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Merge branch 'dev' into copilot/add-webhook-system-ai-events

Browse source 
Resolved merge conflicts in:
- src/documents/ai_deletion_manager.py: Kept webhook integration alongside dev changes
- src/documents/ai_scanner.py: Kept webhook integration and applied_fields tracking
- src/documents/models.py: Integrated AISuggestionFeedback model with webhook imports

All conflicts resolved maintaining both webhook functionality and new AI suggestions features from dev branch.

Co-authored-by: dawnsystem <42047891+dawnsystem@users.noreply.github.com>
This commit is contained in:
copilot-swe-agent[bot] 2025-11-14 15:26:54 +00:00
parent ebc906b713
commit 5ae18e03b5
24 changed files with 5421 additions and 299 deletions
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138
src/documents/ai_deletion_manager.py
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@ -14,15 +14,11 @@ According to agents.md requirements:
from __future__ import annotations
import logging
from datetime import datetime
from typing import TYPE_CHECKING, Dict, List, Optional, Any
from django.conf import settings
from django.contrib.auth.models import User
from django.utils import timezone
from typing import TYPE_CHECKING
from typing import Any
if TYPE_CHECKING:
from documents.models import Document, DeletionRequest
from django.contrib.auth.models import User
logger = logging.getLogger("paperless.ai_deletion")
@ -30,35 +26,35 @@ logger = logging.getLogger("paperless.ai_deletion")
class AIDeletionManager:
"""
Manager for AI-initiated deletion requests.
Ensures all deletions go through proper user approval workflow.
"""
@staticmethod
def create_deletion_request(
documents: List,
documents: list,
reason: str,
user: User,
impact_analysis: Optional[Dict[str, Any]] = None,
impact_analysis: dict[str, Any] | None = None,
):
"""
Create a new deletion request that requires user approval.
Args:
documents: List of documents to be deleted
reason: Detailed explanation from AI
user: User who must approve
impact_analysis: Optional detailed impact analysis
Returns:
Created DeletionRequest instance
"""
from documents.models import DeletionRequest
# Analyze impact if not provided
if impact_analysis is None:
impact_analysis = AIDeletionManager._analyze_impact(documents)
# Create request
request = DeletionRequest.objects.create(
requested_by_ai=True,
@ -67,15 +63,15 @@ class AIDeletionManager:
status=DeletionRequest.STATUS_PENDING,
impact_summary=impact_analysis,
)
# Add documents
request.documents.set(documents)
logger.info(
f"Created deletion request {request.id} for {len(documents)} documents "
f"requiring approval from user {user.username}"
f"requiring approval from user {user.username}",
)
# Send webhook notification about deletion request
try:
from documents.webhooks import send_deletion_request_webhook
@ -85,16 +81,16 @@ class AIDeletionManager:
f"Failed to send deletion request webhook: {webhook_error}",
exc_info=True,
)
# TODO: Send in-app notification to user about pending deletion request
return request
@staticmethod
def _analyze_impact(documents: List) -> Dict[str, Any]:
def _analyze_impact(documents: list) -> dict[str, Any]:
"""
Analyze the impact of deleting the given documents.
Returns comprehensive information about what will be affected.
"""
impact = {
@ -109,7 +105,7 @@ class AIDeletionManager:
"latest": None,
},
}
for doc in documents:
# Document details
doc_info = {
@ -121,77 +117,85 @@ class AIDeletionManager:
"tags": [tag.name for tag in doc.tags.all()],
}
impact["documents"].append(doc_info)
# Track size (if available)
# Note: This would need actual file size tracking
# Track affected metadata
if doc.correspondent:
impact["affected_correspondents"].add(doc.correspondent.name)
if doc.document_type:
impact["affected_types"].add(doc.document_type.name)
for tag in doc.tags.all():
impact["affected_tags"].add(tag.name)
# Track date range
if doc.created:
if impact["date_range"]["earliest"] is None or doc.created < impact["date_range"]["earliest"]:
if (
impact["date_range"]["earliest"] is None
or doc.created < impact["date_range"]["earliest"]
):
impact["date_range"]["earliest"] = doc.created
if impact["date_range"]["latest"] is None or doc.created > impact["date_range"]["latest"]:
if (
impact["date_range"]["latest"] is None
or doc.created > impact["date_range"]["latest"]
):
impact["date_range"]["latest"] = doc.created
# Convert sets to lists for JSON serialization
impact["affected_tags"] = list(impact["affected_tags"])
impact["affected_correspondents"] = list(impact["affected_correspondents"])
impact["affected_types"] = list(impact["affected_types"])
# Convert dates to ISO format
if impact["date_range"]["earliest"]:
impact["date_range"]["earliest"] = impact["date_range"]["earliest"].isoformat()
impact["date_range"]["earliest"] = impact["date_range"][
"earliest"
].isoformat()
if impact["date_range"]["latest"]:
impact["date_range"]["latest"] = impact["date_range"]["latest"].isoformat()
return impact
@staticmethod
def get_pending_requests(user: User) -> List:
def get_pending_requests(user: User) -> list:
"""
Get all pending deletion requests for a user.
Args:
user: User to get requests for
Returns:
List of pending DeletionRequest instances
"""
from documents.models import DeletionRequest
return list(
DeletionRequest.objects.filter(
user=user,
status=DeletionRequest.STATUS_PENDING,
)
),
)
@staticmethod
def format_deletion_request_for_user(request) -> str:
"""
Format a deletion request into a human-readable message.
This provides comprehensive information to the user about what
will be deleted, as required by agents.md.
Args:
request: DeletionRequest to format
Returns:
Formatted message string
"""
impact = request.impact_summary
message = f"""
===========================================
AI DELETION REQUEST #{request.id}
@ -201,27 +205,27 @@ REASON:
{request.ai_reason}
IMPACT SUMMARY:
- Number of documents: {impact.get('document_count', 0)}
- Affected tags: {', '.join(impact.get('affected_tags', [])) or 'None'}
- Affected correspondents: {', '.join(impact.get('affected_correspondents', [])) or 'None'}
- Affected document types: {', '.join(impact.get('affected_types', [])) or 'None'}
- Number of documents: {impact.get("document_count", 0)}
- Affected tags: {", ".join(impact.get("affected_tags", [])) or "None"}
- Affected correspondents: {", ".join(impact.get("affected_correspondents", [])) or "None"}
- Affected document types: {", ".join(impact.get("affected_types", [])) or "None"}
DATE RANGE:
- Earliest: {impact.get('date_range', {}).get('earliest', 'Unknown')}
- Latest: {impact.get('date_range', {}).get('latest', 'Unknown')}
- Earliest: {impact.get("date_range", {}).get("earliest", "Unknown")}
- Latest: {impact.get("date_range", {}).get("latest", "Unknown")}
DOCUMENTS TO BE DELETED:
"""
for i, doc in enumerate(impact.get('documents', []), 1):
for i, doc in enumerate(impact.get("documents", []), 1):
message += f"""
{i}. ID: {doc['id']} - {doc['title']}
Created: {doc['created']}
Correspondent: {doc['correspondent'] or 'None'}
Type: {doc['document_type'] or 'None'}
Tags: {', '.join(doc['tags']) or 'None'}
{i}. ID: {doc["id"]} - {doc["title"]}
Created: {doc["created"]}
Correspondent: {doc["correspondent"] or "None"}
Type: {doc["document_type"] or "None"}
Tags: {", ".join(doc["tags"]) or "None"}
"""
message += """
===========================================
@ -232,21 +236,21 @@ No files will be deleted until you confirm this action.
Please review the above information carefully before
approving or rejecting this request.
"""
return message
@staticmethod
def can_ai_delete_automatically() -> bool:
"""
Check if AI is allowed to delete automatically.
According to agents.md, AI should NEVER delete without user approval.
This method always returns False as a safety measure.
Returns:
Always False - AI cannot auto-delete
"""
return False
__all__ = ['AIDeletionManager']
__all__ = ["AIDeletionManager"]