File size: 6,082 Bytes
6be3dd5 |
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 |
#
# Copyright 2019 The RAG Flow 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 base64
import hashlib
import pathlib
import re
from elasticsearch_dsl import Q
from flask import request
from flask_login import login_required, current_user
from rag.nlp import search, huqie
from rag.utils import ELASTICSEARCH, rmSpace
from web_server.db import LLMType
from web_server.db.services import duplicate_name
from web_server.db.services.kb_service import KnowledgebaseService
from web_server.db.services.llm_service import TenantLLMService
from web_server.db.services.user_service import UserTenantService
from web_server.utils.api_utils import server_error_response, get_data_error_result, validate_request
from web_server.utils import get_uuid
from web_server.db.services.document_service import DocumentService
from web_server.settings import RetCode
from web_server.utils.api_utils import get_json_result
from rag.utils.minio_conn import MINIO
from web_server.utils.file_utils import filename_type
retrival = search.Dealer(ELASTICSEARCH, None)
@manager.route('/list', methods=['POST'])
@login_required
@validate_request("doc_id")
def list():
req = request.json
doc_id = req["doc_id"]
page = req.get("page", 1)
size = req.get("size", 30)
question = req.get("keywords", "")
try:
tenants = UserTenantService.query(user_id=current_user.id)
if not tenants:
return get_data_error_result(retmsg="Tenant not found!")
res = retrival.search({
"doc_ids": [doc_id], "page": page, "size": size, "question": question
}, search.index_name(tenants[0].tenant_id))
return get_json_result(data=res)
except Exception as e:
if str(e).find("not_found") > 0:
return get_json_result(data=False, retmsg=f'Index not found!',
retcode=RetCode.DATA_ERROR)
return server_error_response(e)
@manager.route('/get', methods=['GET'])
@login_required
def get():
chunk_id = request.args["chunk_id"]
try:
tenants = UserTenantService.query(user_id=current_user.id)
if not tenants:
return get_data_error_result(retmsg="Tenant not found!")
res = ELASTICSEARCH.get(chunk_id, search.index_name(tenants[0].tenant_id))
if not res.get("found"):return server_error_response("Chunk not found")
id = res["_id"]
res = res["_source"]
res["chunk_id"] = id
k = []
for n in res.keys():
if re.search(r"(_vec$|_sm_)", n):
k.append(n)
if re.search(r"(_tks|_ltks)", n):
res[n] = rmSpace(res[n])
for n in k: del res[n]
return get_json_result(data=res)
except Exception as e:
if str(e).find("NotFoundError") >= 0:
return get_json_result(data=False, retmsg=f'Chunk not found!',
retcode=RetCode.DATA_ERROR)
return server_error_response(e)
@manager.route('/set', methods=['POST'])
@login_required
@validate_request("doc_id", "chunk_id", "content_ltks", "important_kwd", "docnm_kwd")
def set():
req = request.json
d = {"id": req["chunk_id"]}
d["content_ltks"] = huqie.qie(req["content_ltks"])
d["content_sm_ltks"] = huqie.qieqie(d["content_ltks"])
d["important_kwd"] = req["important_kwd"]
d["important_tks"] = huqie.qie(" ".join(req["important_kwd"]))
try:
tenant_id = DocumentService.get_tenant_id(req["doc_id"])
if not tenant_id: return get_data_error_result(retmsg="Tenant not found!")
embd_mdl = TenantLLMService.model_instance(tenant_id, LLMType.EMBEDDING.value)
v, c = embd_mdl.encode([req["docnm_kwd"], req["content_ltks"]])
v = 0.1 * v[0] + 0.9 * v[1]
d["q_%d_vec"%len(v)] = v.tolist()
ELASTICSEARCH.upsert([d], search.index_name(tenant_id))
return get_json_result(data=True)
except Exception as e:
return server_error_response(e)
@manager.route('/create', methods=['POST'])
@login_required
@validate_request("doc_id", "content_ltks", "important_kwd")
def set():
req = request.json
md5 = hashlib.md5()
md5.update((req["content_ltks"] + req["doc_id"]).encode("utf-8"))
chunck_id = md5.hexdigest()
d = {"id": chunck_id, "content_ltks": huqie.qie(req["content_ltks"])}
d["content_sm_ltks"] = huqie.qieqie(d["content_ltks"])
d["important_kwd"] = req["important_kwd"]
d["important_tks"] = huqie.qie(" ".join(req["important_kwd"]))
try:
e, doc = DocumentService.get_by_id(req["doc_id"])
if not e: return get_data_error_result(retmsg="Document not found!")
d["kb_id"] = [doc.kb_id]
d["docnm_kwd"] = doc.name
d["doc_id"] = doc.id
tenant_id = DocumentService.get_tenant_id(req["doc_id"])
if not tenant_id: return get_data_error_result(retmsg="Tenant not found!")
embd_mdl = TenantLLMService.model_instance(tenant_id, LLMType.EMBEDDING.value)
v, c = embd_mdl.encode([doc.name, req["content_ltks"]])
DocumentService.increment_chunk_num(req["doc_id"], doc.kb_id, c, 1, 0)
v = 0.1 * v[0] + 0.9 * v[1]
d["q_%d_vec"%len(v)] = v.tolist()
ELASTICSEARCH.upsert([d], search.index_name(tenant_id))
return get_json_result(data={"chunk_id": chunck_id})
except Exception as e:
return server_error_response(e)
|