Files
ragflow/rag/graphrag/light/smoke.py
Lynn dc4b82523b Feat: tenant llm provider (#14595)
### What problem does this PR solve?

Python implementation of the Go-based model_provider API suite.

### Type of change

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

---------

Co-authored-by: bill <yibie_jingnian@163.com>
2026-05-29 17:39:41 +08:00

98 lines
2.7 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 argparse
import asyncio
import json
import networkx as nx
import logging
from common.constants import LLMType
from api.db.services.document_service import DocumentService
from api.db.services.knowledgebase_service import KnowledgebaseService
from api.db.services.llm_service import LLMBundle
from api.db.joint_services.tenant_model_service import get_tenant_default_model_by_type, get_model_config_from_provider_instance
from rag.graphrag.general.index import update_graph
from rag.graphrag.light.graph_extractor import GraphExtractor
from common import settings
settings.init_settings()
def callback(prog=None, msg="Processing..."):
logging.info(msg)
async def main():
parser = argparse.ArgumentParser()
parser.add_argument(
"-t",
"--tenant_id",
default=False,
help="Tenant ID",
action="store",
required=True,
)
parser.add_argument(
"-d",
"--doc_id",
default=False,
help="Document ID",
action="store",
required=True,
)
args = parser.parse_args()
e, doc = DocumentService.get_by_id(args.doc_id)
if not e:
raise LookupError("Document not found.")
kb_id = doc.kb_id
chunks = [
d["content_with_weight"]
for d in settings.retriever.chunk_list(
args.doc_id,
args.tenant_id,
[kb_id],
max_count=6,
fields=["content_with_weight"],
)
]
llm_config = get_tenant_default_model_by_type(args.tenant_id, LLMType.CHAT)
llm_bdl = LLMBundle(args.tenant_id, llm_config)
_, kb = KnowledgebaseService.get_by_id(kb_id)
embd_model_config = get_model_config_from_provider_instance(args.tenant_id, LLMType.EMBEDDING, kb.embd_id)
embed_bdl = LLMBundle(args.tenant_id, embd_model_config)
graph, doc_ids = await update_graph(
GraphExtractor,
args.tenant_id,
kb_id,
args.doc_id,
chunks,
"English",
llm_bdl,
embed_bdl,
callback,
)
print(json.dumps(nx.node_link_data(graph), ensure_ascii=False, indent=2))
if __name__ == "__main__":
asyncio.run(main)