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Description:

languageworld 0.1.1

Language-World
A language and robotics benchmark based on Meta-World.
Language-World is packaged as a set of small tools which process Meta-World observations.
Wrapping Meta-World environments directly is left up to the user.
To avoid confusion, please always use the goal-observable, randomized goal and initial state variation of Meta-World (MT50-rand), and always sample length 500 episodes.
If you choose not to, please prominently document what configuration you used instead.
Language-World can be installed via pip:
pip install git+https://github.com/krzentner/language-world.git@v0.1.0

Alternatively, copy this file into your project.
Language-World consists of three main components:
First, a set of natural language task descriptions available as a dictionary: language_world.TASK_DESCRIPTIONS: dict[str, str]
Second, a set of "scripted skills," that can be used to solve MT10 (and also function in other tasks).
language_world.SCRIPTED_SKILL_NAMES: list[str] lists the names of all scripted skills.
language_world.run_scripted_skill(skill_name: str, obs: np.ndarray) -> np.ndarray produces an action given a skill name and observation.
Thirdly, a query answering function:
language_world.eval_queries(task_name: str, queries: List[str],
obs: np.ndarray, fuzzy: bool=False)

The query answering function can evaluate a large number of queries.
Enabling the fuzzy flag will map unsupported queries to the nearest supported queries using string edit distance.
language_world.enumerate_base_queries(task_name: str) -> list[str] provides a list of the "base" queries for a task (i.e. those that do not contain conjunctions).
language_world.enumerate_all_queries(task_name: str) -> list[str] provides a list of all queries for a task.