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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,177 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import openai" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 2, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from dotenv import dotenv_values\n", | ||
| "config = dotenv_values(\".env\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 6, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "openai.api_key = config[\"OPENAI_API_KEY\"]" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "reply = openai.ChatCompletion.create(\n", | ||
| " model=\"gpt-3.5-turbo\",\n", | ||
| " messages=[\n", | ||
| " { \"role\": \"user\", \"content\": \"tell me a joke\" }\n", | ||
| " ]\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "print(reply.choices[O].message.content)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# https://platform.openai.com/docs/guides/chat/chat-vs-completions\n", | ||
| "\n", | ||
| "openai.ChatCompletion.create(\n", | ||
| " model=\"gpt-3.5-turbo\",\n", | ||
| " messages=[\n", | ||
| " # {\"role\": \"system\", \"content\": \"You are a helpful assistant that translates English to French.\"},\n", | ||
| " # {\"role\": \"user\", \"content\": 'Translate the following English text to French: \"I want a dog\"'}\n", | ||
| " {\"role\": \"user\", \"content\": 'Translate the following English text to French: \"I want a dog\"'}\n", | ||
| " ]\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "\n", | ||
| "openai.ChatCompletion.create(\n", | ||
| " model=\"gpt-3.5-turbo\",\n", | ||
| " messages=[\n", | ||
| " {\"role\": \"system\", \"content\": \"You are a helpful assistant that classifies the sentiment in text as either positive, neutral, or negative.\"},\n", | ||
| " {\"role\": \"user\", \"content\": 'Classify the sentiment in the following text: \"I really love chicken biryani\"'},\n", | ||
| " {\"role\": \"assistant\", \"content\": \"Positive\" },\n", | ||
| " {\"role\": \"user\", \"content\": 'Classify the sentiment in the following text: \"I have a complicated relationship with cat\"'},\n", | ||
| " ]\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 6, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from IPython.display import Markdown, display\n", | ||
| "import json\n", | ||
| "\n", | ||
| "def display_colors(colors):\n", | ||
| " display(Markdown(\" \".join(\n", | ||
| " f'<span style=\"color: {color}\">{chr(9608) * 4}</span>'\n", | ||
| " for color in colors\n", | ||
| " )))" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 7, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "def get_and_render_colors(query):\n", | ||
| " messages = [\n", | ||
| " { \"role\": \"system\", \"content\": \"You are a color palette generating assistant that responds to text prompts for color palettes. You should generate color palettes that fit the theme, mood, or instructions in the prompt. The palettes should be between 2 and 8 colors.\" },\n", | ||
| " { \"role\": \"user\", \"content\": \"Convert the following verbal description of a color palette into a list of colors: The Meditation\" },\n", | ||
| " { \"role\": \"assistant\", \"content\": '[\"#594F4F\", \"#A1887F\", \"#BCAAA4\", \"#81C784\", \"#455A64\"]' },\n", | ||
| " { \"role\": \"user\", \"content\": \"Convert the following verbal description of a color palette into a list of colors: The Mediterranean Sea\" },\n", | ||
| " { \"role\": \"assistant\", \"content\": '[\"#1A237E\", \"#1565C0\", \"#1E88E5\", \"#90CAF9\", \"#E1F5FE\"]' },\n", | ||
| " { \"role\": \"user\", \"content\": f\"Convert the following verbal description of a color palette into a list of colors: {query}\"}\n", | ||
| " ]\n", | ||
| "\n", | ||
| " response = openai.ChatCompletion.create(\n", | ||
| " model=\"gpt-3.5-turbo\",\n", | ||
| " messages=messages,\n", | ||
| " max_tokens=100 # default to infinite, provide it!\n", | ||
| " )\n", | ||
| "\n", | ||
| " colors = json.loads(response[\"choices\"][0].message.content)\n", | ||
| " display_colors(colors)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 8, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/markdown": [ | ||
| "<span style=\"color: #4285F4\">████</span> <span style=\"color: #DB4437\">████</span> <span style=\"color: #F4B400\">████</span> <span style=\"color: #0F9D58\">████</span>" | ||
| ], | ||
| "text/plain": [ | ||
| "<IPython.core.display.Markdown object>" | ||
| ] | ||
| }, | ||
| "metadata": {}, | ||
| "output_type": "display_data" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "get_and_render_colors(\"4 google brand colors\")" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": ".venv", | ||
| "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": "3.10.5" | ||
| }, | ||
| "orig_nbformat": 4 | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } |
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