Files
ragflow/rag/flow/tests/client.py
Kevin Hu cbf04ee470 Feat: Use data pipeline to visualize the parsing configuration of the knowledge base (#10423)
### What problem does this PR solve?

#9869

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

---------

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2025-10-09 12:36:19 +08:00

62 lines
2.1 KiB
Python

#
# Copyright 2025 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 argparse
import json
import os
import time
from concurrent.futures import ThreadPoolExecutor
import trio
from api import settings
from rag.flow.pipeline import Pipeline
def print_logs(pipeline: Pipeline):
last_logs = "[]"
while True:
time.sleep(5)
logs = pipeline.fetch_logs()
logs_str = json.dumps(logs, ensure_ascii=False)
if logs_str != last_logs:
print(logs_str)
last_logs = logs_str
if __name__ == "__main__":
parser = argparse.ArgumentParser()
dsl_default_path = os.path.join(
os.path.dirname(os.path.realpath(__file__)),
"dsl_examples",
"general_pdf_all.json",
)
parser.add_argument("-s", "--dsl", default=dsl_default_path, help="input dsl", action="store", required=False)
parser.add_argument("-d", "--doc_id", default=False, help="Document ID", action="store", required=True)
parser.add_argument("-t", "--tenant_id", default=False, help="Tenant ID", action="store", required=True)
args = parser.parse_args()
settings.init_settings()
pipeline = Pipeline(open(args.dsl, "r").read(), tenant_id=args.tenant_id, doc_id=args.doc_id, task_id="xxxx", flow_id="xxx")
pipeline.reset()
exe = ThreadPoolExecutor(max_workers=5)
thr = exe.submit(print_logs, pipeline)
# queue_dataflow(dsl=open(args.dsl, "r").read(), tenant_id=args.tenant_id, doc_id=args.doc_id, task_id="xxxx", flow_id="xxx", priority=0)
trio.run(pipeline.run)
thr.result()