ragflow/api/db/services/document_service.py
Yongteng Lei 2d491188b8
Refa: improve flow of GraphRAG and RAPTOR (#10709)
### What problem does this PR solve?

Improve flow of GraphRAG and RAPTOR.

### Type of change

- [x] Refactoring
2025-10-22 09:29:20 +08:00

984 lines
37 KiB
Python

#
# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import json
import logging
import random
import re
from concurrent.futures import ThreadPoolExecutor
from copy import deepcopy
from datetime import datetime
from io import BytesIO
import trio
import xxhash
from peewee import fn, Case, JOIN
from api import settings
from api.constants import IMG_BASE64_PREFIX, FILE_NAME_LEN_LIMIT
from api.db import FileType, LLMType, ParserType, StatusEnum, TaskStatus, UserTenantRole, CanvasCategory
from api.db.db_models import DB, Document, Knowledgebase, Task, Tenant, UserTenant, File2Document, File, UserCanvas, \
User
from api.db.db_utils import bulk_insert_into_db
from api.db.services.common_service import CommonService
from api.db.services.knowledgebase_service import KnowledgebaseService
from api.utils import current_timestamp, get_format_time, get_uuid
from rag.nlp import rag_tokenizer, search
from rag.settings import get_svr_queue_name, SVR_CONSUMER_GROUP_NAME
from rag.utils.redis_conn import REDIS_CONN
from rag.utils.storage_factory import STORAGE_IMPL
from rag.utils.doc_store_conn import OrderByExpr
class DocumentService(CommonService):
model = Document
@classmethod
def get_cls_model_fields(cls):
return [
cls.model.id,
cls.model.thumbnail,
cls.model.kb_id,
cls.model.parser_id,
cls.model.pipeline_id,
cls.model.parser_config,
cls.model.source_type,
cls.model.type,
cls.model.created_by,
cls.model.name,
cls.model.location,
cls.model.size,
cls.model.token_num,
cls.model.chunk_num,
cls.model.progress,
cls.model.progress_msg,
cls.model.process_begin_at,
cls.model.process_duration,
cls.model.meta_fields,
cls.model.suffix,
cls.model.run,
cls.model.status,
cls.model.create_time,
cls.model.create_date,
cls.model.update_time,
cls.model.update_date,
]
@classmethod
@DB.connection_context()
def get_list(cls, kb_id, page_number, items_per_page,
orderby, desc, keywords, id, name, suffix=None, run = None):
fields = cls.get_cls_model_fields()
docs = cls.model.select(*[*fields, UserCanvas.title]).join(File2Document, on = (File2Document.document_id == cls.model.id))\
.join(File, on = (File.id == File2Document.file_id))\
.join(UserCanvas, on = ((cls.model.pipeline_id == UserCanvas.id) & (UserCanvas.canvas_category == CanvasCategory.DataFlow.value)), join_type=JOIN.LEFT_OUTER)\
.where(cls.model.kb_id == kb_id)
if id:
docs = docs.where(
cls.model.id == id)
if name:
docs = docs.where(
cls.model.name == name
)
if keywords:
docs = docs.where(
fn.LOWER(cls.model.name).contains(keywords.lower())
)
if suffix:
docs = docs.where(cls.model.suffix.in_(suffix))
if run:
docs = docs.where(cls.model.run.in_(run))
if desc:
docs = docs.order_by(cls.model.getter_by(orderby).desc())
else:
docs = docs.order_by(cls.model.getter_by(orderby).asc())
count = docs.count()
docs = docs.paginate(page_number, items_per_page)
return list(docs.dicts()), count
@classmethod
@DB.connection_context()
def check_doc_health(cls, tenant_id: str, filename):
import os
MAX_FILE_NUM_PER_USER = int(os.environ.get("MAX_FILE_NUM_PER_USER", 0))
if MAX_FILE_NUM_PER_USER > 0 and DocumentService.get_doc_count(tenant_id) >= MAX_FILE_NUM_PER_USER:
raise RuntimeError("Exceed the maximum file number of a free user!")
if len(filename.encode("utf-8")) > FILE_NAME_LEN_LIMIT:
raise RuntimeError("Exceed the maximum length of file name!")
return True
@classmethod
@DB.connection_context()
def get_by_kb_id(cls, kb_id, page_number, items_per_page,
orderby, desc, keywords, run_status, types, suffix):
fields = cls.get_cls_model_fields()
if keywords:
docs = cls.model.select(*[*fields, UserCanvas.title.alias("pipeline_name"), User.nickname])\
.join(File2Document, on=(File2Document.document_id == cls.model.id))\
.join(File, on=(File.id == File2Document.file_id))\
.join(UserCanvas, on=(cls.model.pipeline_id == UserCanvas.id), join_type=JOIN.LEFT_OUTER)\
.join(User, on=(cls.model.created_by == User.id), join_type=JOIN.LEFT_OUTER)\
.where(
(cls.model.kb_id == kb_id),
(fn.LOWER(cls.model.name).contains(keywords.lower()))
)
else:
docs = cls.model.select(*[*fields, UserCanvas.title.alias("pipeline_name"), User.nickname])\
.join(File2Document, on=(File2Document.document_id == cls.model.id))\
.join(UserCanvas, on=(cls.model.pipeline_id == UserCanvas.id), join_type=JOIN.LEFT_OUTER)\
.join(File, on=(File.id == File2Document.file_id))\
.join(User, on=(cls.model.created_by == User.id), join_type=JOIN.LEFT_OUTER)\
.where(cls.model.kb_id == kb_id)
if run_status:
docs = docs.where(cls.model.run.in_(run_status))
if types:
docs = docs.where(cls.model.type.in_(types))
if suffix:
docs = docs.where(cls.model.suffix.in_(suffix))
count = docs.count()
if desc:
docs = docs.order_by(cls.model.getter_by(orderby).desc())
else:
docs = docs.order_by(cls.model.getter_by(orderby).asc())
if page_number and items_per_page:
docs = docs.paginate(page_number, items_per_page)
return list(docs.dicts()), count
@classmethod
@DB.connection_context()
def get_filter_by_kb_id(cls, kb_id, keywords, run_status, types, suffix):
"""
returns:
{
"suffix": {
"ppt": 1,
"doxc": 2
},
"run_status": {
"1": 2,
"2": 2
}
}, total
where "1" => RUNNING, "2" => CANCEL
"""
fields = cls.get_cls_model_fields()
if keywords:
query = cls.model.select(*fields).join(File2Document, on=(File2Document.document_id == cls.model.id)).join(File, on=(File.id == File2Document.file_id)).where(
(cls.model.kb_id == kb_id),
(fn.LOWER(cls.model.name).contains(keywords.lower()))
)
else:
query = cls.model.select(*fields).join(File2Document, on=(File2Document.document_id == cls.model.id)).join(File, on=(File.id == File2Document.file_id)).where(cls.model.kb_id == kb_id)
if run_status:
query = query.where(cls.model.run.in_(run_status))
if types:
query = query.where(cls.model.type.in_(types))
if suffix:
query = query.where(cls.model.suffix.in_(suffix))
rows = query.select(cls.model.run, cls.model.suffix)
total = rows.count()
suffix_counter = {}
run_status_counter = {}
for row in rows:
suffix_counter[row.suffix] = suffix_counter.get(row.suffix, 0) + 1
run_status_counter[str(row.run)] = run_status_counter.get(str(row.run), 0) + 1
return {
"suffix": suffix_counter,
"run_status": run_status_counter
}, total
@classmethod
@DB.connection_context()
def count_by_kb_id(cls, kb_id, keywords, run_status, types):
if keywords:
docs = cls.model.select().where(
(cls.model.kb_id == kb_id),
(fn.LOWER(cls.model.name).contains(keywords.lower()))
)
else:
docs = cls.model.select().where(cls.model.kb_id == kb_id)
if run_status:
docs = docs.where(cls.model.run.in_(run_status))
if types:
docs = docs.where(cls.model.type.in_(types))
count = docs.count()
return count
@classmethod
@DB.connection_context()
def get_total_size_by_kb_id(cls, kb_id, keywords="", run_status=[], types=[]):
query = cls.model.select(fn.COALESCE(fn.SUM(cls.model.size), 0)).where(
cls.model.kb_id == kb_id
)
if keywords:
query = query.where(fn.LOWER(cls.model.name).contains(keywords.lower()))
if run_status:
query = query.where(cls.model.run.in_(run_status))
if types:
query = query.where(cls.model.type.in_(types))
return int(query.scalar()) or 0
@classmethod
@DB.connection_context()
def get_all_doc_ids_by_kb_ids(cls, kb_ids):
fields = [cls.model.id]
docs = cls.model.select(*fields).where(cls.model.kb_id.in_(kb_ids))
docs.order_by(cls.model.create_time.asc())
# maybe cause slow query by deep paginate, optimize later
offset, limit = 0, 100
res = []
while True:
doc_batch = docs.offset(offset).limit(limit)
_temp = list(doc_batch.dicts())
if not _temp:
break
res.extend(_temp)
offset += limit
return res
@classmethod
@DB.connection_context()
def get_all_docs_by_creator_id(cls, creator_id):
fields = [
cls.model.id, cls.model.kb_id, cls.model.token_num, cls.model.chunk_num, Knowledgebase.tenant_id
]
docs = cls.model.select(*fields).join(Knowledgebase, on=(Knowledgebase.id == cls.model.kb_id)).where(
cls.model.created_by == creator_id
)
docs.order_by(cls.model.create_time.asc())
# maybe cause slow query by deep paginate, optimize later
offset, limit = 0, 100
res = []
while True:
doc_batch = docs.offset(offset).limit(limit)
_temp = list(doc_batch.dicts())
if not _temp:
break
res.extend(_temp)
offset += limit
return res
@classmethod
@DB.connection_context()
def insert(cls, doc):
if not cls.save(**doc):
raise RuntimeError("Database error (Document)!")
if not KnowledgebaseService.atomic_increase_doc_num_by_id(doc["kb_id"]):
raise RuntimeError("Database error (Knowledgebase)!")
return Document(**doc)
@classmethod
@DB.connection_context()
def remove_document(cls, doc, tenant_id):
from api.db.services.task_service import TaskService
cls.clear_chunk_num(doc.id)
try:
TaskService.filter_delete([Task.doc_id == doc.id])
page = 0
page_size = 1000
all_chunk_ids = []
while True:
chunks = settings.docStoreConn.search(["img_id"], [], {"doc_id": doc.id}, [], OrderByExpr(),
page * page_size, page_size, search.index_name(tenant_id),
[doc.kb_id])
chunk_ids = settings.docStoreConn.getChunkIds(chunks)
if not chunk_ids:
break
all_chunk_ids.extend(chunk_ids)
page += 1
for cid in all_chunk_ids:
if STORAGE_IMPL.obj_exist(doc.kb_id, cid):
STORAGE_IMPL.rm(doc.kb_id, cid)
if doc.thumbnail and not doc.thumbnail.startswith(IMG_BASE64_PREFIX):
if STORAGE_IMPL.obj_exist(doc.kb_id, doc.thumbnail):
STORAGE_IMPL.rm(doc.kb_id, doc.thumbnail)
settings.docStoreConn.delete({"doc_id": doc.id}, search.index_name(tenant_id), doc.kb_id)
graph_source = settings.docStoreConn.getFields(
settings.docStoreConn.search(["source_id"], [], {"kb_id": doc.kb_id, "knowledge_graph_kwd": ["graph"]}, [], OrderByExpr(), 0, 1, search.index_name(tenant_id), [doc.kb_id]), ["source_id"]
)
if len(graph_source) > 0 and doc.id in list(graph_source.values())[0]["source_id"]:
settings.docStoreConn.update({"kb_id": doc.kb_id, "knowledge_graph_kwd": ["entity", "relation", "graph", "subgraph", "community_report"], "source_id": doc.id},
{"remove": {"source_id": doc.id}},
search.index_name(tenant_id), doc.kb_id)
settings.docStoreConn.update({"kb_id": doc.kb_id, "knowledge_graph_kwd": ["graph"]},
{"removed_kwd": "Y"},
search.index_name(tenant_id), doc.kb_id)
settings.docStoreConn.delete({"kb_id": doc.kb_id, "knowledge_graph_kwd": ["entity", "relation", "graph", "subgraph", "community_report"], "must_not": {"exists": "source_id"}},
search.index_name(tenant_id), doc.kb_id)
except Exception:
pass
return cls.delete_by_id(doc.id)
@classmethod
@DB.connection_context()
def get_newly_uploaded(cls):
fields = [
cls.model.id,
cls.model.kb_id,
cls.model.parser_id,
cls.model.parser_config,
cls.model.name,
cls.model.type,
cls.model.location,
cls.model.size,
Knowledgebase.tenant_id,
Tenant.embd_id,
Tenant.img2txt_id,
Tenant.asr_id,
cls.model.update_time]
docs = cls.model.select(*fields) \
.join(Knowledgebase, on=(cls.model.kb_id == Knowledgebase.id)) \
.join(Tenant, on=(Knowledgebase.tenant_id == Tenant.id)) \
.where(
cls.model.status == StatusEnum.VALID.value,
~(cls.model.type == FileType.VIRTUAL.value),
cls.model.progress == 0,
cls.model.update_time >= current_timestamp() - 1000 * 600,
cls.model.run == TaskStatus.RUNNING.value) \
.order_by(cls.model.update_time.asc())
return list(docs.dicts())
@classmethod
@DB.connection_context()
def get_unfinished_docs(cls):
fields = [cls.model.id, cls.model.process_begin_at, cls.model.parser_config, cls.model.progress_msg,
cls.model.run, cls.model.parser_id]
docs = cls.model.select(*fields) \
.where(
cls.model.status == StatusEnum.VALID.value,
~(cls.model.type == FileType.VIRTUAL.value),
cls.model.progress < 1,
cls.model.progress > 0)
return list(docs.dicts())
@classmethod
@DB.connection_context()
def increment_chunk_num(cls, doc_id, kb_id, token_num, chunk_num, duration):
num = cls.model.update(token_num=cls.model.token_num + token_num,
chunk_num=cls.model.chunk_num + chunk_num,
process_duration=cls.model.process_duration + duration).where(
cls.model.id == doc_id).execute()
if num == 0:
logging.warning("Document not found which is supposed to be there")
num = Knowledgebase.update(
token_num=Knowledgebase.token_num +
token_num,
chunk_num=Knowledgebase.chunk_num +
chunk_num).where(
Knowledgebase.id == kb_id).execute()
return num
@classmethod
@DB.connection_context()
def decrement_chunk_num(cls, doc_id, kb_id, token_num, chunk_num, duration):
num = cls.model.update(token_num=cls.model.token_num - token_num,
chunk_num=cls.model.chunk_num - chunk_num,
process_duration=cls.model.process_duration + duration).where(
cls.model.id == doc_id).execute()
if num == 0:
raise LookupError(
"Document not found which is supposed to be there")
num = Knowledgebase.update(
token_num=Knowledgebase.token_num -
token_num,
chunk_num=Knowledgebase.chunk_num -
chunk_num
).where(
Knowledgebase.id == kb_id).execute()
return num
@classmethod
@DB.connection_context()
def clear_chunk_num(cls, doc_id):
doc = cls.model.get_by_id(doc_id)
assert doc, "Can't fine document in database."
num = Knowledgebase.update(
token_num=Knowledgebase.token_num -
doc.token_num,
chunk_num=Knowledgebase.chunk_num -
doc.chunk_num,
doc_num=Knowledgebase.doc_num - 1
).where(
Knowledgebase.id == doc.kb_id).execute()
return num
@classmethod
@DB.connection_context()
def clear_chunk_num_when_rerun(cls, doc_id):
doc = cls.model.get_by_id(doc_id)
assert doc, "Can't fine document in database."
num = (
Knowledgebase.update(
token_num=Knowledgebase.token_num - doc.token_num,
chunk_num=Knowledgebase.chunk_num - doc.chunk_num,
)
.where(Knowledgebase.id == doc.kb_id)
.execute()
)
return num
@classmethod
@DB.connection_context()
def get_tenant_id(cls, doc_id):
docs = cls.model.select(
Knowledgebase.tenant_id).join(
Knowledgebase, on=(
Knowledgebase.id == cls.model.kb_id)).where(
cls.model.id == doc_id, Knowledgebase.status == StatusEnum.VALID.value)
docs = docs.dicts()
if not docs:
return
return docs[0]["tenant_id"]
@classmethod
@DB.connection_context()
def get_knowledgebase_id(cls, doc_id):
docs = cls.model.select(cls.model.kb_id).where(cls.model.id == doc_id)
docs = docs.dicts()
if not docs:
return
return docs[0]["kb_id"]
@classmethod
@DB.connection_context()
def get_tenant_id_by_name(cls, name):
docs = cls.model.select(
Knowledgebase.tenant_id).join(
Knowledgebase, on=(
Knowledgebase.id == cls.model.kb_id)).where(
cls.model.name == name, Knowledgebase.status == StatusEnum.VALID.value)
docs = docs.dicts()
if not docs:
return
return docs[0]["tenant_id"]
@classmethod
@DB.connection_context()
def accessible(cls, doc_id, user_id):
docs = cls.model.select(
cls.model.id).join(
Knowledgebase, on=(
Knowledgebase.id == cls.model.kb_id)
).join(UserTenant, on=(UserTenant.tenant_id == Knowledgebase.tenant_id)
).where(cls.model.id == doc_id, UserTenant.user_id == user_id).paginate(0, 1)
docs = docs.dicts()
if not docs:
return False
return True
@classmethod
@DB.connection_context()
def accessible4deletion(cls, doc_id, user_id):
docs = cls.model.select(cls.model.id
).join(
Knowledgebase, on=(
Knowledgebase.id == cls.model.kb_id)
).join(
UserTenant, on=(
(UserTenant.tenant_id == Knowledgebase.created_by) & (UserTenant.user_id == user_id))
).where(
cls.model.id == doc_id,
UserTenant.status == StatusEnum.VALID.value,
((UserTenant.role == UserTenantRole.NORMAL) | (UserTenant.role == UserTenantRole.OWNER))
).paginate(0, 1)
docs = docs.dicts()
if not docs:
return False
return True
@classmethod
@DB.connection_context()
def get_embd_id(cls, doc_id):
docs = cls.model.select(
Knowledgebase.embd_id).join(
Knowledgebase, on=(
Knowledgebase.id == cls.model.kb_id)).where(
cls.model.id == doc_id, Knowledgebase.status == StatusEnum.VALID.value)
docs = docs.dicts()
if not docs:
return
return docs[0]["embd_id"]
@classmethod
@DB.connection_context()
def get_chunking_config(cls, doc_id):
configs = (
cls.model.select(
cls.model.id,
cls.model.kb_id,
cls.model.parser_id,
cls.model.parser_config,
Knowledgebase.language,
Knowledgebase.embd_id,
Tenant.id.alias("tenant_id"),
Tenant.img2txt_id,
Tenant.asr_id,
Tenant.llm_id,
)
.join(Knowledgebase, on=(cls.model.kb_id == Knowledgebase.id))
.join(Tenant, on=(Knowledgebase.tenant_id == Tenant.id))
.where(cls.model.id == doc_id)
)
configs = configs.dicts()
if not configs:
return None
return configs[0]
@classmethod
@DB.connection_context()
def get_doc_id_by_doc_name(cls, doc_name):
fields = [cls.model.id]
doc_id = cls.model.select(*fields) \
.where(cls.model.name == doc_name)
doc_id = doc_id.dicts()
if not doc_id:
return
return doc_id[0]["id"]
@classmethod
@DB.connection_context()
def get_doc_ids_by_doc_names(cls, doc_names):
if not doc_names:
return []
query = cls.model.select(cls.model.id).where(cls.model.name.in_(doc_names))
return list(query.scalars().iterator())
@classmethod
@DB.connection_context()
def get_thumbnails(cls, docids):
fields = [cls.model.id, cls.model.kb_id, cls.model.thumbnail]
return list(cls.model.select(
*fields).where(cls.model.id.in_(docids)).dicts())
@classmethod
@DB.connection_context()
def update_parser_config(cls, id, config):
if not config:
return
e, d = cls.get_by_id(id)
if not e:
raise LookupError(f"Document({id}) not found.")
def dfs_update(old, new):
for k, v in new.items():
if k not in old:
old[k] = v
continue
if isinstance(v, dict):
assert isinstance(old[k], dict)
dfs_update(old[k], v)
else:
old[k] = v
dfs_update(d.parser_config, config)
if not config.get("raptor") and d.parser_config.get("raptor"):
del d.parser_config["raptor"]
cls.update_by_id(id, {"parser_config": d.parser_config})
@classmethod
@DB.connection_context()
def get_doc_count(cls, tenant_id):
docs = cls.model.select(cls.model.id).join(Knowledgebase,
on=(Knowledgebase.id == cls.model.kb_id)).where(
Knowledgebase.tenant_id == tenant_id)
return len(docs)
@classmethod
@DB.connection_context()
def begin2parse(cls, docid):
cls.update_by_id(
docid, {"progress": random.random() * 1 / 100.,
"progress_msg": "Task is queued...",
"process_begin_at": get_format_time()
})
@classmethod
@DB.connection_context()
def update_meta_fields(cls, doc_id, meta_fields):
return cls.update_by_id(doc_id, {"meta_fields": meta_fields})
@classmethod
@DB.connection_context()
def get_meta_by_kbs(cls, kb_ids):
fields = [
cls.model.id,
cls.model.meta_fields,
]
meta = {}
for r in cls.model.select(*fields).where(cls.model.kb_id.in_(kb_ids)):
doc_id = r.id
for k,v in r.meta_fields.items():
if k not in meta:
meta[k] = {}
v = str(v)
if v not in meta[k]:
meta[k][v] = []
meta[k][v].append(doc_id)
return meta
@classmethod
@DB.connection_context()
def update_progress(cls):
docs = cls.get_unfinished_docs()
cls._sync_progress(docs)
@classmethod
@DB.connection_context()
def update_progress_immediately(cls, docs:list[dict]):
if not docs:
return
cls._sync_progress(docs)
@classmethod
@DB.connection_context()
def _sync_progress(cls, docs:list[dict]):
from api.db.services.task_service import TaskService
for d in docs:
try:
tsks = TaskService.query(doc_id=d["id"], order_by=Task.create_time)
if not tsks:
continue
msg = []
prg = 0
finished = True
bad = 0
e, doc = DocumentService.get_by_id(d["id"])
status = doc.run # TaskStatus.RUNNING.value
priority = 0
for t in tsks:
if 0 <= t.progress < 1:
finished = False
if t.progress == -1:
bad += 1
prg += t.progress if t.progress >= 0 else 0
if t.progress_msg.strip():
msg.append(t.progress_msg)
priority = max(priority, t.priority)
prg /= len(tsks)
if finished and bad:
prg = -1
status = TaskStatus.FAIL.value
elif finished:
prg = 1
status = TaskStatus.DONE.value
msg = "\n".join(sorted(msg))
info = {
"process_duration": datetime.timestamp(
datetime.now()) -
d["process_begin_at"].timestamp(),
"run": status}
if prg != 0:
info["progress"] = prg
if msg:
info["progress_msg"] = msg
if msg.endswith("created task graphrag") or msg.endswith("created task raptor") or msg.endswith("created task mindmap"):
info["progress_msg"] += "\n%d tasks are ahead in the queue..."%get_queue_length(priority)
else:
info["progress_msg"] = "%d tasks are ahead in the queue..."%get_queue_length(priority)
cls.update_by_id(d["id"], info)
except Exception as e:
if str(e).find("'0'") < 0:
logging.exception("fetch task exception")
@classmethod
@DB.connection_context()
def get_kb_doc_count(cls, kb_id):
return cls.model.select().where(cls.model.kb_id == kb_id).count()
@classmethod
@DB.connection_context()
def get_all_kb_doc_count(cls):
result = {}
rows = cls.model.select(cls.model.kb_id, fn.COUNT(cls.model.id).alias('count')).group_by(cls.model.kb_id)
for row in rows:
result[row.kb_id] = row.count
return result
@classmethod
@DB.connection_context()
def do_cancel(cls, doc_id):
try:
_, doc = DocumentService.get_by_id(doc_id)
return doc.run == TaskStatus.CANCEL.value or doc.progress < 0
except Exception:
pass
return False
@classmethod
@DB.connection_context()
def knowledgebase_basic_info(cls, kb_id: str) -> dict[str, int]:
# cancelled: run == "2" but progress can vary
cancelled = (
cls.model.select(fn.COUNT(1))
.where((cls.model.kb_id == kb_id) & (cls.model.run == TaskStatus.CANCEL))
.scalar()
)
row = (
cls.model.select(
# finished: progress == 1
fn.COALESCE(fn.SUM(Case(None, [(cls.model.progress == 1, 1)], 0)), 0).alias("finished"),
# failed: progress == -1
fn.COALESCE(fn.SUM(Case(None, [(cls.model.progress == -1, 1)], 0)), 0).alias("failed"),
# processing: 0 <= progress < 1
fn.COALESCE(
fn.SUM(
Case(
None,
[
(((cls.model.progress == 0) | ((cls.model.progress > 0) & (cls.model.progress < 1))), 1),
],
0,
)
),
0,
).alias("processing"),
)
.where(
(cls.model.kb_id == kb_id)
& ((cls.model.run.is_null(True)) | (cls.model.run != TaskStatus.CANCEL))
)
.dicts()
.get()
)
return {
"processing": int(row["processing"]),
"finished": int(row["finished"]),
"failed": int(row["failed"]),
"cancelled": int(cancelled),
}
def queue_raptor_o_graphrag_tasks(sample_doc_id, ty, priority, fake_doc_id="", doc_ids=[]):
"""
You can provide a fake_doc_id to bypass the restriction of tasks at the knowledgebase level.
Optionally, specify a list of doc_ids to determine which documents participate in the task.
"""
assert ty in ["graphrag", "raptor", "mindmap"], "type should be graphrag, raptor or mindmap"
chunking_config = DocumentService.get_chunking_config(sample_doc_id["id"])
hasher = xxhash.xxh64()
for field in sorted(chunking_config.keys()):
hasher.update(str(chunking_config[field]).encode("utf-8"))
def new_task():
nonlocal sample_doc_id
return {
"id": get_uuid(),
"doc_id": sample_doc_id["id"],
"from_page": 100000000,
"to_page": 100000000,
"task_type": ty,
"progress_msg": datetime.now().strftime("%H:%M:%S") + " created task " + ty,
"begin_at": datetime.now(),
}
task = new_task()
for field in ["doc_id", "from_page", "to_page"]:
hasher.update(str(task.get(field, "")).encode("utf-8"))
hasher.update(ty.encode("utf-8"))
task["digest"] = hasher.hexdigest()
bulk_insert_into_db(Task, [task], True)
task["doc_id"] = fake_doc_id
task["doc_ids"] = doc_ids
DocumentService.begin2parse(sample_doc_id["id"])
assert REDIS_CONN.queue_product(get_svr_queue_name(priority), message=task), "Can't access Redis. Please check the Redis' status."
return task["id"]
def get_queue_length(priority):
group_info = REDIS_CONN.queue_info(get_svr_queue_name(priority), SVR_CONSUMER_GROUP_NAME)
if not group_info:
return 0
return int(group_info.get("lag", 0) or 0)
def doc_upload_and_parse(conversation_id, file_objs, user_id):
from api.db.services.api_service import API4ConversationService
from api.db.services.conversation_service import ConversationService
from api.db.services.dialog_service import DialogService
from api.db.services.file_service import FileService
from api.db.services.llm_service import LLMBundle
from api.db.services.user_service import TenantService
from rag.app import audio, email, naive, picture, presentation
e, conv = ConversationService.get_by_id(conversation_id)
if not e:
e, conv = API4ConversationService.get_by_id(conversation_id)
assert e, "Conversation not found!"
e, dia = DialogService.get_by_id(conv.dialog_id)
if not dia.kb_ids:
raise LookupError("No knowledge base associated with this conversation. "
"Please add a knowledge base before uploading documents")
kb_id = dia.kb_ids[0]
e, kb = KnowledgebaseService.get_by_id(kb_id)
if not e:
raise LookupError("Can't find this knowledgebase!")
embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING, llm_name=kb.embd_id, lang=kb.language)
err, files = FileService.upload_document(kb, file_objs, user_id)
assert not err, "\n".join(err)
def dummy(prog=None, msg=""):
pass
FACTORY = {
ParserType.PRESENTATION.value: presentation,
ParserType.PICTURE.value: picture,
ParserType.AUDIO.value: audio,
ParserType.EMAIL.value: email
}
parser_config = {"chunk_token_num": 4096, "delimiter": "\n!?;。;!?", "layout_recognize": "Plain Text"}
exe = ThreadPoolExecutor(max_workers=12)
threads = []
doc_nm = {}
for d, blob in files:
doc_nm[d["id"]] = d["name"]
for d, blob in files:
kwargs = {
"callback": dummy,
"parser_config": parser_config,
"from_page": 0,
"to_page": 100000,
"tenant_id": kb.tenant_id,
"lang": kb.language
}
threads.append(exe.submit(FACTORY.get(d["parser_id"], naive).chunk, d["name"], blob, **kwargs))
for (docinfo, _), th in zip(files, threads):
docs = []
doc = {
"doc_id": docinfo["id"],
"kb_id": [kb.id]
}
for ck in th.result():
d = deepcopy(doc)
d.update(ck)
d["id"] = xxhash.xxh64((ck["content_with_weight"] + str(d["doc_id"])).encode("utf-8")).hexdigest()
d["create_time"] = str(datetime.now()).replace("T", " ")[:19]
d["create_timestamp_flt"] = datetime.now().timestamp()
if not d.get("image"):
docs.append(d)
continue
output_buffer = BytesIO()
if isinstance(d["image"], bytes):
output_buffer = BytesIO(d["image"])
else:
d["image"].save(output_buffer, format='JPEG')
STORAGE_IMPL.put(kb.id, d["id"], output_buffer.getvalue())
d["img_id"] = "{}-{}".format(kb.id, d["id"])
d.pop("image", None)
docs.append(d)
parser_ids = {d["id"]: d["parser_id"] for d, _ in files}
docids = [d["id"] for d, _ in files]
chunk_counts = {id: 0 for id in docids}
token_counts = {id: 0 for id in docids}
es_bulk_size = 64
def embedding(doc_id, cnts, batch_size=16):
nonlocal embd_mdl, chunk_counts, token_counts
vects = []
for i in range(0, len(cnts), batch_size):
vts, c = embd_mdl.encode(cnts[i: i + batch_size])
vects.extend(vts.tolist())
chunk_counts[doc_id] += len(cnts[i:i + batch_size])
token_counts[doc_id] += c
return vects
idxnm = search.index_name(kb.tenant_id)
try_create_idx = True
_, tenant = TenantService.get_by_id(kb.tenant_id)
llm_bdl = LLMBundle(kb.tenant_id, LLMType.CHAT, tenant.llm_id)
for doc_id in docids:
cks = [c for c in docs if c["doc_id"] == doc_id]
if parser_ids[doc_id] != ParserType.PICTURE.value:
from graphrag.general.mind_map_extractor import MindMapExtractor
mindmap = MindMapExtractor(llm_bdl)
try:
mind_map = trio.run(mindmap, [c["content_with_weight"] for c in docs if c["doc_id"] == doc_id])
mind_map = json.dumps(mind_map.output, ensure_ascii=False, indent=2)
if len(mind_map) < 32:
raise Exception("Few content: " + mind_map)
cks.append({
"id": get_uuid(),
"doc_id": doc_id,
"kb_id": [kb.id],
"docnm_kwd": doc_nm[doc_id],
"title_tks": rag_tokenizer.tokenize(re.sub(r"\.[a-zA-Z]+$", "", doc_nm[doc_id])),
"content_ltks": rag_tokenizer.tokenize("summary summarize 总结 概况 file 文件 概括"),
"content_with_weight": mind_map,
"knowledge_graph_kwd": "mind_map"
})
except Exception as e:
logging.exception("Mind map generation error")
vects = embedding(doc_id, [c["content_with_weight"] for c in cks])
assert len(cks) == len(vects)
for i, d in enumerate(cks):
v = vects[i]
d["q_%d_vec" % len(v)] = v
for b in range(0, len(cks), es_bulk_size):
if try_create_idx:
if not settings.docStoreConn.indexExist(idxnm, kb_id):
settings.docStoreConn.createIdx(idxnm, kb_id, len(vects[0]))
try_create_idx = False
settings.docStoreConn.insert(cks[b:b + es_bulk_size], idxnm, kb_id)
DocumentService.increment_chunk_num(
doc_id, kb.id, token_counts[doc_id], chunk_counts[doc_id], 0)
return [d["id"] for d, _ in files]