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146 lines
4.4 KiB
Python
146 lines
4.4 KiB
Python
"""High-level document storage operations."""
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import hashlib
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import json
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from io import BytesIO
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from typing import Any
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import structlog
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from .client import StorageClient
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logger = structlog.get_logger()
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class DocumentStorage:
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"""High-level document storage operations"""
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def __init__(self, storage_client: StorageClient):
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self.storage = storage_client
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async def store_document( # pylint: disable=too-many-arguments,too-many-positional-arguments
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self,
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tenant_id: str,
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doc_id: str,
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content: bytes,
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content_type: str = "application/pdf",
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metadata: dict[str, str] | None = None,
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bucket_name: str = "raw-documents",
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) -> dict[str, Any]:
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"""Store document with metadata"""
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# Calculate checksum
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checksum = hashlib.sha256(content).hexdigest()
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# Prepare metadata
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doc_metadata = {
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"tenant_id": tenant_id,
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"doc_id": doc_id,
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"checksum": checksum,
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"size": str(len(content)),
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**(metadata or {}),
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}
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# Determine bucket and key
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object_key = f"tenants/{tenant_id}/raw/{doc_id}.pdf"
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# Upload to storage
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success = await self.storage.put_object(
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bucket_name=bucket_name,
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object_name=object_key,
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data=BytesIO(content),
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length=len(content),
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content_type=content_type,
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metadata=doc_metadata,
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)
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if success:
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return {
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"bucket": bucket_name,
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"key": object_key,
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"checksum": checksum,
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"size": len(content),
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"s3_url": f"s3://{bucket_name}/{object_key}",
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}
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raise RuntimeError("Failed to store document")
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async def store_ocr_result(
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self, tenant_id: str, doc_id: str, ocr_data: dict[str, Any]
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) -> str:
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"""Store OCR results as JSON"""
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bucket_name = "evidence"
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object_key = f"tenants/{tenant_id}/ocr/{doc_id}.json"
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# Convert to JSON bytes
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json_data = json.dumps(ocr_data, indent=2).encode("utf-8")
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# Upload to storage
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success = await self.storage.put_object(
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bucket_name=bucket_name,
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object_name=object_key,
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data=BytesIO(json_data),
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length=len(json_data),
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content_type="application/json",
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)
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if success:
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return f"s3://{bucket_name}/{object_key}"
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raise RuntimeError("Failed to store OCR result")
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async def store_extraction_result(
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self, tenant_id: str, doc_id: str, extraction_data: dict[str, Any]
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) -> str:
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"""Store extraction results as JSON"""
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bucket_name = "evidence"
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object_key = f"tenants/{tenant_id}/extractions/{doc_id}.json"
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# Convert to JSON bytes
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json_data = json.dumps(extraction_data, indent=2).encode("utf-8")
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# Upload to storage
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success = await self.storage.put_object(
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bucket_name=bucket_name,
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object_name=object_key,
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data=BytesIO(json_data),
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length=len(json_data),
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content_type="application/json",
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)
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if success:
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return f"s3://{bucket_name}/{object_key}"
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raise RuntimeError("Failed to store extraction result")
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async def get_document(self, tenant_id: str, doc_id: str) -> bytes | None:
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"""Retrieve document content"""
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bucket_name = "raw-documents"
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object_key = f"tenants/{tenant_id}/raw/{doc_id}.pdf"
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return await self.storage.get_object(bucket_name, object_key)
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async def get_ocr_result(
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self, tenant_id: str, doc_id: str
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) -> dict[str, Any] | None:
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"""Retrieve OCR results"""
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bucket_name = "evidence"
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object_key = f"tenants/{tenant_id}/ocr/{doc_id}.json"
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data = await self.storage.get_object(bucket_name, object_key)
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if data:
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return json.loads(data.decode("utf-8")) # type: ignore
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return None
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async def get_extraction_result(
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self, tenant_id: str, doc_id: str
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) -> dict[str, Any] | None:
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"""Retrieve extraction results"""
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bucket_name = "evidence"
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object_key = f"tenants/{tenant_id}/extractions/{doc_id}.json"
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data = await self.storage.get_object(bucket_name, object_key)
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if data:
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return json.loads(data.decode("utf-8")) # type: ignore
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return None
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