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import logging
import json
import os
from typing import List, Dict, Any, Optional
from pathlib import Path
import pickle
from datetime import datetime
import asyncio
from core.models import Document, DocumentType
import config
logger = logging.getLogger(__name__)
class DocumentStoreService:
def __init__(self):
self.config = config.config
self.store_path = Path(self.config.DOCUMENT_STORE_PATH)
self.store_path.mkdir(parents=True, exist_ok=True)
# Separate paths for metadata and content
self.metadata_path = self.store_path / "metadata"
self.content_path = self.store_path / "content"
self.metadata_path.mkdir(exist_ok=True)
self.content_path.mkdir(exist_ok=True)
# In-memory cache for frequently accessed documents
self._cache = {}
self._cache_size_limit = 100
async def store_document(self, document: Document) -> bool:
"""Store a document and its metadata"""
try:
# Store metadata
metadata_file = self.metadata_path / f"{document.id}.json"
metadata = {
"id": document.id,
"filename": document.filename,
"doc_type": document.doc_type.value,
"file_size": document.file_size,
"created_at": document.created_at.isoformat(),
"metadata": document.metadata,
"tags": document.tags,
"summary": document.summary,
"category": document.category,
"language": document.language,
"content_length": len(document.content)
}
with open(metadata_file, 'w', encoding='utf-8') as f:
json.dump(metadata, f, indent=2, ensure_ascii=False)
# Store content separately (can be large)
content_file = self.content_path / f"{document.id}.txt"
with open(content_file, 'w', encoding='utf-8') as f:
f.write(document.content)
# Cache the document
self._add_to_cache(document.id, document)
logger.info(f"Stored document {document.id} ({document.filename})")
return True
except Exception as e:
logger.error(f"Error storing document {document.id}: {str(e)}")
return False
async def get_document(self, document_id: str) -> Optional[Document]:
"""Retrieve a document by ID"""
try:
# Check cache first
if document_id in self._cache:
return self._cache[document_id]
# Load from disk
metadata_file = self.metadata_path / f"{document_id}.json"
content_file = self.content_path / f"{document_id}.txt"
if not metadata_file.exists() or not content_file.exists():
return None
# Load metadata
with open(metadata_file, 'r', encoding='utf-8') as f:
metadata = json.load(f)
# Load content
with open(content_file, 'r', encoding='utf-8') as f:
content = f.read()
# Create document object
document = Document(
id=metadata["id"],
filename=metadata["filename"],
content=content,
doc_type=DocumentType(metadata["doc_type"]),
file_size=metadata["file_size"],
created_at=datetime.fromisoformat(metadata["created_at"]),
metadata=metadata.get("metadata", {}),
tags=metadata.get("tags", []),
summary=metadata.get("summary"),
category=metadata.get("category"),
language=metadata.get("language")
)
# Add to cache
self._add_to_cache(document_id, document)
return document
except Exception as e:
logger.error(f"Error retrieving document {document_id}: {str(e)}")
return None
async def list_documents(self, limit: int = 50, offset: int = 0,
filters: Optional[Dict[str, Any]] = None) -> List[Document]:
"""List documents with pagination and filtering"""
try:
documents = []
metadata_files = list(self.metadata_path.glob("*.json"))
# Sort by creation time (newest first)
metadata_files.sort(key=lambda x: x.stat().st_mtime, reverse=True)
# Apply pagination
start_idx = offset
end_idx = offset + limit
for metadata_file in metadata_files[start_idx:end_idx]:
try:
with open(metadata_file, 'r', encoding='utf-8') as f:
metadata = json.load(f)
# Apply filters
if filters and not self._apply_filters(metadata, filters):
continue
# Load content if needed (for small documents)
content_file = self.content_path / f"{metadata['id']}.txt"
if content_file.exists():
with open(content_file, 'r', encoding='utf-8') as f:
content = f.read()
else:
content = ""
document = Document(
id=metadata["id"],
filename=metadata["filename"],
content=content,
doc_type=DocumentType(metadata["doc_type"]),
file_size=metadata["file_size"],
created_at=datetime.fromisoformat(metadata["created_at"]),
metadata=metadata.get("metadata", {}),
tags=metadata.get("tags", []),
summary=metadata.get("summary"),
category=metadata.get("category"),
language=metadata.get("language")
)
documents.append(document)
except Exception as e:
logger.warning(f"Error loading document metadata from {metadata_file}: {str(e)}")
continue
return documents
except Exception as e:
logger.error(f"Error listing documents: {str(e)}")
return []
def _apply_filters(self, metadata: Dict[str, Any], filters: Dict[str, Any]) -> bool:
"""Apply filters to document metadata"""
try:
for key, value in filters.items():
if key == "doc_type":
if metadata.get("doc_type") != value:
return False
elif key == "filename_contains":
if value.lower() not in metadata.get("filename", "").lower():
return False
elif key == "created_after":
doc_date = datetime.fromisoformat(metadata.get("created_at", ""))
if doc_date < value:
return False
elif key == "created_before":
doc_date = datetime.fromisoformat(metadata.get("created_at", ""))
if doc_date > value:
return False
elif key == "tags":
doc_tags = set(metadata.get("tags", []))
required_tags = set(value) if isinstance(value, list) else {value}
if not required_tags.intersection(doc_tags):
return False
elif key == "category":
if metadata.get("category") != value:
return False
elif key == "language":
if metadata.get("language") != value:
return False
return True
except Exception as e:
logger.error(f"Error applying filters: {str(e)}")
return True
async def update_document_metadata(self, document_id: str, updates: Dict[str, Any]) -> bool:
"""Update document metadata"""
try:
metadata_file = self.metadata_path / f"{document_id}.json"
if not metadata_file.exists():
logger.warning(f"Document {document_id} not found")
return False
# Load existing metadata
with open(metadata_file, 'r', encoding='utf-8') as f:
metadata = json.load(f)
# Apply updates
for key, value in updates.items():
if key in ["tags", "summary", "category", "language", "metadata"]:
metadata[key] = value
# Save updated metadata
with open(metadata_file, 'w', encoding='utf-8') as f:
json.dump(metadata, f, indent=2, ensure_ascii=False)
# Update cache if document is cached
if document_id in self._cache:
document = self._cache[document_id]
for key, value in updates.items():
if hasattr(document, key):
setattr(document, key, value)
logger.info(f"Updated metadata for document {document_id}")
return True
except Exception as e:
logger.error(f"Error updating document metadata: {str(e)}")
return False
async def delete_document(self, document_id: str) -> bool:
"""Delete a document and its metadata"""
try:
metadata_file = self.metadata_path / f"{document_id}.json"
content_file = self.content_path / f"{document_id}.txt"
# Remove files
if metadata_file.exists():
metadata_file.unlink()
if content_file.exists():
content_file.unlink()
# Remove from cache
if document_id in self._cache:
del self._cache[document_id]
logger.info(f"Deleted document {document_id}")
return True
except Exception as e:
logger.error(f"Error deleting document {document_id}: {str(e)}")
return False
async def search_documents(self, query: str, fields: List[str] = None) -> List[Document]:
"""Simple text search across documents"""
if not fields:
fields = ["filename", "content", "tags", "summary"]
try:
matching_documents = []
query_lower = query.lower()
# Get all documents
all_documents = await self.list_documents(limit=1000) # Adjust limit as needed
for document in all_documents:
match_found = False
for field in fields:
field_value = getattr(document, field, "")
if isinstance(field_value, list):
field_value = " ".join(field_value)
elif field_value is None:
field_value = ""
if query_lower in str(field_value).lower():
match_found = True
break
if match_found:
matching_documents.append(document)
logger.info(f"Found {len(matching_documents)} documents matching '{query}'")
return matching_documents
except Exception as e:
logger.error(f"Error searching documents: {str(e)}")
return []
def _add_to_cache(self, document_id: str, document: Document):
"""Add document to cache with size limit"""
try:
# Remove oldest items if cache is full
if len(self._cache) >= self._cache_size_limit:
# Remove first item (FIFO)
oldest_key = next(iter(self._cache))
del self._cache[oldest_key]
self._cache[document_id] = document
except Exception as e:
logger.error(f"Error adding to cache: {str(e)}")
async def get_stats(self) -> Dict[str, Any]:
"""Get statistics about the document store"""
try:
metadata_files = list(self.metadata_path.glob("*.json"))
content_files = list(self.content_path.glob("*.txt"))
# Calculate total storage size
total_size = 0
for file_path in metadata_files + content_files:
total_size += file_path.stat().st_size
# Count by document type
type_counts = {}
for metadata_file in metadata_files:
try:
with open(metadata_file, 'r') as f:
metadata = json.load(f)
doc_type = metadata.get("doc_type", "unknown")
type_counts[doc_type] = type_counts.get(doc_type, 0) + 1
except:
continue
return {
"total_documents": len(metadata_files),
"total_size_bytes": total_size,
"total_size_mb": round(total_size / (1024 * 1024), 2),
"cache_size": len(self._cache),
"document_types": type_counts,
"storage_path": str(self.store_path),
"metadata_files": len(metadata_files),
"content_files": len(content_files)
}
except Exception as e:
logger.error(f"Error getting document store stats: {str(e)}")
return {"error": str(e)} |