352 lines
14 KiB
Plaintext
352 lines
14 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "768629e6",
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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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"from dotenv import load_dotenv\n",
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"from openai import OpenAI\n",
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"\n",
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"from IPython.display import Markdown, display, update_display"
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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": 2,
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"id": "84a945dc",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"OpenAI API Key exists and begins sk-proj-\n",
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"Google API Key exists and begins AIzaSyCW\n"
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]
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}
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],
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"source": [
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"# Load environment variables in a file called .env\n",
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"# Print the key prefixes to help with any debugging\n",
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"\n",
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"load_dotenv(override=True)\n",
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"openai_api_key = os.getenv('OPENAI_API_KEY')\n",
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"google_api_key = os.getenv('GOOGLE_API_KEY')\n",
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"\n",
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"if openai_api_key:\n",
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" print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n",
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"else:\n",
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" print(\"OpenAI API Key not set\")\n",
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"\n",
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"if google_api_key:\n",
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" print(f\"Google API Key exists and begins {google_api_key[:8]}\")\n",
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"else:\n",
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" print(\"Google API Key not set\")"
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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": 3,
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"id": "ad8ae0b6",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Connect to OpenAI, Gemini\n",
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"openai = OpenAI()\n",
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"gemini_via_openai_client = OpenAI(\n",
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" api_key=google_api_key, \n",
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" base_url=\"https://generativelanguage.googleapis.com/v1beta/openai/\"\n",
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")"
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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": 13,
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"id": "f66cf12f",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Let's make a conversation between GPT-4.1-mini and Gemini-2.0-flash\n",
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"# We're using cheap versions of models so the costs will be minimal\n",
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"\n",
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"# game = \"Santorini\"\n",
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"no_questions = 3\n",
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"\n",
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"gpt_model = \"gpt-4o-mini\"\n",
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"gemini_model = \"gemini-2.0-flash\"\n",
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"\n",
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"gpt_system = \"You are a boardgame journalist. \\\n",
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"You tend to be objective and ask right questions to get to the core of the boardgame mechanics, \\\n",
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"visual appeal and time to setup the game. Your goal is to ask the right questions to get the best possible review of the board game.\" \\\n",
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"\"You ask one question at a time and wait for the other person to answer. \\\n",
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"You do not answer any own questions. You always try to build on the previous answer.\"\n",
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"\n",
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"gemini_system = \"You are a boardgame critique; \\\n",
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"you tend to objectively analyze everything when it comes to a board game gameplay, visual appeal and time to setup the game. \\\n",
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"Your goal is to provide constructive criticism so the board gaming community can benefit from these insights.\" \\\n",
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"\"You answer one question at a time and wait for the other person to ask the next question. \\\n",
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"You do not ask any questions you always just answer the previous question. \\\n",
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"If the other person is very positive, you try to point out flaws in the game. \\\n",
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"If the other person is very negative, you try to point out good aspects of the game.\"\n"
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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": "33266f0c",
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"metadata": {},
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"outputs": [],
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"source": [
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"def call_boardgame_journalist(gpt_messages, gemini_messages):\n",
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" messages = [{\"role\": \"system\", \"content\": gpt_system}]\n",
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" for gpt, gemini in zip(gpt_messages, gemini_messages):\n",
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" messages.append({\"role\": \"user\", \"content\": gpt})\n",
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" messages.append({\"role\": \"assistant\", \"content\": gemini})\n",
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" completion = openai.chat.completions.create(\n",
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" model=gpt_model,\n",
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" messages=messages\n",
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" )\n",
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" return completion.choices[0].message.content"
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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": "53d42055",
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"metadata": {},
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"outputs": [],
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"source": [
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"def call_boardgame_critique(gpt_messages, gemini_messages):\n",
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" messages = [{\"role\": \"system\", \"content\": gemini_system}]\n",
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" for gpt, gemini in zip(gpt_messages, gemini_messages):\n",
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" messages.append({\"role\": \"user\", \"content\": gpt})\n",
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" messages.append({\"role\": \"assistant\", \"content\": gemini})\n",
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" messages.append({\"role\": \"user\", \"content\": gpt_messages[-1]})\n",
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" completion = gemini_via_openai_client.chat.completions.create(\n",
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" model=gemini_model,\n",
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" messages=messages\n",
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" )\n",
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" return completion.choices[0].message.content\n"
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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": 21,
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"id": "5aa66868",
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"metadata": {},
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"outputs": [],
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"source": [
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"def run_boardgame_conversation(boardgame_name):\n",
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" gpt_messages = [f\"I would like to review the board game {boardgame_name}.\"]\n",
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" gemini_messages = [f\"Sure, ask me anything about the board game {boardgame_name}.\"]\n",
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"\n",
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" print(f\"Journalist:\\n{gpt_messages[0]}\\n\")\n",
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" print(f\"Critique:\\n{gemini_messages[0]}\\n\")\n",
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"\n",
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" for i in range(no_questions):\n",
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" print(f\"\\n\\n***Question {i + 1}***\\n\\n\")\n",
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" gpt_next = call_boardgame_journalist(gpt_messages, gemini_messages)\n",
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" print(f\"Journalist:\\n{gpt_next}\\n\")\n",
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" gpt_messages.append(gpt_next)\n",
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"\n",
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" gemini_next = call_boardgame_critique(gpt_messages, gemini_messages)\n",
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" print(f\"Critique:\\n{gemini_next}\\n\")\n",
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" gemini_messages.append(gemini_next)\n",
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"\n",
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" return \"\\n\".join(f\"*Journalist*: {g}\\n*Critique*: {c}\" for g, c in zip(gpt_messages, gemini_messages))\n",
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"\n"
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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": 22,
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"id": "51c9dadc",
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"metadata": {},
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"outputs": [],
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"source": [
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"import gradio as gr"
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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": 23,
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"id": "548efb27",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"* Running on local URL: http://127.0.0.1:7863\n",
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"* To create a public link, set `share=True` in `launch()`.\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div><iframe src=\"http://127.0.0.1:7863/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": []
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},
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"execution_count": 23,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Journalist:\n",
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"I would like to review the board game Santorini.\n",
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"\n",
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"Critique:\n",
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"Sure, ask me anything about the board game Santorini.\n",
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"\n",
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"\n",
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"\n",
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"***Question 1***\n",
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"\n",
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"\n",
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"Journalist:\n",
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"\n",
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"\n",
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"To start, could you briefly describe the core gameplay and objective of Santorini?\n",
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"\n",
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"\n",
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"Critique:\n",
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"Santorini is an abstract strategy game at its core. Two players compete to be the first to get one of their two pawns to the third level of a tower. Players take turns moving one of their pawns, and then building a block on an adjacent space. The build can be on the same level, one level higher, or down a level. Certain spaces have a dome, which signifies the tower is complete, and no one can build or move to that space.\n",
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"\n",
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"The game's main draw is the use of God Powers, which give each player a unique ability that breaks the standard rules of the game. This adds a significant layer of asymmetry and strategic depth.\n",
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"\n",
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"\n",
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"\n",
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"\n",
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"***Question 2***\n",
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"\n",
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"\n",
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"Journalist:\n",
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"None\n",
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"\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Traceback (most recent call last):\n",
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" File \"c:\\Users\\Milan Lazic\\projects\\llm_engineering\\venv\\Lib\\site-packages\\gradio\\queueing.py\", line 745, in process_events\n",
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" response = await route_utils.call_process_api(\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" ...<5 lines>...\n",
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" )\n",
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" ^\n",
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" File \"c:\\Users\\Milan Lazic\\projects\\llm_engineering\\venv\\Lib\\site-packages\\gradio\\route_utils.py\", line 354, in call_process_api\n",
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" output = await app.get_blocks().process_api(\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" ...<11 lines>...\n",
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" )\n",
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" ^\n",
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" File \"c:\\Users\\Milan Lazic\\projects\\llm_engineering\\venv\\Lib\\site-packages\\gradio\\blocks.py\", line 2116, in process_api\n",
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" result = await self.call_function(\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" ...<8 lines>...\n",
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" )\n",
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" ^\n",
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" File \"c:\\Users\\Milan Lazic\\projects\\llm_engineering\\venv\\Lib\\site-packages\\gradio\\blocks.py\", line 1623, in call_function\n",
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" prediction = await anyio.to_thread.run_sync( # type: ignore\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" fn, *processed_input, limiter=self.limiter\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" )\n",
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" ^\n",
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" File \"c:\\Users\\Milan Lazic\\projects\\llm_engineering\\venv\\Lib\\site-packages\\anyio\\to_thread.py\", line 56, in run_sync\n",
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" return await get_async_backend().run_sync_in_worker_thread(\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" func, args, abandon_on_cancel=abandon_on_cancel, limiter=limiter\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" )\n",
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" ^\n",
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" File \"c:\\Users\\Milan Lazic\\projects\\llm_engineering\\venv\\Lib\\site-packages\\anyio\\_backends\\_asyncio.py\", line 2476, in run_sync_in_worker_thread\n",
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" return await future\n",
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" ^^^^^^^^^^^^\n",
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" File \"c:\\Users\\Milan Lazic\\projects\\llm_engineering\\venv\\Lib\\site-packages\\anyio\\_backends\\_asyncio.py\", line 967, in run\n",
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" result = context.run(func, *args)\n",
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" File \"c:\\Users\\Milan Lazic\\projects\\llm_engineering\\venv\\Lib\\site-packages\\gradio\\utils.py\", line 915, in wrapper\n",
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" response = f(*args, **kwargs)\n",
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" File \"C:\\Users\\Milan Lazic\\AppData\\Local\\Temp\\ipykernel_29732\\641492170.py\", line 14, in run_boardgame_conversation\n",
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" gemini_next = call_boardgame_critique(gpt_messages, gemini_messages)\n",
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" File \"C:\\Users\\Milan Lazic\\AppData\\Local\\Temp\\ipykernel_29732\\2813548043.py\", line 7, in call_boardgame_critique\n",
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" completion = gemini_via_openai_client.chat.completions.create(\n",
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" model=gemini_model,\n",
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" messages=messages\n",
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" )\n",
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" File \"c:\\Users\\Milan Lazic\\projects\\llm_engineering\\venv\\Lib\\site-packages\\openai\\_utils\\_utils.py\", line 286, in wrapper\n",
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" return func(*args, **kwargs)\n",
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" File \"c:\\Users\\Milan Lazic\\projects\\llm_engineering\\venv\\Lib\\site-packages\\openai\\resources\\chat\\completions\\completions.py\", line 1147, in create\n",
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" return self._post(\n",
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" ~~~~~~~~~~^\n",
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" \"/chat/completions\",\n",
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" ^^^^^^^^^^^^^^^^^^^^\n",
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" ...<46 lines>...\n",
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" stream_cls=Stream[ChatCompletionChunk],\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" )\n",
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" ^\n",
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" File \"c:\\Users\\Milan Lazic\\projects\\llm_engineering\\venv\\Lib\\site-packages\\openai\\_base_client.py\", line 1259, in post\n",
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" return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n",
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" ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"c:\\Users\\Milan Lazic\\projects\\llm_engineering\\venv\\Lib\\site-packages\\openai\\_base_client.py\", line 1047, in request\n",
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" raise self._make_status_error_from_response(err.response) from None\n",
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"openai.BadRequestError: Error code: 400 - [{'error': {'code': 400, 'message': 'Unable to submit request because it must include at least one parts field, which describes the prompt input. Learn more: https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/gemini', 'status': 'INVALID_ARGUMENT'}}]\n"
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]
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}
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],
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"source": [
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"view = gr.Interface(\n",
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" fn=run_boardgame_conversation,\n",
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" inputs=[gr.Textbox(label=\"Input the name of the board game:\")],\n",
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" outputs=[gr.Markdown(label=\"Conversation:\")],\n",
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" flagging_mode=\"never\"\n",
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")\n",
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"view.launch()"
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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": "venv (3.13.5)",
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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": "3.13.5"
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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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