{ "cells": [ { "cell_type": "markdown", "id": "e063b35e-5598-4084-b255-89956bfedaac", "metadata": {}, "source": [ "### Models an interaction between LLama 3.2 and Claude 3.5 Haiku" ] }, { "cell_type": "code", "execution_count": null, "id": "4f534359-cdb4-4441-aa66-d6700fa4d6a5", "metadata": {}, "outputs": [], "source": [ "# imports\n", "\n", "import os\n", "from dotenv import load_dotenv\n", "import anthropic\n", "import ollama" ] }, { "cell_type": "code", "execution_count": null, "id": "3bdff240-9118-4061-9369-585c4d4ce0a7", "metadata": {}, "outputs": [], "source": [ "# Load environment variables in a file called .env\n", "\n", "load_dotenv(override=True)\n", "anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\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": null, "id": "ff110b3f-3986-4fd8-a0b1-fd4b51133a8d", "metadata": {}, "outputs": [], "source": [ "# Connect to Anthropic\n", "\n", "claude = anthropic.Anthropic()" ] }, { "cell_type": "code", "execution_count": null, "id": "e6e596c6-6307-49c1-a29f-5c4e88f8d34d", "metadata": {}, "outputs": [], "source": [ "# Download the llama3.2:1b model for local execution.\n", "!ollama pull llama3.2:1b" ] }, { "cell_type": "code", "execution_count": null, "id": "633b6892-6d04-40cb-8b61-196fc754b00c", "metadata": {}, "outputs": [], "source": [ "# Define models\n", "CLAUDE_MODEL = \"claude-3-5-haiku-latest\"\n", "LLAMA_MODEL = \"llama3.2:1b\"" ] }, { "cell_type": "code", "execution_count": null, "id": "a699a809-e3d3-4392-94bd-e2f80a5aec60", "metadata": {}, "outputs": [], "source": [ "claude_system = \"You are a chatbot designed as a study tutor for undergraduate students. \\\n", "You explain information and key-technical terms related to the subject in a succint yet \\\n", "comprehensive manner. You may use tables, formatting and other visuals to help create \\\n", "'cheat-sheets' of sorts.\"\n", "\n", "llama_system = \"You are a chatbot designed to ask questions about different topics related to \\\n", "computer vision. You are meant to simulate a student, not teacher. Act as if you have no \\\n", "prior knowledge\"" ] }, { "cell_type": "code", "execution_count": null, "id": "bdb049d8-130b-42dd-aaab-29c09e3e2347", "metadata": {}, "outputs": [], "source": [ "llama_messages = [\"Hi\"]\n", "claude_messages = [\"Hello\"]" ] }, { "cell_type": "code", "execution_count": null, "id": "c158f31c-5e8b-48a4-9980-6b280393800b", "metadata": {}, "outputs": [], "source": [ "def call_llama():\n", " messages = [{\"role\": \"system\", \"content\": llama_system}]\n", " for llama_msg, claude_msg in zip(llama_messages, claude_messages):\n", " messages.append({\"role\": \"assistant\", \"content\": llama_msg})\n", " messages.append({\"role\": \"user\", \"content\": claude_msg})\n", " response = ollama.chat(model=LLAMA_MODEL, messages=messages)\n", " return response['message']['content']\n" ] }, { "cell_type": "code", "execution_count": null, "id": "d803c5a2-df54-427a-9b80-8e9dd04ee36d", "metadata": {}, "outputs": [], "source": [ "def call_claude():\n", " messages = []\n", " for llama_msg, claude_msg in zip(llama_messages, claude_messages):\n", " messages.append({\"role\": \"user\", \"content\": llama_msg})\n", " messages.append({\"role\": \"assistant\", \"content\": claude_msg})\n", " messages.append({\"role\": \"user\", \"content\": llama_messages[-1]})\n", " message = claude.messages.create(\n", " model=CLAUDE_MODEL,\n", " system=claude_system,\n", " messages=messages,\n", " max_tokens=500\n", " )\n", " return message.content[0].text" ] }, { "cell_type": "code", "execution_count": null, "id": "a23794bb-0f36-4f91-aa28-24b876203a36", "metadata": {}, "outputs": [], "source": [ "call_llama()" ] }, { "cell_type": "code", "execution_count": null, "id": "7f5c3e2f-a1bb-403b-b6b5-944a10d93305", "metadata": {}, "outputs": [], "source": [ "call_claude()" ] }, { "cell_type": "code", "execution_count": null, "id": "3d6eb874-1c8f-47d8-a9f1-2e0fe197ae83", "metadata": {}, "outputs": [], "source": [ "llama_messages = [\"Hi\"]\n", "claude_messages = [\"Hello there, what would you like to learn today?\"]\n", "\n", "print(f'Ollama:\\n{ollama_messages[0]}')\n", "print(f'Claude:\\n{claude_messages[0]}')\n", "\n", "for _ in range(5):\n", " llama_next = call_llama()\n", " print(f'Llama 3.2:\\n{llama_next}')\n", " llama_messages.append(llama_next)\n", " \n", " claude_next = call_claude()\n", " print(f'Claude 3.5 Haiku:\\n{claude_next}')\n", " claude_messages.append(claude_next)" ] }, { "cell_type": "code", "execution_count": null, "id": "d1e651ad-85c8-45c7-ba83-f7c689080d6b", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.11.11" } }, "nbformat": 4, "nbformat_minor": 5 }