{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello! I'm an AI and don't have feelings, but I'm here and ready to help you. How can I assist you today?\n"
     ]
    }
   ],
   "source": [
    "import litellm \n",
    "\n",
    "messages = [{ \"content\": \"Hello, how are you?\",\"role\": \"user\"}]\n",
    "\n",
    "# hosted_vllm is prefix key word and necessary\n",
    "response = litellm.completion(\n",
    "            model=\"hosted_vllm/Qwen2.5-14B-Instruct\", # pass the vllm model name\n",
    "            messages=messages,\n",
    "            api_base=\"http://127.0.0.1:8000/v1\",\n",
    "            temperature=0.2,\n",
    "            max_tokens=80)\n",
    "\n",
    "print(response.choices[0].message.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "da35003c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "verl2",
   "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": "3.10.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}