From d2684d41cd21e3fcb34b284df469004106044998 Mon Sep 17 00:00:00 2001
From: Jade Choghari <chogharijade@gmail.com>
Date: Fri, 8 Aug 2025 09:34:14 -0400
Subject: [PATCH] add factory

---
 src/lerobot/envs/factory.py | 48 ++++++++++++++++++++++++-------------
 1 file changed, 32 insertions(+), 16 deletions(-)

diff --git a/src/lerobot/envs/factory.py b/src/lerobot/envs/factory.py
index dc6d96d61..cb897e68d 100644
--- a/src/lerobot/envs/factory.py
+++ b/src/lerobot/envs/factory.py
@@ -17,7 +17,7 @@ import importlib
 
 import gymnasium as gym
 
-from lerobot.envs.configs import AlohaEnv, EnvConfig, HILEnvConfig, PushtEnv, XarmEnv
+from lerobot.envs.configs import AlohaEnv, EnvConfig, HILEnvConfig, LiberoEnv, PushtEnv, XarmEnv
 
 
 def make_env_config(env_type: str, **kwargs) -> EnvConfig:
@@ -29,6 +29,8 @@ def make_env_config(env_type: str, **kwargs) -> EnvConfig:
         return XarmEnv(**kwargs)
     elif env_type == "hil":
         return HILEnvConfig(**kwargs)
+    elif env_type == "libero":
+        return LiberoEnv(**kwargs)
     else:
         raise ValueError(f"Policy type '{env_type}' is not available.")
 
@@ -39,12 +41,12 @@ def make_env(cfg: EnvConfig, n_envs: int = 1, use_async_envs: bool = False) -> g
     Args:
         cfg (EnvConfig): the config of the environment to instantiate.
         n_envs (int, optional): The number of parallelized env to return. Defaults to 1.
-        use_async_envs (bool, optional): Whether to return an AsyncVectorEnv or a SyncVectorEnv. Defaults to
+        use_async_envs (bool, optional): Wether to return an AsyncVectorEnv or a SyncVectorEnv. Defaults to
             False.
 
     Raises:
         ValueError: if n_envs < 1
-        ModuleNotFoundError: If the requested env package is not installed
+        ModuleNotFoundError: If the requested env package is not intalled
 
     Returns:
         gym.vector.VectorEnv: The parallelized gym.env instance.
@@ -52,20 +54,34 @@ def make_env(cfg: EnvConfig, n_envs: int = 1, use_async_envs: bool = False) -> g
     if n_envs < 1:
         raise ValueError("`n_envs must be at least 1")
 
-    package_name = f"gym_{cfg.type}"
-
-    try:
-        importlib.import_module(package_name)
-    except ModuleNotFoundError as e:
-        print(f"{package_name} is not installed. Please install it with `pip install 'lerobot[{cfg.type}]'`")
-        raise e
-
-    gym_handle = f"{package_name}/{cfg.task}"
-
     # batched version of the env that returns an observation of shape (b, c)
     env_cls = gym.vector.AsyncVectorEnv if use_async_envs else gym.vector.SyncVectorEnv
-    env = env_cls(
-        [lambda: gym.make(gym_handle, disable_env_checker=True, **cfg.gym_kwargs) for _ in range(n_envs)]
-    )
+
+    if "libero" in cfg.type:
+        from lerobot.envs.libero import create_libero_envs
+
+        env = create_libero_envs(
+            task=cfg.task,
+            n_envs=n_envs,
+            camera_name=cfg.camera_name,
+            init_states=cfg.init_states,
+            gym_kwargs=cfg.gym_kwargs,
+            env_cls=env_cls,
+            multitask_eval=cfg.multitask_eval,
+        )
+    else:
+        package_name = f"gym_{cfg.type}"
+        try:
+            importlib.import_module(package_name)
+        except ModuleNotFoundError as e:
+            print(
+                f"{package_name} is not installed. Please install it with `pip install 'lerobot[{cfg.type}]'`"
+            )
+            raise e
+
+        gym_handle = f"{package_name}/{cfg.task}"
+        env = env_cls(
+            [lambda: gym.make(gym_handle, disable_env_checker=True, **cfg.gym_kwargs) for _ in range(n_envs)]
+        )
 
     return env