feat: integrate Trackio for experiment tracking and add Modal training infrastructure with environment and test utilities.

.gitignore

@@ -2,5 +2,8 @@
 .env.*
 __pycache__/
 *.pyc
+.pytest_cache/
+outputs/
+codex_tmp_*/
 
-*.egg*
+*.egg*

Dockerfile

@@ -21,6 +21,7 @@ WORKDIR /app/env
 COPY --from=builder /app/env /app/env
 ENV PATH="/app/env/.venv/bin:$PATH"
 ENV PYTHONPATH="/app/env:$PYTHONPATH"
+ENV ENABLE_WEB_INTERFACE=true
 
 HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
     CMD curl -f http://localhost:8000/health || exit 1

README.md

@@ -133,6 +133,24 @@ Training files are under `training/`:
 
 The training scaffold is intentionally minimal until the environment/verifier behavior is stable. Trackio metric names and GRPO defaults follow the project brief.
 
+## Trackio Run Tracking
+
+Trackio is the default tracker for official runs. Set `TRACKIO_SPACE_ID` to log to a hosted Hugging Face Trackio Space; otherwise Trackio records locally.
+
+```bash
+export TRACKIO_SPACE_ID=<hf-user>/CyberSecurity_OWASP-trackio
+export TRACKIO_PROJECT=CyberSecurity_OWASP-grpo
+```
+
+Use the tracked smoke wrapper instead of invoking pytest directly when producing run artifacts:
+
+```bash
+bash scripts/smoke_test.sh
+uv run python scripts/track_pytest.py tests
+```
+
+Evaluation summaries saved through `training.eval_before_after.save_eval_summary(...)`, Modal smoke runs, and GRPO training configs all initialize Trackio runs with CyberSecurity_OWASP run names.
+
 ## Modal Ephemeral Runs
 
 Modal Labs support is kept in a separate launcher script so the local OpenEnv server and core training scaffold stay unchanged.
@@ -149,7 +167,7 @@ Run a temporary Modal app for a cheap environment/training smoke check:
 uv run --extra modal modal run scripts/modal_ephemeral_train.py --mode smoke --episodes 4
 ```
 
-The app is ephemeral: Modal starts it for the command and stops it when the command exits. The remote result is written locally under `outputs/rollouts/`.
+The app is ephemeral: Modal starts it for the command and stops it when the command exits. The remote result is written locally under `outputs/rollouts/` and the summary metrics are logged to Trackio.
 
 You can also validate the GRPO config construction remotely:
 
@@ -187,6 +205,20 @@ uv run --extra modal modal run scripts/modal_train_grpo.py \
   --difficulty 0
 ```
 
+If running from a public repository and you do not want Modal to package the
+local workspace, use public source mode:
+
+```bash
+uv run --extra modal modal run scripts/modal_train_grpo.py \
+  --source-mode public \
+  --repo-url https://github.com/humandotlearning/CyberSecurity_OWASP.git \
+  --repo-branch master \
+  --max-steps 10 \
+  --dataset-size 16 \
+  --num-generations 2 \
+  --difficulty 0
+```
+
 Defaults are derived from `HF_TOKEN`:
 
 - Trackio Space: `<hf-user>/CyberSecurity_OWASP-trackio`

pyproject.toml

@@ -18,6 +18,7 @@ dependencies = [
     # install from github
     # "openenv-core[core] @ git+https://github.com/meta-pytorch/OpenEnv.git",
     "openenv-core[core]>=0.2.2",
+    "trackio>=0.22.0",
     # Environment-specific dependencies
     # Add all dependencies needed for your environment here
     # Examples:

scenario_compiler.py

@@ -2,9 +2,11 @@
 
 from __future__ import annotations
 
+import os
 import tempfile
 from pathlib import Path
 from typing import Any
+from uuid import uuid4
 
 try:
     from .fixture_generator import visible_workspace_summary
@@ -16,11 +18,24 @@ except ImportError:  # pragma: no cover
     from template_renderer import render_fastapi_basic
 
 
+def _make_workspace(prefix: str) -> Path:
+    root = Path(os.getenv("CYBERSECURITY_OWASP_WORKSPACE_ROOT", tempfile.gettempdir()))
+    root.mkdir(parents=True, exist_ok=True)
+    for _ in range(100):
+        workspace = root / f"{prefix}{uuid4().hex[:12]}"
+        try:
+            workspace.mkdir()
+        except FileExistsError:
+            continue
+        return workspace
+    raise RuntimeError("Unable to create isolated scenario workspace")
+
+
 def compile_scenario(seed: int, split: str = "train", difficulty: int = 0) -> dict[str, Any]:
     """Compile one isolated MVP authorization-repair scenario."""
 
     compiled = build_invoice_policy(seed)
-    workspace = Path(tempfile.mkdtemp(prefix=f"cybersecurity_owasp_{split}_{seed}_"))
+    workspace = _make_workspace(prefix=f"cybersecurity_owasp_{split}_{seed}_")
     editable_files = render_fastapi_basic(workspace, compiled.public_hint, compiled.hidden_facts)
     task_id = f"{split}-invoices-bola-{seed}"
     hidden = dict(compiled.hidden_facts)

scripts/modal_ephemeral_train.py

@@ -62,12 +62,18 @@ class NoopTrainer:
 
 
 @app.function(image=image, timeout=60 * 30)
-def run_ephemeral_smoke(episodes: int = 4, seed_start: int = 0) -> dict[str, Any]:
+def run_ephemeral_smoke(
+    episodes: int = 4,
+    seed_start: int = 0,
+    trackio_space_id: str = "",
+    trackio_project: str = "CyberSecurity_OWASP-smoke",
+) -> dict[str, Any]:
     from CyberSecurity_OWASP.models import CyberSecurityOWASPAction
     from CyberSecurity_OWASP.server.CyberSecurity_OWASP_environment import (
         CybersecurityOwaspEnvironment,
     )
     from training.rollout import rollout_once
+    from training.trackio_utils import log_trackio_metrics, trackio_run
 
     baseline = []
     oracle = []
@@ -128,8 +134,9 @@ def run_ephemeral_smoke(episodes: int = 4, seed_start: int = 0) -> dict[str, Any
     def mean(items: list[dict[str, Any]], key: str) -> float:
         return sum(float(item.get(key, 0.0)) for item in items) / max(1, len(items))
 
-    return {
-        "run_name": f"{APP_NAME}-{datetime.utcnow().strftime('%Y%m%d-%H%M%S')}",
+    run_name = f"{APP_NAME}-{datetime.utcnow().strftime('%Y%m%d-%H%M%S')}"
+    result = {
+        "run_name": run_name,
         "mode": "smoke",
         "episodes": episodes,
         "seed_start": seed_start,
@@ -139,6 +146,28 @@ def run_ephemeral_smoke(episodes: int = 4, seed_start: int = 0) -> dict[str, Any
         "baseline": baseline,
         "oracle": oracle,
     }
+    with trackio_run(
+        run_name=run_name,
+        run_type="modal_ephemeral_smoke",
+        project=trackio_project,
+        space_id=trackio_space_id,
+        config={
+            "episodes": episodes,
+            "seed_start": seed_start,
+            "mode": "smoke",
+        },
+        group="smoke",
+    ):
+        log_trackio_metrics(
+            {
+                "smoke/baseline_mean_reward": result["baseline_mean_reward"],
+                "smoke/oracle_mean_reward": result["oracle_mean_reward"],
+                "smoke/oracle_success_rate": result["oracle_success_rate"],
+                "smoke/episodes": episodes,
+            },
+            step=0,
+        )
+    return result
 
 
 @app.function(image=image, timeout=60 * 10)
@@ -149,9 +178,20 @@ def run_grpo_config_check() -> str:
 
 
 @app.local_entrypoint()
-def main(mode: str = "smoke", episodes: int = 4, seed_start: int = 0) -> None:
+def main(
+    mode: str = "smoke",
+    episodes: int = 4,
+    seed_start: int = 0,
+    trackio_space_id: str = "",
+    trackio_project: str = "CyberSecurity_OWASP-smoke",
+) -> None:
     if mode == "smoke":
-        result = run_ephemeral_smoke.remote(episodes=episodes, seed_start=seed_start)
+        result = run_ephemeral_smoke.remote(
+            episodes=episodes,
+            seed_start=seed_start,
+            trackio_space_id=trackio_space_id,
+            trackio_project=trackio_project,
+        )
         output_dir = PROJECT_ROOT / "outputs" / "rollouts"
         output_dir.mkdir(parents=True, exist_ok=True)
         output_path = output_dir / f"{result['run_name']}.json"

scripts/modal_run_ephemeral.sh

@@ -1,3 +1,8 @@
 #!/usr/bin/env bash
 set -euo pipefail
-modal run scripts/modal_ephemeral_train.py --mode "${MODE:-smoke}" --episodes "${EPISODES:-4}" --seed-start "${SEED_START:-0}"
+modal run scripts/modal_ephemeral_train.py \
+  --mode "${MODE:-smoke}" \
+  --episodes "${EPISODES:-4}" \
+  --seed-start "${SEED_START:-0}" \
+  --trackio-space-id "${TRACKIO_SPACE_ID:-}" \
+  --trackio-project "${TRACKIO_PROJECT:-CyberSecurity_OWASP-smoke}"

scripts/modal_train_grpo.py

@@ -32,6 +32,8 @@ SECRET_NAME = "CyberSecurity_OWASP-secrets"
 RUNS_DIR = pathlib.Path("/runs")
 REMOTE_PROJECT = "/root/CyberSecurity_OWASP"
 PROJECT_ROOT = pathlib.Path(__file__).resolve().parents[1]
+PUBLIC_REPO_URL = "https://github.com/humandotlearning/CyberSecurity_OWASP.git"
+PUBLIC_REPO_BRANCH = "master"
 
 
 def _load_local_env_file() -> None:
@@ -44,7 +46,7 @@ def _load_local_env_file() -> None:
             continue
         key, value = line.split("=", 1)
         key = key.strip()
-        if key not in {"TRACKIO_SPACE_ID", "TRACKIO_PROJECT"}:
+        if key not in {"TRACKIO_PROJECT"}:
             continue
         value = value.strip().strip('"').strip("'")
         os.environ.setdefault(key, value)
@@ -69,8 +71,23 @@ def _is_config_mode() -> bool:
 _load_local_env_file()
 
 
+def _cli_arg_value(name: str, default: str = "") -> str:
+    args = sys.argv[1:]
+    flag = f"--{name}"
+    for index, arg in enumerate(args):
+        if arg == flag and index + 1 < len(args):
+            return args[index + 1]
+        if arg.startswith(f"{flag}="):
+            return arg.split("=", 1)[1]
+    return default
+
+
+def _source_mode() -> str:
+    return _cli_arg_value("source-mode", os.environ.get("MODAL_SOURCE_MODE", "local"))
+
+
 def _training_image() -> modal.Image:
-    return (
+    image = (
         modal.Image.from_registry(
             "nvidia/cuda:12.8.0-devel-ubuntu22.04",
             add_python="3.11",
@@ -85,21 +102,33 @@ def _training_image() -> modal.Image:
             "datasets",
             "huggingface_hub",
             "peft",
+            "pillow",
             "tokenizers",
             "nvidia-ml-py",
             "trackio>=0.25.0",
             "transformers>=5.5.0",
             "trl>=0.28.0",
             "openenv-core[core]>=0.2.3",
-            "pydantic>=2.11.7,<3",
         )
         .uv_pip_install(
             "unsloth_zoo[base] @ git+https://github.com/unslothai/unsloth-zoo",
             "unsloth[base] @ git+https://github.com/unslothai/unsloth",
         )
+        .uv_pip_install("pydantic==2.10.6")
         .uv_pip_install("mergekit", "immutables==0.21", extra_options="--no-deps")
+        .uv_pip_install("llm-blender", "weave")
         .uv_pip_install("trl>=0.28.0", "transformers>=5.5.0", "jmespath")
-        .add_local_dir(
+    )
+
+    if _source_mode() == "public":
+        repo_url = _cli_arg_value("repo-url", PUBLIC_REPO_URL)
+        repo_branch = _cli_arg_value("repo-branch", PUBLIC_REPO_BRANCH)
+        image = image.run_commands(
+            f"git clone --depth 1 --branch {repo_branch} {repo_url} {REMOTE_PROJECT}",
+            f"python -m pip install -e {REMOTE_PROJECT}",
+        )
+    else:
+        image = image.add_local_dir(
             PROJECT_ROOT,
             remote_path=REMOTE_PROJECT,
             copy=True,
@@ -112,17 +141,18 @@ def _training_image() -> modal.Image:
                 "*.pyc",
             ],
         )
-        .run_commands(
+        image = image.run_commands(
             f"python -m pip install -e {REMOTE_PROJECT}",
-            "python -c \"import os, torch; import transformers.utils.hub as hub; "
-            "hub.TRANSFORMERS_CACHE = getattr(hub, 'TRANSFORMERS_CACHE', "
-            "os.path.join(os.path.expanduser('~'), '.cache', 'huggingface', 'hub')); "
-            "from trl import GRPOConfig, GRPOTrainer; "
-            "from CyberSecurity_OWASP.server.CyberSecurity_OWASP_environment import "
-            "CybersecurityOwaspEnvironment; print('trainer import ok', torch.__version__)\"",
         )
-        .workdir(REMOTE_PROJECT)
-    )
+
+    return image.run_commands(
+        "python -c \"import os, torch; import transformers.utils.hub as hub; "
+        "hub.TRANSFORMERS_CACHE = getattr(hub, 'TRANSFORMERS_CACHE', "
+        "os.path.join(os.path.expanduser('~'), '.cache', 'huggingface', 'hub')); "
+        "from trl import GRPOConfig, GRPOTrainer; "
+        "from CyberSecurity_OWASP.server.CyberSecurity_OWASP_environment import "
+        "CybersecurityOwaspEnvironment; print('trainer import ok', torch.__version__)\"",
+    ).workdir(REMOTE_PROJECT)
 
 
 app = modal.App(APP_NAME)
@@ -186,16 +216,21 @@ def train_cybersecurity_owasp_grpo(
     seed_start: int = 0,
     git_sha: str = "nogit",
     run_name: str = "",
+    source_mode: str = "local",
+    repo_url: str = PUBLIC_REPO_URL,
+    repo_branch: str = PUBLIC_REPO_BRANCH,
 ) -> dict[str, str | int | float]:
+    import inspect
     import statistics
 
     import torch
+    from unsloth import FastLanguageModel
     import transformers.utils.hub as transformers_hub
     from datasets import Dataset
     from huggingface_hub import whoami
     from transformers import TrainerCallback
-    from trl import GRPOConfig, GRPOTrainer
-    from unsloth import FastLanguageModel
+    from trl import GRPOConfig, GRPOTrainer, clone_chat_template
+    from trl.chat_template_utils import add_response_schema
 
     import trackio
 
@@ -363,11 +398,27 @@ def train_cybersecurity_owasp_grpo(
             return self._step("read_openapi")
 
         def read_file(self, path: str) -> str:
-            """Read an editable generated workspace file by relative path."""
+            """
+            Read an editable generated workspace file by relative path.
+
+            Args:
+                path: Relative path inside the generated editable workspace.
+
+            Returns:
+                The file contents or a safe tool error observation.
+            """
             return self._step("read_file", {"path": path})
 
         def search_code(self, query: str) -> str:
-            """Search editable generated workspace files for a string."""
+            """
+            Search editable generated workspace files for a string.
+
+            Args:
+                query: Search text to find in editable generated app files.
+
+            Returns:
+                Matching file lines or a no-match message.
+            """
             return self._step("search_code", {"query": query})
 
         def send_local_request(
@@ -376,7 +427,17 @@ def train_cybersecurity_owasp_grpo(
             method: str = "GET",
             user_id: str | None = None,
         ) -> str:
-            """Send a request to the generated local app only."""
+            """
+            Send a request to the generated local app only.
+
+            Args:
+                path: Local route path such as /health or /invoices/<id>.
+                method: HTTP method to use for the local request.
+                user_id: Optional generated user identifier for authentication.
+
+            Returns:
+                JSON response from the simulated local app request.
+            """
             return self._step(
                 "send_local_request",
                 {"path": path, "method": method, "user_id": user_id},
@@ -389,7 +450,18 @@ def train_cybersecurity_owasp_grpo(
             second_user_id: str,
             method: str = "GET",
         ) -> str:
-            """Compare one local request as two generated users."""
+            """
+            Compare one local request as two generated users.
+
+            Args:
+                path: Local route path to request as both generated users.
+                first_user_id: First generated user identifier.
+                second_user_id: Second generated user identifier.
+                method: HTTP method to use for both local requests.
+
+            Returns:
+                JSON summary of both simulated local responses.
+            """
             return self._step(
                 "compare_identities",
                 {
@@ -406,7 +478,17 @@ def train_cybersecurity_owasp_grpo(
             evidence: str,
             policy_rule: str,
         ) -> str:
-            """Submit structured evidence for the suspected authorization bug."""
+            """
+            Submit structured evidence for the suspected authorization bug.
+
+            Args:
+                summary: Concise description of the suspected access-control bug.
+                evidence: Local reproduction evidence from policy, code, or requests.
+                policy_rule: Policy rule that the observed behavior violates.
+
+            Returns:
+                Finding acceptance result and next phase information.
+            """
             return self._step(
                 "submit_finding",
                 {
@@ -422,7 +504,17 @@ def train_cybersecurity_owasp_grpo(
             content: str | None = None,
             diff: str | None = None,
         ) -> str:
-            """Patch an editable generated app file with full content or a unified diff."""
+            """
+            Patch an editable generated app file with full content or a unified diff.
+
+            Args:
+                path: Relative path of the editable generated app file to patch.
+                content: Complete replacement file content, when using full-file patching.
+                diff: Unified diff to apply, when using diff patching.
+
+            Returns:
+                Patch application result.
+            """
             args: dict[str, Any] = {"path": path}
             if content is not None:
                 args["content"] = content
@@ -573,7 +665,10 @@ def train_cybersecurity_owasp_grpo(
             return control
 
     print(f"CUDA available: {torch.cuda.is_available()}")
-    print(f"Packaged local CyberSecurity_OWASP repo; default env repo id: {env_repo_id}")
+    if source_mode == "public":
+        print(f"Installed CyberSecurity_OWASP from public repo: {repo_url}@{repo_branch}")
+    else:
+        print(f"Packaged local CyberSecurity_OWASP repo; default env repo id: {env_repo_id}")
     print(f"Trackio Space: {trackio_space_id}")
     print(f"Trackio Project: {trackio_project}")
     print(f"Output repo: {output_repo_id}")
@@ -586,6 +681,18 @@ def train_cybersecurity_owasp_grpo(
         fast_inference=False,
         token=hf_token,
     )
+    try:
+        tokenizer = add_response_schema(tokenizer)
+    except Exception as exc:
+        print(f"Tokenizer response schema add failed before cloning: {exc!r}")
+        model, tokenizer, added_tokens = clone_chat_template(
+            model,
+            tokenizer,
+            "Qwen/Qwen3-0.6B",
+        )
+        print(f"Cloned Qwen3 chat template; added {len(added_tokens)} tokens.")
+        tokenizer = add_response_schema(tokenizer)
+
     model = FastLanguageModel.get_peft_model(
         model,
         r=lora_rank,
@@ -604,46 +711,68 @@ def train_cybersecurity_owasp_grpo(
     )
     FastLanguageModel.for_training(model)
 
+    grpo_config_values = {
+        "temperature": 1.0,
+        "learning_rate": 5e-6,
+        "weight_decay": 0.001,
+        "warmup_ratio": 0.1,
+        "lr_scheduler_type": "linear",
+        "optim": "adamw_8bit",
+        "logging_steps": 1,
+        "per_device_train_batch_size": 1,
+        "gradient_accumulation_steps": max(2, num_generations),
+        "num_generations": num_generations,
+        "max_prompt_length": max_seq_length,
+        "max_completion_length": max_completion_length,
+        "max_steps": max_steps,
+        "save_steps": max(10, max_steps),
+        "report_to": "trackio",
+        "trackio_space_id": trackio_space_id,
+        "run_name": run_name,
+        "output_dir": str(output_dir),
+        "push_to_hub": True,
+        "hub_model_id": output_repo_id,
+        "hub_private_repo": True,
+        "hub_strategy": "every_save",
+        "gradient_checkpointing": True,
+        "gradient_checkpointing_kwargs": {"use_reentrant": False},
+        "epsilon": 0.2,
+        "epsilon_high": 0.28,
+        "delta": 1.5,
+        "loss_type": "bnpo",
+        "mask_truncated_completions": False,
+    }
+    grpo_config_parameters = set(inspect.signature(GRPOConfig).parameters)
+    skipped_config_keys = sorted(set(grpo_config_values) - grpo_config_parameters)
+    if skipped_config_keys:
+        print(f"Skipping unsupported GRPOConfig keys: {skipped_config_keys}")
     training_args = GRPOConfig(
-        temperature=1.0,
-        learning_rate=5e-6,
-        weight_decay=0.001,
-        warmup_ratio=0.1,
-        lr_scheduler_type="linear",
-        optim="adamw_8bit",
-        logging_steps=1,
-        per_device_train_batch_size=1,
-        gradient_accumulation_steps=max(2, num_generations),
-        num_generations=num_generations,
-        max_prompt_length=max_seq_length,
-        max_completion_length=max_completion_length,
-        max_steps=max_steps,
-        save_steps=max(10, max_steps),
-        report_to="trackio",
-        trackio_space_id=trackio_space_id,
-        run_name=run_name,
-        output_dir=str(output_dir),
-        push_to_hub=True,
-        hub_model_id=output_repo_id,
-        hub_private_repo=True,
-        hub_strategy="every_save",
-        gradient_checkpointing=True,
-        gradient_checkpointing_kwargs={"use_reentrant": False},
-        epsilon=0.2,
-        epsilon_high=0.28,
-        delta=1.5,
-        loss_type="bnpo",
-        mask_truncated_completions=False,
+        **{
+            key: value
+            for key, value in grpo_config_values.items()
+            if key in grpo_config_parameters
+        }
     )
 
+    trainer_values = {
+        "model": model,
+        "processing_class": tokenizer,
+        "reward_funcs": cybersecurity_owasp_reward,
+        "args": training_args,
+        "train_dataset": dataset,
+        "environment_factory": CyberSecurityOWASPToolEnv,
+        "callbacks": [TrackioSystemMetricsCallback()],
+    }
+    trainer_parameters = set(inspect.signature(GRPOTrainer).parameters)
+    skipped_trainer_keys = sorted(set(trainer_values) - trainer_parameters)
+    if skipped_trainer_keys:
+        print(f"Skipping unsupported GRPOTrainer keys: {skipped_trainer_keys}")
     trainer = GRPOTrainer(
-        model=model,
-        processing_class=tokenizer,
-        reward_funcs=cybersecurity_owasp_reward,
-        args=training_args,
-        train_dataset=dataset,
-        environment_factory=CyberSecurityOWASPToolEnv,
-        callbacks=[TrackioSystemMetricsCallback()],
+        **{
+            key: value
+            for key, value in trainer_values.items()
+            if key in trainer_parameters
+        }
     )
     trainer.train()
     trainer.push_to_hub()
@@ -662,6 +791,9 @@ def train_cybersecurity_owasp_grpo(
         "model_name": model_name,
         "max_completion_length": max_completion_length,
         "num_generations": num_generations,
+        "source_mode": source_mode,
+        "repo_url": repo_url,
+        "repo_branch": repo_branch,
     }
 
 
@@ -683,6 +815,10 @@ def main(
     num_generations: int = 2,
     seed_start: int = 0,
     git_sha: str = "nogit",
+    source_mode: str = "local",
+    repo_url: str = PUBLIC_REPO_URL,
+    repo_branch: str = PUBLIC_REPO_BRANCH,
+    detach: bool = False,
 ) -> None:
     if mode == "config":
         result = check_training_imports.remote()
@@ -732,7 +868,23 @@ def main(
         f"{local_stamp}-{git_sha[:8]}"
     )
 
-    call = train_cybersecurity_owasp_grpo.spawn(
+    print(f"Run name: {run_name}")
+    print(f"Source mode: {source_mode}")
+    if source_mode == "public":
+        print(f"Public repo: {repo_url}@{repo_branch}")
+    if resolved_trackio_space_id:
+        print(f"Trackio Space: https://huggingface.co/spaces/{resolved_trackio_space_id}")
+    else:
+        print("Trackio Space: derived remotely from HF_TOKEN as <hf-user>/CyberSecurity_OWASP-trackio")
+    if resolved_output_repo_id:
+        print(f"Output model repo: https://huggingface.co/{resolved_output_repo_id}")
+    else:
+        print(
+            "Output model repo: derived remotely from HF_TOKEN as "
+            "<hf-user>/CyberSecurity_OWASP-qwen3-1.7b-grpo-lora"
+        )
+
+    kwargs = dict(
         env_repo_id=env_repo_id,
         output_repo_id=output_repo_id,
         max_steps=max_steps,
@@ -749,17 +901,13 @@ def main(
         seed_start=seed_start,
         git_sha=git_sha,
         run_name=run_name,
+        source_mode=source_mode,
+        repo_url=repo_url,
+        repo_branch=repo_branch,
     )
-    print(f"Spawned Modal training call: {call.object_id}")
-    print(f"Run name: {run_name}")
-    if resolved_trackio_space_id:
-        print(f"Trackio Space: https://huggingface.co/spaces/{resolved_trackio_space_id}")
+    if detach:
+        call = train_cybersecurity_owasp_grpo.spawn(**kwargs)
+        print(f"Spawned Modal training call: {call.object_id}")
     else:
-        print("Trackio Space: derived remotely from HF_TOKEN as <hf-user>/CyberSecurity_OWASP-trackio")
-    if resolved_output_repo_id:
-        print(f"Output model repo: https://huggingface.co/{resolved_output_repo_id}")
-    else:
-        print(
-            "Output model repo: derived remotely from HF_TOKEN as "
-            "<hf-user>/CyberSecurity_OWASP-qwen3-1.7b-grpo-lora"
-        )
+        result = train_cybersecurity_owasp_grpo.remote(**kwargs)
+        print(f"Training result: {result}")

scripts/smoke_test.sh

@@ -1,3 +1,3 @@
 #!/usr/bin/env bash
 set -euo pipefail
-uv run pytest tests/test_models.py tests/test_reset_step_state.py
+uv run python scripts/track_pytest.py tests/test_models.py tests/test_reset_step_state.py

scripts/track_pytest.py

@@ -0,0 +1,58 @@
+"""Run pytest and record the result as a Trackio run."""
+
+from __future__ import annotations
+
+import argparse
+import subprocess
+import sys
+import time
+from pathlib import Path
+
+PROJECT_ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(PROJECT_ROOT))
+
+from training.trackio_utils import build_run_name, get_git_sha, log_trackio_metrics, trackio_run
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="Run pytest with Trackio tracking.")
+    parser.add_argument("pytest_args", nargs="*", help="Arguments passed through to pytest.")
+    parser.add_argument("--run-name", default="", help="Trackio run name override.")
+    parser.add_argument("--difficulty", type=int, default=0)
+    args, passthrough = parser.parse_known_args()
+
+    run_name = args.run_name or build_run_name(
+        "pytest",
+        "smoke",
+        args.difficulty,
+        git_sha=get_git_sha(),
+    )
+    pytest_args = [*args.pytest_args, *passthrough] or ["tests"]
+    command = [sys.executable, "-m", "pytest", *pytest_args]
+    started = time.perf_counter()
+
+    with trackio_run(
+        run_name=run_name,
+        run_type="pytest",
+        config={
+            "command": " ".join(command),
+            "pytest_args": pytest_args,
+        },
+        group="smoke",
+    ):
+        completed = subprocess.run(command)
+        duration = time.perf_counter() - started
+        log_trackio_metrics(
+            {
+                "smoke/pytest_exit_code": completed.returncode,
+                "smoke/pytest_passed": completed.returncode == 0,
+                "smoke/duration_seconds": duration,
+            },
+            step=0,
+        )
+
+    return completed.returncode
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

server/Dockerfile

@@ -70,6 +70,7 @@ ENV PATH="/app/.venv/bin:$PATH"
 
 # Set PYTHONPATH so imports work correctly
 ENV PYTHONPATH="/app/env:$PYTHONPATH"
+ENV ENABLE_WEB_INTERFACE=true
 
 # Health check
 HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \

server/app.py

@@ -6,6 +6,13 @@
 
 """FastAPI application for the CyberSecurity_OWASP OpenEnv server."""
 
+import os
+
+# OpenEnv disables the Gradio playground unless this flag is enabled. Default it
+# on so Docker/HF Spaces show the reset/step/state UI, while explicit env values
+# such as ENABLE_WEB_INTERFACE=false still take precedence.
+os.environ.setdefault("ENABLE_WEB_INTERFACE", "true")
+
 try:
     from openenv.core.env_server.http_server import create_app
 except Exception as e:  # pragma: no cover

tests/test_web_interface.py

@@ -0,0 +1,47 @@
+from fastapi.testclient import TestClient
+
+from server.app import app
+
+
+def test_space_root_redirects_to_openenv_web_ui():
+    client = TestClient(app)
+
+    response = client.get("/", follow_redirects=False)
+
+    assert response.status_code == 307
+    assert response.headers["location"] == "/web/"
+
+
+def test_openenv_web_ui_and_api_routes_are_available():
+    client = TestClient(app)
+
+    web_response = client.get("/web/")
+    health_response = client.get("/health")
+    state_response = client.get("/web/state")
+
+    assert web_response.status_code == 200
+    assert "text/html" in web_response.headers["content-type"]
+    assert "Reset" in web_response.text
+    assert "Step" in web_response.text
+    assert "Get state" in web_response.text
+
+    assert health_response.status_code == 200
+    assert health_response.json() == {"status": "healthy"}
+
+    assert state_response.status_code == 200
+    state = state_response.json()
+    assert "episode_id" in state
+    assert "step_count" in state
+
+
+def test_web_reset_returns_cybersecurity_observation():
+    client = TestClient(app)
+
+    response = client.post("/web/reset")
+
+    assert response.status_code == 200
+    payload = response.json()
+    observation = payload["observation"]
+    assert observation["phase"] == "discover"
+    assert "authorization" in observation["task_brief"]
+    assert "inspect_policy_graph" in observation["available_actions"]

training/eval_before_after.py

@@ -5,6 +5,8 @@ from __future__ import annotations
 import json
 from pathlib import Path
 
+from training.trackio_utils import log_eval_summary
+
 
 def summarize_runs(baseline: list[dict], trained: list[dict], heldout: list[dict]) -> dict:
     def mean(items: list[dict], key: str) -> float:
@@ -19,11 +21,27 @@ def summarize_runs(baseline: list[dict], trained: list[dict], heldout: list[dict
         "absolute_reward_improvement": mean(trained, "reward_total") - mean(baseline, "reward_total"),
         "heldout_success_rate": mean(heldout, "success"),
         "heldout_mean_reward": mean(heldout, "reward_total"),
+        "exploit_block_rate": mean(trained, "exploit_blocked"),
+        "regression_preservation_rate": mean(trained, "regression_preserved"),
+        "public_route_preservation_rate": mean(trained, "public_routes_preserved"),
+        "anti_cheat_pass_rate": mean(trained, "anti_cheat_pass"),
+        "invalid_action_rate": mean(trained, "invalid_action_rate"),
+        "timeout_rate": mean(trained, "timeout"),
+        "safety_violation_rate": mean(trained, "safety_violation"),
+        "mean_episode_length": mean(trained, "episode_length"),
     }
 
 
-def save_eval_summary(run_name: str, summary: dict) -> Path:
+def save_eval_summary(
+    run_name: str,
+    summary: dict,
+    *,
+    track: bool = True,
+    trackio_config: dict | None = None,
+) -> Path:
     output = Path("outputs/evals") / f"{run_name}_eval_summary.json"
     output.parent.mkdir(parents=True, exist_ok=True)
     output.write_text(json.dumps(summary, indent=2, sort_keys=True), encoding="utf-8")
+    if track:
+        log_eval_summary(run_name, summary, config=trackio_config)
     return output

training/trackio_utils.py

@@ -2,7 +2,12 @@
 
 from __future__ import annotations
 
+import os
+import subprocess
+from contextlib import contextmanager
 from datetime import datetime
+from pathlib import Path
+from typing import Any, Iterator
 
 
 TRAIN_METRICS = [
@@ -34,7 +39,133 @@ TRAIN_METRICS = [
 ]
 
 
+EVAL_METRICS = [
+    "eval/baseline_success_rate",
+    "eval/trained_success_rate",
+    "eval/absolute_success_improvement",
+    "eval/baseline_mean_reward",
+    "eval/trained_mean_reward",
+    "eval/absolute_reward_improvement",
+    "eval/heldout_success_rate",
+    "eval/heldout_mean_reward",
+    "eval/exploit_block_rate",
+    "eval/regression_preservation_rate",
+    "eval/public_route_preservation_rate",
+    "eval/anti_cheat_pass_rate",
+    "eval/invalid_action_rate",
+    "eval/timeout_rate",
+    "eval/safety_violation_rate",
+    "eval/mean_episode_length",
+]
+
+
 def build_run_name(model: str, algo: str, difficulty: int, git_sha: str = "nogit") -> str:
-    stamp = datetime.utcnow().strftime("%Y%m%d-%H%M")
+    stamp = datetime.utcnow().strftime("%Y%m%d-%H%M%S")
     model_slug = model.replace("/", "-")
     return f"CyberSecurity_OWASP-{model_slug}-{algo}-level{difficulty}-{stamp}-{git_sha[:8]}"
+
+
+def get_git_sha(default: str = "nogit") -> str:
+    try:
+        result = subprocess.run(
+            ["git", "rev-parse", "HEAD"],
+            check=True,
+            capture_output=True,
+            text=True,
+        )
+    except Exception:
+        return default
+    return result.stdout.strip() or default
+
+
+def _load_trackio():
+    os.environ.setdefault("TRACKIO_DIR", str((Path.cwd() / "outputs" / "trackio").resolve()))
+    try:
+        import trackio
+    except ImportError as exc:
+        raise RuntimeError(
+            "Trackio is required for CyberSecurity_OWASP runs. Install dependencies "
+            "with `uv sync` and set TRACKIO_SPACE_ID when you want remote HF Spaces tracking."
+        ) from exc
+    return trackio
+
+
+def init_trackio_run(
+    *,
+    run_name: str,
+    run_type: str,
+    config: dict[str, Any] | None = None,
+    project: str | None = None,
+    space_id: str | None = None,
+    group: str | None = None,
+):
+    trackio = _load_trackio()
+    project = project or os.getenv("TRACKIO_PROJECT", "CyberSecurity_OWASP")
+    space_id = space_id if space_id is not None else os.getenv("TRACKIO_SPACE_ID", "")
+    run_config = {
+        "environment": "CyberSecurity_OWASP",
+        "run_type": run_type,
+        **(config or {}),
+    }
+    kwargs: dict[str, Any] = {
+        "project": project,
+        "name": run_name,
+        "config": run_config,
+    }
+    if space_id:
+        kwargs["space_id"] = space_id
+    if group:
+        kwargs["group"] = group
+    return trackio.init(**kwargs)
+
+
+def log_trackio_metrics(metrics: dict[str, Any], step: int | None = None) -> None:
+    trackio = _load_trackio()
+    numeric = {
+        key: value
+        for key, value in metrics.items()
+        if isinstance(value, (int, float, bool))
+    }
+    if step is None:
+        trackio.log(numeric)
+    else:
+        trackio.log(numeric, step=step)
+
+
+def finish_trackio_run() -> None:
+    trackio = _load_trackio()
+    trackio.finish()
+
+
+@contextmanager
+def trackio_run(
+    *,
+    run_name: str,
+    run_type: str,
+    config: dict[str, Any] | None = None,
+    project: str | None = None,
+    space_id: str | None = None,
+    group: str | None = None,
+) -> Iterator[Any]:
+    run = init_trackio_run(
+        run_name=run_name,
+        run_type=run_type,
+        config=config,
+        project=project,
+        space_id=space_id,
+        group=group,
+    )
+    try:
+        yield run
+    finally:
+        finish_trackio_run()
+
+
+def log_eval_summary(run_name: str, summary: dict[str, Any], config: dict[str, Any] | None = None) -> None:
+    metrics = {
+        f"eval/{key}": float(value)
+        for key, value in summary.items()
+        if isinstance(value, (int, float, bool))
+    }
+    with trackio_run(run_name=run_name, run_type="eval", config=config, group="eval"):
+        log_trackio_metrics(metrics, step=0)

training/train_grpo.py

@@ -9,16 +9,26 @@ from __future__ import annotations
 
 import os
 
+from training.trackio_utils import build_run_name, get_git_sha
+
 
 def build_grpo_config():
     from trl import GRPOConfig
 
+    model_name = os.getenv("MODEL_NAME", "Qwen/Qwen3-1.7B")
+    difficulty = int(os.getenv("DIFFICULTY", "0"))
     output_dir = os.getenv("OUTPUT_DIR", "CyberSecurity_OWASP-qwen3-1.7b-grpo")
     trackio_space_id = os.getenv("TRACKIO_SPACE_ID", output_dir)
+    os.environ.setdefault("TRACKIO_PROJECT", "CyberSecurity_OWASP-grpo")
+    run_name = os.getenv(
+        "RUN_NAME",
+        build_run_name(model_name, "grpo", difficulty, git_sha=get_git_sha()),
+    )
     return GRPOConfig(
         output_dir=output_dir,
         report_to="trackio",
         trackio_space_id=trackio_space_id,
+        run_name=run_name,
         logging_steps=1,
         save_steps=25,
         learning_rate=5e-6,

uv.lock

@@ -1283,6 +1283,49 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55", size = 78784, upload-time = "2025-04-24T22:06:20.566Z" },
 ]
 
+[[package]]
+name = "httptools"
+version = "0.7.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/b5/46/120a669232c7bdedb9d52d4aeae7e6c7dfe151e99dc70802e2fc7a5e1993/httptools-0.7.1.tar.gz", hash = "sha256:abd72556974f8e7c74a259655924a717a2365b236c882c3f6f8a45fe94703ac9", size = 258961, upload-time = "2025-10-10T03:55:08.559Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/c7/e5/c07e0bcf4ec8db8164e9f6738c048b2e66aabf30e7506f440c4cc6953f60/httptools-0.7.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:11d01b0ff1fe02c4c32d60af61a4d613b74fad069e47e06e9067758c01e9ac78", size = 204531, upload-time = "2025-10-10T03:54:20.887Z" },
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 source = { editable = "." }
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     { name = "pytest-cov", marker = "extra == 'dev'", specifier = ">=4.0.0" },
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