diff --git a/README.md b/README.md index d6491b3..7ead192 100644 --- a/README.md +++ b/README.md @@ -1 +1,77 @@ -# planetarium \ No newline at end of file +# planetarium🪐 + +Planetarium🪐 is a [dataset](https://huggingface.co/datasets/BatsResearch/planetarium) and benchmark for assessing LLMs in translating natural language descriptions of planning problems into PDDL. We developed a robust method for comparing PDDL problem descriptions using graph isomorphism. + +## Installation +To install the `planetarium` package, you can use the following command: +```bash +pip install git+https://github.com/BatsResearch/planetarium.git +``` + +For development or using our evaluate & finetune scripts, you can clone the repository and install all dependencies using the following commands: +```bash +git clone https://github.com/BatsResearch/planetarium.git +cd planetarium +poetry install --with all +``` + +To use `planetarium.downward`, you will need to have the [Fast-Downward](https://www.fast-downward.org/) planner installed, and the [VAL](https://github.com/KCL-Planning/VAL) plan validator. The following commands is one way to install them with minimal overhead: +```bash +# Fast-Downward via Apptainer +apptainer pull fast-downward.sif docker://aibasel/downward:latest +# VAL download link might not work, follow instructions to download binary at: https://github.com/KCL-Planning/VAL +mkdir tmp +curl -o tmp/VAL.zip https://dev.azure.com/schlumberger/4e6bcb11-cd68-40fe-98a2-e3777bfec0a6/_apis/build/builds/77/artifacts?artifactName=linux64\&api-version=7.1\&%24format=zip +unzip tmp/VAL.zip -d tmp/ +tar -xzvf tmp/linux64/*.tar.gz -C tmp/ --strip-components=1 +# clean up +rm -rf tmp +# Make sure to add fast-downward.sif and VAL to your PATH or make aliases. +``` + +## Basic Usage +To evaluate a PDDL problem description, we can use the `planetarium.evaluate` module: +```python +from planetarium import evaluate +... +evaluate.evaluate(gt_pddl_str, pred_pddl_str) +``` +The supported domains are `blocksworld` and `gripper` domains. + +## Dataset +The main page for the dataset can be found [here](https://huggingface.co/datasets/BatsResearch/planetarium). + +Here is an example of how to load the dataset: +```python +from datasets import load_dataset + +dataset = load_dataset("BatsResearch/planetarium") +``` + +You can reporduce the dataset, the splits, and a report by running the following command: +```bash +python dataset_generator.py -c dataset_config.yaml +``` + +By modifying the `dataset_config.yaml` file, you can change the dataset splits, the number of samples, and produce even more examples! + +### Dataset Report +Here is a summary of the types of PDDL problems in the dataset: + +Total number of problems: $132,037$. + +#### Abstractness Split +| Init | Goal | blocksworld | gripper | +|:---:|:---:|---:|---:| +| abstract | abstract | $23,144$ | $10,632$ | +| abstract | explicit | $23,086$ | $9,518$ | +| explicit | abstract | $23,087$ | $10,313$ | +| explicit | explicit | $23,033$ | $9,224$ | +#### Size Splits (Number of Propositions in Ground Truth) +| Num. of Propositions | blocksworld | gripper | +|:---:|---:|---:| +| $0$ - $20$ | $1,012$ | $379$ | +| $20$ - $40$ | $10,765$ | $2,112$ | +| $40$ - $60$ | $50,793$ | $9,412$ | +| $60$ - $80$ | $26,316$ | $25,346$ | +| $80$ - inf | $3,464$ | $2,438$ | \ No newline at end of file diff --git a/evaluate.py b/evaluate.py index ab42d1a..0e41028 100644 --- a/evaluate.py +++ b/evaluate.py @@ -17,8 +17,6 @@ from planetarium import builder, graph, metric, oracle import llm_planner as llmp -from utils import apply_template - HF_USER_TOKEN = os.getenv("HF_USER_TOKEN") @@ -82,8 +80,7 @@ def plan( context = [] for example_problem in example_problems: context.extend( - apply_template( - example_problem, + example_problem.apply_template( domain_prompt, problem_prompt, ) @@ -91,8 +88,7 @@ def plan( if isinstance(problem, llmp.PlanningProblem): messages = [ - apply_template( - problem, + problem.apply_template( domain_prompt, problem_prompt, include_answer=False, @@ -100,8 +96,7 @@ def plan( ] else: messages = [ - apply_template( - p, + p.apply_template( domain_prompt, problem_prompt, include_answer=False, diff --git a/finetune.py b/finetune.py index 773142e..8f95616 100644 --- a/finetune.py +++ b/finetune.py @@ -26,7 +26,6 @@ import tqdm as tqdm import llm_planner as llmp -from utils import apply_template from accelerate import Accelerator @@ -137,8 +136,7 @@ def preprocess( inputs = [ strip( tokenizer.apply_chat_template( - apply_template( - llmp.PlanningProblem(nl, d, p), + llmp.PlanningProblem(nl, d, p).apply_template( domain_prompt, problem_prompt, ), diff --git a/llm_planner.py b/llm_planner.py index 3aece5a..19462a3 100644 --- a/llm_planner.py +++ b/llm_planner.py @@ -31,6 +31,39 @@ def __init__( self.domain = domain self.problem = problem + def apply_template( + self, + domain_prompt: str = "", + problem_prompt: str = "", + include_answer: bool = True, + ) -> list[dict[str, str]]: + """Apply problem template to the problem. + + Args: + domain_prompt (str, optional): How to prompt the domain. Defaults to "". + problem_prompt (str, optional): How to prompt the problem. Defaults to "". + include_answer (bool, optional): Whether to include the answer. Defaults to True. + + Returns: + list[dict[str, str]]: Problem prompt. + """ + return [ + { + "role": "user", + "content": f"{problem_prompt} {self.natural_language} " + + f"{domain_prompt}\n{self.domain}\n", + }, + ] + ( + [ + { + "role": "assistant", + "content": " " + self.problem, + }, + ] + if include_answer + else [] + ) + class Planner(abc.ABC): @abc.abstractmethod diff --git a/planetarium/graph.py b/planetarium/graph.py index 2754a27..d4bf4bd 100644 --- a/planetarium/graph.py +++ b/planetarium/graph.py @@ -4,6 +4,8 @@ import enum from functools import cached_property +import matplotlib.pyplot as plt +import networkx as nx import rustworkx as rx @@ -360,6 +362,40 @@ def __eq__(self, other: "PlanGraph") -> bool: and self.domain == other.domain ) + def plot(self, fig: plt.Figure | None = None) -> plt.Figure: + """Generate a plot of the graph, sorted by topological generation. + + Args: + fig (plt.Figure | None, optional): The figure to plot on. Defaults + to None. + + Returns: + plt.Figure: The figure containing the plot. + """ + # rx has no plotting functionality + nx_graph = nx.MultiDiGraph() + nx_graph.add_edges_from( + [(u.node, v.node, {"data": edge}) for u, v, edge in self.edges] + ) + + for layer, nodes in enumerate(nx.topological_generations(nx_graph)): + for node in nodes: + nx_graph.nodes[node]["layer"] = layer + + pos = nx.multipartite_layout( + nx_graph, + align="horizontal", + subset_key="layer", + scale=-1, + ) + + if fig is None: + fig = plt.figure() + + nx.draw(nx_graph, pos=pos, ax=fig.gca(), with_labels=True) + + return fig + class SceneGraph(PlanGraph): """ @@ -523,8 +559,6 @@ def goal_predicates(self) -> list[dict[str, Any]]: return predicates - - @cached_property def _decompose(self) -> tuple[SceneGraph, SceneGraph]: """ diff --git a/poetry.lock b/poetry.lock index 452cdf0..bec858a 100644 --- a/poetry.lock +++ b/poetry.lock @@ -243,33 +243,33 @@ test = ["scipy"] [[package]] name = "black" -version = 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rustworkx = "^0.14.2" +matplotlib = "^3.9.0" [tool.poetry.group.dev.dependencies] ruff = "^0.1.7" pytest = "^7.4.3" mypy = "^1.7.1" -black = {extras = ["jupyter"], version = "^23.11.0"} pytest-cov = "^4.1.0" pytest-timeout = "^2.2.0" +black = {extras = ["jupyter"], version = "^24.4.2"} + + +[tool.poetry.group.all.dependencies] +lark = "^1.1.9" +vllm = "^0.5.0.post1" +python-dotenv = "^1.0.1" +datasets = "^2.20.0" +peft = "^0.11.1" +trl = "^0.9.4" +bitsandbytes = "^0.43.1" +openai = "^1.35.3" [build-system] requires = ["poetry-core"] diff --git a/utils.py b/utils.py deleted file mode 100644 index a2d6269..0000000 --- a/utils.py +++ /dev/null @@ -1,72 +0,0 @@ -import matplotlib.pyplot as plt -import networkx as nx - -from planetarium import graph, oracle -import llm_planner as llmp - - -def apply_template( - problem: llmp.PlanningProblem, - domain_prompt: str = "", - problem_prompt: str = "", - include_answer: bool = True, -) -> list[dict[str, str]]: - """Apply problem template to the problem. - - Args: - problem(llmp.PlanningProblem): The problem to apply the template to. - domain_prompt (str, optional): How to prompt the domain. Defaults to "". - problem_prompt (str, optional): How to prompt the problem. Defaults to "". - include_answer (bool, optional): Whether to include the answer. Defaults to True. - - Returns: - list[dict[str, str]]: Problem prompt. - """ - return [ - { - "role": "user", - "content": f"{problem_prompt} {problem.natural_language} " - + f"{domain_prompt}\n{problem.domain}\n", - }, - ] + ( - [ - { - "role": "assistant", - "content": " " + problem.problem, - }, - ] - if include_answer - else [] - ) - - -def plot(graph: graph.PlanGraph, reduce: bool = False): - """Plot a graph representation of the PDDL description. - - Args: - graph (graph.PlanGraph): The graph to plot. - already_reduced (bool, optional): Whether the graph is already reduced. - Defaults to False. - """ - if reduce: - graph = oracle.reduce(graph, validate=False) - # rx has no plotting functionality - - nx_graph = nx.MultiDiGraph() - nx_graph.add_edges_from([(u.node, v.node, {"data":edge}) for u, v, edge in graph.edges]) - - for layer, nodes in enumerate(nx.topological_generations(nx_graph)): - for node in nodes: - nx_graph.nodes[node]["layer"] = layer - - pos = nx.multipartite_layout( - nx_graph, - align="horizontal", - subset_key="layer", - scale=-1, - ) - - fig = plt.figure() - nx.draw(nx_graph, pos=pos, ax=fig.gca(), with_labels=True) - - return fig