๐Ÿ“ฆ langgenius / dify

๐Ÿ“„ clean_unused_datasets_task.py ยท 157 lines
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157import datetime
import time
from typing import TypedDict

import click
from sqlalchemy import func, select
from sqlalchemy.exc import SQLAlchemyError

import app
from configs import dify_config
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from enums.cloud_plan import CloudPlan
from extensions.ext_database import db
from extensions.ext_redis import redis_client
from models.dataset import Dataset, DatasetAutoDisableLog, DatasetQuery, Document
from services.feature_service import FeatureService


class CleanupConfig(TypedDict):
    clean_day: datetime.datetime
    plan_filter: str | None
    add_logs: bool


@app.celery.task(queue="dataset")
def clean_unused_datasets_task():
    click.echo(click.style("Start clean unused datasets indexes.", fg="green"))
    start_at = time.perf_counter()

    # Define cleanup configurations
    cleanup_configs: list[CleanupConfig] = [
        {
            "clean_day": datetime.datetime.now() - datetime.timedelta(days=dify_config.PLAN_SANDBOX_CLEAN_DAY_SETTING),
            "plan_filter": None,
            "add_logs": True,
        },
        {
            "clean_day": datetime.datetime.now() - datetime.timedelta(days=dify_config.PLAN_PRO_CLEAN_DAY_SETTING),
            "plan_filter": CloudPlan.SANDBOX,
            "add_logs": False,
        },
    ]

    for config in cleanup_configs:
        clean_day = config["clean_day"]
        plan_filter = config["plan_filter"]
        add_logs = config["add_logs"]

        page = 1
        while True:
            try:
                # Subquery for counting new documents
                document_subquery_new = (
                    db.session.query(Document.dataset_id, func.count(Document.id).label("document_count"))
                    .where(
                        Document.indexing_status == "completed",
                        Document.enabled == True,
                        Document.archived == False,
                        Document.updated_at > clean_day,
                    )
                    .group_by(Document.dataset_id)
                    .subquery()
                )

                # Subquery for counting old documents
                document_subquery_old = (
                    db.session.query(Document.dataset_id, func.count(Document.id).label("document_count"))
                    .where(
                        Document.indexing_status == "completed",
                        Document.enabled == True,
                        Document.archived == False,
                        Document.updated_at < clean_day,
                    )
                    .group_by(Document.dataset_id)
                    .subquery()
                )

                # Main query with join and filter
                stmt = (
                    select(Dataset)
                    .outerjoin(document_subquery_new, Dataset.id == document_subquery_new.c.dataset_id)
                    .outerjoin(document_subquery_old, Dataset.id == document_subquery_old.c.dataset_id)
                    .where(
                        Dataset.created_at < clean_day,
                        func.coalesce(document_subquery_new.c.document_count, 0) == 0,
                        func.coalesce(document_subquery_old.c.document_count, 0) > 0,
                    )
                    .order_by(Dataset.created_at.desc())
                )

                datasets = db.paginate(stmt, page=page, per_page=50, error_out=False)

            except SQLAlchemyError:
                raise

            if datasets is None or datasets.items is None or len(datasets.items) == 0:
                break

            for dataset in datasets:
                dataset_query = db.session.scalars(
                    select(DatasetQuery).where(
                        DatasetQuery.created_at > clean_day, DatasetQuery.dataset_id == dataset.id
                    )
                ).all()

                if not dataset_query or len(dataset_query) == 0:
                    try:
                        should_clean = True

                        # Check plan filter if specified
                        if plan_filter:
                            features_cache_key = f"features:{dataset.tenant_id}"
                            plan_cache = redis_client.get(features_cache_key)
                            if plan_cache is None:
                                features = FeatureService.get_features(dataset.tenant_id)
                                redis_client.setex(features_cache_key, 600, features.billing.subscription.plan)
                                plan = features.billing.subscription.plan
                            else:
                                plan = plan_cache.decode()
                            should_clean = plan == plan_filter

                        if should_clean:
                            # Add auto disable log if required
                            if add_logs:
                                documents = db.session.scalars(
                                    select(Document).where(
                                        Document.dataset_id == dataset.id,
                                        Document.enabled == True,
                                        Document.archived == False,
                                    )
                                ).all()
                                for document in documents:
                                    dataset_auto_disable_log = DatasetAutoDisableLog(
                                        tenant_id=dataset.tenant_id,
                                        dataset_id=dataset.id,
                                        document_id=document.id,
                                    )
                                    db.session.add(dataset_auto_disable_log)

                            # Remove index
                            index_processor = IndexProcessorFactory(dataset.doc_form).init_index_processor()
                            index_processor.clean(dataset, None)

                            # Update document
                            db.session.query(Document).filter_by(dataset_id=dataset.id).update(
                                {Document.enabled: False}
                            )
                            db.session.commit()
                            click.echo(click.style(f"Cleaned unused dataset {dataset.id} from db success!", fg="green"))
                    except Exception as e:
                        click.echo(click.style(f"clean dataset index error: {e.__class__.__name__} {str(e)}", fg="red"))

            page += 1

    end_at = time.perf_counter()
    click.echo(click.style(f"Cleaned unused dataset from db success latency: {end_at - start_at}", fg="green"))