[Harbor] Add Modal support and bump Harbor version

skyrl-train/examples/terminal_bench/README.md

@@ -5,7 +5,7 @@ Integration with Terminal-Bench is a work in progress.
 We specify a specific harbor commit in our `pyproject.toml`, which you can easily substitute or even use a local copy of Harbor.
 
 ```toml
-harbor = { git = "https://github.com/laude-institute/harbor", rev = "fdfe296145cf13663dc6a0233f8faab7bfcf5fe1" }
+harbor = { git = "https://github.com/laude-institute/harbor", rev = "5921cc40e8f6b5b0df0a3dc6354e0e679447eb54" }
 ```
 
 Tracked here: https://github.com/NovaSky-AI/SkyRL/issues/866
@@ -46,4 +46,11 @@ To configure the Harbor-specific parameters (e.g. the maximum turns a rollout ca
 
 You can override any config supported by Harbor's `TrialConfig` in the script with `++`, just like what we do for `trials_dir` here.
 
-For all the configurations, see [Harbor's documentation](https://harborframework.com/docs), and the `TrialConfig` definition: https://github.com/laude-institute/harbor/blob/fdfe296145cf13663dc6a0233f8faab7bfcf5fe1/src/harbor/models/trial/config.py
+For all the configurations, see [Harbor's documentation](https://harborframework.com/docs), and the `TrialConfig` definition: https://github.com/laude-institute/harbor/blob/5921cc40e8f6b5b0df0a3dc6354e0e679447eb54/src/harbor/models/trial/config.py
+
+### Main configuration knobs
+
+- `++terminal_bench_config.environment.type=daytona` or `=modal`
+  - Harbor supports various ways of [hosting the sandboxes](https://harborframework.com/docs/core-concepts#container-environment) for the agent to run the task (Daytona, Modal, E2B, GKE (Google Kubernetes Engine))
+  - SkyRL + Harbor integration has tested with Daytona and Modal, but the other providers should work out of the box
+- More documentations to come

skyrl-train/examples/terminal_bench/terminal_bench_config/default.yaml

@@ -12,7 +12,7 @@
 # See Harbor documentation for all available options:
 # https://harborframework.com/docs
 # And a full list of fields that TrialConfig supports:
-# https://github.com/laude-institute/harbor/blob/fdfe296145cf13663dc6a0233f8faab7bfcf5fe1/src/harbor/models/trial/config.py
+# https://github.com/laude-institute/harbor/blob/5921cc40e8f6b5b0df0a3dc6354e0e679447eb54/src/harbor/models/trial/config.py
 
 # Harbor TrialConfig fields below
 # --------------------------------

skyrl-train/pyproject.toml

@@ -97,7 +97,7 @@ torch = [
     { index = "pytorch-cu128", marker = "sys_platform == 'linux'" },
     { index = "pytorch-cpu", marker = "sys_platform == 'darwin'" },
 ]
-harbor = { git = "https://github.com/laude-institute/harbor", rev = "fdfe296145cf13663dc6a0233f8faab7bfcf5fe1" }
+harbor = { git = "https://github.com/laude-institute/harbor", rev = "5921cc40e8f6b5b0df0a3dc6354e0e679447eb54" }
 torchvision = [
     { index = "pytorch-cu128", marker = "sys_platform == 'linux'" },
     { index = "pytorch-cpu", marker = "sys_platform == 'darwin'" },

skyrl-train/skyrl_train/utils/utils.py

@@ -653,9 +653,11 @@ def prepare_runtime_environment(cfg: Union[SkyRLConfig, DictConfig]) -> dict[str
         logger.info("Exporting mlflow tracking token to ray runtime env")
         env_vars["MLFLOW_TRACKING_TOKEN"] = os.environ["MLFLOW_TRACKING_TOKEN"]
 
-    if os.environ.get("DAYTONA_API_KEY"):
-        logger.info("Exporting daytona api key to ray runtime env")
-        env_vars["DAYTONA_API_KEY"] = os.environ["DAYTONA_API_KEY"]
+    # NOTE(charlie): these are for Harbor. We should remove these once we have a sustainable way to handle these environment vars.
+    for var_name in ["DAYTONA_API_KEY", "MODAL_TOKEN_ID", "MODAL_TOKEN_SECRET"]:
+        if value := os.environ.get(var_name):
+            logger.info(f"Exporting {var_name} to ray runtime env")
+            env_vars[var_name] = value
 
     if SKYRL_LD_LIBRARY_PATH_EXPORT:
         # export `LD_LIBRARY_PATH` to ray runtime env.