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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"id": "95d56fde-3f1a-482f-aa25-40687d16e5dc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{\n",
" \"books\": [\n",
" {\n",
" \"book_id\": 1,\n",
" \"title\": \"The Enigma of Elysium\",\n",
" \"author\": \"Aria Nightshade\",\n",
" \"genre\": \"Fantasy\"\n",
" },\n",
" {\n",
" \"book_id\": 2,\n",
" \"title\": \"Shadows of Serendipity\",\n",
" \"author\": \"Elijah Blackwood\",\n",
" \"genre\": \"Mystery\"\n",
" },\n",
" {\n",
" \"book_id\": 3,\n",
" \"title\": \"Whispers in the Wind\",\n",
" \"author\": \"Luna Silvermoon\",\n",
" \"genre\": \"Romance\"\n",
" }\n",
" ]\n",
"}\n"
]
}
],
"source": [
"\n",
"import openai\n",
"import os\n",
"\n",
"openai.api_key = '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'\n",
"MODEL_NAME = 'gpt-3.5-turbo'\n",
"\n",
"# TEXT = f\"\"\"\n",
"# You should express what you want a model to do by \\\n",
"# providing instructions that are as clear and \\\n",
"# specific as you can possibly make them. \\\n",
"# This will guide the model towards the desired output, \\\n",
"# and reduce the chances of receiving irrelevent \\\n",
"# or incorrec5 responses. Don't confuse writing a \\\n",
"# clear prompt with writing a short prompt. \\\n",
"# In many case, longer prompts provide more clearity \\\n",
"# and context for the model, which can lead to \\\n",
"# more detailed and relevant outputs.\n",
"# \"\"\"\n",
"\n",
"# PROMPT = f\"\"\"\n",
"# summarize the text delimited by triple backticks\\\n",
"# into a single sentence.\n",
"# ```{TEXT}```\n",
"# \"\"\"\n",
"\n",
"PROMPT = f\"\"\"\n",
"Generate a list of three made-up book titles along \\\n",
"with their authors and genres.\n",
"Provide them in JSON format with the following keys:\n",
"book_id, title, author, genre.\n",
"\"\"\"\n",
"\n",
"class Assignment4:\n",
" input_val = ''\n",
" def __init__(self, model):\n",
" self.model = model\n",
" \n",
" def get_input(self):\n",
" self.input_val = input('Enter your message')\n",
"\n",
" def get_completion(self, prompt):\n",
" messages = [{\n",
" 'role': 'user',\n",
" 'content': prompt\n",
" }]\n",
" response = openai.ChatCompletion.create(\n",
" model=self.model,\n",
" messages=messages,\n",
" temperature=0\n",
" )\n",
" return response.choices[0].message['content']\n",
"\n",
" \n",
"obj = Assignment4(MODEL_NAME)\n",
"print(obj.get_completion(PROMPT))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fc90ad16-7a94-42ef-bdd4-9ec176da6210",
"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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