{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from hellocomputer.config import settings\n",
    "from langchain_core.utils.function_calling import convert_to_openai_function\n",
    "import openai\n",
    "from operator import itemgetter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_core.tools import tool\n",
    "\n",
    "\n",
    "@tool\n",
    "def add(a: int, b: int) -> int:\n",
    "    \"\"\"Adds a and b.\"\"\"\n",
    "    return a + b\n",
    "\n",
    "\n",
    "@tool\n",
    "def multiply(a: int, b: int) -> int:\n",
    "    \"\"\"Multiplies a and b.\"\"\"\n",
    "    return a * b\n",
    "\n",
    "\n",
    "tools = [convert_to_openai_function(t) for t in [add, multiply]]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "tools_fmt = [\n",
    "    {\"type\": \"function\",\n",
    "     \"function\": tools[0]},\n",
    "    {\"type\": \"function\",\n",
    "     \"function\": tools[1]}\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "messages = [\n",
    "    {\"role\": \"system\", \"content\": \"You are helpful assistant.\"},\n",
    "    {\"role\": \"user\", \"content\": \"What is 2 + 2?\"},\n",
    "]\n",
    "\n",
    "client = openai.OpenAI(\n",
    "    base_url = \"https://api.endpoints.anyscale.com/v1\",\n",
    "    api_key = settings.anyscale_api_key\n",
    ")\n",
    "\n",
    "response = client.chat.completions.create(\n",
    "    model=\"mistralai/Mixtral-8x7B-Instruct-v0.1\",\n",
    "    messages=messages,\n",
    "    tools=tools_fmt,\n",
    "    tool_choice=\"auto\",  # auto is default, but we'll be explicit\n",
    ")\n",
    "\n",
    "get_args = itemgetter(\"arguments\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "call = response.choices[0].message.tool_calls[0].function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "add.func(2,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}