ragflow / api /db /services /task_service.py
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Fix raptor (#4089)
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#
# 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 os
import random
import xxhash
import bisect
from api.db.db_utils import bulk_insert_into_db
from deepdoc.parser import PdfParser
from peewee import JOIN
from api.db.db_models import DB, File2Document, File
from api.db import StatusEnum, FileType, TaskStatus
from api.db.db_models import Task, Document, Knowledgebase, Tenant
from api.db.services.common_service import CommonService
from api.db.services.document_service import DocumentService
from api.utils import current_timestamp, get_uuid
from deepdoc.parser.excel_parser import RAGFlowExcelParser
from rag.settings import SVR_QUEUE_NAME
from rag.utils.storage_factory import STORAGE_IMPL
from rag.utils.redis_conn import REDIS_CONN
from api import settings
from rag.nlp import search
def trim_header_by_lines(text: str, max_length) -> str:
len_text = len(text)
if len_text <= max_length:
return text
for i in range(len_text):
if text[i] == '\n' and len_text - i <= max_length:
return text[i + 1:]
return text
class TaskService(CommonService):
model = Task
@classmethod
@DB.connection_context()
def get_task(cls, task_id):
fields = [
cls.model.id,
cls.model.doc_id,
cls.model.from_page,
cls.model.to_page,
cls.model.retry_count,
Document.kb_id,
Document.parser_id,
Document.parser_config,
Document.name,
Document.type,
Document.location,
Document.size,
Knowledgebase.tenant_id,
Knowledgebase.language,
Knowledgebase.embd_id,
Knowledgebase.pagerank,
Tenant.img2txt_id,
Tenant.asr_id,
Tenant.llm_id,
cls.model.update_time,
]
docs = (
cls.model.select(*fields)
.join(Document, on=(cls.model.doc_id == Document.id))
.join(Knowledgebase, on=(Document.kb_id == Knowledgebase.id))
.join(Tenant, on=(Knowledgebase.tenant_id == Tenant.id))
.where(cls.model.id == task_id)
)
docs = list(docs.dicts())
if not docs:
return None
msg = "\nTask has been received."
prog = random.random() / 10.0
if docs[0]["retry_count"] >= 3:
msg = "\nERROR: Task is abandoned after 3 times attempts."
prog = -1
cls.model.update(
progress_msg=cls.model.progress_msg + msg,
progress=prog,
retry_count=docs[0]["retry_count"] + 1,
).where(cls.model.id == docs[0]["id"]).execute()
if docs[0]["retry_count"] >= 3:
return None
return docs[0]
@classmethod
@DB.connection_context()
def get_tasks(cls, doc_id: str):
fields = [
cls.model.id,
cls.model.from_page,
cls.model.progress,
cls.model.digest,
cls.model.chunk_ids,
]
tasks = (
cls.model.select(*fields).order_by(cls.model.from_page.asc(), cls.model.create_time.desc())
.where(cls.model.doc_id == doc_id)
)
tasks = list(tasks.dicts())
if not tasks:
return None
return tasks
@classmethod
@DB.connection_context()
def update_chunk_ids(cls, id: str, chunk_ids: str):
cls.model.update(chunk_ids=chunk_ids).where(cls.model.id == id).execute()
@classmethod
@DB.connection_context()
def get_ongoing_doc_name(cls):
with DB.lock("get_task", -1):
docs = (
cls.model.select(
*[Document.id, Document.kb_id, Document.location, File.parent_id]
)
.join(Document, on=(cls.model.doc_id == Document.id))
.join(
File2Document,
on=(File2Document.document_id == Document.id),
join_type=JOIN.LEFT_OUTER,
)
.join(
File,
on=(File2Document.file_id == File.id),
join_type=JOIN.LEFT_OUTER,
)
.where(
Document.status == StatusEnum.VALID.value,
Document.run == TaskStatus.RUNNING.value,
~(Document.type == FileType.VIRTUAL.value),
cls.model.progress < 1,
cls.model.create_time >= current_timestamp() - 1000 * 600,
)
)
docs = list(docs.dicts())
if not docs:
return []
return list(
set(
[
(
d["parent_id"] if d["parent_id"] else d["kb_id"],
d["location"],
)
for d in docs
]
)
)
@classmethod
@DB.connection_context()
def do_cancel(cls, id):
task = cls.model.get_by_id(id)
_, doc = DocumentService.get_by_id(task.doc_id)
return doc.run == TaskStatus.CANCEL.value or doc.progress < 0
@classmethod
@DB.connection_context()
def update_progress(cls, id, info):
if os.environ.get("MACOS"):
if info["progress_msg"]:
task = cls.model.get_by_id(id)
progress_msg = trim_header_by_lines(task.progress_msg + "\n" + info["progress_msg"], 1000)
cls.model.update(progress_msg=progress_msg).where(cls.model.id == id).execute()
if "progress" in info:
cls.model.update(progress=info["progress"]).where(
cls.model.id == id
).execute()
return
with DB.lock("update_progress", -1):
if info["progress_msg"]:
task = cls.model.get_by_id(id)
progress_msg = trim_header_by_lines(task.progress_msg + "\n" + info["progress_msg"], 1000)
cls.model.update(progress_msg=progress_msg).where(cls.model.id == id).execute()
if "progress" in info:
cls.model.update(progress=info["progress"]).where(
cls.model.id == id
).execute()
def queue_tasks(doc: dict, bucket: str, name: str):
def new_task():
return {"id": get_uuid(), "doc_id": doc["id"], "progress": 0.0, "from_page": 0, "to_page": 100000000}
tsks = []
if doc["type"] == FileType.PDF.value:
file_bin = STORAGE_IMPL.get(bucket, name)
do_layout = doc["parser_config"].get("layout_recognize", True)
pages = PdfParser.total_page_number(doc["name"], file_bin)
page_size = doc["parser_config"].get("task_page_size", 12)
if doc["parser_id"] == "paper":
page_size = doc["parser_config"].get("task_page_size", 22)
if doc["parser_id"] in ["one", "knowledge_graph"] or not do_layout:
page_size = 10 ** 9
page_ranges = doc["parser_config"].get("pages") or [(1, 10 ** 5)]
for s, e in page_ranges:
s -= 1
s = max(0, s)
e = min(e - 1, pages)
for p in range(s, e, page_size):
task = new_task()
task["from_page"] = p
task["to_page"] = min(p + page_size, e)
tsks.append(task)
elif doc["parser_id"] == "table":
file_bin = STORAGE_IMPL.get(bucket, name)
rn = RAGFlowExcelParser.row_number(doc["name"], file_bin)
for i in range(0, rn, 3000):
task = new_task()
task["from_page"] = i
task["to_page"] = min(i + 3000, rn)
tsks.append(task)
else:
tsks.append(new_task())
chunking_config = DocumentService.get_chunking_config(doc["id"])
for task in tsks:
hasher = xxhash.xxh64()
for field in sorted(chunking_config.keys()):
hasher.update(str(chunking_config[field]).encode("utf-8"))
for field in ["doc_id", "from_page", "to_page"]:
hasher.update(str(task.get(field, "")).encode("utf-8"))
task_digest = hasher.hexdigest()
task["digest"] = task_digest
task["progress"] = 0.0
prev_tasks = TaskService.get_tasks(doc["id"])
ck_num = 0
if prev_tasks:
for task in tsks:
ck_num += reuse_prev_task_chunks(task, prev_tasks, chunking_config)
TaskService.filter_delete([Task.doc_id == doc["id"]])
chunk_ids = []
for task in prev_tasks:
if task["chunk_ids"]:
chunk_ids.extend(task["chunk_ids"].split())
if chunk_ids:
settings.docStoreConn.delete({"id": chunk_ids}, search.index_name(chunking_config["tenant_id"]),
chunking_config["kb_id"])
DocumentService.update_by_id(doc["id"], {"chunk_num": ck_num})
bulk_insert_into_db(Task, tsks, True)
DocumentService.begin2parse(doc["id"])
tsks = [task for task in tsks if task["progress"] < 1.0]
for t in tsks:
assert REDIS_CONN.queue_product(
SVR_QUEUE_NAME, message=t
), "Can't access Redis. Please check the Redis' status."
def reuse_prev_task_chunks(task: dict, prev_tasks: list[dict], chunking_config: dict):
idx = bisect.bisect_left(prev_tasks, (task.get("from_page", 0), task.get("digest", "")),
key=lambda x: (x.get("from_page", 0), x.get("digest", "")))
if idx >= len(prev_tasks):
return 0
prev_task = prev_tasks[idx]
if prev_task["progress"] < 1.0 or prev_task["digest"] != task["digest"] or not prev_task["chunk_ids"]:
return 0
task["chunk_ids"] = prev_task["chunk_ids"]
task["progress"] = 1.0
if "from_page" in task and "to_page" in task:
task["progress_msg"] = f"Page({task['from_page']}~{task['to_page']}): "
else:
task["progress_msg"] = ""
task["progress_msg"] += "reused previous task's chunks."
prev_task["chunk_ids"] = ""
return len(task["chunk_ids"].split())