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bugfix

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yumoqing 2025-09-11 14:33:23 +08:00
parent 9e7ff6c71f
commit e590c1084f
2 changed files with 163 additions and 173 deletions
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261
rag/folderinfo.py
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@ -17,6 +17,7 @@ import traceback
from filetxt.loader import fileloader from filetxt.loader import fileloader
from ahserver.serverenv import get_serverenv from ahserver.serverenv import get_serverenv
from typing import List, Dict, Any from typing import List, Dict, Any
from rag.service_opts import get_service_params, sor_get_service_params
import json import json
class RagFileMgr(FileMgr): class RagFileMgr(FileMgr):
@ -43,73 +44,6 @@ where a.orgid = b.orgid
return r.quota, r.expired_date return r.quota, r.expired_date
return None, None return None, None
async def get_service_params(self,sor, orgid):
""" 根据 orgid 从数据库获取服务参数 (仅 upappid)，假设 service_opts 表返回单条记录。 """
sql_opts = """
SELECT embedding_id, vdb_id, reranker_id, triples_id, gdb_id, entities_id
FROM service_opts
WHERE orgid = ${orgid}$
"""
opts_result = await sor.sqlExe(sql_opts, {"orgid": orgid})
if not opts_result:
error(f"未找到 orgid={orgid} 的服务配置")
return None
opts = opts_result[0]
# 收集服务 ID
service_ids = set()
for key in ['embedding_id', 'vdb_id', 'reranker_id', 'triples_id', 'gdb_id', 'entities_id']:
if opts[key]:
service_ids.add(opts[key])
# 检查 service_ids 是否为空
if not service_ids:
error(f"未找到任何服务 ID for orgid={orgid}")
return None
# 手动构造 IN 子句的 ID 列表
id_list = ','.join([f"'{id}'" for id in service_ids]) # 确保每个 ID 被单引号包裹
sql_services = """
SELECT id, name, upappid
FROM ragservices
WHERE id IN ${id_list}$
"""
services_result = await sor.sqlExe(sql_services, {'id_list': id_list})
if not services_result:
error(f"未找到服务 ID {service_ids} 的 ragservices 配置")
return None
# 构建服务参数字典，基于 name 字段匹配，仅存储 upappid
service_params = {
'embedding': None,
'vdb': None,
'reranker': None,
'triples': None,
'gdb': None,
'entities': None
}
for service in services_result:
name = service['name']
if name == 'bgem3嵌入':
service_params['embedding'] = service['upappid']
elif name == 'milvus向量检索':
service_params['vdb'] = service['upappid']
elif name == 'bgem2v3重排':
service_params['reranker'] = service['upappid']
elif name == 'mrebel三元组抽取':
service_params['triples'] = service['upappid']
elif name == 'neo4j删除知识库':
service_params['gdb'] = service['upappid']
elif name == 'small实体抽取':
service_params['entities'] = service['upappid']
# 检查是否所有服务参数都已填充
missing_services = [k for k, v in service_params.items() if v is None]
if missing_services:
error(f"未找到以下服务的配置: {missing_services}")
return None
return service_params
async def file_uploaded(self, request, ns, userid): async def file_uploaded(self, request, ns, userid):
"""将文档插入 Milvus 并抽取三元组到 Neo4j""" """将文档插入 Milvus 并抽取三元组到 Neo4j"""
debug(f'Received ns: {ns=}') debug(f'Received ns: {ns=}')
@ -128,45 +62,30 @@ where a.orgid = b.orgid
timings = {} timings = {}
start_total = time.time() start_total = time.time()
service_params = await get_service_params(orgid)
chunks = await self.get_doucment_chunks(realpath)
embeddings = await self.docs_embedding(chunks)
await self.embedding_2_vdb(id, fiid, orgid, realpath, embedding)
triples = await self.get_triples(chunks)
await self.triple2graphdb(id, fiid, orgid, realpath, triples)
return
try: try:
if not orgid or not fiid or not id: if not orgid or not fiid or not id:
raise ValueError("orgid、fiid 和 id 不能为空") raise ValueError("orgid、fiid 和 id 不能为空")
if len(orgid) > 32 or len(fiid) > 255: if len(orgid) > 32 or len(fiid) > 255:
raise ValueError("orgid 或 fiid 的长度超出限制") raise ValueError("orgid 或 fiid 的长度超出限制")
if not os.path.exists(realpath): if not os.path.exists(realpath):
raise ValueError(f"文件 {realpath} 不存在") raise ValueError(f"文件 {realpath} 不存在")
# 检查 hashvalue 是否已存在
db = DBPools()
dbname = env.get_module_dbname('rag')
sql_check_hash = """
SELECT hashvalue
FROM file
WHERE hashvalue = ${hashvalue}$
"""
async with db.sqlorContext(dbname) as sor:
hash_result = await sor.sqlExe(sql_check_hash, {"hashvalue": hashvalue})
if hash_result:
debug(f"文件已存在: hashvalue={hashvalue}")
timings["total"] = time.time() - start_total
return {
"status": "error",
"document_id": id,
"collection_name": "ragdb",
"timings": timings,
"message": f"文件已存在: hashvalue={hashvalue}",
"status_code": 400
}
# 获取服务参数 # 获取服务参数
service_params = await self.get_service_params(sor, orgid) service_params = await get_service_params(orgid)
if not service_params: if not service_params:
raise ValueError("无法获取服务参数") raise ValueError("无法获取服务参数")
supported_formats = {'pdf', 'docx', 'xlsx', 'pptx', 'csv', 'txt'} supported_formats = {'pdf', 'docx', 'xlsx', 'pptx', 'csv', 'txt'}
ext = realpath.rsplit('.', 1)[1].lower() if '.' in realpath else '' ext = realpath.rsplit('.', 1)[1].lower() if '.' in realpath else ''
if ext not in supported_formats: if ext not in supported_formats:
raise ValueError(f"不支持的文件格式: {ext}, 支持的格式: {', '.join(supported_formats)}") raise ValueError(f"不支持的文件格式: {ext}, 支持的格式: {', '.join(supported_formats)}")
debug(f"加载文件: {realpath}") debug(f"加载文件: {realpath}")
start_load = time.time() start_load = time.time()
@ -176,22 +95,22 @@ where a.orgid = b.orgid
timings["load_file"] = time.time() - start_load timings["load_file"] = time.time() - start_load
debug(f"加载文件耗时: {timings['load_file']:.2f} 秒, 文本长度: {len(text)}") debug(f"加载文件耗时: {timings['load_file']:.2f} 秒, 文本长度: {len(text)}")
if not text or not text.strip(): if not text or not text.strip():
raise ValueError(f"文件 {realpath} 加载为空") raise ValueError(f"文件 {realpath} 加载为空")
document = Document(page_content=text) document = Document(page_content=text)
text_splitter = RecursiveCharacterTextSplitter( text_splitter = RecursiveCharacterTextSplitter(
chunk_size=500, chunk_size=500,
chunk_overlap=100, chunk_overlap=100,
length_function=len) length_function=len)
debug("开始分片文件内容") debug("开始分片文件内容")
start_split = time.time() start_split = time.time()
chunks = text_splitter.split_documents([document]) chunks = text_splitter.split_documents([document])
timings["split_text"] = time.time() - start_split timings["split_text"] = time.time() - start_split
debug( debug(
f"文本分片耗时: {timings['split_text']:.2f} 秒, 分片数量: {len(chunks)}, 分片内容: {[chunk.page_content[:50] for chunk in chunks[:5]]}") f"文本分片耗时: {timings['split_text']:.2f} 秒, 分片数量: {len(chunks)}, 分片内容: {[chunk.page_content[:50] for chunk in chunks[:5]]}")
debug(f"分片内容: {[chunk.page_content[:100] + '...' for chunk in chunks]}") debug(f"分片内容: {[chunk.page_content[:100] + '...' for chunk in chunks]}")
if not chunks: if not chunks:
raise ValueError(f"文件 {realpath} 未生成任何文档块") raise ValueError(f"文件 {realpath} 未生成任何文档块")
filename = os.path.basename(realpath).rsplit('.', 1)[0] filename = os.path.basename(realpath).rsplit('.', 1)[0]
upload_time = datetime.now().isoformat() upload_time = datetime.now().isoformat()
@ -201,23 +120,23 @@ where a.orgid = b.orgid
texts = [chunk.page_content for chunk in chunks] texts = [chunk.page_content for chunk in chunks]
embeddings = [] embeddings = []
for i in range(0, len(texts), 10): # 每次处理 10 个文本块 for i in range(0, len(texts), 10): # 每次处理 10 个文本块
batch_texts = texts[i:i + 10] batch_texts = texts[i:i + 10]
batch_embeddings = await api_service.get_embeddings( batch_embeddings = await api_service.get_embeddings(
request=request, request=request,
texts=batch_texts, texts=batch_texts,
upappid=service_params['embedding'], upappid=service_params['embedding'],
apiname="BAAI/bge-m3", apiname="BAAI/bge-m3",
user=userid user=userid
) )
embeddings.extend(batch_embeddings) embeddings.extend(batch_embeddings)
if not embeddings or not all(len(vec) == 1024 for vec in embeddings): if not embeddings or not all(len(vec) == 1024 for vec in embeddings):
raise ValueError("所有嵌入向量必须是长度为 1024 的浮点数列表") raise ValueError("所有嵌入向量必须是长度为 1024 的浮点数列表")
timings["generate_embeddings"] = time.time() - start_embedding timings["generate_embeddings"] = time.time() - start_embedding
debug(f"生成嵌入向量耗时: {timings['generate_embeddings']:.2f} 秒, 嵌入数量: {len(embeddings)}") debug(f"生成嵌入向量耗时: {timings['generate_embeddings']:.2f} 秒, 嵌入数量: {len(embeddings)}")
chunks_data = [] chunks_data = []
for i, chunk in enumerate(chunks): for i, chunk in enumerate(chunks):
chunks_data.append({ chunks_data.append({
"userid": orgid, "userid": orgid,
"knowledge_base_id": fiid, "knowledge_base_id": fiid,
"text": chunk.page_content, "text": chunk.page_content,
@ -227,38 +146,38 @@ where a.orgid = b.orgid
"file_path": realpath, "file_path": realpath,
"upload_time": upload_time, "upload_time": upload_time,
"file_type": ext, "file_type": ext,
}) })
debug(f"调用插入文件端点: {realpath}") debug(f"调用插入文件端点: {realpath}")
start_milvus = time.time() start_milvus = time.time()
for i in range(0, len(chunks_data), 10): # 每次处理 10 条数据 for i in range(0, len(chunks_data), 10): # 每次处理 10 条数据
batch_chunks = chunks_data[i:i + 10] batch_chunks = chunks_data[i:i + 10]
result = await api_service.milvus_insert_document( result = await api_service.milvus_insert_document(
request=request, request=request,
chunks=batch_chunks, chunks=batch_chunks,
db_type=db_type, db_type=db_type,
upappid=service_params['vdb'], upappid=service_params['vdb'],
apiname="milvus/insertdocument", apiname="milvus/insertdocument",
user=userid user=userid
) )
if result.get("status") != "success": if result.get("status") != "success":
raise ValueError(result.get("message", "Milvus 插入失败")) raise ValueError(result.get("message", "Milvus 插入失败"))
timings["insert_milvus"] = time.time() - start_milvus timings["insert_milvus"] = time.time() - start_milvus
debug(f"Milvus 插入耗时: {timings['insert_milvus']:.2f} 秒") debug(f"Milvus 插入耗时: {timings['insert_milvus']:.2f} 秒")
if result.get("status") != "success": if result.get("status") != "success":
timings["total"] = time.time() - start_total timings["total"] = time.time() - start_total
return {"status": "error", "document_id": id, "timings": timings, return {"status": "error", "document_id": id, "timings": timings,
"message": result.get("message", "未知错误"), "status_code": 400} "message": result.get("message", "未知错误"), "status_code": 400}
debug("调用三元组抽取服务") debug("调用三元组抽取服务")
start_triples = time.time() start_triples = time.time()
unique_triples = [] unique_triples = []
try: try:
chunk_texts = [doc.page_content for doc in chunks] chunk_texts = [doc.page_content for doc in chunks]
debug(f"处理 {len(chunk_texts)} 个分片进行三元组抽取") debug(f"处理 {len(chunk_texts)} 个分片进行三元组抽取")
triples = [] triples = []
for i, chunk in enumerate(chunk_texts): for i, chunk in enumerate(chunk_texts):
result = await api_service.extract_triples( result = await api_service.extract_triples(
request=request, request=request,
text=chunk, text=chunk,
@ -283,16 +202,16 @@ where a.orgid = b.orgid
if (existing['head'].lower() == t['head'].lower() and if (existing['head'].lower() == t['head'].lower() and
existing['tail'].lower() == t['tail'].lower() and existing['tail'].lower() == t['tail'].lower() and
len(t['type']) > len(existing['type'])): len(t['type']) > len(existing['type'])):
unique_triples.remove(existing) unique_triples.remove(existing)
unique_triples.append(t) unique_triples.append(t)
debug(f"替换三元组为更具体类型: {t}") debug(f"替换三元组为更具体类型: {t}")
break break
timings["extract_triples"] = time.time() - start_triples timings["extract_triples"] = time.time() - start_triples
debug( debug(
f"三元组抽取耗时: {timings['extract_triples']:.2f} 秒, 抽取到 {len(unique_triples)} 个三元组: {unique_triples[:5]}") f"三元组抽取耗时: {timings['extract_triples']:.2f} 秒, 抽取到 {len(unique_triples)} 个三元组: {unique_triples[:5]}")
if unique_triples: if unique_triples:
debug(f"抽取到 {len(unique_triples)} 个三元组，调用 Neo4j 服务插入") debug(f"抽取到 {len(unique_triples)} 个三元组，调用 Neo4j 服务插入")
start_neo4j = time.time() start_neo4j = time.time()
for i in range(0, len(unique_triples), 30): # 每次插入 30 个三元组 for i in range(0, len(unique_triples), 30): # 每次插入 30 个三元组
@ -322,11 +241,11 @@ where a.orgid = b.orgid
info(f"文件 {realpath} 三元组成功插入 Neo4j: {neo4j_result.get('message')}") info(f"文件 {realpath} 三元组成功插入 Neo4j: {neo4j_result.get('message')}")
timings["insert_neo4j"] = time.time() - start_neo4j timings["insert_neo4j"] = time.time() - start_neo4j
debug(f"Neo4j 插入耗时: {timings['insert_neo4j']:.2f} 秒") debug(f"Neo4j 插入耗时: {timings['insert_neo4j']:.2f} 秒")
else: else:
debug(f"文件 {realpath} 未抽取到三元组") debug(f"文件 {realpath} 未抽取到三元组")
timings["insert_neo4j"] = 0.0 timings["insert_neo4j"] = 0.0
except Exception as e: except Exception as e:
timings["extract_triples"] = time.time() - start_triples if "extract_triples" not in timings else \ timings["extract_triples"] = time.time() - start_triples if "extract_triples" not in timings else \
timings["extract_triples"] timings["extract_triples"]
timings["insert_neo4j"] = time.time() - start_neo4j if "insert_neo4j" not in timings else timings[ timings["insert_neo4j"] = time.time() - start_neo4j if "insert_neo4j" not in timings else timings[
@ -386,36 +305,34 @@ where a.orgid = b.orgid
collection_name = "ragdb" if not db_type else f"ragdb_{db_type}" collection_name = "ragdb" if not db_type else f"ragdb_{db_type}"
try: try:
required_fields = ['id', 'realpath', 'fiid', 'ownerid'] required_fields = ['id', 'realpath', 'fiid', 'ownerid']
missing_fields = [field for field in required_fields if not rec.get(field, '')] missing_fields = [field for field in required_fields if not rec.get(field, '')]
if missing_fields: if missing_fields:
raise ValueError(f"缺少必填字段: {', '.join(missing_fields)}") raise ValueError(f"缺少必填字段: {', '.join(missing_fields)}")
# 获取服务参数 # 获取服务参数
service_params = await self.get_service_params(sor, orgid) service_params = await get_service_params(orgid)
if not service_params: if not service_params:
raise ValueError("无法获取服务参数") raise ValueError("无法获取服务参数")
debug( debug(f"调用删除文件端点: userid={orgid}, file_path={realpath}, knowledge_base_id={fiid}, document_id={id}")
f"调用删除文件端点: userid={orgid}, file_path={realpath}, knowledge_base_id={fiid}, document_id={id}") milvus_result = await api_service.milvus_delete_document(
milvus_result = await api_service.milvus_delete_document( request=request,
request=request, userid=orgid,
userid=orgid, file_path=realpath,
file_path=realpath, knowledge_base_id=fiid,
knowledge_base_id=fiid, document_id=id,
document_id=id, db_type=db_type,
db_type=db_type, upappid=service_params['vdb'],
upappid=service_params['vdb'], apiname="milvus/deletedocument",
apiname="milvus/deletedocument", user=userid
user=userid )
)
if milvus_result.get("status") != "success": if milvus_result.get("status") != "success":
raise ValueError(milvus_result.get("message", "Milvus 删除失败")) raise ValueError(milvus_result.get("message", "Milvus 删除失败"))
neo4j_deleted_nodes = 0 neo4j_deleted_nodes = 0
neo4j_deleted_rels = 0 neo4j_deleted_rels = 0
try:
debug(f"调用 Neo4j 删除文档端点: document_id={id}") debug(f"调用 Neo4j 删除文档端点: document_id={id}")
neo4j_result = await api_service.neo4j_delete_document( neo4j_result = await api_service.neo4j_delete_document(
request=request, request=request,
@ -433,26 +350,24 @@ where a.orgid = b.orgid
total_nodes_deleted += nodes_deleted total_nodes_deleted += nodes_deleted
total_rels_deleted += rels_deleted total_rels_deleted += rels_deleted
info(f"成功删除 document_id={id} 的 {nodes_deleted} 个 Neo4j 节点和 {rels_deleted} 个关系") info(f"成功删除 document_id={id} 的 {nodes_deleted} 个 Neo4j 节点和 {rels_deleted} 个关系")
except Exception as e:
error(f"删除 document_id={id} 的 Neo4j 数据失败: {str(e)}")
results.append({ results.append({
"status": "success", "status": "success",
"collection_name": collection_name, "collection_name": collection_name,
"document_id": id, "document_id": id,
"message": f"成功删除文件 {realpath} 的 Milvus 记录，{neo4j_deleted_nodes} 个 Neo4j 节点，{neo4j_deleted_rels} 个 Neo4j 关系", "message": f"成功删除文件 {realpath} 的 Milvus 记录，{neo4j_deleted_nodes} 个 Neo4j 节点，{neo4j_deleted_rels} 个 Neo4j 关系",
"status_code": 200 "status_code": 200
}) })
except Exception as e: except Exception as e:
error(f"删除文档 {realpath} 失败: {str(e)}, 堆栈: {traceback.format_exc()}") error(f"删除文档 {realpath} 失败: {str(e)}, 堆栈: {traceback.format_exc()}")
results.append({ results.append({
"status": "error", "status": "error",
"collection_name": collection_name, "collection_name": collection_name,
"document_id": id, "document_id": id,
"message": f"删除文档 {realpath} 失败: {str(e)}", "message": f"删除文档 {realpath} 失败: {str(e)}",
"status_code": 400 "status_code": 400
}) })
return { return {
"status": "success" if all(r["status"] == "success" for r in results) else "partial", "status": "success" if all(r["status"] == "success" for r in results) else "partial",

75
rag/service_opts.py Normal file
View File

@ -0,0 +1,75 @@
from ahserver.serverenv import get_serverenv
async def sor_get_service_params(sor, orgid):
""" 根据 orgid 从数据库获取服务参数 (仅 upappid)，假设 service_opts 表返回单条记录。 """
sql_opts = """
SELECT embedding_id, vdb_id, reranker_id, triples_id, gdb_id, entities_id
FROM service_opts
WHERE orgid = ${orgid}$
"""
opts_result = await sor.sqlExe(sql_opts, {"orgid": orgid})
if not opts_result:
error(f"未找到 orgid={orgid} 的服务配置")
return None
opts = opts_result[0]
# 收集服务 ID
service_ids = set()
for key in ['embedding_id', 'vdb_id', 'reranker_id', 'triples_id', 'gdb_id', 'entities_id']:
if opts[key]:
service_ids.add(opts[key])
# 检查 service_ids 是否为空
if not service_ids:
error(f"未找到任何服务 ID for orgid={orgid}")
return None
# 手动构造 IN 子句的 ID 列表
id_list = ','.join([f"'{id}'" for id in service_ids]) # 确保每个 ID 被单引号包裹
sql_services = """
SELECT id, name, upappid
FROM ragservices
WHERE id IN ${id_list}$
"""
services_result = await sor.sqlExe(sql_services, {'id_list': id_list})
if not services_result:
error(f"未找到服务 ID {service_ids} 的 ragservices 配置")
return None
# 构建服务参数字典，基于 name 字段匹配，仅存储 upappid
service_params = {
'embedding': None,
'vdb': None,
'reranker': None,
'triples': None,
'gdb': None,
'entities': None
}
for service in services_result:
name = service['name']
if name == 'bgem3嵌入':
service_params['embedding'] = service['upappid']
elif name == 'milvus向量检索':
service_params['vdb'] = service['upappid']
elif name == 'bgem2v3重排':
service_params['reranker'] = service['upappid']
elif name == 'mrebel三元组抽取':
service_params['triples'] = service['upappid']
elif name == 'neo4j删除知识库':
service_params['gdb'] = service['upappid']
elif name == 'small实体抽取':
service_params['entities'] = service['upappid']
# 检查是否所有服务参数都已填充
missing_services = [k for k, v in service_params.items() if v is None]
if missing_services:
error(f"未找到以下服务的配置: {missing_services}")
return None
return service_params
async def get_service_params(orgid):
db = DBPools()
dbname = get_serverenv('get_module_dbname')('rag')
async with db.sqlorContext(dbname) as sor:
return await sor_get_server_params(sor, orgid)
return None