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{
"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": []
}
],
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"display_name": "Python 3 (ipykernel)",
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},
"language_info": {
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},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
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