添加llmengine/base_collection.py llmengine/base_collection_delete.py llmengine/collection.py llmengine/collection_delete.py llmengine/milvus_collection.py llmengine/milvus_collection_delete.py test/collections/ test/deletecollections/
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23
llmengine/base_collection.py
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23
llmengine/base_collection.py
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from abc import ABC, abstractmethod
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from typing import Dict
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model_pathMap = {}
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def collection_register(model_key, Klass):
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"""Register a model class for a given model key."""
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global model_pathMap
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model_pathMap[model_key] = Klass
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def get_collection_class(model_path):
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"""Find the model class for a given model path."""
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for k, klass in model_pathMap.items():
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if len(model_path.split(k)) > 1:
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return klass
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print(f'{model_pathMap=}')
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return None
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class BaseCollection(ABC):
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@abstractmethod
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def create_collection(self, db_type: str) -> Dict:
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"""Create a Milvus collection for the given db_type."""
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pass
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23
llmengine/base_collection_delete.py
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23
llmengine/base_collection_delete.py
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from abc import ABC, abstractmethod
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from typing import Dict
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model_pathMap = {}
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def collection_delete_register(model_key, Klass):
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"""Register a model class for a given model key."""
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global model_pathMap
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model_pathMap[model_key] = Klass
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def get_collection_delete_class(model_path):
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"""Find the model class for a given model path."""
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for k, klass in model_pathMap.items():
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if len(model_path.split(k)) > 1:
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return klass
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print(f'{model_pathMap=}')
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return None
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class BaseCollectionDelete(ABC):
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@abstractmethod
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def delete_collection(self, db_type: str) -> Dict:
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"""Delete a Milvus collection for the given db_type."""
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pass
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77
llmengine/collection.py
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77
llmengine/collection.py
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from traceback import format_exc
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import os
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import sys
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import argparse
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from llmengine.milvus_collection import *
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from llmengine.base_collection import get_collection_class
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from typing import Dict
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from appPublic.registerfunction import RegisterFunction
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from appPublic.worker import awaitify
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from appPublic.log import debug, exception
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from ahserver.serverenv import ServerEnv
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from ahserver.globalEnv import stream_response
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from ahserver.webapp import webserver
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helptext = """Milvus Collection Creation API:
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1. Create Collection Endpoint:
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path: /v1/collections
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headers: {
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"Content-Type": "application/json"
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}
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data: {
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"db_type": "textdb"
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}
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response: {
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"status": "success",
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"collection_name": "ragdb_textdb",
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"message": "集合 ragdb_textdb 创建成功"
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}
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2. Docs Endpoint:
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path: /v1/docs
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response: This help text
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"""
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def init():
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rf = RegisterFunction()
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rf.register('collections', create_collection)
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rf.register('docs', docs)
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async def docs(request, params_kw, *params, **kw):
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return helptext
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async def create_collection(request, params_kw, *params, **kw):
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debug(f'{params_kw=}')
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se = ServerEnv()
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engine = se.engine
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f = awaitify(engine.create_collection)
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db_type = params_kw.get('db_type')
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if db_type is None:
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e = exception(f'db_type is None')
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raise e
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result = await f(db_type)
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debug(f'{result=}')
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return result
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def main():
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parser = argparse.ArgumentParser(prog="Milvus Collection Service")
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parser.add_argument('-w', '--workdir')
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parser.add_argument('-p', '--port')
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parser.add_argument('model_path')
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args = parser.parse_args()
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Klass = get_collection_class(args.model_path)
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if Klass is None:
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e = Exception(f'{args.model_path} has not mapping to a model class')
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exception(f'{e}, {format_exc()}')
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raise e
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se = ServerEnv()
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se.engine = Klass(args.model_path)
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workdir = args.workdir or os.getcwd()
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port = args.port
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debug(f'{args=}')
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webserver(init, workdir, port)
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if __name__ == '__main__':
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main()
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77
llmengine/collection_delete.py
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77
llmengine/collection_delete.py
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from traceback import format_exc
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import os
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import sys
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import argparse
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from llmengine.milvus_collection_delete import *
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from llmengine.base_collection_delete import get_collection_delete_class
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from typing import Dict
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from appPublic.registerfunction import RegisterFunction
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from appPublic.worker import awaitify
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from appPublic.log import debug, exception
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from ahserver.serverenv import ServerEnv
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from ahserver.globalEnv import stream_response
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from ahserver.webapp import webserver
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helptext = """Milvus Collection Deletion API:
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1. Delete Collection Endpoint:
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path: /v1/collections/delete
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headers: {
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"Content-Type": "application/json"
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}
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data: {
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"db_type": "textdb"
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}
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response: {
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"status": "success",
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"collection_name": "ragdb_textdb",
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"message": "集合 ragdb_textdb 删除成功"
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}
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2. Docs Endpoint:
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path: /v1/docs
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response: This help text
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"""
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def init():
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rf = RegisterFunction()
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rf.register('collections/delete', delete_collection)
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rf.register('docs', docs)
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async def docs(request, params_kw, *params, **kw):
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return helptext
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async def delete_collection(request, params_kw, *params, **kw):
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debug(f'{params_kw=}')
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se = ServerEnv()
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engine = se.engine
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f = awaitify(engine.delete_collection)
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db_type = params_kw.get('db_type')
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if db_type is None:
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e = exception(f'db_type is None')
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raise e
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result = await f(db_type)
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debug(f'{result=}')
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return result
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def main():
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parser = argparse.ArgumentParser(prog="Milvus Collection Delete Service")
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parser.add_argument('-w', '--workdir')
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parser.add_argument('-p', '--port')
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parser.add_argument('model_path')
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args = parser.parse_args()
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Klass = get_collection_delete_class(args.model_path)
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if Klass is None:
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e = Exception(f'{args.model_path} has not mapping to a model class')
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exception(f'{e}, {format_exc()}')
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raise e
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se = ServerEnv()
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se.engine = Klass(args.model_path)
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workdir = args.workdir or os.getcwd()
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port = args.port
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debug(f'{args=}')
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webserver(init, workdir, port)
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if __name__ == '__main__':
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main()
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144
llmengine/milvus_collection.py
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144
llmengine/milvus_collection.py
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import os
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import logging
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from typing import Dict
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from pymilvus import connections, utility, Collection, CollectionSchema, FieldSchema, DataType
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from llmengine.base_collection import BaseCollection, collection_register
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logger = logging.getLogger(__name__)
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CONFIG_PATH = os.getenv('CONFIG_PATH', '/share/wangmeihua/rag/conf/milvusconfig.yaml')
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try:
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with open(CONFIG_PATH, 'r', encoding='utf-8') as f:
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import yaml
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config = yaml.safe_load(f)
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MILVUS_DB_PATH = config['database']['milvus_db_path']
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except Exception as e:
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logger.error(f"加载配置文件 {CONFIG_PATH} 失败: {str(e)}")
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raise RuntimeError(f"无法加载配置文件: {str(e)}")
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class MilvusCollection(BaseCollection):
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def __init__(self, model_id):
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self.model_id = model_id
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self.db_path = MILVUS_DB_PATH
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def ensure_milvus_directory(self) -> None:
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"""确保 Milvus 数据库目录存在"""
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db_dir = os.path.dirname(self.db_path)
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if not os.path.exists(db_dir):
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os.makedirs(db_dir, exist_ok=True)
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logger.debug(f"创建 Milvus 目录: {db_dir}")
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if not os.access(db_dir, os.W_OK):
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raise RuntimeError(f"Milvus 目录 {db_dir} 不可写")
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def initialize_milvus_connection(self) -> None:
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"""初始化 Milvus 连接"""
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try:
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if not connections.has_connection("default"):
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connections.connect("default", uri=self.db_path)
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logger.debug(f"已连接到 Milvus Lite,路径: {self.db_path}")
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else:
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logger.debug("已存在 Milvus 连接,跳过重复连接")
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except Exception as e:
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logger.error(f"连接 Milvus 失败: {str(e)}")
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raise RuntimeError(f"连接 Milvus 失败: {str(e)}")
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def cleanup_milvus_connection(self) -> None:
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"""清理 Milvus 连接"""
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try:
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if connections.has_connection("default"):
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connections.disconnect("default")
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logger.debug("已断开 Milvus 连接")
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except Exception as e:
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logger.warning(f"断开 Milvus 连接失败: {str(e)}")
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def create_collection(self, db_type: str) -> Dict:
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"""
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为指定 db_type 创建 Milvus 集合。
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返回创建结果,包含集合名称和状态。
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"""
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try:
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# 参数验证
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if not db_type:
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raise ValueError("db_type 不能为空")
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if "_" in db_type:
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raise ValueError("db_type 不能包含下划线")
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if len(db_type) > 100:
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raise ValueError("db_type 的长度应小于 100")
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self.ensure_milvus_directory()
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self.initialize_milvus_connection()
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# 集合名称
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collection_name = f"ragdb_{db_type}"
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if len(collection_name) > 255:
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raise ValueError(f"集合名称 {collection_name} 超过 255 个字符")
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logger.debug(f"集合名称: {collection_name}")
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# 如果集合已存在,检查 schema 兼容性
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if utility.has_collection(collection_name):
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try:
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collection = Collection(collection_name)
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collection.load()
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logger.debug(f"集合 {collection_name} 已存在并加载成功")
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return {
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"status": "success",
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"collection_name": collection_name,
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"message": f"集合 {collection_name} 已存在"
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}
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except Exception as e:
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logger.error(f"加载集合 {collection_name} 失败: {str(e)}")
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raise RuntimeError(f"加载集合失败: {str(e)}")
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# 定义 schema
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fields = [
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FieldSchema(name="pk", dtype=DataType.VARCHAR, is_primary=True, max_length=36, auto_id=True),
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FieldSchema(name="userid", dtype=DataType.VARCHAR, max_length=100),
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FieldSchema(name="document_id", dtype=DataType.VARCHAR, max_length=36),
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FieldSchema(name="text", dtype=DataType.VARCHAR, max_length=65535),
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FieldSchema(name="vector", dtype=DataType.FLOAT_VECTOR, dim=1024),
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FieldSchema(name="filename", dtype=DataType.VARCHAR, max_length=255),
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FieldSchema(name="file_path", dtype=DataType.VARCHAR, max_length=1024),
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FieldSchema(name="upload_time", dtype=DataType.VARCHAR, max_length=64),
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FieldSchema(name="file_type", dtype=DataType.VARCHAR, max_length=64),
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]
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schema = CollectionSchema(
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fields=fields,
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description=f"{db_type} 数据集合,跨用户使用,包含 document_id 和元数据字段",
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auto_id=True,
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primary_field="pk",
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)
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# 创建集合
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try:
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collection = Collection(collection_name, schema)
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collection.create_index(
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field_name="vector",
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index_params={"index_type": "AUTOINDEX", "metric_type": "COSINE"}
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)
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for field in ["userid", "document_id", "filename", "file_path", "upload_time", "file_type"]:
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collection.create_index(
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field_name=field,
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index_params={"index_type": "INVERTED"}
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)
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collection.load()
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logger.debug(f"成功创建并加载集合: {collection_name}")
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return {
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"status": "success",
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"collection_name": collection_name,
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"message": f"集合 {collection_name} 创建成功"
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}
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except Exception as e:
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logger.error(f"创建集合 {collection_name} 失败: {str(e)}")
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raise RuntimeError(f"创建集合失败: {str(e)}")
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except Exception as e:
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logger.error(f"创建集合失败: {str(e)}")
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return {
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"status": "error",
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"collection_name": collection_name,
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"message": str(e)
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}
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finally:
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self.cleanup_milvus_connection()
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collection_register('Milvus', MilvusCollection)
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107
llmengine/milvus_collection_delete.py
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107
llmengine/milvus_collection_delete.py
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import os
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import logging
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from typing import Dict
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from pymilvus import connections, utility
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from llmengine.base_collection_delete import BaseCollectionDelete, collection_delete_register
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logger = logging.getLogger(__name__)
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CONFIG_PATH = os.getenv('CONFIG_PATH', '/share/wangmeihua/rag/conf/milvusconfig.yaml')
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try:
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with open(CONFIG_PATH, 'r', encoding='utf-8') as f:
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import yaml
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config = yaml.safe_load(f)
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MILVUS_DB_PATH = config['database']['milvus_db_path']
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except Exception as e:
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logger.error(f"加载配置文件 {CONFIG_PATH} 失败: {str(e)}")
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raise RuntimeError(f"无法加载配置文件: {str(e)}")
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class MilvusCollectionDelete(BaseCollectionDelete):
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def __init__(self, model_id):
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self.model_id = model_id
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self.db_path = MILVUS_DB_PATH
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def ensure_milvus_directory(self) -> None:
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"""确保 Milvus 数据库目录存在"""
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db_dir = os.path.dirname(self.db_path)
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if not os.path.exists(db_dir):
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os.makedirs(db_dir, exist_ok=True)
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logger.debug(f"创建 Milvus 目录: {db_dir}")
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if not os.access(db_dir, os.W_OK):
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raise RuntimeError(f"Milvus 目录 {db_dir} 不可写")
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def initialize_milvus_connection(self) -> None:
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"""初始化 Milvus 连接"""
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try:
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if not connections.has_connection("default"):
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connections.connect("default", uri=self.db_path)
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logger.debug(f"已连接到 Milvus Lite,路径: {self.db_path}")
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else:
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logger.debug("已存在 Milvus 连接,跳过重复连接")
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except Exception as e:
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logger.error(f"连接 Milvus 失败: {str(e)}")
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raise RuntimeError(f"连接 Milvus 失败: {str(e)}")
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def cleanup_milvus_connection(self) -> None:
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"""清理 Milvus 连接"""
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try:
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if connections.has_connection("default"):
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connections.disconnect("default")
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logger.debug("已断开 Milvus 连接")
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except Exception as e:
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logger.warning(f"断开 Milvus 连接失败: {str(e)}")
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def delete_collection(self, db_type: str) -> Dict:
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"""
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删除指定 db_type 的 Milvus 集合。
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返回删除结果,包含集合名称和状态。
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"""
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try:
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# 参数验证
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if not db_type:
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raise ValueError("db_type 不能为空")
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if "_" in db_type:
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raise ValueError("db_type 不能包含下划线")
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if len(db_type) > 100:
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raise ValueError("db_type 的长度应小于 100")
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self.ensure_milvus_directory()
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self.initialize_milvus_connection()
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# 集合名称
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collection_name = f"ragdb_{db_type}"
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logger.debug(f"集合名称: {collection_name}")
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# 检查集合是否存在
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if not utility.has_collection(collection_name):
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logger.debug(f"集合 {collection_name} 不存在")
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return {
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"status": "success",
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"collection_name": collection_name,
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"message": f"集合 {collection_name} 不存在,无需删除"
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}
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# 删除集合
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try:
|
||||
utility.drop_collection(collection_name)
|
||||
logger.debug(f"成功删除集合: {collection_name}")
|
||||
return {
|
||||
"status": "success",
|
||||
"collection_name": collection_name,
|
||||
"message": f"集合 {collection_name} 删除成功"
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"删除集合 {collection_name} 失败: {str(e)}")
|
||||
raise RuntimeError(f"删除集合失败: {str(e)}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"删除集合失败: {str(e)}")
|
||||
return {
|
||||
"status": "error",
|
||||
"collection_name": collection_name,
|
||||
"message": str(e)
|
||||
}
|
||||
finally:
|
||||
self.cleanup_milvus_connection()
|
||||
|
||||
collection_delete_register('Milvus', MilvusCollectionDelete)
|
50
test/collections/conf/config.json
Normal file
50
test/collections/conf/config.json
Normal file
@ -0,0 +1,50 @@
|
||||
{
|
||||
"filesroot":"$[workdir]$/files",
|
||||
"logger":{
|
||||
"name":"llmengine",
|
||||
"levelname":"info",
|
||||
"logfile":"$[workdir]$/logs/llmengine.log"
|
||||
},
|
||||
"website":{
|
||||
"paths":[
|
||||
["$[workdir]$/wwwroot",""]
|
||||
],
|
||||
"client_max_size":10000,
|
||||
"host":"0.0.0.0",
|
||||
"port":9992,
|
||||
"coding":"utf-8",
|
||||
"indexes":[
|
||||
"index.html",
|
||||
"index.ui"
|
||||
],
|
||||
"startswiths":[
|
||||
{
|
||||
"leading":"/idfile",
|
||||
"registerfunction":"idfile"
|
||||
},{
|
||||
"leading": "/v1/collections",
|
||||
"registerfunction": "collections"
|
||||
},{
|
||||
"leading": "/docs",
|
||||
"registerfunction": "docs"
|
||||
}
|
||||
],
|
||||
"processors":[
|
||||
[".tmpl","tmpl"],
|
||||
[".app","app"],
|
||||
[".ui","bui"],
|
||||
[".dspy","dspy"],
|
||||
[".md","md"]
|
||||
],
|
||||
"rsakey_oops":{
|
||||
"privatekey":"$[workdir]$/conf/rsa_private_key.pem",
|
||||
"publickey":"$[workdir]$/conf/rsa_public_key.pem"
|
||||
},
|
||||
"session_max_time":3000,
|
||||
"session_issue_time":2500,
|
||||
"session_redis_notuse":{
|
||||
"url":"redis://127.0.0.1:6379"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
0
test/collections/logs/llmengine.log
Normal file
0
test/collections/logs/llmengine.log
Normal file
3
test/collections/start.sh
Executable file
3
test/collections/start.sh
Executable file
@ -0,0 +1,3 @@
|
||||
#!/bin/bash
|
||||
export CONFIG_PATH=/share/wangmeihua/rag/conf/milvusconfig.yaml
|
||||
CUDA_VISIBLE_DEVICES=7 /share/vllm-0.8.5/bin/python -m llmengine.collection -p 8889 /share/wangmeihua/rag/conf/Milvus/milvus.db
|
50
test/deletecollections/conf/config.json
Normal file
50
test/deletecollections/conf/config.json
Normal file
@ -0,0 +1,50 @@
|
||||
{
|
||||
"filesroot":"$[workdir]$/files",
|
||||
"logger":{
|
||||
"name":"llmengine",
|
||||
"levelname":"info",
|
||||
"logfile":"$[workdir]$/logs/llmengine.log"
|
||||
},
|
||||
"website":{
|
||||
"paths":[
|
||||
["$[workdir]$/wwwroot",""]
|
||||
],
|
||||
"client_max_size":10000,
|
||||
"host":"0.0.0.0",
|
||||
"port":8888,
|
||||
"coding":"utf-8",
|
||||
"indexes":[
|
||||
"index.html",
|
||||
"index.ui"
|
||||
],
|
||||
"startswiths":[
|
||||
{
|
||||
"leading":"/idfile",
|
||||
"registerfunction":"idfile"
|
||||
},{
|
||||
"leading": "/v1/collections/delete",
|
||||
"registerfunction": "collections/delete"
|
||||
},{
|
||||
"leading": "/docs",
|
||||
"registerfunction": "docs"
|
||||
}
|
||||
],
|
||||
"processors":[
|
||||
[".tmpl","tmpl"],
|
||||
[".app","app"],
|
||||
[".ui","bui"],
|
||||
[".dspy","dspy"],
|
||||
[".md","md"]
|
||||
],
|
||||
"rsakey_oops":{
|
||||
"privatekey":"$[workdir]$/conf/rsa_private_key.pem",
|
||||
"publickey":"$[workdir]$/conf/rsa_public_key.pem"
|
||||
},
|
||||
"session_max_time":3000,
|
||||
"session_issue_time":2500,
|
||||
"session_redis_notuse":{
|
||||
"url":"redis://127.0.0.1:6379"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
0
test/deletecollections/logs/llmengine.log
Normal file
0
test/deletecollections/logs/llmengine.log
Normal file
3
test/deletecollections/start.sh
Executable file
3
test/deletecollections/start.sh
Executable file
@ -0,0 +1,3 @@
|
||||
#!/bin/bash
|
||||
export CONFIG_PATH=/share/wangmeihua/rag/conf/milvusconfig.yaml
|
||||
CUDA_VISIBLE_DEVICES=7 /share/vllm-0.8.5/bin/python -m llmengine.collection_delete -p 8888 /share/wangmeihua/rag/conf/Milvus/milvus.db
|
Loading…
Reference in New Issue
Block a user