product}\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "03ef9080-77ba-4406-a402-e4d5b889be47",
"metadata": {},
"outputs": [],
"source": [
"chain = LLMChain(llm=llm, prompt=prompt)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "0a172ea1-18ce-407b-bcd9-b4146c5f5610",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\"1. Royal Rest\\n2. Majestic Beddings\\n3. Luxurio Linens\\n4. Queen's Haven\\n5. Dreamy Slumber\\n6. Palace Sheets\\n7. Regal Comfort\\n8. Crowned Beddings\\n9. Serene Sleep\\n10. Imperial Linens\""
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"product = \"Queen Size Sheet Set\"\n",
"chain.run(product)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b0ff950c-1c09-4ba5-8661-626fb69b24ca",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.4"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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