From 85de3d9a503fec159962569fb77329a43af4594e Mon Sep 17 00:00:00 2001
From: James Braza <jamesbraza@gmail.com>
Date: Tue, 10 Oct 2023 11:55:21 -0400
Subject: [PATCH] More `ruff` enables (PYI, SIM, etc.) (#8038)
---
benchmarks/agent/math_tasks.py | 4 +-
benchmarks/embeddings/bench_embeddings.py | 2 +-
experimental/cli/cli_add.py | 4 +-
experimental/cli/cli_init.py | 4 +-
experimental/cli/cli_query.py | 4 +-
experimental/cli/configuration.py | 14 +-
experimental/colbert_index/base.py | 2 +-
llama_index/agent/react/formatter.py | 2 +-
llama_index/callbacks/llama_debug.py | 2 +-
.../callbacks/open_inference_callback.py | 2 +-
llama_index/callbacks/simple_llm_handler.py | 2 +-
llama_index/chat_engine/context.py | 2 +-
llama_index/chat_engine/types.py | 4 +-
llama_index/embeddings/adapter.py | 2 +-
llama_index/evaluation/benchmarks/hotpotqa.py | 2 +-
llama_index/evaluation/dataset_generation.py | 2 +-
llama_index/indices/base_retriever.py | 2 +-
llama_index/indices/loading.py | 2 +-
llama_index/indices/managed/base.py | 2 +-
llama_index/indices/managed/vectara/base.py | 2 +-
.../indices/managed/vectara/retriever.py | 2 +-
llama_index/indices/postprocessor/node.py | 2 +-
llama_index/llm_predictor/base.py | 4 +-
llama_index/llms/azure_openai.py | 2 +-
llama_index/llms/portkey.py | 4 +-
llama_index/llms/portkey_utils.py | 2 +-
llama_index/llms/predibase.py | 2 +-
.../extractors/metadata_extractors.py | 3 +-
llama_index/node_parser/file/html.py | 4 +-
llama_index/node_parser/file/json.py | 4 +-
llama_index/node_parser/file/markdown.py | 6 +-
llama_index/objects/tool_node_mapping.py | 2 +-
.../query_engine/citation_query_engine.py | 2 +-
.../knowledge_graph_query_engine.py | 2 +-
.../query_engine/retriever_query_engine.py | 2 +-
llama_index/readers/bagel.py | 20 +--
llama_index/readers/deeplake.py | 4 +-
llama_index/readers/discord_reader.py | 24 ++-
llama_index/readers/file/docs_reader.py | 2 +-
llama_index/readers/file/flat_reader.py | 2 +-
.../github_repository_reader.py | 72 ++++----
llama_index/readers/google_readers/gsheets.py | 3 +-
llama_index/readers/myscale.py | 2 +-
llama_index/readers/psychic.py | 2 +-
llama_index/readers/redis/utils.py | 2 +-
.../response_synthesizers/accumulate.py | 4 +-
llama_index/selectors/llm_selectors.py | 4 +-
.../storage/docstore/firestore_docstore.py | 2 +-
.../index_store/firestore_indexstore.py | 2 +-
.../tools/tool_spec/load_and_search/base.py | 2 +-
llama_index/tts/elevenlabs.py | 2 -
llama_index/utils.py | 4 +-
llama_index/vector_stores/cassandra.py | 2 +-
llama_index/vector_stores/cogsearch.py | 12 +-
llama_index/vector_stores/dynamodb.py | 2 +-
llama_index/vector_stores/elasticsearch.py | 4 +-
llama_index/vector_stores/myscale.py | 2 +-
llama_index/vector_stores/neo4jvector.py | 6 +-
llama_index/vector_stores/postgres.py | 163 +++++++++---------
llama_index/vector_stores/redis.py | 2 +-
llama_index/vector_stores/rocksetdb.py | 8 +-
llama_index/vector_stores/tair.py | 2 +-
llama_index/vector_stores/timescalevector.py | 2 +-
pyproject.toml | 64 +------
tests/conftest.py | 2 +-
tests/indices/postprocessor/test_base.py | 2 +-
tests/indices/query/test_embedding_utils.py | 4 +-
tests/indices/tree/test_index.py | 2 +-
tests/llm_predictor/vellum/test_predictor.py | 4 +-
.../vellum/test_prompt_registry.py | 6 +-
tests/llms/test_localai.py | 5 +-
tests/llms/test_openai_utils.py | 2 +-
tests/memory/test_chat_memory_buffer.py | 2 +-
tests/readers/test_file.py | 5 +-
tests/text_splitter/test_code_splitter.py | 10 +-
tests/text_splitter/test_sentence_splitter.py | 4 +-
tests/tools/test_utils.py | 2 +-
77 files changed, 251 insertions(+), 326 deletions(-)
diff --git a/benchmarks/agent/math_tasks.py b/benchmarks/agent/math_tasks.py
index 76b6e09552..bf79876337 100644
--- a/benchmarks/agent/math_tasks.py
+++ b/benchmarks/agent/math_tasks.py
@@ -7,12 +7,12 @@ from llama_index.tools.function_tool import FunctionTool
def add(a: int, b: int) -> int:
- """Add two integers and returns the result integer"""
+ """Add two integers and returns the result integer."""
return a + b
def multiply(a: int, b: int) -> int:
- """Multiple two integers and returns the result integer"""
+ """Multiple two integers and returns the result integer."""
return a * b
diff --git a/benchmarks/embeddings/bench_embeddings.py b/benchmarks/embeddings/bench_embeddings.py
index b3498cd04b..1d0320ecb5 100644
--- a/benchmarks/embeddings/bench_embeddings.py
+++ b/benchmarks/embeddings/bench_embeddings.py
@@ -16,7 +16,7 @@ def generate_strings(num_strings: int = 100, string_length: int = 10) -> List[st
offset 0: [0:string_length], [string_length:2*string_length], ...
offset 1: [1:1+string_length], [1+string_length:1+2*string_length],...
...
- """
+ """ # noqa: D415
content = (
SimpleDirectoryReader("../../examples/paul_graham_essay/data")
.load_data()[0]
diff --git a/experimental/cli/cli_add.py b/experimental/cli/cli_add.py
index aecb98d9ba..076c52b26d 100644
--- a/experimental/cli/cli_add.py
+++ b/experimental/cli/cli_add.py
@@ -7,7 +7,7 @@ from .configuration import load_index, save_index
def add_cli(args: Namespace) -> None:
- """Handle subcommand "add" """
+ """Handle subcommand "add"."""
index = load_index()
for p in args.files:
@@ -26,7 +26,7 @@ def add_cli(args: Namespace) -> None:
def register_add_cli(subparsers: _SubParsersAction) -> None:
- """Register subcommand "add" to ArgumentParser"""
+ """Register subcommand "add" to ArgumentParser."""
parser = subparsers.add_parser("add")
parser.add_argument(
"files",
diff --git a/experimental/cli/cli_init.py b/experimental/cli/cli_init.py
index 2d1b68fbe6..65728d31ed 100644
--- a/experimental/cli/cli_init.py
+++ b/experimental/cli/cli_init.py
@@ -4,13 +4,13 @@ from .configuration import load_config, save_config
def init_cli(args: Namespace) -> None:
- """Handle subcommand "init" """
+ """Handle subcommand "init"."""
config = load_config(args.directory)
save_config(config, args.directory)
def register_init_cli(subparsers: _SubParsersAction) -> None:
- """Register subcommand "init" to ArgumentParser"""
+ """Register subcommand "init" to ArgumentParser."""
parser = subparsers.add_parser("init")
parser.add_argument(
"directory",
diff --git a/experimental/cli/cli_query.py b/experimental/cli/cli_query.py
index 3550f73a71..dc4543fa12 100644
--- a/experimental/cli/cli_query.py
+++ b/experimental/cli/cli_query.py
@@ -4,14 +4,14 @@ from .configuration import load_index
def query_cli(args: Namespace) -> None:
- """Handle subcommand "query" """
+ """Handle subcommand "query"."""
index = load_index()
query_engine = index.as_query_engine()
print(query_engine.query(args.query))
def register_query_cli(subparsers: _SubParsersAction) -> None:
- """Register subcommand "query" to ArgumentParser"""
+ """Register subcommand "query" to ArgumentParser."""
parser = subparsers.add_parser("query")
parser.add_argument(
"query",
diff --git a/experimental/cli/configuration.py b/experimental/cli/configuration.py
index 395393b48b..4d2d8516cb 100644
--- a/experimental/cli/configuration.py
+++ b/experimental/cli/configuration.py
@@ -28,7 +28,7 @@ DEFAULT_CONFIG = {
def load_config(root: str = ".") -> ConfigParser:
- """Load configuration from file"""
+ """Load configuration from file."""
config = ConfigParser()
config.read_dict(DEFAULT_CONFIG)
config.read(os.path.join(root, CONFIG_FILE_NAME))
@@ -36,13 +36,13 @@ def load_config(root: str = ".") -> ConfigParser:
def save_config(config: ConfigParser, root: str = ".") -> None:
- """Load configuration to file"""
+ """Load configuration to file."""
with open(os.path.join(root, CONFIG_FILE_NAME), "w") as fd:
config.write(fd)
def load_index(root: str = ".") -> BaseIndex[Any]:
- """Load existing index file"""
+ """Load existing index file."""
config = load_config(root)
service_context = _load_service_context(config)
@@ -69,14 +69,14 @@ def load_index(root: str = ".") -> BaseIndex[Any]:
def save_index(index: BaseIndex[Any], root: str = ".") -> None:
- """Save index to file"""
+ """Save index to file."""
config = load_config(root)
persist_dir = config["store"]["persist_dir"]
index.storage_context.persist(persist_dir=persist_dir)
def _load_service_context(config: ConfigParser) -> ServiceContext:
- """Internal function to load service context based on configuration"""
+ """Internal function to load service context based on configuration."""
embed_model = _load_embed_model(config)
llm_predictor = _load_llm_predictor(config)
return ServiceContext.from_defaults(
@@ -90,7 +90,7 @@ def _load_storage_context(config: ConfigParser) -> StorageContext:
def _load_llm_predictor(config: ConfigParser) -> LLMPredictor:
- """Internal function to load LLM predictor based on configuration"""
+ """Internal function to load LLM predictor based on configuration."""
model_type = config["llm_predictor"]["type"].lower()
if model_type == "default":
llm = _load_llm(config["llm_predictor"])
@@ -110,7 +110,7 @@ def _load_llm(section: SectionProxy) -> LLM:
def _load_embed_model(config: ConfigParser) -> BaseEmbedding:
- """Internal function to load embedding model based on configuration"""
+ """Internal function to load embedding model based on configuration."""
model_type = config["embed_model"]["type"]
if model_type == "default":
return OpenAIEmbedding()
diff --git a/experimental/colbert_index/base.py b/experimental/colbert_index/base.py
index 487a1ba2cc..c0d3bfa143 100644
--- a/experimental/colbert_index/base.py
+++ b/experimental/colbert_index/base.py
@@ -145,7 +145,7 @@ class ColbertIndex(BaseIndex[IndexDict]):
"""
doc_ids, _, scores = self.store.search(text=query_str, k=top_k)
- node_doc_ids = list(map(lambda id: self._docs_pos_to_node_id[id], doc_ids))
+ node_doc_ids = [self._docs_pos_to_node_id[id] for id in doc_ids]
nodes = self.docstore.get_nodes(node_doc_ids)
nodes_with_score = []
diff --git a/llama_index/agent/react/formatter.py b/llama_index/agent/react/formatter.py
index 97d131fe31..7680521239 100644
--- a/llama_index/agent/react/formatter.py
+++ b/llama_index/agent/react/formatter.py
@@ -11,7 +11,7 @@ from llama_index.tools import BaseTool
def get_react_tool_descriptions(tools: Sequence[BaseTool]) -> List[str]:
- """Tool"""
+ """Tool."""
tool_descs = []
for tool in tools:
tool_desc = (
diff --git a/llama_index/callbacks/llama_debug.py b/llama_index/callbacks/llama_debug.py
index 1fff689514..dd1073ec8e 100644
--- a/llama_index/callbacks/llama_debug.py
+++ b/llama_index/callbacks/llama_debug.py
@@ -116,7 +116,7 @@ class LlamaDebugHandler(BaseCallbackHandler):
def _get_time_stats_from_event_pairs(
self, event_pairs: List[List[CBEvent]]
) -> EventStats:
- """Calculate time-based stats for a set of event pairs"""
+ """Calculate time-based stats for a set of event pairs."""
total_secs = 0.0
for event_pair in event_pairs:
start_time = datetime.strptime(event_pair[0].time, TIMESTAMP_FORMAT)
diff --git a/llama_index/callbacks/open_inference_callback.py b/llama_index/callbacks/open_inference_callback.py
index 0e6a0ff50f..9b105ca241 100644
--- a/llama_index/callbacks/open_inference_callback.py
+++ b/llama_index/callbacks/open_inference_callback.py
@@ -112,7 +112,7 @@ def as_dataframe(data: Iterable[BaseDataType]) -> "DataFrame":
@dataclass
class TraceData:
- """Trace data"""
+ """Trace data."""
query_data: QueryData = field(default_factory=QueryData)
node_datas: List[NodeData] = field(default_factory=list)
diff --git a/llama_index/callbacks/simple_llm_handler.py b/llama_index/callbacks/simple_llm_handler.py
index 3a89f34faa..cc53a35960 100644
--- a/llama_index/callbacks/simple_llm_handler.py
+++ b/llama_index/callbacks/simple_llm_handler.py
@@ -5,7 +5,7 @@ from llama_index.callbacks.schema import CBEventType, EventPayload
class SimpleLLMHandler(BaseCallbackHandler):
- """Callback handler for printing llms inputs/outputs"""
+ """Callback handler for printing llms inputs/outputs."""
def __init__(self) -> None:
super().__init__(event_starts_to_ignore=[], event_ends_to_ignore=[])
diff --git a/llama_index/chat_engine/context.py b/llama_index/chat_engine/context.py
index 10ee892c04..dde6e5698d 100644
--- a/llama_index/chat_engine/context.py
+++ b/llama_index/chat_engine/context.py
@@ -127,7 +127,7 @@ class ContextChatEngine(BaseChatEngine):
return self._context_template.format(context_str=context_str), nodes
def _get_prefix_messages_with_context(self, context_str: str) -> List[ChatMessage]:
- """Get the prefix messages with context"""
+ """Get the prefix messages with context."""
# ensure we grab the user-configured system prompt
system_prompt = ""
prefix_messages = self._prefix_messages
diff --git a/llama_index/chat_engine/types.py b/llama_index/chat_engine/types.py
index 6b96ba91cb..5b73cb5da7 100644
--- a/llama_index/chat_engine/types.py
+++ b/llama_index/chat_engine/types.py
@@ -18,12 +18,12 @@ logger.setLevel(logging.WARNING)
def is_function(message: ChatMessage) -> bool:
- """Utility for ChatMessage responses from OpenAI models"""
+ """Utility for ChatMessage responses from OpenAI models."""
return "function_call" in message.additional_kwargs
class ChatResponseMode(str, Enum):
- """Flag toggling waiting/streaming in `Agent._chat`"""
+ """Flag toggling waiting/streaming in `Agent._chat`."""
WAIT = "wait"
STREAM = "stream"
diff --git a/llama_index/embeddings/adapter.py b/llama_index/embeddings/adapter.py
index e27e0e3144..a02516225e 100644
--- a/llama_index/embeddings/adapter.py
+++ b/llama_index/embeddings/adapter.py
@@ -47,7 +47,7 @@ class AdapterEmbeddingModel(BaseEmbedding):
embed_batch_size: int = DEFAULT_EMBED_BATCH_SIZE,
callback_manager: Optional[CallbackManager] = None,
) -> None:
- """Init params"""
+ """Init params."""
import torch
from llama_index.embeddings.adapter_utils import BaseAdapter, LinearLayer
diff --git a/llama_index/evaluation/benchmarks/hotpotqa.py b/llama_index/evaluation/benchmarks/hotpotqa.py
index f09ef85629..4651fb70f7 100644
--- a/llama_index/evaluation/benchmarks/hotpotqa.py
+++ b/llama_index/evaluation/benchmarks/hotpotqa.py
@@ -22,7 +22,7 @@ hotpot/hotpot_dev_distractor_v1.json"""
class HotpotQAEvaluator:
"""
- Refer to https://hotpotqa.github.io/ for more details on the dataset
+ Refer to https://hotpotqa.github.io/ for more details on the dataset.
"""
def _download_datasets(self) -> Dict[str, str]:
diff --git a/llama_index/evaluation/dataset_generation.py b/llama_index/evaluation/dataset_generation.py
index 299e24c159..3232f5d7fd 100644
--- a/llama_index/evaluation/dataset_generation.py
+++ b/llama_index/evaluation/dataset_generation.py
@@ -1,4 +1,4 @@
-"""Dataset generation from documents"""
+"""Dataset generation from documents."""
from __future__ import annotations
import asyncio
diff --git a/llama_index/indices/base_retriever.py b/llama_index/indices/base_retriever.py
index 2885698a53..3d2f52b5b9 100644
--- a/llama_index/indices/base_retriever.py
+++ b/llama_index/indices/base_retriever.py
@@ -47,7 +47,7 @@ class BaseRetriever(ABC):
def get_service_context(self) -> Optional[ServiceContext]:
"""Attempts to resolve a service context.
Short-circuits at self.service_context, self._service_context,
- or self._index.service_context
+ or self._index.service_context.
"""
if hasattr(self, "service_context"):
return self.service_context
diff --git a/llama_index/indices/loading.py b/llama_index/indices/loading.py
index b917f93e33..4c65946e70 100644
--- a/llama_index/indices/loading.py
+++ b/llama_index/indices/loading.py
@@ -50,7 +50,7 @@ def load_indices_from_storage(
index_ids: Optional[Sequence[str]] = None,
**kwargs: Any,
) -> List[BaseIndex]:
- """Load multiple indices from storage context
+ """Load multiple indices from storage context.
Args:
storage_context (StorageContext): storage context containing
diff --git a/llama_index/indices/managed/base.py b/llama_index/indices/managed/base.py
index ac649407bb..928ba66d50 100644
--- a/llama_index/indices/managed/base.py
+++ b/llama_index/indices/managed/base.py
@@ -20,7 +20,7 @@ class BaseManagedIndex(BaseIndex[IndexDict], ABC):
The managed service can index documents into a managed service.
How documents are structured into nodes is a detail for the managed service,
and not exposed in this interface (although could be controlled by
- configuration parameters)
+ configuration parameters).
Args:
show_progress (bool): Whether to show tqdm progress bars. Defaults to False.
diff --git a/llama_index/indices/managed/vectara/base.py b/llama_index/indices/managed/vectara/base.py
index 21db9ccc4b..abd6c1c491 100644
--- a/llama_index/indices/managed/vectara/base.py
+++ b/llama_index/indices/managed/vectara/base.py
@@ -203,7 +203,7 @@ class VectaraIndex(BaseManagedIndex):
) -> Optional[str]:
"""Vectara provides a way to add files (binary or text) directly via our API
where pre-processing and chunking occurs internally in an optimal way
- This method provides a way to use that API in Llama_index
+ This method provides a way to use that API in Llama_index.
# ruff: noqa: E501
Full API Docs: https://docs.vectara.com/docs/api-reference/indexing-apis/
diff --git a/llama_index/indices/managed/vectara/retriever.py b/llama_index/indices/managed/vectara/retriever.py
index 25155d1b64..5fb08c2637 100644
--- a/llama_index/indices/managed/vectara/retriever.py
+++ b/llama_index/indices/managed/vectara/retriever.py
@@ -1,5 +1,5 @@
"""Vectara index.
-An index that that is built on top of Vectara
+An index that that is built on top of Vectara.
"""
import json
diff --git a/llama_index/indices/postprocessor/node.py b/llama_index/indices/postprocessor/node.py
index 6a32ab1260..b101109736 100644
--- a/llama_index/indices/postprocessor/node.py
+++ b/llama_index/indices/postprocessor/node.py
@@ -362,7 +362,7 @@ class LongContextReorder(BaseNodePostprocessor):
performance typically arises when crucial data is positioned
at the start or conclusion of the input context. Additionally,
as the input context lengthens, performance drops notably, even
- in models designed for long contexts."
+ in models designed for long contexts.".
"""
@classmethod
diff --git a/llama_index/llm_predictor/base.py b/llama_index/llm_predictor/base.py
index 776226587c..5de8690182 100644
--- a/llama_index/llm_predictor/base.py
+++ b/llama_index/llm_predictor/base.py
@@ -263,7 +263,7 @@ class LLMPredictor(BaseLLMPredictor):
self,
formatted_prompt: str,
) -> str:
- """Add system and query wrapper prompts to base prompt"""
+ """Add system and query wrapper prompts to base prompt."""
extended_prompt = formatted_prompt
if self.system_prompt:
extended_prompt = self.system_prompt + "\n\n" + extended_prompt
@@ -276,7 +276,7 @@ class LLMPredictor(BaseLLMPredictor):
return extended_prompt
def _extend_messages(self, messages: List[ChatMessage]) -> List[ChatMessage]:
- """Add system prompt to chat message list"""
+ """Add system prompt to chat message list."""
if self.system_prompt:
messages = [
ChatMessage(role=MessageRole.SYSTEM, content=self.system_prompt),
diff --git a/llama_index/llms/azure_openai.py b/llama_index/llms/azure_openai.py
index 2dd0eae9c6..21bf029ab4 100644
--- a/llama_index/llms/azure_openai.py
+++ b/llama_index/llms/azure_openai.py
@@ -10,7 +10,7 @@ AZURE_OPENAI_API_TYPE = "azure"
class AzureOpenAI(OpenAI):
"""
- Azure OpenAI
+ Azure OpenAI.
To use this, you must first deploy a model on Azure OpenAI.
Unlike OpenAI, you need to specify a `engine` parameter to identify
diff --git a/llama_index/llms/portkey.py b/llama_index/llms/portkey.py
index 4fcbcdf452..c9e444af99 100644
--- a/llama_index/llms/portkey.py
+++ b/llama_index/llms/portkey.py
@@ -1,5 +1,5 @@
"""
-Portkey integration with Llama_index for enhanced monitoring
+Portkey integration with Llama_index for enhanced monitoring.
"""
from typing import TYPE_CHECKING, Any, List, Optional, Sequence, Union, cast
@@ -38,7 +38,7 @@ if TYPE_CHECKING:
class Portkey(CustomLLM):
- """_summary_
+ """_summary_.
Args:
LLM (_type_): _description_
diff --git a/llama_index/llms/portkey_utils.py b/llama_index/llms/portkey_utils.py
index d15cb41367..b328ea402f 100644
--- a/llama_index/llms/portkey_utils.py
+++ b/llama_index/llms/portkey_utils.py
@@ -1,5 +1,5 @@
"""
-Utility Tools for the Portkey Class
+Utility Tools for the Portkey Class.
This file module contains a collection of utility functions designed to enhance
the functionality and usability of the Portkey class
diff --git a/llama_index/llms/predibase.py b/llama_index/llms/predibase.py
index e0a279653b..c70dc631d1 100644
--- a/llama_index/llms/predibase.py
+++ b/llama_index/llms/predibase.py
@@ -14,7 +14,7 @@ from llama_index.llms.custom import CustomLLM
class PredibaseLLM(CustomLLM):
- """Predibase LLM"""
+ """Predibase LLM."""
model_name: str = Field(description="The Predibase model to use.")
predibase_api_key: str = Field(description="The Predibase API key to use.")
diff --git a/llama_index/node_parser/extractors/metadata_extractors.py b/llama_index/node_parser/extractors/metadata_extractors.py
index 88846e61d6..166e5b559a 100644
--- a/llama_index/node_parser/extractors/metadata_extractors.py
+++ b/llama_index/node_parser/extractors/metadata_extractors.py
@@ -403,7 +403,8 @@ class SummaryExtractor(MetadataFeatureExtractor):
"""
Summary extractor. Node-level extractor with adjacent sharing.
Extracts `section_summary`, `prev_section_summary`, `next_section_summary`
- metadata fields
+ metadata fields.
+
Args:
llm_predictor (Optional[BaseLLMPredictor]): LLM predictor
summaries (List[str]): list of summaries to extract: 'self', 'prev', 'next'
diff --git a/llama_index/node_parser/file/html.py b/llama_index/node_parser/file/html.py
index 60b1e387f8..c45498a1a9 100644
--- a/llama_index/node_parser/file/html.py
+++ b/llama_index/node_parser/file/html.py
@@ -88,7 +88,7 @@ class HTMLNodeParser(NodeParser):
return all_nodes
def get_nodes_from_node(self, node: BaseNode) -> List[TextNode]:
- """Get nodes from document"""
+ """Get nodes from document."""
try:
from bs4 import BeautifulSoup
except ImportError:
@@ -144,7 +144,7 @@ class HTMLNodeParser(NodeParser):
node: BaseNode,
metadata: dict,
) -> TextNode:
- """Build node from single text split"""
+ """Build node from single text split."""
node = build_nodes_from_splits(
[text_split], node, self.include_metadata, self.include_prev_next_rel
)[0]
diff --git a/llama_index/node_parser/file/json.py b/llama_index/node_parser/file/json.py
index 207143e55c..aa8e79a4b6 100644
--- a/llama_index/node_parser/file/json.py
+++ b/llama_index/node_parser/file/json.py
@@ -80,7 +80,7 @@ class JSONNodeParser(NodeParser):
return all_nodes
def get_nodes_from_node(self, node: BaseNode) -> List[TextNode]:
- """Get nodes from document"""
+ """Get nodes from document."""
text = node.get_content(metadata_mode=MetadataMode.NONE)
try:
data = json.loads(text)
@@ -132,7 +132,7 @@ class JSONNodeParser(NodeParser):
node: BaseNode,
metadata: dict,
) -> TextNode:
- """Build node from single text split"""
+ """Build node from single text split."""
node = build_nodes_from_splits(
[text_split], node, self.include_metadata, self.include_prev_next_rel
)[0]
diff --git a/llama_index/node_parser/file/markdown.py b/llama_index/node_parser/file/markdown.py
index c5f9920509..13ccf80f8e 100644
--- a/llama_index/node_parser/file/markdown.py
+++ b/llama_index/node_parser/file/markdown.py
@@ -80,7 +80,7 @@ class MarkdownNodeParser(NodeParser):
return all_nodes
def get_nodes_from_node(self, node: BaseNode) -> List[TextNode]:
- """Get nodes from document"""
+ """Get nodes from document."""
text = node.get_content(metadata_mode=MetadataMode.NONE)
markdown_nodes = []
lines = text.split("\n")
@@ -115,7 +115,7 @@ class MarkdownNodeParser(NodeParser):
def _update_metadata(
self, headers_metadata: dict, new_header: str, new_header_level: int
) -> dict:
- """Update the markdown headers for metadata
+ """Update the markdown headers for metadata.
Removes all headers that are equal or less than the level
of the newly found header
@@ -136,7 +136,7 @@ class MarkdownNodeParser(NodeParser):
node: BaseNode,
metadata: dict,
) -> TextNode:
- """Build node from single text split"""
+ """Build node from single text split."""
node = build_nodes_from_splits(
[text_split], node, self.include_metadata, self.include_prev_next_rel
)[0]
diff --git a/llama_index/objects/tool_node_mapping.py b/llama_index/objects/tool_node_mapping.py
index e17d9cfb58..18ee0c9ae5 100644
--- a/llama_index/objects/tool_node_mapping.py
+++ b/llama_index/objects/tool_node_mapping.py
@@ -1,4 +1,4 @@
-"""Tool mapping"""
+"""Tool mapping."""
from typing import Any, Optional, Sequence
diff --git a/llama_index/query_engine/citation_query_engine.py b/llama_index/query_engine/citation_query_engine.py
index 7f01c049bd..52bc021a53 100644
--- a/llama_index/query_engine/citation_query_engine.py
+++ b/llama_index/query_engine/citation_query_engine.py
@@ -136,7 +136,7 @@ class CitationQueryEngine(BaseQueryEngine):
# class-specific args
**kwargs: Any,
) -> "CitationQueryEngine":
- """Initialize a CitationQueryEngine object."
+ """Initialize a CitationQueryEngine object.".
Args:
index: (BastGPTIndex): index to use for querying
diff --git a/llama_index/query_engine/knowledge_graph_query_engine.py b/llama_index/query_engine/knowledge_graph_query_engine.py
index 53b8b9430f..8d00b2a448 100644
--- a/llama_index/query_engine/knowledge_graph_query_engine.py
+++ b/llama_index/query_engine/knowledge_graph_query_engine.py
@@ -1,4 +1,4 @@
-""" Knowledge Graph Query Engine"""
+""" Knowledge Graph Query Engine."""
import logging
from typing import Any, List, Optional, Sequence
diff --git a/llama_index/query_engine/retriever_query_engine.py b/llama_index/query_engine/retriever_query_engine.py
index c6bfd389c2..ad9915390e 100644
--- a/llama_index/query_engine/retriever_query_engine.py
+++ b/llama_index/query_engine/retriever_query_engine.py
@@ -67,7 +67,7 @@ class RetrieverQueryEngine(BaseQueryEngine):
# class-specific args
**kwargs: Any,
) -> "RetrieverQueryEngine":
- """Initialize a RetrieverQueryEngine object."
+ """Initialize a RetrieverQueryEngine object.".
Args:
retriever (BaseRetriever): A retriever object.
diff --git a/llama_index/readers/bagel.py b/llama_index/readers/bagel.py
index aecb94ca65..cdf647f8c4 100644
--- a/llama_index/readers/bagel.py
+++ b/llama_index/readers/bagel.py
@@ -18,15 +18,8 @@ Metadatas = List[Metadata]
# Metadata Query Grammar
LiteralValue = Union[str, int, float]
-LogicalOperator = Union[Literal["$and"], Literal["$or"]]
-WhereOperator = Union[
- Literal["$gt"],
- Literal["$gte"],
- Literal["$lt"],
- Literal["$lte"],
- Literal["$ne"],
- Literal["$eq"],
-]
+LogicalOperator = Literal["$and", "$or"]
+WhereOperator = Literal["$gt", "$gte", "$lt", "$lte", "$ne", "$eq"]
OperatorExpression = Dict[Union[WhereOperator, LogicalOperator], LiteralValue]
Where = Dict[
@@ -47,14 +40,7 @@ OneOrMany = Union[T, List[T]]
# This should ust be List[Literal["documents", "embeddings", "metadatas", "distances"]]
# However, this provokes an incompatibility with the Overrides library and Python 3.7
-Include = List[
- Union[
- Literal["documents"],
- Literal["embeddings"],
- Literal["metadatas"],
- Literal["distances"],
- ]
-]
+Include = List[Literal["documents", "embeddings", "metadatas", "distances"]]
LiteralValue = LiteralValue
LogicalOperator = LogicalOperator
diff --git a/llama_index/readers/deeplake.py b/llama_index/readers/deeplake.py
index fa9fb3471c..00c00f43a6 100644
--- a/llama_index/readers/deeplake.py
+++ b/llama_index/readers/deeplake.py
@@ -30,7 +30,7 @@ def vector_search(
distance_metric: distance function 'L2' for Euclidean, 'L1' for Nuclear, 'Max'
l-infinity distance, 'cos' for cosine similarity, 'dot' for dot product
returns:
- nearest_indices: List, indices of nearest neighbors
+ nearest_indices: List, indices of nearest neighbors.
"""
# Calculate the distance between the query_vector and all data_vectors
if isinstance(query_vector, list):
@@ -62,7 +62,7 @@ class DeepLakeReader(BaseReader):
self,
token: Optional[str] = None,
):
- """Initializing the deepLake reader"""
+ """Initializing the deepLake reader."""
import_err_msg = (
"`deeplake` package not found, please run `pip install deeplake`"
)
diff --git a/llama_index/readers/discord_reader.py b/llama_index/readers/discord_reader.py
index 8ea42a0f2e..0b400d2b38 100644
--- a/llama_index/readers/discord_reader.py
+++ b/llama_index/readers/discord_reader.py
@@ -70,20 +70,18 @@ async def read_channel(
### Wraps each message in a Document containing the text \
# as well as some useful metadata properties.
- return list(
- map(
- lambda msg: Document(
- text=msg.content,
- metadata={
- "message_id": msg.id,
- "username": msg.author.name,
- "created_at": msg.created_at,
- "edited_at": msg.edited_at,
- },
- ),
- messages,
+ return [
+ Document(
+ text=msg.content,
+ metadata={
+ "message_id": msg.id,
+ "username": msg.author.name,
+ "created_at": msg.created_at,
+ "edited_at": msg.edited_at,
+ },
)
- )
+ for msg in messages
+ ]
class DiscordReader(BasePydanticReader):
diff --git a/llama_index/readers/file/docs_reader.py b/llama_index/readers/file/docs_reader.py
index 4817086932..4203e37c54 100644
--- a/llama_index/readers/file/docs_reader.py
+++ b/llama_index/readers/file/docs_reader.py
@@ -71,7 +71,7 @@ class DocxReader(BaseReader):
class HWPReader(BaseReader):
- """Hwp Parser"""
+ """Hwp Parser."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
super().__init__(*args, **kwargs)
diff --git a/llama_index/readers/file/flat_reader.py b/llama_index/readers/file/flat_reader.py
index 4ba16679cf..05130cfb38 100644
--- a/llama_index/readers/file/flat_reader.py
+++ b/llama_index/readers/file/flat_reader.py
@@ -7,7 +7,7 @@ from llama_index.schema import Document
class FlatReader(BaseReader):
- """Flat reader
+ """Flat reader.
Extract raw text from a file and save the file type in the metadata
"""
diff --git a/llama_index/readers/github_readers/github_repository_reader.py b/llama_index/readers/github_readers/github_repository_reader.py
index ef3265e7b0..bceee82511 100644
--- a/llama_index/readers/github_readers/github_repository_reader.py
+++ b/llama_index/readers/github_readers/github_repository_reader.py
@@ -348,44 +348,42 @@ class GithubRepositoryReader(BaseReader):
+ f"as {file_extension} with "
+ f"{reader.__class__.__name__}",
)
- with tempfile.TemporaryDirectory() as tmpdirname:
- with tempfile.NamedTemporaryFile(
- dir=tmpdirname,
- suffix=f".{file_extension}",
- mode="w+b",
- delete=False,
- ) as tmpfile:
- print_if_verbose(
- self._verbose,
- "created a temporary file"
- + f"{tmpfile.name} for parsing {file_path}",
- )
- tmpfile.write(file_content)
- tmpfile.flush()
- tmpfile.close()
- try:
- docs = reader.load_data(pathlib.Path(tmpfile.name))
- parsed_file = "\n\n".join([doc.get_content() for doc in docs])
- except Exception as e:
- print_if_verbose(self._verbose, f"error while parsing {file_path}")
- logger.error(
- "Error while parsing "
- + f"{file_path} with "
- + f"{reader.__class__.__name__}:\n{e}"
- )
- parsed_file = None
- finally:
- os.remove(tmpfile.name)
- if parsed_file is None:
- return None
- return Document(
- text=parsed_file,
- id_=tree_sha,
- metadata={
- "file_path": file_path,
- "file_name": tree_path,
- },
+ with tempfile.TemporaryDirectory() as tmpdirname, tempfile.NamedTemporaryFile(
+ dir=tmpdirname,
+ suffix=f".{file_extension}",
+ mode="w+b",
+ delete=False,
+ ) as tmpfile:
+ print_if_verbose(
+ self._verbose,
+ "created a temporary file" + f"{tmpfile.name} for parsing {file_path}",
+ )
+ tmpfile.write(file_content)
+ tmpfile.flush()
+ tmpfile.close()
+ try:
+ docs = reader.load_data(pathlib.Path(tmpfile.name))
+ parsed_file = "\n\n".join([doc.get_content() for doc in docs])
+ except Exception as e:
+ print_if_verbose(self._verbose, f"error while parsing {file_path}")
+ logger.error(
+ "Error while parsing "
+ + f"{file_path} with "
+ + f"{reader.__class__.__name__}:\n{e}"
)
+ parsed_file = None
+ finally:
+ os.remove(tmpfile.name)
+ if parsed_file is None:
+ return None
+ return Document(
+ text=parsed_file,
+ id_=tree_sha,
+ metadata={
+ "file_path": file_path,
+ "file_name": tree_path,
+ },
+ )
if __name__ == "__main__":
diff --git a/llama_index/readers/google_readers/gsheets.py b/llama_index/readers/google_readers/gsheets.py
index 03a2a642a5..74a3f0d4cd 100644
--- a/llama_index/readers/google_readers/gsheets.py
+++ b/llama_index/readers/google_readers/gsheets.py
@@ -104,8 +104,7 @@ class GoogleSheetsReader(BasePydanticReader):
.execute()
)
sheet_text += (
- "\n".join(map(lambda row: "\t".join(row), response.get("values", [])))
- + "\n"
+ "\n".join("\t".join(row) for row in response.get("values", [])) + "\n"
)
return sheet_text
diff --git a/llama_index/readers/myscale.py b/llama_index/readers/myscale.py
index aa166307d9..fbb31db01e 100644
--- a/llama_index/readers/myscale.py
+++ b/llama_index/readers/myscale.py
@@ -21,7 +21,7 @@ def format_list_to_string(lst: List) -> str:
class MyScaleSettings:
- """MyScale Client Configuration
+ """MyScale Client Configuration.
Attribute:
table (str) : Table name to operate on.
diff --git a/llama_index/readers/psychic.py b/llama_index/readers/psychic.py
index 8c0edf44af..28485c75c8 100644
--- a/llama_index/readers/psychic.py
+++ b/llama_index/readers/psychic.py
@@ -47,7 +47,7 @@ class PsychicReader(BaseReader):
def load_data(
self, connector_id: Optional[str] = None, account_id: Optional[str] = None
) -> List[Document]:
- """Load data from a Psychic connection
+ """Load data from a Psychic connection.
Args:
connector_id (str): The connector ID to connect to
diff --git a/llama_index/readers/redis/utils.py b/llama_index/readers/redis/utils.py
index 007aa6ee90..da7e1e3e12 100644
--- a/llama_index/readers/redis/utils.py
+++ b/llama_index/readers/redis/utils.py
@@ -70,7 +70,7 @@ def get_redis_query(
sort: bool = True,
filters: str = "*",
) -> "Query":
- """Create a vector query for use with a SearchIndex
+ """Create a vector query for use with a SearchIndex.
Args:
return_fields (t.List[str]): A list of fields to return in the query results
diff --git a/llama_index/response_synthesizers/accumulate.py b/llama_index/response_synthesizers/accumulate.py
index b13b5485d1..a95a63b228 100644
--- a/llama_index/response_synthesizers/accumulate.py
+++ b/llama_index/response_synthesizers/accumulate.py
@@ -47,7 +47,7 @@ class Accumulate(BaseSynthesizer):
separator: str = "\n---------------------\n",
**response_kwargs: Any,
) -> RESPONSE_TEXT_TYPE:
- """Apply the same prompt to text chunks and return async responses"""
+ """Apply the same prompt to text chunks and return async responses."""
if self._streaming:
raise ValueError("Unable to stream in Accumulate response mode")
@@ -68,7 +68,7 @@ class Accumulate(BaseSynthesizer):
separator: str = "\n---------------------\n",
**response_kwargs: Any,
) -> RESPONSE_TEXT_TYPE:
- """Apply the same prompt to text chunks and return responses"""
+ """Apply the same prompt to text chunks and return responses."""
if self._streaming:
raise ValueError("Unable to stream in Accumulate response mode")
diff --git a/llama_index/selectors/llm_selectors.py b/llama_index/selectors/llm_selectors.py
index f596cda908..1ed035b198 100644
--- a/llama_index/selectors/llm_selectors.py
+++ b/llama_index/selectors/llm_selectors.py
@@ -41,7 +41,7 @@ def _structured_output_to_selector_result(output: Any) -> SelectorResult:
class LLMSingleSelector(BaseSelector):
- """LLM single selector
+ """LLM single selector.
LLM-based selector that chooses one out of many options.
@@ -124,7 +124,7 @@ class LLMSingleSelector(BaseSelector):
class LLMMultiSelector(BaseSelector):
- """LLM multi selector
+ """LLM multi selector.
LLM-based selector that chooses multiple out of many options.
diff --git a/llama_index/storage/docstore/firestore_docstore.py b/llama_index/storage/docstore/firestore_docstore.py
index 8f335700f9..26f71dac4b 100644
--- a/llama_index/storage/docstore/firestore_docstore.py
+++ b/llama_index/storage/docstore/firestore_docstore.py
@@ -34,7 +34,7 @@ class FirestoreDocumentStore(KVDocumentStore):
Args:
project (str): The project which the client acts on behalf of.
database (str): The database name that the client targets.
- namespace (str): namespace for the docstore
+ namespace (str): namespace for the docstore.
"""
firestore_kvstore = FirestoreKVStore(project=project, database=database)
return cls(firestore_kvstore, namespace)
diff --git a/llama_index/storage/index_store/firestore_indexstore.py b/llama_index/storage/index_store/firestore_indexstore.py
index 1cea883bf2..8f777f849a 100644
--- a/llama_index/storage/index_store/firestore_indexstore.py
+++ b/llama_index/storage/index_store/firestore_indexstore.py
@@ -32,7 +32,7 @@ class FirestoreIndexStore(KVIndexStore):
Args:
project (str): The project which the client acts on behalf of.
database (str): The database name that the client targets.
- namespace (str): namespace for the docstore
+ namespace (str): namespace for the docstore.
"""
firestore_kvstore = FirestoreKVStore(project=project, database=database)
return cls(firestore_kvstore, namespace)
diff --git a/llama_index/tools/tool_spec/load_and_search/base.py b/llama_index/tools/tool_spec/load_and_search/base.py
index 0ee04b533d..bde2bc6a8b 100644
--- a/llama_index/tools/tool_spec/load_and_search/base.py
+++ b/llama_index/tools/tool_spec/load_and_search/base.py
@@ -17,7 +17,7 @@ from llama_index.tools.utils import create_schema_from_function
class LoadAndSearchToolSpec(BaseToolSpec):
- """Load and Search Tool
+ """Load and Search Tool.
This tool can be used with other tools that load large amounts of
information. Compared to OndemandLoaderTool this returns two tools,
diff --git a/llama_index/tts/elevenlabs.py b/llama_index/tts/elevenlabs.py
index 5b8f2309a1..64aa65868b 100644
--- a/llama_index/tts/elevenlabs.py
+++ b/llama_index/tts/elevenlabs.py
@@ -14,8 +14,6 @@ class ElevenLabsTTS(BaseTTS):
"""
def __init__(self, api_key: Optional[str] = None) -> None:
- """ """
-
super().__init__()
self.api_key = api_key
diff --git a/llama_index/utils.py b/llama_index/utils.py
index 59241bb6c4..c2be210b13 100644
--- a/llama_index/utils.py
+++ b/llama_index/utils.py
@@ -241,7 +241,7 @@ def get_transformer_tokenizer_fn(model_name: str) -> Callable[[str], List[str]]:
"""
Args:
model_name(str): the model name of the tokenizer.
- For instance, fxmarty/tiny-llama-fast-tokenizer
+ For instance, fxmarty/tiny-llama-fast-tokenizer.
"""
try:
from transformers import AutoTokenizer
@@ -255,7 +255,7 @@ def get_transformer_tokenizer_fn(model_name: str) -> Callable[[str], List[str]]:
def get_cache_dir() -> str:
"""Locate a platform-appropriate cache directory for llama_index,
- and create it if it doesn't yet exist
+ and create it if it doesn't yet exist.
"""
# User override
if "LLAMA_INDEX_CACHE_DIR" in os.environ:
diff --git a/llama_index/vector_stores/cassandra.py b/llama_index/vector_stores/cassandra.py
index 2722259289..6afdc7aab5 100644
--- a/llama_index/vector_stores/cassandra.py
+++ b/llama_index/vector_stores/cassandra.py
@@ -171,7 +171,7 @@ class CassandraVectorStore(VectorStore):
@property
def client(self) -> Any:
- """Return the underlying cassIO vector table object"""
+ """Return the underlying cassIO vector table object."""
return self.vector_table
@staticmethod
diff --git a/llama_index/vector_stores/cogsearch.py b/llama_index/vector_stores/cogsearch.py
index ac194b76c9..51e99fb327 100644
--- a/llama_index/vector_stores/cogsearch.py
+++ b/llama_index/vector_stores/cogsearch.py
@@ -27,7 +27,7 @@ class MetadataIndexFieldType(int, enum.Enum):
"""
Enumeration representing the supported types for metadata fields in an
Azure Cognitive Search Index, corresponds with types supported in a flat
- metadata dictionary
+ metadata dictionary.
"""
STRING = auto() # "Edm.String"
@@ -38,7 +38,7 @@ class MetadataIndexFieldType(int, enum.Enum):
class IndexManagement(int, enum.Enum):
- """Enumeration representing the supported index management operations"""
+ """Enumeration representing the supported index management operations."""
NO_VALIDATION = auto()
VALIDATE_INDEX = auto()
@@ -85,7 +85,7 @@ class CognitiveSearchVectorStore(VectorStore):
self._create_index(index_name)
def _create_metadata_index_fields(self) -> List[Any]:
- """Create a list of index fields for storing metadata values"""
+ """Create a list of index fields for storing metadata values."""
from azure.search.documents.indexes.models import SimpleField
index_fields = []
@@ -113,7 +113,7 @@ class CognitiveSearchVectorStore(VectorStore):
def _create_index(self, index_name: Optional[str]) -> None:
"""
Creates a default index based on the supplied index name, key field names and
- metadata filtering keys
+ metadata filtering keys.
"""
from azure.search.documents.indexes.models import (
HnswParameters,
@@ -438,7 +438,7 @@ class CognitiveSearchVectorStore(VectorStore):
return ids
def _create_index_document(self, node: BaseNode) -> Dict[str, Any]:
- """Create Cognitive Search index document from embedding result"""
+ """Create Cognitive Search index document from embedding result."""
doc: Dict[str, Any] = {}
doc["id"] = node.node_id
doc["chunk"] = node.get_content(metadata_mode=MetadataMode.NONE) or ""
@@ -478,7 +478,7 @@ class CognitiveSearchVectorStore(VectorStore):
self._search_client.delete_documents(docs_to_delete)
def _create_odata_filter(self, metadata_filters: MetadataFilters) -> str:
- """Generate an OData filter string using supplied metadata filters"""
+ """Generate an OData filter string using supplied metadata filters."""
odata_filter: List[str] = []
for f in metadata_filters.filters:
if not isinstance(f, ExactMatchFilter):
diff --git a/llama_index/vector_stores/dynamodb.py b/llama_index/vector_stores/dynamodb.py
index 8e4c8e6dfb..bd89f72447 100644
--- a/llama_index/vector_stores/dynamodb.py
+++ b/llama_index/vector_stores/dynamodb.py
@@ -109,7 +109,7 @@ class DynamoDBVectorStore(VectorStore):
)
def query(self, query: VectorStoreQuery, **kwargs: Any) -> VectorStoreQueryResult:
- """Get nodes for response"""
+ """Get nodes for response."""
if query.filters is not None:
raise ValueError(
"Metadata filters not implemented for SimpleVectorStore yet."
diff --git a/llama_index/vector_stores/elasticsearch.py b/llama_index/vector_stores/elasticsearch.py
index dab60f7eb9..cba936152b 100644
--- a/llama_index/vector_stores/elasticsearch.py
+++ b/llama_index/vector_stores/elasticsearch.py
@@ -199,12 +199,12 @@ class ElasticsearchStore(VectorStore):
@property
def client(self) -> Any:
- """Get async elasticsearch client"""
+ """Get async elasticsearch client."""
return self._client
@staticmethod
def get_user_agent() -> str:
- """Get user agent for elasticsearch client"""
+ """Get user agent for elasticsearch client."""
import llama_index
return f"llama_index-py-vs/{llama_index.__version__}"
diff --git a/llama_index/vector_stores/myscale.py b/llama_index/vector_stores/myscale.py
index 05e4f25c31..94022cd956 100644
--- a/llama_index/vector_stores/myscale.py
+++ b/llama_index/vector_stores/myscale.py
@@ -241,7 +241,7 @@ class MyScaleVectorStore(VectorStore):
raise NotImplementedError("Delete not yet implemented for MyScale index.")
def drop(self) -> None:
- """Drop MyScale Index and table"""
+ """Drop MyScale Index and table."""
self._client.command(
f"DROP TABLE IF EXISTS {self.config.database}.{self.config.table}"
)
diff --git a/llama_index/vector_stores/neo4jvector.py b/llama_index/vector_stores/neo4jvector.py
index c25a0c5fa3..be3afe357d 100644
--- a/llama_index/vector_stores/neo4jvector.py
+++ b/llama_index/vector_stores/neo4jvector.py
@@ -10,7 +10,7 @@ from llama_index.vector_stores.utils import metadata_dict_to_node, node_to_metad
def check_if_not_null(props: List[str], values: List[Any]) -> None:
- """Check if variable is not null and raise error accordingly"""
+ """Check if variable is not null and raise error accordingly."""
for prop, value in zip(props, values):
if not value:
raise ValueError(f"Parameter `{prop}` must not be None or empty string")
@@ -19,12 +19,12 @@ def check_if_not_null(props: List[str], values: List[Any]) -> None:
def sort_by_index_name(
lst: List[Dict[str, Any]], index_name: str
) -> List[Dict[str, Any]]:
- """Sort first element to match the index_name if exists"""
+ """Sort first element to match the index_name if exists."""
return sorted(lst, key=lambda x: x.get("index_name") != index_name)
def clean_params(params: List[BaseNode]) -> List[Dict[str, Any]]:
- """Convert BaseNode object to a dictionary to be imported into Neo4j"""
+ """Convert BaseNode object to a dictionary to be imported into Neo4j."""
clean_params = []
for record in params:
text = record.get_content(metadata_mode=MetadataMode.NONE)
diff --git a/llama_index/vector_stores/postgres.py b/llama_index/vector_stores/postgres.py
index faa32c99d9..a603af5c13 100644
--- a/llama_index/vector_stores/postgres.py
+++ b/llama_index/vector_stores/postgres.py
@@ -1,6 +1,5 @@
import logging
-from collections import namedtuple
-from typing import Any, List, Optional, Type
+from typing import Any, List, NamedTuple, Optional, Type
from llama_index.bridge.pydantic import PrivateAttr
from llama_index.schema import BaseNode, MetadataMode, TextNode
@@ -13,9 +12,12 @@ from llama_index.vector_stores.types import (
)
from llama_index.vector_stores.utils import metadata_dict_to_node, node_to_metadata_dict
-DBEmbeddingRow = namedtuple(
- "DBEmbeddingRow", ["node_id", "text", "metadata", "similarity"]
-)
+
+class DBEmbeddingRow(NamedTuple):
+ node_id: str # FIXME: verify this type hint
+ text: str
+ metadata: dict
+ similarity: float
_logger = logging.getLogger(__name__)
@@ -30,7 +32,7 @@ def get_data_model(
embed_dim: int = 1536,
) -> Any:
"""
- This part create a dynamic sqlalchemy model with a new table
+ This part create a dynamic sqlalchemy model with a new table.
"""
from pgvector.sqlalchemy import Vector
from sqlalchemy import Column, Computed
@@ -229,18 +231,16 @@ class PGVectorStore(BasePydanticVectorStore):
self._async_session = async_sessionmaker(self._async_engine)
def _create_tables_if_not_exists(self) -> None:
- with self._session() as session:
- with session.begin():
- self._base.metadata.create_all(session.connection())
+ with self._session() as session, session.begin():
+ self._base.metadata.create_all(session.connection())
def _create_extension(self) -> None:
import sqlalchemy
- with self._session() as session:
- with session.begin():
- statement = sqlalchemy.text("CREATE EXTENSION IF NOT EXISTS vector")
- session.execute(statement)
- session.commit()
+ with self._session() as session, session.begin():
+ statement = sqlalchemy.text("CREATE EXTENSION IF NOT EXISTS vector")
+ session.execute(statement)
+ session.commit()
def _initialize(self) -> None:
if not self._is_initialized:
@@ -264,25 +264,23 @@ class PGVectorStore(BasePydanticVectorStore):
def add(self, nodes: List[BaseNode]) -> List[str]:
self._initialize()
ids = []
- with self._session() as session:
- with session.begin():
- for node in nodes:
- ids.append(node.node_id)
- item = self._node_to_table_row(node)
- session.add(item)
- session.commit()
+ with self._session() as session, session.begin():
+ for node in nodes:
+ ids.append(node.node_id)
+ item = self._node_to_table_row(node)
+ session.add(item)
+ session.commit()
return ids
async def async_add(self, nodes: List[BaseNode]) -> List[str]:
self._initialize()
ids = []
- async with self._async_session() as session:
- async with session.begin():
- for node in nodes:
- ids.append(node.node_id)
- item = self._node_to_table_row(node)
- session.add(item)
- await session.commit()
+ async with self._async_session() as session, session.begin():
+ for node in nodes:
+ ids.append(node.node_id)
+ item = self._node_to_table_row(node)
+ session.add(item)
+ await session.commit()
return ids
def _apply_filters_and_limit(
@@ -325,20 +323,19 @@ class PGVectorStore(BasePydanticVectorStore):
metadata_filters: Optional[MetadataFilters] = None,
) -> List[DBEmbeddingRow]:
stmt = self._build_query(embedding, limit, metadata_filters)
- with self._session() as session:
- with session.begin():
- res = session.execute(
- stmt,
+ with self._session() as session, session.begin():
+ res = session.execute(
+ stmt,
+ )
+ return [
+ DBEmbeddingRow(
+ node_id=item.node_id,
+ text=item.text,
+ metadata=item.metadata_,
+ similarity=(1 - distance) if distance is not None else 0,
)
- return [
- DBEmbeddingRow(
- node_id=item.node_id,
- text=item.text,
- metadata=item.metadata_,
- similarity=(1 - distance) if distance is not None else 0,
- )
- for item, distance in res.all()
- ]
+ for item, distance in res.all()
+ ]
async def _aquery_with_score(
self,
@@ -347,18 +344,17 @@ class PGVectorStore(BasePydanticVectorStore):
metadata_filters: Optional[MetadataFilters] = None,
) -> List[DBEmbeddingRow]:
stmt = self._build_query(embedding, limit, metadata_filters)
- async with self._async_session() as async_session:
- async with async_session.begin():
- res = await async_session.execute(stmt)
- return [
- DBEmbeddingRow(
- node_id=item.node_id,
- text=item.text,
- metadata=item.metadata_,
- similarity=(1 - distance) if distance is not None else 0,
- )
- for item, distance in res.all()
- ]
+ async with self._async_session() as async_session, async_session.begin():
+ res = await async_session.execute(stmt)
+ return [
+ DBEmbeddingRow(
+ node_id=item.node_id,
+ text=item.text,
+ metadata=item.metadata_,
+ similarity=(1 - distance) if distance is not None else 0,
+ )
+ for item, distance in res.all()
+ ]
def _build_sparse_query(
self,
@@ -392,18 +388,17 @@ class PGVectorStore(BasePydanticVectorStore):
metadata_filters: Optional[MetadataFilters] = None,
) -> List[DBEmbeddingRow]:
stmt = self._build_sparse_query(query_str, limit, metadata_filters)
- async with self._async_session() as async_session:
- async with async_session.begin():
- res = await async_session.execute(stmt)
- return [
- DBEmbeddingRow(
- node_id=item.node_id,
- text=item.text,
- metadata=item.metadata_,
- similarity=rank,
- )
- for item, rank in res.all()
- ]
+ async with self._async_session() as async_session, async_session.begin():
+ res = await async_session.execute(stmt)
+ return [
+ DBEmbeddingRow(
+ node_id=item.node_id,
+ text=item.text,
+ metadata=item.metadata_,
+ similarity=rank,
+ )
+ for item, rank in res.all()
+ ]
def _sparse_query_with_rank(
self,
@@ -412,18 +407,17 @@ class PGVectorStore(BasePydanticVectorStore):
metadata_filters: Optional[MetadataFilters] = None,
) -> List[DBEmbeddingRow]:
stmt = self._build_sparse_query(query_str, limit, metadata_filters)
- with self._session() as session:
- with session.begin():
- res = session.execute(stmt)
- return [
- DBEmbeddingRow(
- node_id=item.node_id,
- text=item.text,
- metadata=item.metadata_,
- similarity=rank,
- )
- for item, rank in res.all()
- ]
+ with self._session() as session, session.begin():
+ res = session.execute(stmt)
+ return [
+ DBEmbeddingRow(
+ node_id=item.node_id,
+ text=item.text,
+ metadata=item.metadata_,
+ similarity=rank,
+ )
+ for item, rank in res.all()
+ ]
async def _async_hybrid_query(
self, query: VectorStoreQuery
@@ -540,15 +534,14 @@ class PGVectorStore(BasePydanticVectorStore):
import sqlalchemy
self._initialize()
- with self._session() as session:
- with session.begin():
- stmt = sqlalchemy.text(
- f"DELETE FROM public.data_{self.table_name} where "
- f"(metadata_->>'doc_id')::text = '{ref_doc_id}' "
- )
+ with self._session() as session, session.begin():
+ stmt = sqlalchemy.text(
+ f"DELETE FROM public.data_{self.table_name} where "
+ f"(metadata_->>'doc_id')::text = '{ref_doc_id}' "
+ )
- session.execute(stmt)
- session.commit()
+ session.execute(stmt)
+ session.commit()
def _dedup_results(results: List[DBEmbeddingRow]) -> List[DBEmbeddingRow]:
diff --git a/llama_index/vector_stores/redis.py b/llama_index/vector_stores/redis.py
index 0833546140..ff1c9774de 100644
--- a/llama_index/vector_stores/redis.py
+++ b/llama_index/vector_stores/redis.py
@@ -124,7 +124,7 @@ class RedisVectorStore(VectorStore):
@property
def client(self) -> "RedisType":
- """Return the redis client instance"""
+ """Return the redis client instance."""
return self._redis_client
def add(self, nodes: List[BaseNode]) -> List[str]:
diff --git a/llama_index/vector_stores/rocksetdb.py b/llama_index/vector_stores/rocksetdb.py
index 5b715ba773..0c3c1e596e 100644
--- a/llama_index/vector_stores/rocksetdb.py
+++ b/llama_index/vector_stores/rocksetdb.py
@@ -24,7 +24,7 @@ T = TypeVar("T", bound="RocksetVectorStore")
def _get_rockset() -> ModuleType:
"""Gets the rockset module and raises an ImportError if
- the rockset package hasn't been installed
+ the rockset package hasn't been installed.
Returns:
rockset module (ModuleType)
@@ -124,7 +124,7 @@ class RocksetVectorStore(VectorStore):
return self.rs
def add(self, nodes: List[BaseNode]) -> List[str]:
- """Stores vectors in the collection
+ """Stores vectors in the collection.
Args:
nodes (List[BaseNode]): List of nodes with embeddings
@@ -151,7 +151,7 @@ class RocksetVectorStore(VectorStore):
]
def delete(self, ref_doc_id: str, **delete_kwargs: Any) -> None:
- """Deletes nodes stored in the collection by their ref_doc_id
+ """Deletes nodes stored in the collection by their ref_doc_id.
Args:
ref_doc_id (str): The ref_doc_id of the document
@@ -177,7 +177,7 @@ class RocksetVectorStore(VectorStore):
)
def query(self, query: VectorStoreQuery, **kwargs: Any) -> VectorStoreQueryResult:
- """Gets nodes relevant to a query
+ """Gets nodes relevant to a query.
Args:
query (llama_index.vector_stores.types.VectorStoreQuery): The query
diff --git a/llama_index/vector_stores/tair.py b/llama_index/vector_stores/tair.py
index e611be1cac..7eb1501253 100644
--- a/llama_index/vector_stores/tair.py
+++ b/llama_index/vector_stores/tair.py
@@ -122,7 +122,7 @@ class TairVectorStore(VectorStore):
@property
def client(self) -> "Tair":
- """Return the Tair client instance"""
+ """Return the Tair client instance."""
return self._tair_client
def add(self, nodes: List[BaseNode]) -> List[str]:
diff --git a/llama_index/vector_stores/timescalevector.py b/llama_index/vector_stores/timescalevector.py
index bb67bda141..ec90fdfc5f 100644
--- a/llama_index/vector_stores/timescalevector.py
+++ b/llama_index/vector_stores/timescalevector.py
@@ -15,7 +15,7 @@ from llama_index.vector_stores.utils import metadata_dict_to_node, node_to_metad
class IndexType(enum.Enum):
- """Enumerator for the supported Index types"""
+ """Enumerator for the supported Index types."""
TIMESCALE_VECTOR = 1
PGVECTOR_IVFFLAT = 2
diff --git a/pyproject.toml b/pyproject.toml
index a02d1e4f79..95eb022344 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -18,7 +18,9 @@ exclude = [
"notebooks",
]
ignore = [
- "COM812",
+ "COM812", # Too aggressive
+ "D212", # Using D213
+ "D417", # Too aggressive
"F541", # Messes with prompts.py
"TCH002",
"UP006", # Messes with pydantic
@@ -31,22 +33,7 @@ select = [
"B011",
"B013",
"B014",
- "C400",
- "C401",
- "C402",
- "C403",
- "C404",
- "C405",
- "C406",
- "C408",
- "C409",
- "C410",
- "C411",
- "C413",
- "C414",
- "C416",
- "C418",
- "C419",
+ "C4",
"COM812",
"COM819",
"D201",
@@ -60,23 +47,9 @@ select = [
"D213",
"D214",
"D215",
- "D400",
- "D403",
- "D405",
- "D406",
- "D407",
- "D408",
- "D409",
- "D410",
- "D411",
- "D412",
- "D413",
- "D416",
- "E703",
- "E711",
- "E712",
- "E713",
- "E714",
+ "D3",
+ "D4",
+ "E7",
"EXE004",
"F504",
"F541",
@@ -102,18 +75,7 @@ select = [
"PT006",
"PT02",
"PTH201",
- "PYI009",
- "PYI010",
- "PYI011",
- "PYI012",
- "PYI014",
- "PYI015",
- "PYI020",
- "PYI026",
- "PYI029",
- "PYI032",
- "PYI053",
- "PYI054",
+ "PYI",
"Q",
"RET501",
"RET502",
@@ -128,15 +90,7 @@ select = [
"SIM103",
"SIM109",
"SIM118",
- "SIM201",
- "SIM202",
- "SIM208",
- "SIM211",
- "SIM212",
- "SIM220",
- "SIM221",
- "SIM222",
- "SIM223",
+ "SIM2",
"SIM300",
"SIM9",
"TCH005",
diff --git a/tests/conftest.py b/tests/conftest.py
index 54f5d47b95..cc6dac336c 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -122,7 +122,7 @@ class CachedOpenAIApiKeys:
openai.api_key = "sk-" + "a" * 48
# No matter what, set the environment variable back to what it was
- def __exit__(self, *exc: Any) -> None:
+ def __exit__(self, *exc: object) -> None:
os.environ["OPENAI_API_KEY"] = str(self.api_env_variable_was)
os.environ["OPENAI_API_TYPE"] = str(self.api_env_type_was)
openai.api_key = self.openai_api_key_was
diff --git a/tests/indices/postprocessor/test_base.py b/tests/indices/postprocessor/test_base.py
index 2d64821c00..955002fb51 100644
--- a/tests/indices/postprocessor/test_base.py
+++ b/tests/indices/postprocessor/test_base.py
@@ -25,7 +25,7 @@ from llama_index.schema import (
)
from llama_index.storage.docstore.simple_docstore import SimpleDocumentStore
-spacy_installed = True if find_spec("spacy") else False
+spacy_installed = bool(find_spec("spacy"))
def test_forward_back_processor(tmp_path: Path) -> None:
diff --git a/tests/indices/query/test_embedding_utils.py b/tests/indices/query/test_embedding_utils.py
index 2dbb83e8de..646650d6f6 100644
--- a/tests/indices/query/test_embedding_utils.py
+++ b/tests/indices/query/test_embedding_utils.py
@@ -1,4 +1,4 @@
-""" Test embedding utility functions"""
+""" Test embedding utility functions."""
import numpy as np
from llama_index.indices.query.embedding_utils import (
@@ -8,7 +8,7 @@ from llama_index.indices.query.embedding_utils import (
def test_get_top_k_mmr_embeddings() -> None:
- """Test Maximum Marginal Relevance"""
+ """Test Maximum Marginal Relevance."""
# Results score should follow from the mmr algorithm
query_embedding = [5.0, 0.0, 0.0]
embeddings = [[4.0, 3.0, 0.0], [3.0, 4.0, 0.0], [-4.0, 3.0, 0.0]]
diff --git a/tests/indices/tree/test_index.py b/tests/indices/tree/test_index.py
index 9cb651ba2d..629ca8d8d1 100644
--- a/tests/indices/tree/test_index.py
+++ b/tests/indices/tree/test_index.py
@@ -197,7 +197,7 @@ def test_insert(
def test_twice_insert_empty(
mock_service_context: ServiceContext,
) -> None:
- """# test twice insert from empty (with_id)"""
+ """# test twice insert from empty (with_id)."""
tree = TreeIndex.from_documents([], service_context=mock_service_context)
# test first insert
diff --git a/tests/llm_predictor/vellum/test_predictor.py b/tests/llm_predictor/vellum/test_predictor.py
index cdf5f16ecd..938111fa1b 100644
--- a/tests/llm_predictor/vellum/test_predictor.py
+++ b/tests/llm_predictor/vellum/test_predictor.py
@@ -11,7 +11,7 @@ def test_predict__basic(
vellum_predictor_factory: Callable[..., VellumPredictor],
dummy_prompt: BasePromptTemplate,
) -> None:
- """When the Vellum API returns expected values, so should our predictor"""
+ """When the Vellum API returns expected values, so should our predictor."""
vellum_client = mock_vellum_client_factory(
compiled_prompt_text="What's you're favorite greeting?",
completion_text="Hello, world!",
@@ -29,7 +29,7 @@ def test_stream__basic(
vellum_predictor_factory: Callable[..., VellumPredictor],
dummy_prompt: BasePromptTemplate,
) -> None:
- """When the Vellum API streams expected values, so should our predictor"""
+ """When the Vellum API streams expected values, so should our predictor."""
import vellum
vellum_client = mock_vellum_client_factory(
diff --git a/tests/llm_predictor/vellum/test_prompt_registry.py b/tests/llm_predictor/vellum/test_prompt_registry.py
index 0e845bb4c2..0e3146425f 100644
--- a/tests/llm_predictor/vellum/test_prompt_registry.py
+++ b/tests/llm_predictor/vellum/test_prompt_registry.py
@@ -13,7 +13,7 @@ def test_from_prompt__new(
mock_vellum_client_factory: Callable[..., mock.MagicMock],
vellum_prompt_registry_factory: Callable[..., VellumPromptRegistry],
) -> None:
- """We should register a new prompt if no deployment exists"""
+ """We should register a new prompt if no deployment exists."""
from vellum.core import ApiError
dummy_prompt = PromptTemplate(template="What's your favorite {thing}?")
@@ -32,7 +32,7 @@ def test_from_prompt__existing(
mock_vellum_client_factory: Callable[..., mock.MagicMock],
vellum_prompt_registry_factory: Callable[..., VellumPromptRegistry],
) -> None:
- """We shouldn't register a new prompt if a deployment id or name is provided"""
+ """We shouldn't register a new prompt if a deployment id or name is provided."""
dummy_prompt = PromptTemplate(
template="What's your favorite {thing}?",
metadata={"vellum_deployment_id": "abc"},
@@ -54,7 +54,7 @@ def test_get_compiled_prompt__basic(
mock_vellum_client_factory: Callable[..., mock.MagicMock],
vellum_prompt_registry_factory: Callable[..., VellumPromptRegistry],
) -> None:
- """Verify that we can get a compiled prompt from the registry"""
+ """Verify that we can get a compiled prompt from the registry."""
registered_prompt = VellumRegisteredPrompt(
deployment_id="abc",
deployment_name="my-deployment",
diff --git a/tests/llms/test_localai.py b/tests/llms/test_localai.py
index a468ad65a4..5dafe59b49 100644
--- a/tests/llms/test_localai.py
+++ b/tests/llms/test_localai.py
@@ -77,9 +77,8 @@ def test_forgetting_kwarg() -> None:
with patch(
"llama_index.llms.openai.completion_with_retry", return_value={}
- ) as mock_completion:
- with pytest.raises(NotImplementedError, match="/chat/completions"):
- llm.complete("A long time ago in a galaxy far, far away")
+ ) as mock_completion, pytest.raises(NotImplementedError, match="/chat/completions"):
+ llm.complete("A long time ago in a galaxy far, far away")
mock_completion.assert_not_called()
diff --git a/tests/llms/test_openai_utils.py b/tests/llms/test_openai_utils.py
index 0a9d1f8844..b61491efb7 100644
--- a/tests/llms/test_openai_utils.py
+++ b/tests/llms/test_openai_utils.py
@@ -57,7 +57,7 @@ def openi_message_dicts_with_function_calling() -> List[dict]:
def azure_openi_message_dicts_with_function_calling() -> List[dict]:
"""
Taken from:
- - https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/function-calling
+ - https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/function-calling.
"""
return [
{
diff --git a/tests/memory/test_chat_memory_buffer.py b/tests/memory/test_chat_memory_buffer.py
index c263984268..7b116880d5 100644
--- a/tests/memory/test_chat_memory_buffer.py
+++ b/tests/memory/test_chat_memory_buffer.py
@@ -69,7 +69,7 @@ def test_dict_save_load() -> None:
def test_pickle() -> None:
- """Unpickleable tiktoken tokenizer should be circumvented when pickling"""
+ """Unpickleable tiktoken tokenizer should be circumvented when pickling."""
memory = ChatMemoryBuffer.from_defaults()
bytes_ = pickle.dumps(memory)
assert isinstance(pickle.loads(bytes_), ChatMemoryBuffer)
diff --git a/tests/readers/test_file.py b/tests/readers/test_file.py
index 27b12b9afe..4d1bee1d01 100644
--- a/tests/readers/test_file.py
+++ b/tests/readers/test_file.py
@@ -343,6 +343,5 @@ def test_error_if_not_dir_or_file() -> None:
SimpleDirectoryReader("not_a_dir")
with pytest.raises(ValueError, match="File"):
SimpleDirectoryReader(input_files=["not_a_file"])
- with TemporaryDirectory() as tmp_dir:
- with pytest.raises(ValueError, match="No files"):
- SimpleDirectoryReader(tmp_dir)
+ with TemporaryDirectory() as tmp_dir, pytest.raises(ValueError, match="No files"):
+ SimpleDirectoryReader(tmp_dir)
diff --git a/tests/text_splitter/test_code_splitter.py b/tests/text_splitter/test_code_splitter.py
index 075469c56a..e0580d9a39 100644
--- a/tests/text_splitter/test_code_splitter.py
+++ b/tests/text_splitter/test_code_splitter.py
@@ -5,7 +5,7 @@ from llama_index.text_splitter import CodeSplitter
def test_python_code_splitter() -> None:
- """Test case for code splitting using python"""
+ """Test case for code splitting using python."""
if "CI" in os.environ:
return
@@ -26,7 +26,7 @@ def baz():
def test_typescript_code_splitter() -> None:
- """Test case for code splitting using typescript"""
+ """Test case for code splitting using typescript."""
if "CI" in os.environ:
return
@@ -49,7 +49,7 @@ function baz() {
def test_html_code_splitter() -> None:
- """Test case for code splitting using typescript"""
+ """Test case for code splitting using typescript."""
if "CI" in os.environ:
return
@@ -82,7 +82,7 @@ def test_html_code_splitter() -> None:
def test_tsx_code_splitter() -> None:
- """Test case for code splitting using typescript"""
+ """Test case for code splitting using typescript."""
if "CI" in os.environ:
return
@@ -120,7 +120,7 @@ export default ExampleComponent;"""
def test_cpp_code_splitter() -> None:
- """Test case for code splitting using typescript"""
+ """Test case for code splitting using typescript."""
if "CI" in os.environ:
return
diff --git a/tests/text_splitter/test_sentence_splitter.py b/tests/text_splitter/test_sentence_splitter.py
index 82b1df214d..928dcb30ab 100644
--- a/tests/text_splitter/test_sentence_splitter.py
+++ b/tests/text_splitter/test_sentence_splitter.py
@@ -58,7 +58,7 @@ def test_split_with_metadata(english_text: str) -> None:
def test_edge_case() -> None:
- """Test case from: https://github.com/jerryjliu/llama_index/issues/7287"""
+ """Test case from: https://github.com/jerryjliu/llama_index/issues/7287."""
text = "\n\nMarch 2020\n\nL&D Metric (Org) - 2.92%\n\n| Training Name | Category | Duration (hrs) | Invitees | Attendance | Target Training Hours | Actual Training Hours | Adoption % |\n| ---------------------------------------------------------------------------------------------------------------------- | --------------- | -------------- | -------- | ---------- | --------------------- | --------------------- | ---------- |\n| Overview of Data Analytics | Technical | 1 | 23 | 10 | 23 | 10 | 43.5 |\n| Sales & Learning Best Practices - Introduction to OTT Platforms | Technical | 0.5 | 16 | 12 | 8 | 6 | 75 |\n| Leading Through OKRs | Lifeskill | 1 | 1 | 1 | 1 | 1 | 100 |\n| COVID: Lockdown Awareness Session | Lifeskill | 2 | 1 | 1 | 2 | 2 | 100 |\n| Navgati Interview | Lifeskill | 2 | 6 | 6 | 12 | 12 | 100 |\n| leadership Summit | Leadership | 18 | 42 | 42 | 756 | 756 | 100 |\n| AWS - AI/ML - Online Conference | Project Related | 15 | 2 | 2 | 30 | 30 | 100 |\n"
splitter = SentenceSplitter(tokenizer=tiktoken.get_encoding("gpt2").encode)
chunks = splitter.split_text(text)
@@ -109,7 +109,7 @@ def test_split_texts_multiple() -> None:
def test_split_texts_with_metadata(english_text: str) -> None:
- """Test case for a list of texts with metadata"""
+ """Test case for a list of texts with metadata."""
chunk_size = 100
metadata_str = "word " * 50
tokenizer = tiktoken.get_encoding("cl100k_base")
diff --git a/tests/tools/test_utils.py b/tests/tools/test_utils.py
index 6f5cc1ae36..f727d8400b 100644
--- a/tests/tools/test_utils.py
+++ b/tests/tools/test_utils.py
@@ -23,7 +23,7 @@ def test_create_schema_from_function() -> None:
assert schema["properties"]["a"]["type"] == "boolean"
def test_fn2(x: int = 1) -> None:
- """Optional input"""
+ """Optional input."""
SchemaCls = create_schema_from_function("test_schema", test_fn2)
schema = SchemaCls.schema()
--
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