Files
dify/api/services/clear_free_plan_tenant_expired_logs.py
Asuka Minato 24e2b72b71 Update ast-grep pattern for session.query (#24828)
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
2025-08-31 17:03:51 +08:00

464 lines
19 KiB
Python

import datetime
import json
import logging
import time
from concurrent.futures import ThreadPoolExecutor
import click
from flask import Flask, current_app
from sqlalchemy.orm import Session, sessionmaker
from configs import dify_config
from core.model_runtime.utils.encoders import jsonable_encoder
from extensions.ext_database import db
from extensions.ext_storage import storage
from models.account import Tenant
from models.model import (
App,
AppAnnotationHitHistory,
Conversation,
Message,
MessageAgentThought,
MessageAnnotation,
MessageChain,
MessageFeedback,
MessageFile,
)
from models.web import SavedMessage
from models.workflow import WorkflowAppLog
from repositories.factory import DifyAPIRepositoryFactory
from services.billing_service import BillingService
logger = logging.getLogger(__name__)
class ClearFreePlanTenantExpiredLogs:
@classmethod
def _clear_message_related_tables(cls, session: Session, tenant_id: str, batch_message_ids: list[str]) -> None:
"""
Clean up message-related tables to avoid data redundancy.
This method cleans up tables that have foreign key relationships with Message.
Args:
session: Database session, the same with the one in process_tenant method
tenant_id: Tenant ID for logging purposes
batch_message_ids: List of message IDs to clean up
"""
if not batch_message_ids:
return
# Clean up each related table
related_tables = [
(MessageFeedback, "message_feedbacks"),
(MessageFile, "message_files"),
(MessageAnnotation, "message_annotations"),
(MessageChain, "message_chains"),
(MessageAgentThought, "message_agent_thoughts"),
(AppAnnotationHitHistory, "app_annotation_hit_histories"),
(SavedMessage, "saved_messages"),
]
for model, table_name in related_tables:
# Query records related to expired messages
records = (
session.query(model)
.where(
model.message_id.in_(batch_message_ids), # type: ignore
)
.all()
)
if len(records) == 0:
continue
# Save records before deletion
record_ids = [record.id for record in records]
try:
record_data = []
for record in records:
try:
if hasattr(record, "to_dict"):
record_data.append(record.to_dict())
else:
# if record doesn't have to_dict method, we need to transform it to dict manually
record_dict = {}
for column in record.__table__.columns:
record_dict[column.name] = getattr(record, column.name)
record_data.append(record_dict)
except Exception:
logger.exception("Failed to transform %s record: %s", table_name, record.id)
continue
if record_data:
storage.save(
f"free_plan_tenant_expired_logs/"
f"{tenant_id}/{table_name}/{datetime.datetime.now().strftime('%Y-%m-%d')}"
f"-{time.time()}.json",
json.dumps(
jsonable_encoder(record_data),
).encode("utf-8"),
)
except Exception:
logger.exception("Failed to save %s records", table_name)
session.query(model).where(
model.id.in_(record_ids), # type: ignore
).delete(synchronize_session=False)
click.echo(
click.style(
f"[{datetime.datetime.now()}] Processed {len(record_ids)} "
f"{table_name} records for tenant {tenant_id}"
)
)
@classmethod
def process_tenant(cls, flask_app: Flask, tenant_id: str, days: int, batch: int):
with flask_app.app_context():
apps = db.session.query(App).where(App.tenant_id == tenant_id).all()
app_ids = [app.id for app in apps]
while True:
with Session(db.engine).no_autoflush as session:
messages = (
session.query(Message)
.where(
Message.app_id.in_(app_ids),
Message.created_at < datetime.datetime.now() - datetime.timedelta(days=days),
)
.limit(batch)
.all()
)
if len(messages) == 0:
break
storage.save(
f"free_plan_tenant_expired_logs/"
f"{tenant_id}/messages/{datetime.datetime.now().strftime('%Y-%m-%d')}"
f"-{time.time()}.json",
json.dumps(
jsonable_encoder(
[message.to_dict() for message in messages],
),
).encode("utf-8"),
)
message_ids = [message.id for message in messages]
# delete messages
session.query(Message).where(
Message.id.in_(message_ids),
).delete(synchronize_session=False)
cls._clear_message_related_tables(session, tenant_id, message_ids)
session.commit()
click.echo(
click.style(
f"[{datetime.datetime.now()}] Processed {len(message_ids)} messages for tenant {tenant_id} "
)
)
while True:
with Session(db.engine).no_autoflush as session:
conversations = (
session.query(Conversation)
.where(
Conversation.app_id.in_(app_ids),
Conversation.updated_at < datetime.datetime.now() - datetime.timedelta(days=days),
)
.limit(batch)
.all()
)
if len(conversations) == 0:
break
storage.save(
f"free_plan_tenant_expired_logs/"
f"{tenant_id}/conversations/{datetime.datetime.now().strftime('%Y-%m-%d')}"
f"-{time.time()}.json",
json.dumps(
jsonable_encoder(
[conversation.to_dict() for conversation in conversations],
),
).encode("utf-8"),
)
conversation_ids = [conversation.id for conversation in conversations]
session.query(Conversation).where(
Conversation.id.in_(conversation_ids),
).delete(synchronize_session=False)
session.commit()
click.echo(
click.style(
f"[{datetime.datetime.now()}] Processed {len(conversation_ids)}"
f" conversations for tenant {tenant_id}"
)
)
# Process expired workflow node executions with backup
session_maker = sessionmaker(bind=db.engine, expire_on_commit=False)
node_execution_repo = DifyAPIRepositoryFactory.create_api_workflow_node_execution_repository(session_maker)
before_date = datetime.datetime.now() - datetime.timedelta(days=days)
total_deleted = 0
while True:
# Get a batch of expired executions for backup
workflow_node_executions = node_execution_repo.get_expired_executions_batch(
tenant_id=tenant_id,
before_date=before_date,
batch_size=batch,
)
if len(workflow_node_executions) == 0:
break
# Save workflow node executions to storage
storage.save(
f"free_plan_tenant_expired_logs/"
f"{tenant_id}/workflow_node_executions/{datetime.datetime.now().strftime('%Y-%m-%d')}"
f"-{time.time()}.json",
json.dumps(
jsonable_encoder(workflow_node_executions),
).encode("utf-8"),
)
# Extract IDs for deletion
workflow_node_execution_ids = [
workflow_node_execution.id for workflow_node_execution in workflow_node_executions
]
# Delete the backed up executions
deleted_count = node_execution_repo.delete_executions_by_ids(workflow_node_execution_ids)
total_deleted += deleted_count
click.echo(
click.style(
f"[{datetime.datetime.now()}] Processed {len(workflow_node_execution_ids)}"
f" workflow node executions for tenant {tenant_id}"
)
)
# If we got fewer than the batch size, we're done
if len(workflow_node_executions) < batch:
break
# Process expired workflow runs with backup
session_maker = sessionmaker(bind=db.engine, expire_on_commit=False)
workflow_run_repo = DifyAPIRepositoryFactory.create_api_workflow_run_repository(session_maker)
before_date = datetime.datetime.now() - datetime.timedelta(days=days)
total_deleted = 0
while True:
# Get a batch of expired workflow runs for backup
workflow_runs = workflow_run_repo.get_expired_runs_batch(
tenant_id=tenant_id,
before_date=before_date,
batch_size=batch,
)
if len(workflow_runs) == 0:
break
# Save workflow runs to storage
storage.save(
f"free_plan_tenant_expired_logs/"
f"{tenant_id}/workflow_runs/{datetime.datetime.now().strftime('%Y-%m-%d')}"
f"-{time.time()}.json",
json.dumps(
jsonable_encoder(
[workflow_run.to_dict() for workflow_run in workflow_runs],
),
).encode("utf-8"),
)
# Extract IDs for deletion
workflow_run_ids = [workflow_run.id for workflow_run in workflow_runs]
# Delete the backed up workflow runs
deleted_count = workflow_run_repo.delete_runs_by_ids(workflow_run_ids)
total_deleted += deleted_count
click.echo(
click.style(
f"[{datetime.datetime.now()}] Processed {len(workflow_run_ids)}"
f" workflow runs for tenant {tenant_id}"
)
)
# If we got fewer than the batch size, we're done
if len(workflow_runs) < batch:
break
while True:
with Session(db.engine).no_autoflush as session:
workflow_app_logs = (
session.query(WorkflowAppLog)
.where(
WorkflowAppLog.tenant_id == tenant_id,
WorkflowAppLog.created_at < datetime.datetime.now() - datetime.timedelta(days=days),
)
.limit(batch)
.all()
)
if len(workflow_app_logs) == 0:
break
# save workflow app logs
storage.save(
f"free_plan_tenant_expired_logs/"
f"{tenant_id}/workflow_app_logs/{datetime.datetime.now().strftime('%Y-%m-%d')}"
f"-{time.time()}.json",
json.dumps(
jsonable_encoder(
[workflow_app_log.to_dict() for workflow_app_log in workflow_app_logs],
),
).encode("utf-8"),
)
workflow_app_log_ids = [workflow_app_log.id for workflow_app_log in workflow_app_logs]
# delete workflow app logs
session.query(WorkflowAppLog).where(WorkflowAppLog.id.in_(workflow_app_log_ids)).delete(
synchronize_session=False
)
session.commit()
click.echo(
click.style(
f"[{datetime.datetime.now()}] Processed {len(workflow_app_log_ids)}"
f" workflow app logs for tenant {tenant_id}"
)
)
@classmethod
def process(cls, days: int, batch: int, tenant_ids: list[str]):
"""
Clear free plan tenant expired logs.
"""
click.echo(click.style("Clearing free plan tenant expired logs", fg="white"))
ended_at = datetime.datetime.now()
started_at = datetime.datetime(2023, 4, 3, 8, 59, 24)
current_time = started_at
with Session(db.engine) as session:
total_tenant_count = session.query(Tenant.id).count()
click.echo(click.style(f"Total tenant count: {total_tenant_count}", fg="white"))
handled_tenant_count = 0
thread_pool = ThreadPoolExecutor(max_workers=10)
def process_tenant(flask_app: Flask, tenant_id: str) -> None:
try:
if (
not dify_config.BILLING_ENABLED
or BillingService.get_info(tenant_id)["subscription"]["plan"] == "sandbox"
):
# only process sandbox tenant
cls.process_tenant(flask_app, tenant_id, days, batch)
except Exception:
logger.exception("Failed to process tenant %s", tenant_id)
finally:
nonlocal handled_tenant_count
handled_tenant_count += 1
if handled_tenant_count % 100 == 0:
click.echo(
click.style(
f"[{datetime.datetime.now()}] "
f"Processed {handled_tenant_count} tenants "
f"({(handled_tenant_count / total_tenant_count) * 100:.1f}%), "
f"{handled_tenant_count}/{total_tenant_count}",
fg="green",
)
)
futures = []
if tenant_ids:
for tenant_id in tenant_ids:
futures.append(
thread_pool.submit(
process_tenant,
current_app._get_current_object(), # type: ignore[attr-defined]
tenant_id,
)
)
else:
while current_time < ended_at:
click.echo(
click.style(f"Current time: {current_time}, Started at: {datetime.datetime.now()}", fg="white")
)
# Initial interval of 1 day, will be dynamically adjusted based on tenant count
interval = datetime.timedelta(days=1)
# Process tenants in this batch
with Session(db.engine) as session:
# Calculate tenant count in next batch with current interval
# Try different intervals until we find one with a reasonable tenant count
test_intervals = [
datetime.timedelta(days=1),
datetime.timedelta(hours=12),
datetime.timedelta(hours=6),
datetime.timedelta(hours=3),
datetime.timedelta(hours=1),
]
for test_interval in test_intervals:
tenant_count = (
session.query(Tenant.id)
.where(Tenant.created_at.between(current_time, current_time + test_interval))
.count()
)
if tenant_count <= 100:
interval = test_interval
break
else:
# If all intervals have too many tenants, use minimum interval
interval = datetime.timedelta(hours=1)
# Adjust interval to target ~100 tenants per batch
if tenant_count > 0:
# Scale interval based on ratio to target count
interval = min(
datetime.timedelta(days=1), # Max 1 day
max(
datetime.timedelta(hours=1), # Min 1 hour
interval * (100 / tenant_count), # Scale to target 100
),
)
batch_end = min(current_time + interval, ended_at)
rs = (
session.query(Tenant.id)
.where(Tenant.created_at.between(current_time, batch_end))
.order_by(Tenant.created_at)
)
tenants = []
for row in rs:
tenant_id = str(row.id)
try:
tenants.append(tenant_id)
except Exception:
logger.exception("Failed to process tenant %s", tenant_id)
continue
futures.append(
thread_pool.submit(
process_tenant,
current_app._get_current_object(), # type: ignore[attr-defined]
tenant_id,
)
)
current_time = batch_end
# wait for all threads to finish
for future in futures:
future.result()