252 lines
9.6 KiB
Plaintext
252 lines
9.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "cc02832b-7f4b-445a-b9d6-fe79dd8f5e8e",
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"metadata": {},
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"source": [
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"# A Cryptic City Scandal.\n",
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"\n",
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"## A trilogue between three chatbots that impersonate Sherlock Holmes, Dr Watson and Inspetor Lastrade, respetively."
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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": "dc042bb9-02f2-49ca-942a-9bd17c5c20d2",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Crucial 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": null,
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"id": "b60ee2d6-543d-4b1a-9d97-3f2380d35146",
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"metadata": {},
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"outputs": [],
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"source": [
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"#We load environment variables in a file called .env and 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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"\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\")"
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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": "99e4f5e5-1098-4890-ab3e-6006a66ca875",
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"metadata": {},
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"outputs": [],
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"source": [
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"# We connect to OpenAI and 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": "54b650de-36e8-42f5-835d-cc2de60da1b4",
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"metadata": {},
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"outputs": [],
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"source": [
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"# We now generate a conversation between one GPT-4o-mini chatbot and two Claude-3-haiku chatbots.\n",
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"# We model it upon the conversations between Sherlock Holmes, Dr Watson and Inspector Lastrade from the famous short stories and novels by Conan Doyle.\n",
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"# Since Claude-3-haiku appears to be the wittier one, we assign to it the roles of Holmes and Watson.\n",
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"# We don't include Gemini because of the lack of comprehension it exhibited in dozens of test runs.\n",
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"\n",
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"claude_model = \"claude-3-haiku-20240307\"\n",
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"gpt_model = \"gpt-4o-mini\"\n",
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"\n",
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"\n",
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"lestrade_system = \"You are Inspector Lestrade from the novels by Conan Doyle.\\\n",
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"You visit Sherlock Holmes and Dr Watson at 221B Baker Street to inquire whether Holmes knows anything \\\n",
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"about the recent mysterious events in the City of London, especially the disappearance billions of pounds \\\n",
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"worth of crypto currency and the strange behavior of the Lord Mayor. \\\n",
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"You engage in a conversation with Sherlock Holmes and Dr John Watson. \\\n",
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"Any description of the situation should be given from a narrator's perspective, in the present tense and within parentheses. \\\n",
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"Whatever Holmes and Watson reply within parantheses is merely a description of the situation. \\\n",
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"Do not impersonate Holmes. Do not impersonate Watson.\"\n",
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"\n",
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"\n",
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"holmes_system = \"You are the famous detective Sherlock Holmes from the novels by Conan Doyle Your best friend and housemate is Dr John Watson. \\\n",
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"You engage in a witty conversation with Inspector Lestrade from Scotland Yard and Watson. \\\n",
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"You believe that the mysterious events menionted by Lestrade are proof that the so-called Q-Day has occurred and that it has been brought about by a \\\n",
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"successful combination of artificial general intelligence and quantum computing. \\\n",
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"Moreover, you are convinced that this could be a sinister conspiracy by your arch enemy Prof Moriarty. \\\n",
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"Any description of the situation should be given from a narrator's perspective, in the present tense and within parentheses. \\\n",
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"Whatever Lestrade and Watson reply within parantheses is merely a description of the situation. \\\n",
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"Do not impersonate Lestrade. Do not impersonate Watson.\"\n",
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"\n",
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"\n",
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"watson_system = \"You are Dr John Watson from the novels by Conan Doyle, Sherlock Holmes's housemate and closest friend. \\\n",
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"You engage in a witty conversation with Inspector Lestrade from Scotland Yard and Holmes about the events mentioned by Lestrade. \\\n",
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"While you aren't totally convinced by Holmes's theory and express doubts the capabilities of Holmes's arch enemy Prof Moriarty,\\\n",
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"you wonder whether Sherlock Holmes's brother, Mycroft Holmes, might be involved. \\\n",
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"Any description of your behavior should be given from a narrator's perspective, in the present tense and within parentheses. \\\n",
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"Whatever Lestrade and Holmes reply within parantheses is merely a description of the situation. \\\n",
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"Do not impersonate Lestrade. Do not impersonate Holmes.\"\n",
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"\n",
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"\n",
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"lestrade_messages = [\"Good evening, gentlemen! I apologize for showing up unexpectedly at this late hour!\"]\n",
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"\n",
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"holmes_messages = [\"Inspector Lestrade, please come in! As a matter of fact, we've been expecting you for a few hours already!\"]\n",
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"\n",
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"watson_messages = [\"Good evening, Inspector!\"]"
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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": "11177d3f-4649-440c-a399-5906bbd6cf17",
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"metadata": {},
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"outputs": [],
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"source": [
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"def call_lestrade():\n",
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" messages = [{\"role\": \"system\", \"content\": lestrade_system}]\n",
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" \n",
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" for les_mes, hol_mes, wat_mes in zip(lestrade_messages, holmes_messages, watson_messages):\n",
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" messages.append({\"role\": \"assistant\", \"content\": les_mes})\n",
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" messages.append({\"role\": \"user\", \"content\": hol_mes})\n",
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" messages.append({\"role\": \"user\", \"content\": wat_mes})\n",
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"\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": "7a40d11a-86ec-455d-b3c3-fdfd0776fc8a",
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"metadata": {},
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"outputs": [],
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"source": [
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"def call_holmes():\n",
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" messages = []\n",
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" \n",
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" for les_mes, hol_mes, wat_mes in zip(lestrade_messages, holmes_messages, watson_messages):\n",
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" messages.append({\"role\": \"user\", \"content\": les_mes})\n",
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" messages.append({\"role\": \"assistant\", \"content\": hol_mes})\n",
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" messages.append({\"role\": \"user\", \"content\": wat_mes})\n",
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" \n",
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" messages.append({\"role\": \"user\", \"content\": lestrade_messages[-1]})\n",
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" messages.append({\"role\": \"user\", \"content\": watson_messages[-1]})\n",
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"\n",
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" message = claude.messages.create(\n",
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" model=claude_model,\n",
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" system=holmes_system,\n",
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" messages=messages,\n",
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" max_tokens=500\n",
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" )\n",
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" return message.content[0].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": "bcc0f046-0103-4486-93be-609514ed762b",
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"metadata": {},
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"outputs": [],
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"source": [
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"def call_watson():\n",
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" messages = []\n",
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" \n",
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" for les_mes, hol_mes, wat_mes in zip(lestrade_messages, holmes_messages, watson_messages):\n",
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" messages.append({\"role\": \"user\", \"content\": les_mes})\n",
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" messages.append({\"role\": \"user\", \"content\": hol_mes})\n",
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" messages.append({\"role\": \"assistant\", \"content\": wat_mes})\n",
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" \n",
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" messages.append({\"role\": \"user\", \"content\": lestrade_messages[-1]})\n",
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" messages.append({\"role\": \"user\", \"content\": holmes_messages[-1]})\n",
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"\n",
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" message = claude.messages.create(\n",
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" model=claude_model,\n",
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" system=watson_system,\n",
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" messages=messages,\n",
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" max_tokens=500\n",
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" )\n",
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" return message.content[0].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": "5b1a39e9-9783-4a2e-869f-ed3c3f2849a2",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(f\"Inspector Lestrade:\\n{lestrade_messages[0]}\\n\")\n",
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"print(f\"Holmes:\\n{holmes_messages[0]}\\n\")\n",
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"print(f\"Dr Watson:\\n{watson_messages[0]}\\n\")\n",
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"\n",
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"for i in range(2):\n",
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" \n",
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" les_next = call_lestrade()\n",
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" print(f\"Inspector Lestrade:\\n{les_next}\\n\")\n",
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" lestrade_messages.append(les_next)\n",
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" \n",
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" hol_next = call_holmes()\n",
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" print(f\"Holmes:\\n{hol_next}\\n\")\n",
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" holmes_messages.append(hol_next)\n",
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" \n",
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" wat_next = call_watson()\n",
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" print(f\"Dr Watson:\\n{wat_next}\\n\")\n",
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" watson_messages.append(wat_next)"
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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": "ae92e29a-8419-4f95-8b82-b60017088e47",
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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": "3.11.12"
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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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