Week2Day1 Multimodel chat
This commit is contained in:
Jawad Hussain
232
week2/community-contributions/day1-Multimodel_Chat.ipynb
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232
week2/community-contributions/day1-Multimodel_Chat.ipynb
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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": 1,
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"id": "12ca6f8a",
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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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"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": "4b53a815",
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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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"Anthropic API Key exists and begins sk-ant-\n",
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"Google API Key not set\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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"anthropic_api_key = os.getenv('ANTHROPIC_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 anthropic_api_key:\n",
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" print(f\"Anthropic API Key exists and begins {anthropic_api_key[:7]}\")\n",
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"else:\n",
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" print(\"Anthropic 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": null,
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"id": "3d2b7cfe",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Connect to OpenAI, Anthropic\n",
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"\n",
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"openai = OpenAI()\n",
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"\n",
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"claude = anthropic.Anthropic()"
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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": "b7d88d4b",
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"metadata": {},
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"outputs": [],
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"source": [
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"class ConversationManager:\n",
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" def __init__(self):\n",
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" self.conversation_history = []\n",
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" self.participants = {}\n",
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" \n",
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" def add_participant(self, name, chatbot):\n",
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" \"\"\"Add a model to the conversation\"\"\"\n",
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" self.participants[name] = chatbot\n",
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" \n",
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" def add_message(self, speaker, message):\n",
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" \"\"\"Add a message to the shared conversation history\"\"\"\n",
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" self.conversation_history.append({\n",
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" \"speaker\": speaker,\n",
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" \"role\": \"assistant\" if speaker in self.participants else \"user\",\n",
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" \"content\": message\n",
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" })\n",
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" \n",
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" def get_context_for_model(self, model_name):\n",
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" \"\"\"Create context appropriate for the given model\"\"\"\n",
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" # Convert the shared history to model-specific format\n",
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" messages = []\n",
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" for msg in self.conversation_history:\n",
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" if msg[\"speaker\"] == model_name:\n",
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" messages.append({\"role\": \"assistant\", \"content\": msg[\"content\"]})\n",
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" else:\n",
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" messages.append({\"role\": \"user\", \"content\": msg[\"content\"]})\n",
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" return messages\n",
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" \n",
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" def run_conversation(self, starting_message, turns=3, round_robin=True):\n",
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" \"\"\"Run a multi-model conversation for specified number of turns\"\"\"\n",
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" current_message = starting_message\n",
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" models = list(self.participants.keys())\n",
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" \n",
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" # Add initial message\n",
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" self.add_message(\"user\", current_message)\n",
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" \n",
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" for _ in range(turns):\n",
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" for model_name in models:\n",
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" # Get context appropriate for this model\n",
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" model_context = self.get_context_for_model(model_name)\n",
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" \n",
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" # Get response from this model\n",
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" chatbot = self.participants[model_name]\n",
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" response = chatbot.generate_response(model_context)\n",
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" \n",
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" # Add to conversation history\n",
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" self.add_message(model_name, response)\n",
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" \n",
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" print(f\"{model_name}:\\n{response}\\n\")\n",
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" \n",
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" if not round_robin:\n",
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" # If not round-robin, use this response as input to next model\n",
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" current_message = response"
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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": "80c537c3",
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"metadata": {},
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"outputs": [],
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"source": [
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"class ChatBot:\n",
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" def __init__(self, model_name, system_prompt, **kwargs):\n",
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" self.model_name = model_name\n",
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" self.system_prompt = system_prompt\n",
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" self.api_key = kwargs.get('api_key', None)\n",
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" self.base_url = kwargs.get('base_url', None)\n",
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" \n",
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" def generate_response(self, messages):\n",
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" \"\"\"Generate a response based on provided messages without storing history\"\"\"\n",
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" # Prepare messages including system prompt\n",
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" full_messages = [{\"role\": \"system\", \"content\": self.system_prompt}] + messages\n",
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" \n",
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" try:\n",
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" if \"claude\" in self.model_name.lower():\n",
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" # Format messages for Claude API\n",
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" claude_messages = [m for m in messages if m[\"role\"] != \"system\"]\n",
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" response = anthropic.Anthropic().messages.create(\n",
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" model=self.model_name,\n",
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" system=self.system_prompt,\n",
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" messages=claude_messages,\n",
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" max_tokens=200,\n",
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" )\n",
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" return response.content[0].text\n",
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" \n",
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" else:\n",
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" # Use OpenAI API (works for OpenAI, Gemini via OpenAI client, etc)\n",
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" openai_client = OpenAI(api_key=self.api_key, base_url=self.base_url)\n",
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" response = openai_client.chat.completions.create(\n",
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" model=self.model_name,\n",
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" messages=full_messages,\n",
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" max_tokens=200,\n",
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" )\n",
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" return response.choices[0].message.content\n",
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" \n",
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" except Exception as e:\n",
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" return f\"Error: {str(e)}\""
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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": "d197c3ef",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Initialize models\n",
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"gpt_bot = ChatBot(\"gpt-4o-mini\", \"You are witty and sarcastic.\")\n",
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"claude_bot = ChatBot(\"claude-3-haiku-20240307\", \"You are thoughtful and philosophical.\")\n",
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"\n",
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"model_name = \"qwen2.5:1.5b\"\n",
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"system_prompt = \"You are a helpful assistant that is very argumentative in a snarky way.\"\n",
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"kwargs = {\n",
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" \"api_key\": \"ollama\",\n",
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" \"base_url\": 'http://localhost:11434/v1'\n",
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"}\n",
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"qwen = ChatBot(model_name, system_prompt, **kwargs)\n",
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"\n",
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"# Set up conversation manager\n",
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"conversation = ConversationManager()\n",
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"conversation.add_participant(\"GPT\", gpt_bot)\n",
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"conversation.add_participant(\"Claude\", claude_bot)\n",
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"conversation.add_participant(\"Qwen\", qwen)\n",
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"\n",
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"# Run a multi-model conversation\n",
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"conversation.run_conversation(\"What's the most interesting technology trend right now?\", turns=2)"
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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": "Python (llms)",
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"language": "python",
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"name": "llms"
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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": "3.11.9"
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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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