ddc789b231
- All examples now have --embedding-mode parameter (unified interface benefit) - Default is 'sentence-transformers' (consistent with original behavior) - Users can now use OpenAI or MLX embeddings with any data source - Maintains functional equivalence with original scripts
141 lines
4.5 KiB
Python
141 lines
4.5 KiB
Python
"""
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Email RAG example using the unified interface.
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Supports Apple Mail on macOS.
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"""
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import sys
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from pathlib import Path
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# Add parent directory to path for imports
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sys.path.insert(0, str(Path(__file__).parent))
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from base_rag_example import BaseRAGExample, create_text_chunks
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from email_data.LEANN_email_reader import EmlxReader
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class EmailRAG(BaseRAGExample):
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"""RAG example for Apple Mail processing."""
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def __init__(self):
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super().__init__(
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name="Email",
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description="Process and query Apple Mail emails with LEANN",
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default_index_name="mail_index",
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)
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def _add_specific_arguments(self, parser):
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"""Add email-specific arguments."""
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email_group = parser.add_argument_group("Email Parameters")
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email_group.add_argument(
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"--mail-path",
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type=str,
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default=None,
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help="Path to Apple Mail directory (auto-detected if not specified)",
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)
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email_group.add_argument(
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"--include-html", action="store_true", help="Include HTML content in email processing"
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)
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def _find_mail_directories(self) -> list[Path]:
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"""Auto-detect all Apple Mail directories."""
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mail_base = Path.home() / "Library" / "Mail"
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if not mail_base.exists():
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return []
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# Find all Messages directories
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messages_dirs = []
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for item in mail_base.rglob("Messages"):
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if item.is_dir():
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messages_dirs.append(item)
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return messages_dirs
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async def load_data(self, args) -> list[str]:
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"""Load emails and convert to text chunks."""
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# Determine mail directories
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if args.mail_path:
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messages_dirs = [Path(args.mail_path)]
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else:
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print("Auto-detecting Apple Mail directories...")
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messages_dirs = self._find_mail_directories()
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if not messages_dirs:
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print("No Apple Mail directories found!")
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print("Please specify --mail-path manually")
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return []
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print(f"Found {len(messages_dirs)} mail directories")
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# Create reader
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reader = EmlxReader()
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# Process each directory
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all_documents = []
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total_processed = 0
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for i, messages_dir in enumerate(messages_dirs):
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print(f"\nProcessing directory {i + 1}/{len(messages_dirs)}: {messages_dir}")
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try:
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# Count emlx files
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emlx_files = list(messages_dir.glob("*.emlx"))
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print(f"Found {len(emlx_files)} email files")
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# Apply max_items limit per directory
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max_per_dir = -1
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if args.max_items > 0:
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remaining = args.max_items - total_processed
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if remaining <= 0:
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break
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max_per_dir = remaining
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# Load emails
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documents = reader.load_data(
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file_path=str(messages_dir),
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max_count=max_per_dir,
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include_html=args.include_html,
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)
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if documents:
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all_documents.extend(documents)
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total_processed += len(documents)
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print(f"Processed {len(documents)} emails from this directory")
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except Exception as e:
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print(f"Error processing {messages_dir}: {e}")
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continue
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if not all_documents:
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print("No emails found to process!")
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return []
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print(f"\nTotal emails processed: {len(all_documents)}")
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# Convert to text chunks
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# Email reader uses chunk_overlap=25 as in original
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all_texts = create_text_chunks(all_documents, chunk_overlap=25)
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return all_texts
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if __name__ == "__main__":
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import asyncio
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# Check platform
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if sys.platform != "darwin":
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print("\n⚠️ Warning: This example is designed for macOS (Apple Mail)")
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print(" Windows/Linux support coming soon!\n")
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# Example queries for email RAG
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print("\n📧 Email RAG Example")
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print("=" * 50)
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print("\nExample queries you can try:")
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print("- 'What did my boss say about deadlines?'")
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print("- 'Find emails about travel expenses'")
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print("- 'Show me emails from last month about the project'")
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print("- 'What food did I order from DoorDash?'")
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print("\nNote: You may need to grant Full Disk Access to your terminal\n")
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rag = EmailRAG()
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asyncio.run(rag.run())
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