{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "AZURE_KEY = \"API_KEY::URL\"\n",
    "OPENAI_KEY = \"sk-XXX\""
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use Azure and OpenAI models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from manifest import Manifest\n",
    "from manifest.connections.client_pool import ClientConnection\n",
    "from pathlib import Path\n",
    "\n",
    "cache_path = Path(\"manifest.db\")\n",
    "if cache_path.exists():\n",
    "    cache_path.unlink()\n",
    "\n",
    "\n",
    "azure = ClientConnection(\n",
    "    client_name=\"azureopenai\",\n",
    "    client_connection=AZURE_KEY,\n",
    "    engine=\"text-davinci-003\",\n",
    ")\n",
    "\n",
    "manifest = Manifest(client_pool=[azure], \n",
    "    cache_name=\"sqlite\",\n",
    "    cache_connection=\"manifest.db\"\n",
    ")\n",
    "\n",
    "\n",
    "openai = ClientConnection(\n",
    "    client_name=\"openai\",\n",
    "    client_connection=OPENAI_KEY,\n",
    "    engine=\"text-davinci-003\",\n",
    ")\n",
    "\n",
    "manifest_openai_nocache = Manifest(client_pool=[openai])\n",
    "\n",
    "manifest_openai = Manifest(client_pool=[openai], \n",
    "    cache_name=\"sqlite\",\n",
    "    cache_connection=\"manifest.db\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Show caches are the same\n",
    "text = \"What is the meaning of life?\"\n",
    "res = manifest.run(text, max_tokens=100, temperature=0.7, return_response=True)\n",
    "print(res.get_response())\n",
    "print(res.is_cached())\n",
    "res2 = manifest_openai.run(text, max_tokens=100, temperature=0.7, return_response=True)\n",
    "print(res2.is_cached())\n",
    "\n",
    "assert res2.get_response() == res.get_response()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "azure_chat = ClientConnection(\n",
    "    client_name=\"azureopenaichat\",\n",
    "    client_connection=AZURE_KEY,\n",
    "    engine=\"gpt-3.5-turbo\",\n",
    ")\n",
    "\n",
    "manifest = Manifest(client_pool=[azure_chat])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(manifest.run(\"What do you think is the best food?\", max_tokens=100))\n",
    "\n",
    "chat_dict = [\n",
    "    {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
    "    {\"role\": \"user\", \"content\": \"Who won the world series in 2020?\"},\n",
    "    {\"role\": \"assistant\", \"content\": \"The Los Angeles Dodgers won the World Series in 2020.\"},\n",
    "    {\"role\": \"user\", \"content\": \"Where was it played?\"}\n",
    "]\n",
    "print(manifest.run(chat_dict, max_tokens=100))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "manifest",
   "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": "3.10.4"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "fddffe4ac3b9f00470127629076101c1b5f38ecb1e7358b567d19305425e9491"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}