116 lines
3.2 KiB
Plaintext
116 lines
3.2 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "44aba2a0-c6eb-4fc1-a5cc-0a8f8679dbb8",
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"metadata": {},
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"source": [
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"## Far Far Away..."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d4d58124-5e9a-4f5a-9e0a-ff74f43896a8",
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"metadata": {},
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"outputs": [],
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"source": [
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"# imports\n",
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"\n",
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"import os\n",
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"import requests\n",
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"from dotenv import load_dotenv\n",
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"from bs4 import BeautifulSoup\n",
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"from IPython.display import Markdown, display\n",
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"from openai import OpenAI\n",
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"\n",
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"# Load environment variables in a file called .env\n",
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"\n",
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"load_dotenv(override=True)\n",
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"api_key = os.getenv('OPENAI_API_KEY')\n",
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"\n",
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"openai = OpenAI()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "33179b68-7ed5-46ab-b583-d67ed57cd39d",
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"metadata": {},
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"outputs": [],
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"source": [
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"def add_user_greeting(greeting):\n",
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" user_prompt = \"\"\"\n",
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" The following is the greeting from the user. Please respond in character as a barman in the Mos Eisley Cantina.\\n\\n\n",
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" \"\"\"\n",
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" user_prompt += greeting\n",
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"\n",
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" return user_prompt"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "67dc3099-2ccc-4ee8-8ff2-0dbbe4ae2fcb",
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"metadata": {},
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"outputs": [],
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"source": [
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"def approach_the_bar(greeting):\n",
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"\n",
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" system_prompt = \"You are a barman in the Mos Eisley Cantina from the Star Wars universe.\\\n",
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"It is a Tuesday evening, the year is 3BBY, and the Cantina is quiet except for a few lonely regulars.\\\n",
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"The barman (you) is slightly skeptical but eager to share some interesting news regarding some nearby imperial activity.\\\n",
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"You will recieve a greeting from the user, you must respond and provide them with some gossip detailing \\\n",
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"some local shady dealings occuring in Mos Eisley. Please format your response using markdown to provide a sense of the conversation.\"\n",
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"\n",
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" user_prompt = add_user_greeting(greeting)\n",
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" \n",
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" messages = [\n",
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" {\"role\": \"system\", \"content\": system_prompt},\n",
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" {\"role\": \"user\", \"content\": user_prompt},\n",
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" ]\n",
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" \n",
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" response = openai.chat.completions.create(\n",
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" model = \"gpt-4o-mini\",\n",
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" messages = messages\n",
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" )\n",
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" \n",
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" # Step 4: print the result in markdown format\n",
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" pretty_response = Markdown(response.choices[0].message.content)\n",
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" display(pretty_response)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "fb47e2b7-5509-4d1a-8e71-ff103fc8a885",
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"metadata": {},
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"outputs": [],
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"source": [
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"approach_the_bar(\"\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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