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/dataset_generator.py b/dataset_generator.py
index 94cb6e2..c57b769 100644
--- a/dataset_generator.py
+++ b/dataset_generator.py
@@ -154,7 +154,7 @@ def get_task(
         init: str,
         goal: str,
         *args,
-    ) -> tuple[Problem, dict[str, dict[str, str]], dict[str]]:
+    ) -> tuple[Problem, dict[str, dict[str, str]], dict[str, int | float | str]]:
         """Generate a task.
 
         Args:
@@ -257,6 +257,7 @@ def _get_height(num_blocks) -> list[int]:
                 if num_blocks % height == 0:
                     num_blocks = [height] * (num_blocks // height)
                     return num_blocks
+            return num_blocks
 
         if isinstance(num_blocks, int):
             num_blocks = _get_height(num_blocks)
diff --git a/evaluate.py b/evaluate.py
index 8ef7292..ec62adf 100644
--- a/evaluate.py
+++ b/evaluate.py
@@ -1,4 +1,4 @@
-from typing import Any
+from typing import Any, Callable, Mapping
 
 import dotenv
 
@@ -20,8 +20,6 @@
 from planetarium import builder, downward, graph, metric, oracle
 import llm_planner as llmp
 
-from utils import apply_template
-
 HF_USER_TOKEN = os.getenv("HF_USER_TOKEN")
 VALIDATE = os.getenv("VALIDATE", "Validate")
 
@@ -34,7 +32,7 @@ def signal_handler(signum, frame):
 
 
 def timeout_and_retry(
-    func: callable,
+    func: Callable,
     *args,
     timeout: int = 30,
     retries: int = 5,
@@ -43,7 +41,7 @@ def timeout_and_retry(
     """Run a function with a timeout and retries.
 
     Args:
-        func (callable): The function to run.
+        func (Callable): The function to run.
         timeout (int, optional): Seconds per attempt. Defaults to 30.
         retries (int, optional): Number of retries. Defaults to 5.
 
@@ -86,8 +84,7 @@ def plan(
     context = []
     for example_problem in example_problems:
         context.extend(
-            apply_template(
-                example_problem,
+            example_problem.apply_template(
                 domain_prompt,
                 problem_prompt,
             )
@@ -95,8 +92,7 @@ def plan(
 
     if isinstance(problem, llmp.PlanningProblem):
         messages = [
-            apply_template(
-                problem,
+            problem.apply_template(
                 domain_prompt,
                 problem_prompt,
                 include_answer=False,
@@ -104,8 +100,7 @@ def plan(
         ]
     else:
         messages = [
-            apply_template(
-                p,
+            p.apply_template(
                 domain_prompt,
                 problem_prompt,
                 include_answer=False,
@@ -117,8 +112,6 @@ def plan(
     messages = [context + m for m in messages]
     if isinstance(planner, llmp.HFPlanner):
         device = planner.model.device
-    elif isinstance(planner, llmp.OpenAIPlanner):
-        messages = messages[0]  # can't handle multiple messages
 
     return planner.plan_chat(
         messages,
@@ -127,11 +120,11 @@ def plan(
     )
 
 
-def load_planner(config: dict[str, dict[str, str]]) -> llmp.Planner:
+def load_planner(config: Mapping[str, dict[str, str]]) -> llmp.Planner:
     """Load a model based on the configuration.
 
     Args:
-        config (dict[str, str]): The configuration for the model.
+        config (Mapping[str, str]): The configuration for the model.
 
     Raises:
         ValueError: If the model type is not 'openai' or 'hf'.
@@ -369,14 +362,14 @@ def load_problem_ids(config: dict, splits: list[str]) -> list[int]:
 
 
 def load_ungenerated_problems(
-    config: dict[str, str | Any],
+    config: Mapping[str, str | Any],
     config_str: str,
     problem_ids: list[int],
 ) -> dict[int, llmp.PlanningProblem]:
     """Load a list of problems from the database.
 
     Args:
-        config (dict[str, str | Any]): The configuration for the database.
+        config (Mapping[str, str | Any]): The configuration for the database.
         config_str (str): The configuration string.
         problem_ids (list[int]): The list of problem ids to load.
 
@@ -653,7 +646,7 @@ def main(config_path: str):
             configuration for the evaluation.
     """
     with open(config_path, "r") as f:
-        config: dict[str, dict[str, str | list[str] | bool]] = yaml.safe_load(f)
+        config: dict = yaml.safe_load(f)
 
     config_str = yaml.dump(config["evaluate"]["model"])
 
@@ -661,13 +654,18 @@ def main(config_path: str):
 
     # Get LLM output first
     problems = load_ungenerated_problems(config, config_str, problem_ids)
-    # if len(problems) > 0:
-    #     if config["evaluate"]["model"]["type"] == "openai":
-    #         generate_openai(problems, config, config_str)
-    #     elif config["evaluate"]["model"]["type"] == "hf":
-    #         generate_hf(problems, config, config_str)
 
-    evaluate(problem_ids, config)
+    if len(problems) > 0:
+        print("Generating: Run script with same arguments again to evaluate.")
+        # It is very hard if not impossible at the moment to kill the vLLM
+        # Ray, so re-running the script is the best option at the
+        # moment.
+        if config["evaluate"]["model"]["type"] == "openai":
+            generate_openai(problems, config, config_str)
+        elif config["evaluate"]["model"]["type"] == "hf":
+            generate_hf(problems, config, config_str)
+    else:
+        evaluate(problem_ids, config)
 
 
 if __name__ == "__main__":
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 39be4a6..19462a3 100644
--- a/llm_planner.py
+++ b/llm_planner.py
@@ -9,11 +9,10 @@
     PreTrainedModel,
 )
 
-# from vllm import LLM, RequestOutput, SamplingParams
+from vllm import LLM, RequestOutput, SamplingParams
 
 
 class PlanningProblem:
-
     def __init__(
         self,
         natural_language: str,
@@ -32,25 +31,60 @@ 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):
 
+class Planner(abc.ABC):
     @abc.abstractmethod
     def plan_chat(
         self,
-        messages: list[dict[str, str]],
+        messages: list[list[dict[str, str]]],
         device=None,
+        max_new_tokens: int = 8_000,
         **kwargs,
-    ) -> str:
+    ) -> list[str]:
         """Passes messages to a model for completion.
 
         Args:
-            messages (list[dict[str, str]]): A list of messages to be passed to
-                the model.
+            messages (list[list[dict[str, str]]]): A list of messages to be
+                passed to the model.
             device (optional): The device to run the model on. Defaults to None.
+            max_new_tokens (int): The maximum number of tokens to generate.
+                Defaults to 8_000.
 
         Returns:
-            str: The message completion.
+            list[str]: The message completion.
         """
         pass
 
@@ -114,7 +148,7 @@ def plan_chat(
         messages: list[dict[str, str]],
         device=None,
         **kwargs,
-    ) -> str:
+    ) -> list[str]:
         """Passes messages to the model for completion, applying a chat template.
 
         Args:
@@ -171,10 +205,9 @@ def __init__(self, model_name: str, **kwargs):
 
     def plan_chat(
         self,
-        prompts: list[list[dict[str, str]]],
+        messages: list[list[dict[str, str]]],
         device=None,
         max_new_tokens: int = 8_000,
-        use_tqdm=False,
         **kwargs,
     ) -> list[str]:
         """Passes messages to the model for completion.
@@ -182,28 +215,27 @@ def plan_chat(
         Args:
             messages (list[dict[str, str]]): A list of messages to be passed to
                 the model.
-            use_tqdm (bool): Whether to use tqdm for progress tracking. Defaults
-                to False.
 
         Returns:
             list[str]: The message completions.
         """
         encoded = self.tokenizer.apply_chat_template(
-            prompts,
+            messages,
             add_generation_prompt=True,
             tokenize=False,
         )
-        generate_config = {  # default generate config
-            "max_tokens": max_new_tokens,
-            "temperature": 0.0,
-        }
-        generate_config.update(kwargs)
-        params = SamplingParams(**generate_config)
+        params = SamplingParams(
+            max_tokens=max_new_tokens,
+            temperature=kwargs.get("temperature", 0.0),
+            top_p=kwargs.get("top_p", 1.0),
+            top_k=kwargs.get("top_k", -1),
+            min_p=kwargs.get("min_p", 0.0),
+        )
 
         outputs: list[RequestOutput] = self.model.generate(
             encoded,
             params,
-            use_tqdm=use_tqdm,
+            use_tqdm=False,
         )
 
         return [output.outputs[0].text for output in outputs]
@@ -223,7 +255,7 @@ def __init__(self, model_name: str, **kwargs):
         self.client = OpenAI(**kwargs)
         self.model_name = model_name
 
-    def plan_chat(
+    def _plan_chat(
         self,
         messages: list[dict[str, str]],
         max_new_tokens: int | None = None,
@@ -240,18 +272,45 @@ def plan_chat(
         Returns:
             str: The message completion.
         """
-        generate_config = {  # default generate config
-            "max_tokens": max_new_tokens,
-            "temperature": 0.0,
-        }
-        generate_config.update(kwargs)
 
         return (
             self.client.chat.completions.create(
                 model=self.model_name,
                 messages=messages,
-                **generate_config,
+                frequency_penalty=kwargs.get("frequency_penalty", None),
+                max_tokens=max_new_tokens,
+                n=1,
+                presence_penalty=kwargs.get("presence_penalty", None),
+                temperature=kwargs.get("temperature", 0.0),
+                top_p=kwargs.get("top_p", None),
             )
             .choices[0]
             .message.content
         )
+
+    def plan_chat(
+        self,
+        messages: list[list[dict[str, str]]],
+        max_new_tokens: int | None = None,
+        device=None,
+        **kwargs,
+    ) -> list[str]:
+        """Passes messages to the model for completion.
+
+        Args:
+            messages (list[list[dict[str, str]]]): A list of messages to be
+                passed to the model.
+            device (optional): The device to run the model on (ignored for OpenAI).
+
+        Returns:
+            list[str]: The message completions.
+        """
+        return [
+            self._plan_chat(
+                message,
+                max_new_tokens=max_new_tokens,
+                device=device,
+                **kwargs,
+            )
+            for message in messages
+        ]
\ No newline at end of file
diff --git a/planetarium/downward.py b/planetarium/downward.py
index 05ef8cc..90a7599 100644
--- a/planetarium/downward.py
+++ b/planetarium/downward.py
@@ -7,18 +7,29 @@
 import tempfile
 
 
-def _get_best_plan(plan_filepath: str) -> tuple[str, float]:
+def _get_best_plan(plan_filepath: str) -> tuple[str | None, float]:
+    """Get the best plan from a FastDownward plan file.
+
+    Args:
+        plan_filepath (str): The path to the plan file.
+
+    Returns:
+        The best plan and its cost.
+    """
+
     best_cost = float("inf")
     best_plan = None
 
     for plan_fp in glob.glob(f"{plan_filepath}.*"):
         with open(plan_fp, "r") as f:
             *pddl_plan, cost_str = f.readlines()
-            cost = float(re.search(r"cost = ([-\d\.]+)", cost_str).group(1))
+            match = re.search(r"cost = ([-\d\.]+)", cost_str)
+            if match:
+                cost = float(match.group(1))
 
-            if cost < best_cost:
-                best_cost = cost
-                best_plan = "\n".join([*pddl_plan, ";"])
+                if cost < best_cost:
+                    best_cost = cost
+                    best_plan = "\n".join([*pddl_plan, ";"])
     return best_plan, best_cost
 
 
@@ -28,7 +39,7 @@ def plan(
     downward: str = "downward",
     alias: str = "lama",
     **kwargs,
-) -> tuple[str | None, int]:
+) -> tuple[str | None, float]:
     """Find plan using FastDownward.
 
     Args:
diff --git a/planetarium/graph.py b/planetarium/graph.py
index e07a04f..75de566 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
 
 
@@ -364,6 +366,40 @@ def __eq__(self, other: "PlanGraph") -> bool:
             and set(self._requirements) == set(other._requirements)
         )
 
+    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):
     """
diff --git a/planetarium/metric.py b/planetarium/metric.py
index 12fe0f6..d1201a7 100644
--- a/planetarium/metric.py
+++ b/planetarium/metric.py
@@ -1,6 +1,5 @@
 import functools
 import rustworkx as rx
-import typing
 
 from planetarium import graph
 
@@ -49,7 +48,7 @@ def _same_typing(source: graph.PlanGraphNode, target: graph.PlanGraphNode) -> bo
 def _node_matching(
     source: graph.PlanGraphNode,
     target: graph.PlanGraphNode,
-    mapping: typing.Optional[dict],
+    mapping: dict | None,
 ) -> bool:
     """
     Check if two nodes match based on their labels, positions, and typings.
@@ -57,7 +56,7 @@ def _node_matching(
     Parameters:
         source (graph.PlanGraphNode): The source node.
         target (graph.PlanGraphNode): The target node.
-        mapping (Optional[dict]): The mapping between node names.
+        mapping (dict | None): The mapping between node names.
 
     Returns:
         bool: True if nodes match, False otherwise.
@@ -103,7 +102,7 @@ def _getattr(obj, attr):
 def isomorphic(
     source: graph.ProblemGraph | graph.SceneGraph,
     target: graph.ProblemGraph | graph.SceneGraph,
-    mapping: typing.Optional[dict] = None,
+    mapping: dict | None = None,
 ) -> bool:
     """
     Find all valid isomorphic mappings between nodes of two scene graphs.
@@ -111,7 +110,7 @@ def isomorphic(
     Parameters:
         source (ProblemGraph): The source problem graph.
         target (ProblemGraph): The target problem graph.
-        mapping (Optional[dict]): The initial mapping between node names.
+        mapping (dict | None): The initial mapping between node names.
 
     Returns:
         bool: True if there is a valid mapping, False otherwise.
diff --git a/poetry.lock b/poetry.lock
index 282a0f2..7cdfe88 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,5 +1,179 @@
 # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
+[[package]]
+name = "accelerate"
+version = "0.31.0"
+description = "Accelerate"
+optional = false
+python-versions = ">=3.8.0"
+files = [
+    {file = "accelerate-0.31.0-py3-none-any.whl", hash = "sha256:0fc608dc49584f64d04711a39711d73cb0ad4ef3d21cddee7ef2216e29471144"},
+    {file = "accelerate-0.31.0.tar.gz", hash = "sha256:b5199865b26106ccf9205acacbe8e4b3b428ad585e7c472d6a46f6fb75b6c176"},
+]
+
+[package.dependencies]
+huggingface-hub = "*"
+numpy = ">=1.17"
+packaging = ">=20.0"
+psutil = "*"
+pyyaml = "*"
+safetensors = ">=0.3.1"
+torch = ">=1.10.0"
+
+[package.extras]
+deepspeed = ["deepspeed (<=0.14.0)"]
+dev = ["bitsandbytes", "black (>=23.1,<24.0)", "datasets", "diffusers", "evaluate", "hf-doc-builder (>=0.3.0)", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "rich", "ruff (>=0.2.1,<0.3.0)", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
+quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.2.1,<0.3.0)"]
+rich = ["rich"]
+sagemaker = ["sagemaker"]
+test-dev = ["bitsandbytes", "datasets", "diffusers", "evaluate", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
+test-prod = ["parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist"]
+test-trackers = ["comet-ml", "dvclive", "tensorboard", "wandb"]
+testing = ["bitsandbytes", "datasets", "diffusers", "evaluate", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "timm", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
+
+[[package]]
+name = "aiohttp"
+version = "3.9.5"
+description = "Async http client/server framework (asyncio)"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "aiohttp-3.9.5-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:fcde4c397f673fdec23e6b05ebf8d4751314fa7c24f93334bf1f1364c1c69ac7"},
+    {file = "aiohttp-3.9.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:5d6b3f1fabe465e819aed2c421a6743d8debbde79b6a8600739300630a01bf2c"},
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+
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+trio = ["trio (>=0.23)"]
+
 [[package]]
 name = "asttokens"
 version = "2.4.1"
@@ -18,6 +192,17 @@ six = ">=1.12.0"
 astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"]
 test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
 
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 version = "23.2.0"
@@ -37,35 +222,54 @@ tests = ["attrs[tests-no-zope]", "zope-interface"]
 tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
 tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
 
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+]
+
+[package.dependencies]
+numpy = ">=1.20"
+
+[package.extras]
+bokeh = ["bokeh", "selenium"]
+docs = ["furo", "sphinx (>=7.2)", "sphinx-copybutton"]
+mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.8.0)", "types-Pillow"]
+test = ["Pillow", "contourpy[test-no-images]", "matplotlib"]
+test-no-images = ["pytest", "pytest-cov", "pytest-xdist", "wurlitzer"]
+
 [[package]]
 name = "coverage"
 version = "7.4.0"
@@ -177,6 +594,65 @@ tomli = {version = "*", optional = true, markers = "python_full_version <= \"3.1
 [package.extras]
 toml = ["tomli"]
 
+[[package]]
+name = "cycler"
+version = "0.12.1"
+description = "Composable style cycles"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "cycler-0.12.1.tar.gz", hash = "sha256:88bb128f02ba341da8ef447245a9e138fae777f6a23943da4540077d3601eb1c"},
+]
+
+[package.extras]
+docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
+tests = ["pytest", "pytest-cov", "pytest-xdist"]
+
+[[package]]
+name = "datasets"
+version = "2.20.0"
+description = "HuggingFace community-driven open-source library of datasets"
+optional = false
+python-versions = ">=3.8.0"
+files = [
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+    {file = "datasets-2.20.0.tar.gz", hash = "sha256:3c4dbcd27e0f642b9d41d20ff2efa721a5e04b32b2ca4009e0fc9139e324553f"},
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+[package.dependencies]
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+dill = ">=0.3.0,<0.3.9"
+filelock = "*"
+fsspec = {version = ">=2023.1.0,<=2024.5.0", extras = ["http"]}
+huggingface-hub = ">=0.21.2"
+multiprocess = "*"
+numpy = ">=1.17"
+packaging = "*"
+pandas = "*"
+pyarrow = ">=15.0.0"
+pyarrow-hotfix = "*"
+pyyaml = ">=5.1"
+requests = ">=2.32.2"
+tqdm = ">=4.66.3"
+xxhash = "*"
+
+[package.extras]
+apache-beam = ["apache-beam (>=2.26.0)"]
+audio = ["librosa", "soundfile (>=0.12.1)"]
+benchmarks = ["tensorflow (==2.12.0)", "torch (==2.0.1)", "transformers (==4.30.1)"]
+dev = ["Pillow (>=9.4.0)", "absl-py", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "ruff (>=0.3.0)", "s3fs", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy", "tensorflow (>=2.6.0)", "tiktoken", "torch", "torch (>=2.0.0)", "transformers", "typing-extensions (>=4.6.1)", "zstandard"]
+docs = ["s3fs", "tensorflow (>=2.6.0)", "torch", "transformers"]
+jax = ["jax (>=0.3.14)", "jaxlib (>=0.3.14)"]
+metrics-tests = ["Werkzeug (>=1.0.1)", "accelerate", "bert-score (>=0.3.6)", "jiwer", "langdetect", "mauve-text", "nltk", "requests-file (>=1.5.1)", "rouge-score", "sacrebleu", "sacremoses", "scikit-learn", "scipy", "sentencepiece", "seqeval", "six (>=1.15.0,<1.16.0)", "spacy (>=3.0.0)", "texttable (>=1.6.3)", "tldextract", "tldextract (>=3.1.0)", "toml (>=0.10.1)", "typer (<0.5.0)"]
+quality = ["ruff (>=0.3.0)"]
+s3 = ["s3fs"]
+tensorflow = ["tensorflow (>=2.6.0)"]
+tensorflow-gpu = ["tensorflow (>=2.6.0)"]
+tests = ["Pillow (>=9.4.0)", "absl-py", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy", "tensorflow (>=2.6.0)", "tiktoken", "torch (>=2.0.0)", "transformers", "typing-extensions (>=4.6.1)", "zstandard"]
+torch = ["torch"]
+vision = ["Pillow (>=9.4.0)"]
+
 [[package]]
 name = "decorator"
 version = "5.1.1"
@@ -188,6 +664,89 @@ files = [
     {file = "decorator-5.1.1.tar.gz", hash = "sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330"},
 ]
 
+[[package]]
+name = "dill"
+version = "0.3.8"
+description = "serialize all of Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "dill-0.3.8-py3-none-any.whl", hash = "sha256:c36ca9ffb54365bdd2f8eb3eff7d2a21237f8452b57ace88b1ac615b7e815bd7"},
+    {file = "dill-0.3.8.tar.gz", hash = "sha256:3ebe3c479ad625c4553aca177444d89b486b1d84982eeacded644afc0cf797ca"},
+]
+
+[package.extras]
+graph = ["objgraph (>=1.7.2)"]
+profile = ["gprof2dot (>=2022.7.29)"]
+
+[[package]]
+name = "diskcache"
+version = "5.6.3"
+description = "Disk Cache -- Disk and file backed persistent cache."
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "diskcache-5.6.3-py3-none-any.whl", hash = "sha256:5e31b2d5fbad117cc363ebaf6b689474db18a1f6438bc82358b024abd4c2ca19"},
+    {file = "diskcache-5.6.3.tar.gz", hash = "sha256:2c3a3fa2743d8535d832ec61c2054a1641f41775aa7c556758a109941e33e4fc"},
+]
+
+[[package]]
+name = "distro"
+version = "1.9.0"
+description = "Distro - an OS platform information API"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"},
+    {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
+]
+
+[[package]]
+name = "dnspython"
+version = "2.6.1"
+description = "DNS toolkit"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "dnspython-2.6.1-py3-none-any.whl", hash = "sha256:5ef3b9680161f6fa89daf8ad451b5f1a33b18ae8a1c6778cdf4b43f08c0a6e50"},
+    {file = "dnspython-2.6.1.tar.gz", hash = "sha256:e8f0f9c23a7b7cb99ded64e6c3a6f3e701d78f50c55e002b839dea7225cff7cc"},
+]
+
+[package.extras]
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+dnssec = ["cryptography (>=41)"]
+doh = ["h2 (>=4.1.0)", "httpcore (>=1.0.0)", "httpx (>=0.26.0)"]
+doq = ["aioquic (>=0.9.25)"]
+idna = ["idna (>=3.6)"]
+trio = ["trio (>=0.23)"]
+wmi = ["wmi (>=1.5.1)"]
+
+[[package]]
+name = "docstring-parser"
+version = "0.16"
+description = "Parse Python docstrings in reST, Google and Numpydoc format"
+optional = false
+python-versions = ">=3.6,<4.0"
+files = [
+    {file = "docstring_parser-0.16-py3-none-any.whl", hash = "sha256:bf0a1387354d3691d102edef7ec124f219ef639982d096e26e3b60aeffa90637"},
+    {file = "docstring_parser-0.16.tar.gz", hash = "sha256:538beabd0af1e2db0146b6bd3caa526c35a34d61af9fd2887f3a8a27a739aa6e"},
+]
+
+[[package]]
+name = "email-validator"
+version = "2.2.0"
+description = "A robust email address syntax and deliverability validation library."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "email_validator-2.2.0-py3-none-any.whl", hash = "sha256:561977c2d73ce3611850a06fa56b414621e0c8faa9d66f2611407d87465da631"},
+    {file = "email_validator-2.2.0.tar.gz", hash = "sha256:cb690f344c617a714f22e66ae771445a1ceb46821152df8e165c5f9a364582b7"},
+]
+
+[package.dependencies]
+dnspython = ">=2.0.0"
+idna = ">=2.0.0"
+
 [[package]]
 name = "exceptiongroup"
 version = "1.2.0"
@@ -217,123 +776,770 @@ files = [
 tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich"]
 
 [[package]]
-name = "iniconfig"
-version = "2.0.0"
-description = "brain-dead simple config-ini parsing"
+name = "fastapi"
+version = "0.111.0"
+description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"},
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+    {file = "fastapi-0.111.0-py3-none-any.whl", hash = "sha256:97ecbf994be0bcbdadedf88c3150252bed7b2087075ac99735403b1b76cc8fc0"},
+    {file = "fastapi-0.111.0.tar.gz", hash = "sha256:b9db9dd147c91cb8b769f7183535773d8741dd46f9dc6676cd82eab510228cd7"},
 ]
 
+[package.dependencies]
+email_validator = ">=2.0.0"
+fastapi-cli = ">=0.0.2"
+httpx = ">=0.23.0"
+jinja2 = ">=2.11.2"
+orjson = ">=3.2.1"
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+python-multipart = ">=0.0.7"
+starlette = ">=0.37.2,<0.38.0"
+typing-extensions = ">=4.8.0"
+ujson = ">=4.0.1,<4.0.2 || >4.0.2,<4.1.0 || >4.1.0,<4.2.0 || >4.2.0,<4.3.0 || >4.3.0,<5.0.0 || >5.0.0,<5.1.0 || >5.1.0"
+uvicorn = {version = ">=0.12.0", extras = ["standard"]}
+
+[package.extras]
+all = ["email_validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.7)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
+
 [[package]]
-name = "ipython"
-version = "8.20.0"
-description = "IPython: Productive Interactive Computing"
+name = "fastapi-cli"
+version = "0.0.4"
+description = "Run and manage FastAPI apps from the command line with FastAPI CLI. 🚀"
 optional = false
-python-versions = ">=3.10"
+python-versions = ">=3.8"
 files = [
-    {file = "ipython-8.20.0-py3-none-any.whl", hash = "sha256:bc9716aad6f29f36c449e30821c9dd0c1c1a7b59ddcc26931685b87b4c569619"},
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+    {file = "fastapi_cli-0.0.4.tar.gz", hash = "sha256:e2e9ffaffc1f7767f488d6da34b6f5a377751c996f397902eb6abb99a67bde32"},
 ]
 
 [package.dependencies]
-colorama = {version = "*", markers = "sys_platform == \"win32\""}
-decorator = "*"
-exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
-jedi = ">=0.16"
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-pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
-prompt-toolkit = ">=3.0.41,<3.1.0"
-pygments = ">=2.4.0"
-stack-data = "*"
-traitlets = ">=5"
+typer = ">=0.12.3"
 
 [package.extras]
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-doc = ["docrepr", "exceptiongroup", "ipykernel", "matplotlib", "pickleshare", "pytest", "pytest-asyncio (<0.22)", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"]
-kernel = ["ipykernel"]
-nbconvert = ["nbconvert"]
-nbformat = ["nbformat"]
-notebook = ["ipywidgets", "notebook"]
-parallel = ["ipyparallel"]
-qtconsole = ["qtconsole"]
-test = ["pickleshare", "pytest", "pytest-asyncio (<0.22)", "testpath"]
-test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.23)", "pandas", "pickleshare", "pytest", "pytest-asyncio (<0.22)", "testpath", "trio"]
+standard = ["fastapi", "uvicorn[standard] (>=0.15.0)"]
 
 [[package]]
-name = "jedi"
-version = "0.19.1"
-description = "An autocompletion tool for Python that can be used for text editors."
+name = "filelock"
+version = "3.15.4"
+description = "A platform independent file lock."
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
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+referencing = "*"
+requests = "*"
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+typing-extensions = "*"
+
+[package.extras]
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+
 [[package]]
 name = "packaging"
 version = "23.2"
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+xml = ["lxml (>=4.9.2)"]
+
 [[package]]
 name = "parso"
-version = "0.8.3"
+version = "0.8.4"
 description = "A Python Parser"
 optional = false
 python-versions = ">=3.6"
 files = [
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 [package.extras]
-qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
-testing = ["docopt", "pytest (<6.0.0)"]
+qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
+testing = ["docopt", "pytest"]
 
 [[package]]
 name = "pathspec"
@@ -576,6 +2478,35 @@ url = "https://github.com/maxzuo/pddl.git"
 reference = "HEAD"
 resolved_reference = "4b84b77e0925cc64ebe00e71558d56ec77a25d1a"
 
+[[package]]
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+description = "Parameter-Efficient Fine-Tuning (PEFT)"
+optional = false
+python-versions = ">=3.8.0"
+files = [
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+numpy = ">=1.17"
+packaging = ">=20.0"
+psutil = "*"
+pyyaml = "*"
+safetensors = "*"
+torch = ">=1.13.0"
+tqdm = "*"
+transformers = "*"
+
+[package.extras]
+dev = ["black", "hf-doc-builder", "ruff (>=0.2.1,<0.3.0)"]
+docs-specific = ["black", "hf-doc-builder"]
+quality = ["black", "hf-doc-builder", "ruff (>=0.2.1,<0.3.0)"]
+test = ["black", "datasets", "diffusers (<0.21.0)", "hf-doc-builder", "parameterized", "pytest", "pytest-cov", "pytest-xdist", "ruff (>=0.2.1,<0.3.0)", "scipy"]
+
 [[package]]
 name = "pexpect"
 version = "4.9.0"
@@ -590,20 +2521,107 @@ files = [
 [package.dependencies]
 ptyprocess = ">=0.5"
 
+[[package]]
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+version = "10.3.0"
+description = "Python Imaging Library (Fork)"
+optional = false
+python-versions = ">=3.8"
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 testing = ["pytest", "pytest-benchmark"]
 
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 ]
 
-[package.dependencies]
-pytest = ">=5.0.0"
-
 [[package]]
 name = "ruff"
 version = "0.1.11"
@@ -848,46 +3573,213 @@ graphviz = ["pillow (>=5.4)"]
 mpl = ["matplotlib (>=3.0)"]
 
 [[package]]
-name = "scipy"
-version = "1.11.4"
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+optional = false
+python-versions = ">=3.7"
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+
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 name = "stack-data"
 version = "0.6.3"
@@ -919,6 +3822,102 @@ pure-eval = "*"
 [package.extras]
 tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
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+
+[[package]]
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+description = "Computer algebra system (CAS) in Python"
+optional = false
+python-versions = ">=3.8"
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+
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+description = "Intel® oneAPI Threading Building Blocks (oneTBB)"
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+
+[package.extras]
+blobfile = ["blobfile (>=2)"]
+
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 name = "tokenize-rt"
 version = "5.2.0"
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 [[package]]
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 version = "0.2.13"
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 ]
 
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+    {file = "yarl-1.9.4.tar.gz", hash = "sha256:566db86717cf8080b99b58b083b773a908ae40f06681e87e589a976faf8246bf"},
+]
+
+[package.dependencies]
+idna = ">=2.0"
+multidict = ">=4.0"
+
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "bf8df906c23f25bf86af97015696384e0420c3d2d58298c208c4e9bb01119bbd"
+content-hash = "711c27fc13ea254561cee36bccf745a7cfc450f6f317d25e0fb4948c0cb55c2e"
diff --git a/pyproject.toml b/pyproject.toml
index 6a38195..19bc510 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -3,7 +3,7 @@ name = "planetarium"
 version = "0.1.0"
 description = "Benchmark framework for evaluating LLMs performance in the context of PDDL code generation."
 authors = [
-  "Max Zuo <maxzuo@brown.edu>",
+  "Max Zuo <zuo@brown.edu>",
   "Francisco J. Piedrahita-Velez <fpiedrah@brown.edu>",
 ]
 readme = "README.md"
@@ -12,20 +12,31 @@ readme = "README.md"
 python = "^3.10"
 networkx = "^3.2.1"
 pddl = {git = "https://github.com/maxzuo/pddl.git"}
-numpy = "^1.26.2"
-scipy = "^1.11.4"
-rustworkx = "^0.14.2"
+pyyaml = "^6.0.1"
 jinja2 = "^3.1.4"
+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"
 pytest-subtests = "^0.12.1"
+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/tests/test_evaluate.py b/tests/test_evaluate.py
index 84288a0..368941f 100644
--- a/tests/test_evaluate.py
+++ b/tests/test_evaluate.py
@@ -21,6 +21,7 @@ def test_evaluate_equivalent(
         blocksworld_missing_clears,
         blocksworld_fully_specified,
         blocksworld_missing_ontables,
+        blocksworld_underspecified,
     ):
         """
         Test if the evaluation of PDDL problem descriptions is correct.
@@ -34,6 +35,9 @@ def test_evaluate_equivalent(
             with subtests.test(f"{name1} equals {name2}"):
                 assert all(evaluate.evaluate(desc1, desc2))
 
+        with subtests.test("blocksworld_underspecified equals blocksworld_underspecified"):
+            assert all(evaluate.evaluate(blocksworld_underspecified, blocksworld_underspecified))
+
     def test_evaluate_inequivalent(
         self,
         subtests,
@@ -56,4 +60,4 @@ def test_evaluate_inequivalent(
                     True,
                     True,
                     False,
-                )
+                )
\ No newline at end of file
diff --git a/tests/test_graph.py b/tests/test_graph.py
index e202a11..95f9634 100644
--- a/tests/test_graph.py
+++ b/tests/test_graph.py
@@ -47,3 +47,10 @@ def test_predicate_names(self, sgraph):
                     assert True
                 case _:
                     assert False
+
+    def test_plot(self, sgraph):
+        """
+        Test if the graph can be plotted.
+        """
+        sgraph.plot()
+        assert True
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