|
| 1 | +import pandas as pd |
| 2 | +import hashlib |
| 3 | +import uuid |
| 4 | + |
| 5 | +from typing import Dict, List, Optional |
| 6 | +from qdrant_client import QdrantClient |
| 7 | +from qdrant_client.conversions import common_types as types |
| 8 | +from qdrant_client.http import models as rest |
| 9 | +from qdrant_client.http.exceptions import UnexpectedResponse |
| 10 | + |
| 11 | +from datapipe.types import DataSchema, MetaSchema, IndexDF, DataDF, data_to_index |
| 12 | +from datapipe.store.table_store import TableStore |
| 13 | + |
| 14 | + |
| 15 | +class CollectionParams(rest.CreateCollection): |
| 16 | + pass |
| 17 | + |
| 18 | + |
| 19 | +class QdrantStore(TableStore): |
| 20 | + def __init__( |
| 21 | + self, |
| 22 | + name: str, |
| 23 | + host: str, |
| 24 | + port: int, |
| 25 | + schema: DataSchema, |
| 26 | + pk_field: str, |
| 27 | + embedding_field: str, |
| 28 | + collection_params: CollectionParams |
| 29 | + ): |
| 30 | + super().__init__() |
| 31 | + self.name = name |
| 32 | + self.host = host |
| 33 | + self.port = port |
| 34 | + self.schema = schema |
| 35 | + self.pk_field = pk_field |
| 36 | + self.embedding_field = embedding_field |
| 37 | + self.collection_params = collection_params |
| 38 | + self.inited = False |
| 39 | + self.client: QdrantClient = None |
| 40 | + |
| 41 | + pk_columns = [column for column in self.schema if column.primary_key] |
| 42 | + |
| 43 | + if len(pk_columns) != 1 and pk_columns[0].name != pk_field: |
| 44 | + raise ValueError("Incorrect prymary key columns in schema") |
| 45 | + |
| 46 | + self.paylods_filelds = [column.name for column in self.schema if column.name != self.embedding_field] |
| 47 | + |
| 48 | + def __init(self): |
| 49 | + self.client = QdrantClient(host=self.host, port=self.port) |
| 50 | + |
| 51 | + try: |
| 52 | + self.client.get_collection(self.name) |
| 53 | + except UnexpectedResponse as e: |
| 54 | + if e.status_code == 404: |
| 55 | + self.client.http.collections_api.create_collection( |
| 56 | + collection_name=self.name, |
| 57 | + create_collection=self.collection_params |
| 58 | + ) |
| 59 | + |
| 60 | + def __check_init(self): |
| 61 | + if not self.inited: |
| 62 | + self.__init() |
| 63 | + self.inited = True |
| 64 | + |
| 65 | + def __get_ids(self, df): |
| 66 | + return df[self.pk_field].apply( |
| 67 | + lambda x: str(uuid.UUID(bytes=hashlib.md5(str(x).encode('utf-8')).digest())) |
| 68 | + ).to_list() |
| 69 | + |
| 70 | + def get_primary_schema(self) -> DataSchema: |
| 71 | + return [column for column in self.schema if column.primary_key] |
| 72 | + |
| 73 | + def get_meta_schema(self) -> MetaSchema: |
| 74 | + return [] |
| 75 | + |
| 76 | + def insert_rows(self, df: DataDF) -> None: |
| 77 | + self.__check_init() |
| 78 | + |
| 79 | + if len(df) == 0: |
| 80 | + return |
| 81 | + |
| 82 | + self.client.upsert( |
| 83 | + self.name, |
| 84 | + rest.Batch( |
| 85 | + ids=self.__get_ids(df), |
| 86 | + vectors=df[self.embedding_field].apply(list).to_list(), |
| 87 | + payloads=df[self.paylods_filelds].to_dict(orient='records') |
| 88 | + ), |
| 89 | + wait=True, |
| 90 | + ) |
| 91 | + |
| 92 | + def update_rows(self, df: DataDF) -> None: |
| 93 | + self.insert_rows(df) |
| 94 | + |
| 95 | + def delete_rows(self, idx: IndexDF) -> None: |
| 96 | + self.__check_init() |
| 97 | + |
| 98 | + if len(idx) == 0: |
| 99 | + return |
| 100 | + |
| 101 | + self.client.delete( |
| 102 | + self.name, |
| 103 | + rest.PointIdsList( |
| 104 | + points=self.__get_ids(idx) |
| 105 | + ), |
| 106 | + wait=True, |
| 107 | + ) |
| 108 | + |
| 109 | + def read_rows(self, idx: Optional[IndexDF] = None) -> DataDF: |
| 110 | + self.__check_init() |
| 111 | + |
| 112 | + if not idx: |
| 113 | + raise Exception("Qrand doesn't support full store reading") |
| 114 | + |
| 115 | + response = self.client.http.points_api.get_points( |
| 116 | + self.name, |
| 117 | + point_request=rest.PointRequest( |
| 118 | + ids=self.__get_ids(idx), |
| 119 | + with_payload=True, |
| 120 | + with_vector=True |
| 121 | + ) |
| 122 | + ) |
| 123 | + |
| 124 | + records = [] |
| 125 | + |
| 126 | + for point in response.result: |
| 127 | + record = point.payload |
| 128 | + record[self.embedding_field] = point.vector |
| 129 | + |
| 130 | + records.append(record) |
| 131 | + |
| 132 | + return pd.DataFrame.from_records(records)[[column.name for column in self.schema]] |
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