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fix: resolve all ruff linting errors and add lint CI check

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- Fix ambiguous fullwidth characters (commas, parentheses) in strings and comments
- Replace Chinese comments with English equivalents
- Fix unused imports with proper noqa annotations for intentional imports
- Fix bare except clauses with specific exception types
- Fix redefined variables and undefined names
- Add ruff noqa annotations for generated protobuf files
- Add lint and format check to GitHub Actions CI pipeline
This commit is contained in:
Andy Lee
2025-07-26 22:35:12 -07:00
parent 8537a6b17e
commit b3e9ee96fa
53 changed files with 5655 additions and 5220 deletions
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136
test/mail_reader_small_chunks.py
View File

@@ -1,77 +1,82 @@
import os
import email
from pathlib import Path
from typing import List, Any
from llama_index.core import VectorStoreIndex, Document, StorageContext
from llama_index.core.readers.base import BaseReader
import os
from typing import Any
from llama_index.core import Document, StorageContext, VectorStoreIndex
from llama_index.core.node_parser import SentenceSplitter
from llama_index.core.readers.base import BaseReader
class EmlxReader(BaseReader):
"""
Apple Mail .emlx file reader with reduced metadata.
Reads individual .emlx files from Apple Mail's storage format.
"""
def __init__(self) -> None:
"""Initialize."""
pass
def load_data(self, input_dir: str, **load_kwargs: Any) -> List[Document]:
def load_data(self, input_dir: str, **load_kwargs: Any) -> list[Document]:
"""
Load data from the input directory containing .emlx files.
Args:
input_dir: Directory containing .emlx files
**load_kwargs:
max_count (int): Maximum amount of messages to read.
"""
docs: List[Document] = []
max_count = load_kwargs.get('max_count', 1000)
docs: list[Document] = []
max_count = load_kwargs.get("max_count", 1000)
count = 0
# Walk through the directory recursively
for dirpath, dirnames, filenames in os.walk(input_dir):
# Skip hidden directories
dirnames[:] = [d for d in dirnames if not d.startswith(".")]
for filename in filenames:
if count >= max_count:
break
if filename.endswith(".emlx"):
filepath = os.path.join(dirpath, filename)
try:
# Read the .emlx file
with open(filepath, 'r', encoding='utf-8', errors='ignore') as f:
with open(filepath, encoding="utf-8", errors="ignore") as f:
content = f.read()
# .emlx files have a length prefix followed by the email content
# The first line contains the length, followed by the email
lines = content.split('\n', 1)
lines = content.split("\n", 1)
if len(lines) >= 2:
email_content = lines[1]
# Parse the email using Python's email module
try:
msg = email.message_from_string(email_content)
# Extract email metadata
subject = msg.get('Subject', 'No Subject')
from_addr = msg.get('From', 'Unknown')
to_addr = msg.get('To', 'Unknown')
date = msg.get('Date', 'Unknown')
subject = msg.get("Subject", "No Subject")
from_addr = msg.get("From", "Unknown")
to_addr = msg.get("To", "Unknown")
date = msg.get("Date", "Unknown")
# Extract email body
body = ""
if msg.is_multipart():
for part in msg.walk():
if part.get_content_type() == "text/plain":
body = part.get_payload(decode=True).decode('utf-8', errors='ignore')
body = part.get_payload(decode=True).decode(
"utf-8", errors="ignore"
)
break
else:
body = msg.get_payload(decode=True).decode('utf-8', errors='ignore')
body = msg.get_payload(decode=True).decode(
"utf-8", errors="ignore"
)
# Create document content with metadata embedded in text
doc_content = f"""
From: {from_addr}
@@ -81,95 +86,96 @@ Date: {date}
{body}
"""
# Create minimal metadata (only essential info)
metadata = {
'subject': subject[:50], # Truncate subject
'from': from_addr[:30], # Truncate from
'date': date[:20], # Truncate date
'filename': filename # Keep filename
"subject": subject[:50], # Truncate subject
"from": from_addr[:30], # Truncate from
"date": date[:20], # Truncate date
"filename": filename, # Keep filename
}
doc = Document(text=doc_content, metadata=metadata)
docs.append(doc)
count += 1
except Exception as e:
print(f"Error parsing email from {filepath}: {e}")
continue
except Exception as e:
print(f"Error reading file {filepath}: {e}")
continue
print(f"Loaded {len(docs)} email documents")
return docs
def create_and_save_index(mail_path: str, save_dir: str = "mail_index_small", max_count: int = 1000):
def create_and_save_index(
mail_path: str, save_dir: str = "mail_index_small", max_count: int = 1000
):
"""
Create the index from mail data and save it to disk.
Args:
mail_path: Path to the mail directory
save_dir: Directory to save the index
max_count: Maximum number of emails to process
"""
print("Creating index from mail data with small chunks...")
# Load documents
documents = EmlxReader().load_data(mail_path, max_count=max_count)
if not documents:
print("No documents loaded. Exiting.")
return None
# Create text splitter with small chunk size
text_splitter = SentenceSplitter(chunk_size=512, chunk_overlap=50)
# Create index
index = VectorStoreIndex.from_documents(
documents,
transformations=[text_splitter]
)
index = VectorStoreIndex.from_documents(documents, transformations=[text_splitter])
# Save the index
os.makedirs(save_dir, exist_ok=True)
index.storage_context.persist(persist_dir=save_dir)
print(f"Index saved to {save_dir}")
return index
def load_index(save_dir: str = "mail_index_small"):
"""
Load the saved index from disk.
Args:
save_dir: Directory where the index is saved
Returns:
Loaded index or None if loading fails
"""
try:
# Load storage context
storage_context = StorageContext.from_defaults(persist_dir=save_dir)
# Load index
index = VectorStoreIndex.from_vector_store(
storage_context.vector_store,
storage_context=storage_context
storage_context.vector_store, storage_context=storage_context
)
print(f"Index loaded from {save_dir}")
return index
except Exception as e:
print(f"Error loading index: {e}")
return None
def query_index(index, query: str):
"""
Query the loaded index.
Args:
index: The loaded index
query: The query string
@@ -177,16 +183,17 @@ def query_index(index, query: str):
if index is None:
print("No index available for querying.")
return
query_engine = index.as_query_engine()
response = query_engine.query(query)
print(f"Query: {query}")
print(f"Response: {response}")
def main():
mail_path = "/Users/yichuan/Library/Mail/V10/0FCA0879-FD8C-4B7E-83BF-FDDA930791C5/[Gmail].mbox/All Mail.mbox/78BA5BE1-8819-4F9A-9613-EB63772F1DD0/Data/9/Messages"
save_dir = "mail_index_small"
# Check if index already exists
if os.path.exists(save_dir) and os.path.exists(os.path.join(save_dir, "vector_store.json")):
print("Loading existing index...")
@@ -194,18 +201,19 @@ def main():
else:
print("Creating new index...")
index = create_and_save_index(mail_path, save_dir, max_count=1000)
if index:
# Example queries
queries = [
"Hows Berkeley Graduate Student Instructor",
"What emails mention GSR appointments?",
"Find emails about deadlines"
"Find emails about deadlines",
]
for query in queries:
print("\n" + "="*50)
print("\n" + "=" * 50)
query_index(index, query)
if __name__ == "__main__":
main()
main()