Merge pull request stanford-oval#159 from stanford-oval/dev-code-form…

…atter

Use `black` as the python code formatter.

.pre-commit-config.yaml

@@ -0,0 +1,10 @@
+repos:
+  - repo: https://github.com/psf/black
+    rev: 24.8.0
+    hooks:
+      - id: black
+        name: Format Python code with black
+        entry: black
+        args: ["knowledge_storm/"]
+        language: python
+        pass_filenames: true

CONTRIBUTING.md

@@ -40,4 +40,9 @@ Following the suggested format can lead to a faster review process.
 
 **Code Format:**
 
-We adopt [PEP8 rules](https://peps.python.org/pep-0008/) for arranging and formatting Python code. Please use a code formatter tool in your IDE to reformat the code before submitting the PR.
+We adopt [`black`](https://github.com/psf/black) for arranging and formatting Python code. To streamline the contribution process, we set up a [pre-commit hook](https://pre-commit.com/) to format the code under `knowledge_storm/` before committing. To install the pre-commit hook, run:
+```
+pip install pre-commit
+pre-commit install
+```
+The hook will automatically format the code before each commit.

README.md

@@ -17,6 +17,8 @@
 - [2024/05] We add Bing Search support in [rm.py](knowledge_storm/rm.py). Test STORM with `GPT-4o` - we now configure the article generation part in our demo using `GPT-4o` model.
 - [2024/04] We release refactored version of STORM codebase! We define [interface](knowledge_storm/interface.py) for STORM pipeline and reimplement STORM-wiki (check out [`src/storm_wiki`](knowledge_storm/storm_wiki)) to demonstrate how to instantiate the pipeline. We provide API to support customization of different language models and retrieval/search integration.
 
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+
 ## Overview [(Try STORM now!)](https://storm.genie.stanford.edu/)
 
 <p align="center">

knowledge_storm/__init__.py

@@ -1,7 +1,7 @@
 from .storm_wiki.engine import (
     STORMWikiLMConfigs,
     STORMWikiRunnerArguments,
-    STORMWikiRunner
+    STORMWikiRunner,
 )
 
 __version__ = "0.2.5"

knowledge_storm/interface.py

@@ -5,7 +5,9 @@
 from collections import OrderedDict
 from typing import Dict, List, Optional, Union
 
-logging.basicConfig(level=logging.INFO, format='%(name)s : %(levelname)-8s : %(message)s')
+logging.basicConfig(
+    level=logging.INFO, format="%(name)s : %(levelname)-8s : %(message)s"
+)
 logger = logging.getLogger(__name__)
 
 
@@ -70,7 +72,9 @@ class Article(ABC):
     def __init__(self, topic_name):
         self.root = ArticleSectionNode(topic_name)
 
-    def find_section(self, node: ArticleSectionNode, name: str) -> Optional[ArticleSectionNode]:
+    def find_section(
+        self, node: ArticleSectionNode, name: str
+    ) -> Optional[ArticleSectionNode]:
         """
         Return the node of the section given the section name.
 
@@ -152,7 +156,9 @@ def prune_empty_nodes(self, node=None):
         if node is None:
             node = self.root
 
-        node.children[:] = [child for child in node.children if self.prune_empty_nodes(child)]
+        node.children[:] = [
+            child for child in node.children if self.prune_empty_nodes(child)
+        ]
 
         if (node.content is None or node.content == "") and not node.children:
             return None
@@ -178,7 +184,9 @@ def update_search_top_k(self, k):
     def collect_and_reset_rm_usage(self):
         combined_usage = []
         for attr_name in self.__dict__:
-            if '_rm' in attr_name and hasattr(getattr(self, attr_name), 'get_usage_and_reset'):
+            if "_rm" in attr_name and hasattr(
+                getattr(self, attr_name), "get_usage_and_reset"
+            ):
                 combined_usage.append(getattr(self, attr_name).get_usage_and_reset())
 
         name_to_usage = {}
@@ -240,7 +248,9 @@ class OutlineGenerationModule(ABC):
     """
 
     @abstractmethod
-    def generate_outline(self, topic: str, information_table: InformationTable, **kwargs) -> Article:
+    def generate_outline(
+        self, topic: str, information_table: InformationTable, **kwargs
+    ) -> Article:
         """
         Generate outline for the article. Required arguments include:
             topic: the topic of interest
@@ -263,11 +273,13 @@ class ArticleGenerationModule(ABC):
     """
 
     @abstractmethod
-    def generate_article(self,
-                         topic: str,
-                         information_table: InformationTable,
-                         article_with_outline: Article,
-                         **kwargs) -> Article:
+    def generate_article(
+        self,
+        topic: str,
+        information_table: InformationTable,
+        article_with_outline: Article,
+        **kwargs,
+    ) -> Article:
         """
         Generate article. Required arguments include:
             topic: the topic of interest
@@ -312,22 +324,23 @@ def wrapper(self, *args, **kwargs):
 class LMConfigs(ABC):
     """Abstract base class for language model configurations of the knowledge curation engine.
 
-    The language model used for each part should be declared with a suffix '_lm' in the attribute name."""
+    The language model used for each part should be declared with a suffix '_lm' in the attribute name.
+    """
 
     def __init__(self):
         pass
 
     def init_check(self):
         for attr_name in self.__dict__:
-            if '_lm' in attr_name and getattr(self, attr_name) is None:
+            if "_lm" in attr_name and getattr(self, attr_name) is None:
                 logging.warning(
                     f"Language model for {attr_name} is not initialized. Please call set_{attr_name}()"
                 )
 
     def collect_and_reset_lm_history(self):
         history = []
         for attr_name in self.__dict__:
-            if '_lm' in attr_name and hasattr(getattr(self, attr_name), 'history'):
+            if "_lm" in attr_name and hasattr(getattr(self, attr_name), "history"):
                 history.extend(getattr(self, attr_name).history)
                 getattr(self, attr_name).history = []
 
@@ -336,7 +349,9 @@ def collect_and_reset_lm_history(self):
     def collect_and_reset_lm_usage(self):
         combined_usage = []
         for attr_name in self.__dict__:
-            if '_lm' in attr_name and hasattr(getattr(self, attr_name), 'get_usage_and_reset'):
+            if "_lm" in attr_name and hasattr(
+                getattr(self, attr_name), "get_usage_and_reset"
+            ):
                 combined_usage.append(getattr(self, attr_name).get_usage_and_reset())
 
         model_name_to_usage = {}
@@ -345,17 +360,22 @@ def collect_and_reset_lm_usage(self):
                 if model_name not in model_name_to_usage:
                     model_name_to_usage[model_name] = tokens
                 else:
-                    model_name_to_usage[model_name]['prompt_tokens'] += tokens['prompt_tokens']
-                    model_name_to_usage[model_name]['completion_tokens'] += tokens['completion_tokens']
+                    model_name_to_usage[model_name]["prompt_tokens"] += tokens[
+                        "prompt_tokens"
+                    ]
+                    model_name_to_usage[model_name]["completion_tokens"] += tokens[
+                        "completion_tokens"
+                    ]
 
         return model_name_to_usage
 
     def log(self):
 
         return OrderedDict(
             {
-                attr_name: getattr(self, attr_name).kwargs for attr_name in self.__dict__ if
-                '_lm' in attr_name and hasattr(getattr(self, attr_name), 'kwargs')
+                attr_name: getattr(self, attr_name).kwargs
+                for attr_name in self.__dict__
+                if "_lm" in attr_name and hasattr(getattr(self, attr_name), "kwargs")
             }
         )
 
@@ -379,16 +399,21 @@ def wrapper(*args, **kwargs):
             self.time[func.__name__] = execution_time
             logger.info(f"{func.__name__} executed in {execution_time:.4f} seconds")
             self.lm_cost[func.__name__] = self.lm_configs.collect_and_reset_lm_usage()
-            if hasattr(self, 'retriever'):
-                self.rm_cost[func.__name__] = self.retriever.collect_and_reset_rm_usage()
+            if hasattr(self, "retriever"):
+                self.rm_cost[func.__name__] = (
+                    self.retriever.collect_and_reset_rm_usage()
+                )
             return result
 
         return wrapper
 
     def apply_decorators(self):
         """Apply decorators to methods that need them."""
-        methods_to_decorate = [method_name for method_name in dir(self)
-                               if callable(getattr(self, method_name)) and method_name.startswith('run_')]
+        methods_to_decorate = [
+            method_name
+            for method_name in dir(self)
+            if callable(getattr(self, method_name)) and method_name.startswith("run_")
+        ]
         for method_name in methods_to_decorate:
             original_method = getattr(self, method_name)
             decorated_method = self.log_execution_time_and_lm_rm_usage(original_method)