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{ |
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"cells": [ |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "1194d35b-0b9f-4eb4-a539-5ddf55523367", |
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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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"#import anthropic\n", |
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"import ollama\n", |
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"import google.generativeai\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": null, |
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"id": "f8a1f0b3-6d93-4de1-bc79-2132726598e3", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"#constants\n", |
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"MODEL=\"llama3.2\"" |
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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": "88fe4149-1ef5-4007-a117-6d3ccab3e3c3", |
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"metadata": {}, |
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"outputs": [], |
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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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"google_api_key = os.getenv('GOOGLE_API_KEY')\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": null, |
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"id": "d186cf6e-fadd-450c-821c-df32e2574f5d", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# This is the set up code for Gemini\n", |
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"\n", |
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"google.generativeai.configure()" |
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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": "19a55117-f2ac-4a58-af6b-8b75259e80df", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"system_message = \"You are an assistant that is great at telling jokes\"\n", |
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"user_prompt = \"Tell a light-hearted joke for an audience of Data Scientists\"" |
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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": "908f69b1-54f8-42da-827b-f667631bc666", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"prompts = [\n", |
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" {\"role\": \"system\", \"content\": system_message},\n", |
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" {\"role\": \"user\", \"content\": user_prompt}\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": null, |
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"id": "4ec81488-883a-446f-91cf-2b3d92bbd3ba", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# The API for Gemini\n", |
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"gemini = google.generativeai.GenerativeModel(\n", |
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" model_name='gemini-2.0-flash-exp',\n", |
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" system_instruction=system_message\n", |
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")\n", |
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"response = gemini.generate_content(user_prompt)\n", |
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"print(response.text)" |
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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": "baf411fa-48bd-46a3-8bc8-1b22d0888a1a", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# API for ollama\n", |
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"response = ollama.chat(model=MODEL,messages=prompts)\n", |
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"print(response['message']['content'])" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "74ba5fc4-e4c6-44ee-b66f-e76d847933d2", |
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"metadata": {}, |
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"source": [ |
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"# Ardiversarial conversation between models" |
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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": "fd348154-18fa-4da8-815a-77f5f00107c3", |
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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 Ollama and Gemini\n", |
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"# Adjusted models accordingly\n", |
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"\n", |
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"ollama_model = \"llama3.2\"\n", |
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"gemini_model = \"gemini-2.0-flash-exp\"\n", |
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"\n", |
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"#ollama_system = \"You are a chatbot who is very argumentative; \\\n", |
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"#you disagree with anything in the conversation and you challenge everything, in a snarky way.\"\n", |
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"\n", |
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"ollama_system=\"You are a chatbot talking with the other person try to convince them to buy your proct of an ai app, \\\n", |
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"apply marketing strategies to make this client buy your product, use short clear explanations\"\n", |
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"\n", |
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"#gemini_system = \"You are a very polite, courteous chatbot. You try to agree with \\\n", |
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"#everything the other person says, or find common ground. If the other person is argumentative, \\\n", |
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"#you try to calm them down and keep chatting.\"\n", |
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"\n", |
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"gemini_system = \"You are the chatbot triying to be convinced by another person to buy their product, \\\n", |
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"ask important short questions and see if it is worth to give it a go, dont be too naive or easy go client\"\n", |
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"\n", |
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"ollama_messages = [\"Hi there\"]\n", |
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"gemini_messages = [\"Hi\"]\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": "becf327a-5485-4e78-8002-03272a99a3b9", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def call_ollama():\n", |
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" messages = [{\"role\": \"system\", \"content\": ollama_system}]\n", |
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" for ollama_msg, gemini_msg in zip(ollama_messages, gemini_messages):\n", |
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" messages.append({\"role\": \"assistant\", \"content\": ollama_msg})\n", |
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" messages.append({\"role\": \"user\", \"content\": gemini_msg})\n", |
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" \n", |
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" response = ollama.chat(model=ollama_model, messages=messages)\n", |
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" \n", |
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" return response['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": null, |
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"id": "d0c6dbe7-0baf-4c43-a03b-9134654685f4", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"call_ollama()" |
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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": "f68a134a-279a-4629-aec6-171587378991", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def call_gemini():\n", |
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" gemini = google.generativeai.GenerativeModel(\n", |
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" model_name=gemini_model,\n", |
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" system_instruction=gemini_system\n", |
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" )\n", |
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"\n", |
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" # Build a list of dictionaries representing the conversation\n", |
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" conversation = []\n", |
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" for ollama_msg, gemini_msg in zip(ollama_messages, gemini_messages):\n", |
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" conversation.append({\"role\": \"user\", \"content\": ollama_msg})\n", |
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" conversation.append({\"role\": \"assistant\", \"content\": gemini_msg})\n", |
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" conversation.append({\"role\": \"user\", \"content\": ollama_messages[-1]})\n", |
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"\n", |
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" # Format the conversation into a string for the prompt\n", |
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" prompt = \"\"\n", |
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" for msg in conversation:\n", |
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" prompt += f\"{msg['role'].capitalize()}: {msg['content']}\\n\"\n", |
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"\n", |
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" message = gemini.generate_content(prompt)\n", |
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" \n", |
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" return message.text\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": "7511003a-f2b6-45f5-8cb0-1c9190d33ce9", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"call_gemini()" |
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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": "d0e81f1f-9754-4790-8b73-5f52fef4ea64", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"call_ollama()" |
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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": "6fbe59f6-a3ef-4062-ab4b-b999f6d1abe9", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"ollama_messages = [\"Hi there\"]\n", |
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"gemini_messages = [\"Hi\"]\n", |
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"\n", |
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"print(f\"Ollama:\\n{ollama_messages[0]}\\n\")\n", |
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"print(f\"Gemini:\\n{gemini_messages[0]}\\n\")\n", |
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"\n", |
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"for i in range(5):\n", |
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" # Call Ollama to generate the next message\n", |
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" ollama_next = call_ollama() \n", |
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" print(f\"Ollama:\\n{ollama_next}\\n\")\n", |
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" ollama_messages.append(ollama_next)\n", |
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" \n", |
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" # Call Gemini to generate the next message\n", |
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" gemini_next = call_gemini() \n", |
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" print(f\"Gemini:\\n{gemini_next}\\n\")\n", |
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" gemini_messages.append(gemini_next)\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": "9525600b-082e-417f-9088-c6483a613bf3", |
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"metadata": {}, |
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"outputs": [], |
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"source": [] |
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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": "3.13.2" |
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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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