{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "de23bb9e-37c5-4377-9a82-d7b6c648eeb6", "metadata": {}, "outputs": [], "source": [ "# imports\n", "\n", "from dotenv import load_dotenv\n", "import anthropic\n", "import requests\n", "from bs4 import BeautifulSoup\n", "from selenium import webdriver\n", "from selenium.webdriver.chrome.options import Options\n", "import os\n", "import json\n", "from typing import List\n", "from dotenv import load_dotenv\n", "from IPython.display import Markdown, display, update_display\n", "from openai import OpenAI\n", "import gradio as gr # oh yeah!" ] }, { "cell_type": "code", "execution_count": 2, "id": "1179b4c5-cd1f-4131-a876-4c9f3f38d2ba", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "OpenAI API Key exists and begins sk-proj-\n", "Anthropic API Key exists and begins sk-ant-\n" ] } ], "source": [ "# Load environment variables in a file called .env\n", "# Print the key prefixes to help with any debugging\n", "\n", "load_dotenv(override=True)\n", "openai_api_key = os.getenv('OPENAI_API_KEY')\n", "anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n", "\n", "if openai_api_key:\n", " print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n", "else:\n", " print(\"OpenAI API Key not set\")\n", " \n", "if anthropic_api_key:\n", " print(f\"Anthropic API Key exists and begins {anthropic_api_key[:7]}\")\n", "else:\n", " print(\"Anthropic API Key not set\")" ] }, { "cell_type": "code", "execution_count": 3, "id": "797fe7b0-ad43-42d2-acf0-e4f309b112f0", "metadata": {}, "outputs": [], "source": [ "# Connect to OpenAI, Anthropic\n", "\n", "openai = OpenAI()\n", "\n", "claude = anthropic.Anthropic()" ] }, { "cell_type": "code", "execution_count": 4, "id": "bcb54183-45d3-4d08-b5b6-55e380dfdf1b", "metadata": {}, "outputs": [], "source": [ "gpt_model = \"gpt-4o-mini\"\n", "claude_model = \"claude-3-haiku-20240307\"\n", "\n", "gpt_name=\"GPT\"\n", "claude_name=\"Claude\"\n" ] }, { "cell_type": "code", "execution_count": 5, "id": "1df47dc7-b445-4852-b21b-59f0e6c2030f", "metadata": {}, "outputs": [], "source": [ "def call_gpt(Language, Genre, gpt_messages, claude_messages, Remarks):\n", " \n", " if Remarks == \"\":\n", " # print(\"remarks is not there\")\n", " gpt_system = f\"You are a chatbot who is a short story writer; Your name is g1. \\\n", " Please write a story in markdown in {Language} , the genre being {Genre}. \\\n", " Please also incorporate feedback such as areas of improvement (if any) coming from the user \\\n", " and only publish the improved version without any extra comments.\"\n", " else :\n", " # print(\"remarks is there\")\n", " gpt_system = f\"You are a chatbot who is a short story writer; Your name is g1. \\\n", " Please write a story in markdown in {Language} , the genre being {Genre}. \\\n", " The story should consist {Remarks}\\\n", " Please also incorporate feedback such as areas of improvement (if any) coming from the user \\\n", " and only publish the improved version without any extra comments.\"\n", " \n", " messages = [{\"role\": \"system\", \"content\": gpt_system}]\n", " for gpt, claude in zip(gpt_messages, claude_messages):\n", " messages.append({\"role\": \"assistant\", \"content\": gpt})\n", " messages.append({\"role\": \"user\", \"content\": claude})\n", " # print(messages)\n", " \n", " completion = openai.chat.completions.create(\n", " model=gpt_model,\n", " messages=messages\n", " )\n", " return completion.choices[0].message.content\n", " \n", " # stream = openai.chat.completions.create(\n", " # model=gpt_model,\n", " # messages=messages,\n", " # stream=True\n", " # )\n", " # result = \"\"\n", " # for chunk in stream:\n", " # result += chunk.choices[0].delta.content or \"\"\n", " # yield result" ] }, { "cell_type": "code", "execution_count": 6, "id": "9dc6e913-02be-4eb6-9581-ad4b2cffa606", "metadata": {}, "outputs": [], "source": [ "# call_gpt()" ] }, { "cell_type": "code", "execution_count": 7, "id": "7d2ed227-48c9-4cad-b146-2c4ecbac9690", "metadata": {}, "outputs": [], "source": [ "def call_claude(Language, Genre, gpt_messages, claude_messages):\n", "\n", " claude_system = f\"You are a chatbot who is a short story analyser; Your name is c1. \\\n", " You will accept an input story in {Genre} genre and {Language} language and publish only the areas of improvement if you find any with no other comments\"\n", " \n", " messages1 = []\n", " for gpt, claude1 in zip(gpt_messages, claude_messages):\n", " messages1.append({\"role\": \"user\", \"content\": gpt})\n", " messages1.append({\"role\": \"assistant\", \"content\": claude1})\n", " messages1.append({\"role\": \"user\", \"content\": gpt_messages[-1]})\n", " # print(messages1)\n", " message = claude.messages.create(\n", " model=claude_model,\n", " system=claude_system,\n", " messages=messages1,\n", " max_tokens=500\n", " )\n", " return message.content[0].text\n", "\n", " # result = claude.messages.stream(\n", " # model=claude_model,\n", " # max_tokens=1000,\n", " # temperature=0.7,\n", " # system=claude_system,\n", " # messages=messages\n", " # )\n", " # response = \"\"\n", " # with result as stream:\n", " # for text in stream.text_stream:\n", " # response += text or \"\"\n", " # yield response\n", "\n", " " ] }, { "cell_type": "code", "execution_count": 8, "id": "0275b97f-7f90-4696-bbf5-b6642bd53cbd", "metadata": {}, "outputs": [], "source": [ "def Write_Me(Language, Genre, Iterations, Remarks):\n", " \n", " gpt_messages = [\"Hi I will share a story now!!\"]\n", " claude_messages = [\"Please share, I will critique the story.\"]\n", " \n", " print(f\"{gpt_name}:\\n{gpt_messages[0]}\\n\")\n", " print(f\"{claude_name}:\\n{claude_messages[0]}\\n\")\n", "\n", " for i in range(int(Iterations)):\n", " gpt_next = call_gpt(Language, Genre, gpt_messages, claude_messages, Remarks)\n", " print(f\"{gpt_name}:\\n{gpt_next}\\n\")\n", " # yield gpt_next\n", " gpt_messages.append(gpt_next)\n", " \n", " claude_next = f\"After {i+1} iterations, this is the critique for the provided story - \\\n", " \\n\\n{call_claude(Language, Genre, gpt_messages, claude_messages)}\"\n", " print(f\"{claude_name}:\\n{claude_next}\\n\")\n", " # yield claude_next\n", " claude_messages.append(claude_next)\n", "\n", " yield gpt_next, claude_next\n", " \n", " # yield gpt_next, claude_next\n", " # return (gpt_next, claude_next)" ] }, { "cell_type": "code", "execution_count": 9, "id": "19e66ed3-d2c3-4a71-aec4-7869e5295215", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "* Running on local URL: http://127.0.0.1:7860\n", "\n", "To create a public link, set `share=True` in `launch()`.\n" ] }, { "data": { "text/html": [ "
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