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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### In this notebook, I’ll use the OpenAI class to connect to the OpenRouter API.\n",
    "#### This way, I can use the OpenAI class just as it’s shown in the course."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# First let's do an import\n",
    "from dotenv import load_dotenv\n",
    "from openai import OpenAI\n",
    "from IPython.display import Markdown, display\n",
    "import requests\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Next it's time to load the API keys into environment variables\n",
    "\n",
    "load_dotenv(override=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Check the keys\n",
    "\n",
    "import os\n",
    "openRouter_api_key = os.getenv('OPENROUTER_API_KEY')\n",
    "\n",
    "if openRouter_api_key:\n",
    "    print(f\"OpenAI API Key exists and begins {openRouter_api_key[:8]}\")\n",
    "else:\n",
    "    print(\"OpenAI API Key not set - please head to the troubleshooting guide in the setup folder\")\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now let's define the model names\n",
    "# The model names are used to specify which model you want to use when making requests to the OpenAI API.\n",
    "Gpt_41_nano = \"openai/gpt-4.1-nano\"\n",
    "Gpt_41_mini = \"openai/gpt-4.1-mini\"\n",
    "Claude_35_haiku = \"anthropic/claude-3.5-haiku\"\n",
    "Claude_37_sonnet = \"anthropic/claude-3.7-sonnet\"\n",
    "#Gemini_25_Pro_Preview = \"google/gemini-2.5-pro-preview\"\n",
    "Gemini_25_Flash_Preview_thinking = \"google/gemini-2.5-flash-preview:thinking\"\n",
    "\n",
    "\n",
    "free_mistral_Small_31_24B = \"mistralai/mistral-small-3.1-24b-instruct:free\"\n",
    "free_deepSeek_V3_Base = \"deepseek/deepseek-v3-base:free\"\n",
    "free_meta_Llama_4_Maverick = \"meta-llama/llama-4-maverick:free\"\n",
    "free_nous_Hermes_3_Mistral_24B = \"nousresearch/deephermes-3-mistral-24b-preview:free\"\n",
    "free_gemini_20_flash_exp = \"google/gemini-2.0-flash-exp:free\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "chatHistory = []\n",
    "# This is a list that will hold the chat history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def chatWithOpenRouter(model:str, prompt:str)-> str:\n",
    "    \"\"\" This function takes a model and a prompt and returns the response\n",
    "    from the OpenRouter API, using the OpenAI class from the openai package.\"\"\"\n",
    "\n",
    "    # here instantiate the OpenAI class but with the OpenRouter\n",
    "    # API URL\n",
    "    llmRequest = OpenAI(\n",
    "        api_key=openRouter_api_key,\n",
    "        base_url=\"https://openrouter.ai/api/v1\"\n",
    "    )\n",
    "\n",
    "    # add the prompt to the chat history\n",
    "    chatHistory.append({\"role\": \"user\", \"content\": prompt})\n",
    "\n",
    "    # make the request to the OpenRouter API\n",
    "    response = llmRequest.chat.completions.create(\n",
    "        model=model,\n",
    "        messages=chatHistory\n",
    "    )\n",
    "\n",
    "    # get the output from the response\n",
    "    assistantResponse = response.choices[0].message.content\n",
    "\n",
    "    # show the answer\n",
    "    display(Markdown(f\"**Assistant:**\\n {assistantResponse}\"))\n",
    "    \n",
    "    # add the assistant response to the chat history\n",
    "    chatHistory.append({\"role\": \"assistant\", \"content\": assistantResponse})\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# message to use with the chatWithOpenRouter function\n",
    "userPrompt = \"Shortly. Difference between git and github. Response in markdown.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "chatWithOpenRouter(free_mistral_Small_31_24B, userPrompt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#clear chat history\n",
    "def clearChatHistory():\n",
    "    \"\"\" This function clears the chat history\"\"\"\n",
    "    chatHistory.clear()"
   ]
  }
 ],
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