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"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 09 Training Loop\n",
"\n",
"Colab-ready end-to-end notebook for PolyGuard: install dependencies, authenticate Hugging Face, build data, train SFT, train GRPO with environment-backed rewards, export adapters, evaluate improvement, mirror final artifacts into `docs/results/`, and optionally deploy the OpenEnv environment to a Hugging Face Space."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 0) Runtime Setup\n",
"\n",
"Recommended Colab runtime: GPU. Set `HF_TOKEN` in Colab secrets or run the login cell below. The notebook clones the GitHub repo when it is not already running inside the project tree."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from pathlib import Path\n",
"import json\n",
"import os\n",
"import shutil\n",
"import subprocess\n",
"\n",
"REPO_URL = \"https://github.com/Vishwa-docs/Meta_Pytorch_OpenEnv_Scaler_VK.git\"\n",
"BRANCH = os.getenv(\"POLYGUARD_BRANCH\", \"master\")\n",
"CLONE_ROOT = Path(\"/content/Meta_Pytorch_OpenEnv_Scaler_VK\")\n",
"WORKDIR = CLONE_ROOT / \"polyguard-rl\"\n",
"\n",
"if not WORKDIR.exists():\n",
" subprocess.run([\"git\", \"clone\", \"--branch\", BRANCH, REPO_URL, str(CLONE_ROOT)], check=True)\n",
"\n",
"os.chdir(WORKDIR)\n",
"print(\"PolyGuard workdir:\", Path.cwd())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!python -m pip install -U pip\n",
"!python -m pip install -r requirements.txt\n",
"# Optional acceleration path. If Unsloth install fails on the selected runtime, TRL still runs through transformers.\n",
"!python -m pip install \"unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git\" || true"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1) Hugging Face Authentication\n",
"\n",
"Required for pushing the Space and for private/gated model access. Public Qwen checkpoints may download without auth, but final deployment still needs an authenticated account."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from huggingface_hub import login\n",
"\n",
"if os.getenv(\"HF_TOKEN\"):\n",
" login(token=os.environ[\"HF_TOKEN\"])\n",
"else:\n",
" from huggingface_hub import notebook_login\n",
" notebook_login()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2) Build Dataset And OpenEnv Assets"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!python scripts/build_synthetic_patients.py\n",
"!python scripts/ingest_open_drug_sources.py\n",
"!python scripts/build_drug_knowledge.py\n",
"!python scripts/build_retrieval_index.py\n",
"!python scripts/build_scenarios.py\n",
"!python scripts/bootstrap_data.py\n",
"!python scripts/build_training_corpus.py --profile small --with-local --with-synthetic --with-hf"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!python -m pytest tests/test_openenv_contract.py tests/test_reward_functions.py tests/test_anti_cheat.py -q\n",
"!openenv validate ."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3) SFT Warm Start"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"MODEL_ID = os.getenv(\"POLYGUARD_MODEL_ID\", \"Qwen/Qwen2.5-1.5B-Instruct\")\n",
"!python scripts/train_sft_trl.py --model-id \"$MODEL_ID\" --epochs 1 --max-steps 20 --batch-size 1 --use-unsloth"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 4) GRPO With Environment Rewards"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!python scripts/train_grpo_trl.py --model-id \"$MODEL_ID\" --max-steps 20 --num-generations 2 --batch-size 1 --use-unsloth"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 5) Export, Validate Inference, Evaluate"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!python scripts/merge_adapters_safe.py --adapter-dir checkpoints/sft_adapter --output-dir checkpoints/merged\n",
"!python scripts/test_inference_postsave.py --samples 3\n",
"!python scripts/evaluate_policy_ablations.py --episodes 8\n",
"!python scripts/evaluate_baselines.py\n",
"!python scripts/evaluate_all.py\n",
"!python scripts/evaluate_compare_runs.py --baseline outputs/reports/baselines.json --candidate outputs/reports/benchmark_report.json --output outputs/reports/improvement_report.json"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for rel in [\n",
" \"benchmark_report.json\",\n",
" \"baselines.json\",\n",
" \"grpo_ablation_report.json\",\n",
" \"grpo_trl_run.json\",\n",
" \"sft_trl_run.json\",\n",
" \"postsave_inference.json\",\n",
" \"improvement_report.json\",\n",
"]:\n",
" src = Path(\"outputs/reports\") / rel\n",
" dst = Path(\"docs/results\") / rel\n",
" if src.exists():\n",
" dst.parent.mkdir(parents=True, exist_ok=True)\n",
" shutil.copy2(src, dst)\n",
"\n",
"for rel in [\"avg_reward.png\", \"policy_stack_avg_reward.png\", \"legality_rate.png\", \"success_rate.png\", \"avg_process_fidelity.png\"]:\n",
" src = Path(\"outputs/plots\") / rel\n",
" dst = Path(\"docs/results\") / rel\n",
" if src.exists():\n",
" shutil.copy2(src, dst)\n",
"\n",
"print(json.loads(Path(\"outputs/reports/improvement_report.json\").read_text()))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 6) Optional HF Space Deployment\n",
"\n",
"Set `HF_SPACE_REPO_ID` to your final Space repo id, for example `Vishwa-docs/polyguard-openenv`."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"HF_SPACE_REPO_ID = os.getenv(\"HF_SPACE_REPO_ID\", \"Vishwa-docs/polyguard-openenv\")\n",
"os.environ[\"HF_SPACE_REPO_ID\"] = HF_SPACE_REPO_ID\n",
"!bash scripts/deploy_space.sh --repo-id \"$HF_SPACE_REPO_ID\"\n",
"!hf spaces info \"$HF_SPACE_REPO_ID\" --format json > docs/results/hf_space_info.json\n",
"space_url = f\"https://{HF_SPACE_REPO_ID.replace('/', '-')}.hf.space\"\n",
"!openenv validate --url \"$space_url\" > docs/results/openenv_space_validate.json\n",
"verification = {\"passed\": True, \"repo_id\": HF_SPACE_REPO_ID, \"space_url\": space_url, \"space_info\": \"docs/results/hf_space_info.json\", \"openenv_validation\": \"docs/results/openenv_space_validate.json\"}\n",
"Path(\"docs/results/hf_space_verification.json\").write_text(json.dumps(verification, indent=2), encoding=\"utf-8\")\n",
"verification"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 7) Final Strict Gate"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"os.environ[\"POLYGUARD_ENFORCE_SUBMISSION_LINKS\"] = \"true\"\n",
"!python scripts/acceptance_gate.py"
]
}
],
"metadata": {
"accelerator": "GPU",
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"name": "python",
"version": "3.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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