Fix codestyle errors

Author: joy13975

src/ragas/embeddings/base.py

@@ -44,7 +44,9 @@ def set_run_config(self, run_config: RunConfig):
 
 class LangchainEmbeddingsWrapper(BaseRagasEmbeddings):
     def __init__(
-        self, embeddings: Embeddings, run_config: t.Optional[RunConfig] = None
+        self,
+        embeddings: Embeddings,
+        run_config: t.Optional[RunConfig] = None
     ):
         self.embeddings = embeddings
         if run_config is None:

src/ragas/executor.py

@@ -25,19 +25,18 @@ def runner_exception_hook(args: threading.ExceptHookArgs):
 # threading.excepthook = runner_exception_hook
 
 def as_completed(loop, coros, max_workers):
+    loop_arg_dict = {"loop": loop} if sys.version_info[:2] < (3, 10) else {}
     if max_workers == -1:
-        return asyncio.as_completed(coros, loop=loop)
+        return asyncio.as_completed(coros, **loop_arg_dict)
 
     # loop argument is removed since Python 3.10
-    semaphore = asyncio.Semaphore(
-        max_workers,
-        **({"loop": loop} if sys.version_info[:2] < (3, 10) else {})
-    )
-    async def sem_coro(coro):
+    semaphore = asyncio.Semaphore(max_workers, **loop_arg_dict)
+    async def sema_coro(coro):
         async with semaphore:
             return await coro
 
-    return asyncio.as_completed([sem_coro(c) for c in coros], loop=loop)
+    sema_coros = [sema_coro(c) for c in coros]
+    return asyncio.as_completed(sema_coros, **loop_arg_dict)
 
 class Runner(threading.Thread):
     def __init__(
@@ -46,7 +45,7 @@ def __init__(
         desc: str,
         keep_progress_bar: bool = True,
         raise_exceptions: bool = True,
-        run_config: RunConfig = None,
+        run_config: t.Optional[RunConfig] = None
     ):
         super().__init__()
         self.jobs = jobs
@@ -103,7 +102,7 @@ class Executor:
     keep_progress_bar: bool = True
     jobs: t.List[t.Any] = field(default_factory=list, repr=False)
     raise_exceptions: bool = False
-    run_config: RunConfig = None
+    run_config: t.Optional[RunConfig] = field(default_factory=RunConfig, repr=False)
 
     def wrap_callable_with_index(self, callable: t.Callable, counter):
         async def wrapped_callable_async(*args, **kwargs):

src/ragas/llms/base.py

@@ -119,7 +119,9 @@ class LangchainLLMWrapper(BaseRagasLLM):
     """
 
     def __init__(
-        self, langchain_llm: BaseLanguageModel, run_config: t.Optional[RunConfig] = None
+        self,
+        langchain_llm: BaseLanguageModel,
+        run_config: t.Optional[RunConfig] = None
     ):
         self.langchain_llm = langchain_llm
         if run_config is None:
@@ -204,7 +206,8 @@ def set_run_config(self, run_config: RunConfig):
 
 
 def llm_factory(
-    model: str = "gpt-3.5-turbo-16k", run_config: t.Optional[RunConfig] = None
+    model: str = "gpt-3.5-turbo-16k",
+    run_config: t.Optional[RunConfig] = None
 ) -> BaseRagasLLM:
     timeout = None
     if run_config is not None:

src/ragas/testset/docstore.py

@@ -190,7 +190,7 @@ class InMemoryDocumentStore(DocumentStore):
     nodes: t.List[Node] = field(default_factory=list)
     node_embeddings_list: t.List[Embedding] = field(default_factory=list)
     node_map: t.Dict[str, Node] = field(default_factory=dict)
-    run_config: RunConfig = None
+    run_config: t.Optional[RunConfig]
 
     def _embed_items(self, items: t.Union[t.Sequence[Document], t.Sequence[Node]]):
         ...

src/ragas/testset/evolutions.py

@@ -84,7 +84,11 @@ def merge_nodes(nodes: CurrentNodes) -> Node:
             new_node.embedding = np.average(node_embeddings, axis=0)
         return new_node
 
-    def init(self, is_async: bool = True, run_config: t.Optional[RunConfig] = None):
+    def init(
+        self,
+        is_async: bool = True,
+        run_config: t.Optional[RunConfig] = None
+    ):
         self.is_async = is_async
         if run_config is None:
             run_config = RunConfig()
@@ -323,7 +327,11 @@ class ComplexEvolution(Evolution):
         default_factory=lambda: compress_question_prompt
     )
 
-    def init(self, is_async: bool = True, run_config: t.Optional[RunConfig] = None):
+    def init(
+        self,
+        is_async: bool = True,
+        run_config: t.Optional[RunConfig] = None
+    ):
         if run_config is None:
             run_config = RunConfig()
         super().init(is_async=is_async, run_config=run_config)

src/ragas/testset/generator.py

@@ -78,7 +78,7 @@ def with_openai(
         embeddings: str = "text-embedding-ada-002",
         docstore: t.Optional[DocumentStore] = None,
         chunk_size: int = 512,
-        run_config: RunConfig = None,
+        run_config: t.Optional[RunConfig] = None,
     ) -> "TestsetGenerator":
         generator_llm_model = LangchainLLMWrapper(ChatOpenAI(model=generator_llm))
         critic_llm_model = LangchainLLMWrapper(ChatOpenAI(model=critic_llm))
@@ -120,7 +120,7 @@ def generate_with_llamaindex_docs(
         with_debugging_logs=False,
         is_async: bool = True,
         raise_exceptions: bool = True,
-        run_config: t.Optional[RunConfig] = None,
+        run_config: t.Optional[RunConfig] = None
     ):
         # chunk documents and add to docstore
         self.docstore.add_documents(
@@ -146,7 +146,7 @@ def generate_with_langchain_docs(
         with_debugging_logs=False,
         is_async: bool = True,
         raise_exceptions: bool = True,
-        run_config: t.Optional[RunConfig] = None,
+        run_config: t.Optional[RunConfig] = None
     ):
         # chunk documents and add to docstore
         self.docstore.add_documents(
@@ -184,7 +184,7 @@ def generate(
         with_debugging_logs=False,
         is_async: bool = True,
         raise_exceptions: bool = True,
-        run_config: t.Optional[RunConfig] = None,
+        run_config: t.Optional[RunConfig] = None
     ):
         # validate distributions
         if not check_if_sum_is_close(list(distributions.values()), 1.0, 3):