add traverse all dict interface

This commit is contained in:
yichuan520030910320
2025-07-10 15:59:16 -07:00
parent 8a961f8ab3
commit 16ee9d0422
4 changed files with 438 additions and 106 deletions

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@@ -0,0 +1,130 @@
import os
import email
from pathlib import Path
from typing import List, Any
from llama_index.core import Document
from llama_index.core.readers.base import BaseReader
class EmlxReader(BaseReader):
"""
Apple Mail .emlx file reader with embedded 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]:
"""
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)
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:
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)
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')
# Extract email body
body = ""
if msg.is_multipart():
for part in msg.walk():
if part.get_content_type() == "text/plain" or part.get_content_type() == "text/html":
# if part.get_content_type() == "text/html":
# continue
body += part.get_payload(decode=True).decode('utf-8', errors='ignore')
# break
else:
body = msg.get_payload(decode=True).decode('utf-8', errors='ignore')
# Create document content with metadata embedded in text
doc_content = f"""
[EMAIL METADATA]
File: {filename}
From: {from_addr}
To: {to_addr}
Subject: {subject}
Date: {date}
[END METADATA]
{body}
"""
# No separate metadata - everything is in the text
doc = Document(text=doc_content, 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
@staticmethod
def find_all_messages_directories(base_path: str) -> List[Path]:
"""
Find all Messages directories under the given base path.
Args:
base_path: Base path to search for Messages directories
Returns:
List of Path objects pointing to Messages directories
"""
base_path_obj = Path(base_path)
messages_dirs = []
if not base_path_obj.exists():
print(f"Base path {base_path} does not exist")
return messages_dirs
# Find all Messages directories recursively
for messages_dir in base_path_obj.rglob("Messages"):
if messages_dir.is_dir():
messages_dirs.append(messages_dir)
print(f"Found Messages directory: {messages_dir}")
print(f"Found {len(messages_dirs)} Messages directories")
return messages_dirs

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@@ -0,0 +1,192 @@
"""
Mbox parser.
Contains simple parser for mbox files.
"""
import logging
from pathlib import Path
from typing import Any, Dict, List, Optional
from fsspec import AbstractFileSystem
from llama_index.core.readers.base import BaseReader
from llama_index.core.schema import Document
logger = logging.getLogger(__name__)
class MboxReader(BaseReader):
"""
Mbox parser.
Extract messages from mailbox files.
Returns string including date, subject, sender, receiver and
content for each message.
"""
DEFAULT_MESSAGE_FORMAT: str = (
"Date: {_date}\n"
"From: {_from}\n"
"To: {_to}\n"
"Subject: {_subject}\n"
"Content: {_content}"
)
def __init__(
self,
*args: Any,
max_count: int = 0,
message_format: str = DEFAULT_MESSAGE_FORMAT,
**kwargs: Any,
) -> None:
"""Init params."""
try:
from bs4 import BeautifulSoup # noqa
except ImportError:
raise ImportError(
"`beautifulsoup4` package not found: `pip install beautifulsoup4`"
)
super().__init__(*args, **kwargs)
self.max_count = max_count
self.message_format = message_format
def load_data(
self,
file: Path,
extra_info: Optional[Dict] = None,
fs: Optional[AbstractFileSystem] = None,
) -> List[Document]:
"""Parse file into string."""
# Import required libraries
import mailbox
from email.parser import BytesParser
from email.policy import default
from bs4 import BeautifulSoup
if fs:
logger.warning(
"fs was specified but MboxReader doesn't support loading "
"from fsspec filesystems. Will load from local filesystem instead."
)
i = 0
results: List[str] = []
# Load file using mailbox
bytes_parser = BytesParser(policy=default).parse
mbox = mailbox.mbox(file, factory=bytes_parser) # type: ignore
# Iterate through all messages
for _, _msg in enumerate(mbox):
try:
msg: mailbox.mboxMessage = _msg
# Parse multipart messages
if msg.is_multipart():
for part in msg.walk():
ctype = part.get_content_type()
cdispo = str(part.get("Content-Disposition"))
if "attachment" in cdispo:
print(f"Attachment found: {part.get_filename()}")
if ctype == "text/plain" and "attachment" not in cdispo:
content = part.get_payload(decode=True) # decode
break
# Get plain message payload for non-multipart messages
else:
content = msg.get_payload(decode=True)
# Parse message HTML content and remove unneeded whitespace
soup = BeautifulSoup(content)
stripped_content = " ".join(soup.get_text().split())
# Format message to include date, sender, receiver and subject
msg_string = self.message_format.format(
_date=msg["date"],
_from=msg["from"],
_to=msg["to"],
_subject=msg["subject"],
_content=stripped_content,
)
# Add message string to results
results.append(msg_string)
except Exception as e:
logger.warning(f"Failed to parse message:\n{_msg}\n with exception {e}")
# Increment counter and return if max count is met
i += 1
if self.max_count > 0 and i >= self.max_count:
break
return [Document(text=result, metadata=extra_info or {}) for result in results]
class EmlxMboxReader(MboxReader):
"""
EmlxMboxReader - Modified MboxReader that handles directories of .emlx files.
Extends MboxReader to work with Apple Mail's .emlx format by:
1. Reading .emlx files from a directory
2. Converting them to mbox format in memory
3. Using the parent MboxReader's parsing logic
"""
def load_data(
self,
directory: Path,
extra_info: Optional[Dict] = None,
fs: Optional[AbstractFileSystem] = None,
) -> List[Document]:
"""Parse .emlx files from directory into strings using MboxReader logic."""
import tempfile
import os
if fs:
logger.warning(
"fs was specified but EmlxMboxReader doesn't support loading "
"from fsspec filesystems. Will load from local filesystem instead."
)
# Find all .emlx files in the directory
emlx_files = list(directory.glob("*.emlx"))
logger.info(f"Found {len(emlx_files)} .emlx files in {directory}")
if not emlx_files:
logger.warning(f"No .emlx files found in {directory}")
return []
# Create a temporary mbox file
with tempfile.NamedTemporaryFile(mode='w', suffix='.mbox', delete=False) as temp_mbox:
temp_mbox_path = temp_mbox.name
# Convert .emlx files to mbox format
for emlx_file in emlx_files:
try:
# Read the .emlx file
with open(emlx_file, 'r', encoding='utf-8', errors='ignore') as f:
content = f.read()
# .emlx format: first line is length, rest is email content
lines = content.split('\n', 1)
if len(lines) >= 2:
email_content = lines[1] # Skip the length line
# Write to mbox format (each message starts with "From " and ends with blank line)
temp_mbox.write(f"From {emlx_file.name} {email_content}\n\n")
except Exception as e:
logger.warning(f"Failed to process {emlx_file}: {e}")
continue
# Close the temporary file so MboxReader can read it
temp_mbox.close()
try:
# Use the parent MboxReader's logic to parse the mbox file
return super().load_data(Path(temp_mbox_path), extra_info, fs)
finally:
# Clean up temporary file
try:
os.unlink(temp_mbox_path)
except:
pass

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@@ -4,11 +4,104 @@ import dotenv
from pathlib import Path from pathlib import Path
from typing import List, Any from typing import List, Any
from leann.api import LeannBuilder, LeannSearcher, LeannChat from leann.api import LeannBuilder, LeannSearcher, LeannChat
from mail_reader_llamaindex import EmlxReader
from llama_index.core.node_parser import SentenceSplitter from llama_index.core.node_parser import SentenceSplitter
dotenv.load_dotenv() dotenv.load_dotenv()
def create_leann_index_from_multiple_sources(messages_dirs: List[Path], index_path: str = "mail_index.leann", max_count: int = -1):
"""
Create LEANN index from multiple mail data sources.
Args:
messages_dirs: List of Path objects pointing to Messages directories
index_path: Path to save the LEANN index
max_count: Maximum number of emails to process per directory
"""
print("Creating LEANN index from multiple mail data sources...")
# Load documents using EmlxReader from LEANN_email_reader
from LEANN_email_reader import EmlxReader
reader = EmlxReader()
# from email_data.email import EmlxMboxReader
# from pathlib import Path
# reader = EmlxMboxReader()
all_documents = []
total_processed = 0
# Process each Messages directory
for i, messages_dir in enumerate(messages_dirs):
print(f"\nProcessing Messages directory {i+1}/{len(messages_dirs)}: {messages_dir}")
try:
documents = reader.load_data(messages_dir)
if documents:
print(f"Loaded {len(documents)} email documents from {messages_dir}")
all_documents.extend(documents)
total_processed += len(documents)
# Check if we've reached the max count
if max_count > 0 and total_processed >= max_count:
print(f"Reached max count of {max_count} documents")
break
else:
print(f"No documents loaded from {messages_dir}")
except Exception as e:
print(f"Error processing {messages_dir}: {e}")
continue
if not all_documents:
print("No documents loaded from any source. Exiting.")
return None
print(f"\nTotal loaded {len(all_documents)} email documents from {len(messages_dirs)} directories")
# Create text splitter with 256 chunk size
text_splitter = SentenceSplitter(chunk_size=256, chunk_overlap=25)
# Convert Documents to text strings and chunk them
all_texts = []
for doc in all_documents:
# Split the document into chunks
nodes = text_splitter.get_nodes_from_documents([doc])
for node in nodes:
all_texts.append(node.get_content())
print(f"Created {len(all_texts)} text chunks from {len(all_documents)} documents")
# Create LEANN index directory
INDEX_DIR = Path(index_path).parent
if not INDEX_DIR.exists():
print(f"--- Index directory not found, building new index ---")
INDEX_DIR.mkdir(exist_ok=True)
print(f"--- Building new LEANN index ---")
print(f"\n[PHASE 1] Building Leann index...")
# Use HNSW backend for better macOS compatibility
builder = LeannBuilder(
backend_name="hnsw",
embedding_model="facebook/contriever",
graph_degree=32,
complexity=64,
is_compact=True,
is_recompute=True,
num_threads=1 # Force single-threaded mode
)
print(f"Adding {len(all_texts)} email chunks to index...")
for chunk_text in all_texts:
builder.add_text(chunk_text)
builder.build_index(index_path)
print(f"\nLEANN index built at {index_path}!")
else:
print(f"--- Using existing index at {INDEX_DIR} ---")
return index_path
def create_leann_index(mail_path: str, index_path: str = "mail_index.leann", max_count: int = 1000): def create_leann_index(mail_path: str, index_path: str = "mail_index.leann", max_count: int = 1000):
""" """
Create LEANN index from mail data. Create LEANN index from mail data.
@@ -20,9 +113,13 @@ def create_leann_index(mail_path: str, index_path: str = "mail_index.leann", max
""" """
print("Creating LEANN index from mail data...") print("Creating LEANN index from mail data...")
# Load documents using EmlxReader from mail_reader_llamaindex # Load documents using EmlxReader from LEANN_email_reader
from LEANN_email_reader import EmlxReader
reader = EmlxReader() reader = EmlxReader()
documents = reader.load_data(mail_path, max_count=max_count) # from email_data.email import EmlxMboxReader
# from pathlib import Path
# reader = EmlxMboxReader()
documents = reader.load_data(Path(mail_path))
if not documents: if not documents:
print("No documents loaded. Exiting.") print("No documents loaded. Exiting.")
@@ -98,13 +195,22 @@ async def query_leann_index(index_path: str, query: str):
print(f"Leann: {chat_response}") print(f"Leann: {chat_response}")
async def main(): async 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" # Base path to the mail data directory
base_mail_path = "/Users/yichuan/Library/Mail/V10/0FCA0879-FD8C-4B7E-83BF-FDDA930791C5/[Gmail].mbox/All Mail.mbox/78BA5BE1-8819-4F9A-9613-EB63772F1DD0/Data"
INDEX_DIR = Path("./mail_index_leann_raw_text") INDEX_DIR = Path("./mail_index_leann_raw_text_all")
INDEX_PATH = str(INDEX_DIR / "mail_documents.leann") INDEX_PATH = str(INDEX_DIR / "mail_documents.leann")
# Create or load the LEANN index # Find all Messages directories
index_path = create_leann_index(mail_path, INDEX_PATH, max_count=1000) from LEANN_email_reader import EmlxReader
messages_dirs = EmlxReader.find_all_messages_directories(base_mail_path)
if not messages_dirs:
print("No Messages directories found. Exiting.")
return
# Create or load the LEANN index from all sources
index_path = create_leann_index_from_multiple_sources(messages_dirs, INDEX_PATH)
if index_path: if index_path:
# Example queries # Example queries

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@@ -1,9 +1,7 @@
import os import os
import email
from pathlib import Path from pathlib import Path
from typing import List, Any from typing import List, Any
from llama_index.core import VectorStoreIndex, Document, StorageContext from llama_index.core import VectorStoreIndex, StorageContext
from llama_index.core.readers.base import BaseReader
from llama_index.core.node_parser import SentenceSplitter from llama_index.core.node_parser import SentenceSplitter
# --- EMBEDDING MODEL --- # --- EMBEDDING MODEL ---
@@ -12,102 +10,8 @@ import torch
# --- END EMBEDDING MODEL --- # --- END EMBEDDING MODEL ---
class EmlxReader(BaseReader): # Import EmlxReader from the new module
""" from LEANN_email_reader import EmlxReader
Apple Mail .emlx file reader with embedded 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]:
"""
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)
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:
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)
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')
# Extract email body
body = ""
if msg.is_multipart():
for part in msg.walk():
if part.get_content_type() == "text/plain" or part.get_content_type() == "text/html":
if part.get_content_type() == "text/html":
continue
body += part.get_payload(decode=True).decode('utf-8', errors='ignore')
# break
else:
body = msg.get_payload(decode=True).decode('utf-8', errors='ignore')
# Create document content with metadata embedded in text
doc_content = f"""
[EMAIL METADATA]
File: {filename}
From: {from_addr}
To: {to_addr}
Subject: {subject}
Date: {date}
[END METADATA]
{body}
"""
# No separate metadata - everything is in the text
doc = Document(text=doc_content, 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_embedded", max_count: int = 1000): def create_and_save_index(mail_path: str, save_dir: str = "mail_index_embedded", max_count: int = 1000):
print("Creating index from mail data with embedded metadata...") print("Creating index from mail data with embedded metadata...")