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 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "# OpenEnv Autonomy Calibration \u2014 Training Notebook\n",
    "\n",
    "This notebook demonstrates how to train a calibrated AI agent using **GRPO (Group Relative Policy Optimization)** through the Hugging Face TRL framework.\n",
    "\n",
    "### 1. Install Dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install --upgrade numpy trl transformers accelerate peft torchao bitsandbytes requests matplotlib\n",
    "print('\u2705 Done. Please Restart Session if this is your first run!')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Configure the Training Loop\n",
    "The training script `train_rl.py` connects to the live environment API to fetch rewards and update the policy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# In a real Colab, you would clone the repo and run:\n",
    "# !python3 train_rl.py"
   ]
  }
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