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feat: support MyScale vector database (#6092)
This commit is contained in:
Zhuo Qiu
GitHub
parent
c606295ea6
commit
63e34e5227
3
.github/workflows/api-tests.yml
vendored
3
.github/workflows/api-tests.yml
vendored
@ -75,7 +75,7 @@ jobs:
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- name: Run Workflow
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run: poetry run -C api bash dev/pytest/pytest_workflow.sh
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- name: Set up Vector Stores (Weaviate, Qdrant, PGVector, Milvus, PgVecto-RS, Chroma)
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- name: Set up Vector Stores (Weaviate, Qdrant, PGVector, Milvus, PgVecto-RS, Chroma, MyScale)
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uses: hoverkraft-tech/compose-action@v2.0.0
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with:
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compose-file: |
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@ -89,5 +89,6 @@ jobs:
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pgvecto-rs
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pgvector
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chroma
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myscale
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- name: Test Vector Stores
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run: poetry run -C api bash dev/pytest/pytest_vdb.sh
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@ -83,7 +83,7 @@ OCI_REGION=your-region
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WEB_API_CORS_ALLOW_ORIGINS=http://127.0.0.1:3000,*
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CONSOLE_CORS_ALLOW_ORIGINS=http://127.0.0.1:3000,*
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# Vector database configuration, support: weaviate, qdrant, milvus, relyt, pgvecto_rs, pgvector, pgvector, chroma, opensearch, tidb_vector
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# Vector database configuration, support: weaviate, qdrant, milvus, myscale, relyt, pgvecto_rs, pgvector, pgvector, chroma, opensearch, tidb_vector
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VECTOR_STORE=weaviate
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# Weaviate configuration
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@ -106,6 +106,14 @@ MILVUS_USER=root
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MILVUS_PASSWORD=Milvus
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MILVUS_SECURE=false
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# MyScale configuration
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MYSCALE_HOST=127.0.0.1
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MYSCALE_PORT=8123
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MYSCALE_USER=default
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MYSCALE_PASSWORD=
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MYSCALE_DATABASE=default
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MYSCALE_FTS_PARAMS=
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# Relyt configuration
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RELYT_HOST=127.0.0.1
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RELYT_PORT=5432
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@ -13,6 +13,7 @@ from configs.middleware.storage.tencent_cos_storage_config import TencentCloudCO
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from configs.middleware.vdb.analyticdb_config import AnalyticdbConfig
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from configs.middleware.vdb.chroma_config import ChromaConfig
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from configs.middleware.vdb.milvus_config import MilvusConfig
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from configs.middleware.vdb.myscale_config import MyScaleConfig
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from configs.middleware.vdb.opensearch_config import OpenSearchConfig
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from configs.middleware.vdb.oracle_config import OracleConfig
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from configs.middleware.vdb.pgvector_config import PGVectorConfig
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@ -187,6 +188,7 @@ class MiddlewareConfig(
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AnalyticdbConfig,
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ChromaConfig,
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MilvusConfig,
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MyScaleConfig,
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OpenSearchConfig,
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OracleConfig,
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PGVectorConfig,
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39
api/configs/middleware/vdb/myscale_config.py
Normal file
39
api/configs/middleware/vdb/myscale_config.py
Normal file
@ -0,0 +1,39 @@
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from typing import Optional
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from pydantic import BaseModel, Field, PositiveInt
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class MyScaleConfig(BaseModel):
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"""
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MyScale configs
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"""
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MYSCALE_HOST: Optional[str] = Field(
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description='MyScale host',
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default=None,
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)
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MYSCALE_PORT: Optional[PositiveInt] = Field(
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description='MyScale port',
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default=8123,
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)
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MYSCALE_USER: Optional[str] = Field(
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description='MyScale user',
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default=None,
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)
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MYSCALE_PASSWORD: Optional[str] = Field(
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description='MyScale password',
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default=None,
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)
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MYSCALE_DATABASE: Optional[str] = Field(
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description='MyScale database name',
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default=None,
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)
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MYSCALE_FTS_PARAMS: Optional[str] = Field(
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description='MyScale fts index parameters',
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default=None,
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)
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@ -548,7 +548,7 @@ class DatasetRetrievalSettingApi(Resource):
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RetrievalMethod.SEMANTIC_SEARCH
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]
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}
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case VectorType.QDRANT | VectorType.WEAVIATE | VectorType.OPENSEARCH | VectorType.ANALYTICDB:
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case VectorType.QDRANT | VectorType.WEAVIATE | VectorType.OPENSEARCH | VectorType.ANALYTICDB | VectorType.MYSCALE:
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return {
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'retrieval_method': [
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RetrievalMethod.SEMANTIC_SEARCH,
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@ -572,7 +572,7 @@ class DatasetRetrievalSettingMockApi(Resource):
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RetrievalMethod.SEMANTIC_SEARCH
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]
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}
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case VectorType.QDRANT | VectorType.WEAVIATE | VectorType.OPENSEARCH| VectorType.ANALYTICDB:
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case VectorType.QDRANT | VectorType.WEAVIATE | VectorType.OPENSEARCH| VectorType.ANALYTICDB | VectorType.MYSCALE:
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return {
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'retrieval_method': [
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RetrievalMethod.SEMANTIC_SEARCH,
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0
api/core/rag/datasource/vdb/myscale/__init__.py
Normal file
0
api/core/rag/datasource/vdb/myscale/__init__.py
Normal file
170
api/core/rag/datasource/vdb/myscale/myscale_vector.py
Normal file
170
api/core/rag/datasource/vdb/myscale/myscale_vector.py
Normal file
@ -0,0 +1,170 @@
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import json
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import logging
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import uuid
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from enum import Enum
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from typing import Any
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from clickhouse_connect import get_client
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from flask import current_app
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from pydantic import BaseModel
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from core.rag.datasource.entity.embedding import Embeddings
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from core.rag.datasource.vdb.vector_base import BaseVector
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from core.rag.datasource.vdb.vector_factory import AbstractVectorFactory
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from core.rag.datasource.vdb.vector_type import VectorType
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from core.rag.models.document import Document
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from models.dataset import Dataset
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class MyScaleConfig(BaseModel):
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host: str
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port: int
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user: str
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password: str
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database: str
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fts_params: str
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class SortOrder(Enum):
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ASC = "ASC"
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DESC = "DESC"
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class MyScaleVector(BaseVector):
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def __init__(self, collection_name: str, config: MyScaleConfig, metric: str = "Cosine"):
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super().__init__(collection_name)
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self._config = config
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self._metric = metric
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self._vec_order = SortOrder.ASC if metric.upper() in ["COSINE", "L2"] else SortOrder.DESC
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self._client = get_client(
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host=config.host,
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port=config.port,
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username=config.user,
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password=config.password,
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)
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self._client.command("SET allow_experimental_object_type=1")
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def get_type(self) -> str:
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return VectorType.MYSCALE
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def create(self, texts: list[Document], embeddings: list[list[float]], **kwargs):
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dimension = len(embeddings[0])
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self._create_collection(dimension)
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return self.add_texts(documents=texts, embeddings=embeddings, **kwargs)
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def _create_collection(self, dimension: int):
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logging.info(f"create MyScale collection {self._collection_name} with dimension {dimension}")
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self._client.command(f"CREATE DATABASE IF NOT EXISTS {self._config.database}")
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fts_params = f"('{self._config.fts_params}')" if self._config.fts_params else ""
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sql = f"""
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CREATE TABLE IF NOT EXISTS {self._config.database}.{self._collection_name}(
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id String,
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text String,
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vector Array(Float32),
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metadata JSON,
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CONSTRAINT cons_vec_len CHECK length(vector) = {dimension},
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VECTOR INDEX vidx vector TYPE DEFAULT('metric_type = {self._metric}'),
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INDEX text_idx text TYPE fts{fts_params}
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) ENGINE = MergeTree ORDER BY id
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"""
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self._client.command(sql)
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def add_texts(self, documents: list[Document], embeddings: list[list[float]], **kwargs):
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ids = []
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columns = ["id", "text", "vector", "metadata"]
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values = []
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for i, doc in enumerate(documents):
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doc_id = doc.metadata.get("doc_id", str(uuid.uuid4()))
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row = (
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doc_id,
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self.escape_str(doc.page_content),
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embeddings[i],
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json.dumps(doc.metadata) if doc.metadata else {}
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)
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values.append(str(row))
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ids.append(doc_id)
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sql = f"""
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INSERT INTO {self._config.database}.{self._collection_name}
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({",".join(columns)}) VALUES {",".join(values)}
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"""
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self._client.command(sql)
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return ids
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@staticmethod
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def escape_str(value: Any) -> str:
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return "".join(f"\\{c}" if c in ("\\", "'") else c for c in str(value))
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def text_exists(self, id: str) -> bool:
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results = self._client.query(f"SELECT id FROM {self._config.database}.{self._collection_name} WHERE id='{id}'")
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return results.row_count > 0
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def delete_by_ids(self, ids: list[str]) -> None:
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self._client.command(
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f"DELETE FROM {self._config.database}.{self._collection_name} WHERE id IN {str(tuple(ids))}")
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def get_ids_by_metadata_field(self, key: str, value: str):
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rows = self._client.query(
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f"SELECT DISTINCT id FROM {self._config.database}.{self._collection_name} WHERE metadata.{key}='{value}'"
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).result_rows
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return [row[0] for row in rows]
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def delete_by_metadata_field(self, key: str, value: str) -> None:
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self._client.command(
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f"DELETE FROM {self._config.database}.{self._collection_name} WHERE metadata.{key}='{value}'"
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)
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def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]:
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return self._search(f"distance(vector, {str(query_vector)})", self._vec_order, **kwargs)
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def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
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return self._search(f"TextSearch(text, '{query}')", SortOrder.DESC, **kwargs)
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def _search(self, dist: str, order: SortOrder, **kwargs: Any) -> list[Document]:
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top_k = kwargs.get("top_k", 5)
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score_threshold = kwargs.get("score_threshold", 0.0)
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where_str = f"WHERE dist < {1 - score_threshold}" if \
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self._metric.upper() == "COSINE" and order == SortOrder.ASC and score_threshold > 0.0 else ""
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sql = f"""
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SELECT text, metadata, {dist} as dist FROM {self._config.database}.{self._collection_name}
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{where_str} ORDER BY dist {order.value} LIMIT {top_k}
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"""
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try:
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return [
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Document(
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page_content=r["text"],
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metadata=r["metadata"],
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)
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for r in self._client.query(sql).named_results()
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]
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except Exception as e:
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logging.error(f"\033[91m\033[1m{type(e)}\033[0m \033[95m{str(e)}\033[0m")
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return []
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def delete(self) -> None:
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self._client.command(f"DROP TABLE IF EXISTS {self._config.database}.{self._collection_name}")
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class MyScaleVectorFactory(AbstractVectorFactory):
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def init_vector(self, dataset: Dataset, attributes: list, embeddings: Embeddings) -> MyScaleVector:
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if dataset.index_struct_dict:
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class_prefix: str = dataset.index_struct_dict['vector_store']['class_prefix']
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collection_name = class_prefix.lower()
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else:
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dataset_id = dataset.id
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collection_name = Dataset.gen_collection_name_by_id(dataset_id).lower()
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dataset.index_struct = json.dumps(
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self.gen_index_struct_dict(VectorType.MYSCALE, collection_name))
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config = current_app.config
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return MyScaleVector(
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collection_name=collection_name,
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config=MyScaleConfig(
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host=config.get("MYSCALE_HOST", "localhost"),
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port=int(config.get("MYSCALE_PORT", 8123)),
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user=config.get("MYSCALE_USER", "default"),
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password=config.get("MYSCALE_PASSWORD", ""),
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database=config.get("MYSCALE_DATABASE", "default"),
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fts_params=config.get("MYSCALE_FTS_PARAMS", ""),
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),
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)
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@ -57,6 +57,9 @@ class Vector:
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case VectorType.MILVUS:
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from core.rag.datasource.vdb.milvus.milvus_vector import MilvusVectorFactory
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return MilvusVectorFactory
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case VectorType.MYSCALE:
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from core.rag.datasource.vdb.myscale.myscale_vector import MyScaleVectorFactory
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return MyScaleVectorFactory
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case VectorType.PGVECTOR:
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from core.rag.datasource.vdb.pgvector.pgvector import PGVectorFactory
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return PGVectorFactory
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@ -5,6 +5,7 @@ class VectorType(str, Enum):
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ANALYTICDB = 'analyticdb'
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CHROMA = 'chroma'
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MILVUS = 'milvus'
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MYSCALE = 'myscale'
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PGVECTOR = 'pgvector'
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PGVECTO_RS = 'pgvecto-rs'
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QDRANT = 'qdrant'
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203
api/poetry.lock
generated
203
api/poetry.lock
generated
@ -1398,6 +1398,96 @@ prompt-toolkit = ">=3.0.36"
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[package.extras]
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testing = ["pytest (>=7.2.1)", "pytest-cov (>=4.0.0)", "tox (>=4.4.3)"]
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[[package]]
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name = "clickhouse-connect"
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version = "0.7.16"
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description = "ClickHouse Database Core Driver for Python, Pandas, and Superset"
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optional = false
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python-versions = "~=3.8"
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files = [
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{file = "clickhouse-connect-0.7.16.tar.gz", hash = "sha256:253a2089efad5729903d00382f73fa8da2cbbfdb118db498cf708ee9f4a2134f"},
|
||||
{file = "clickhouse_connect-0.7.16-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:00413deb9e086aabf661d18ac3a3539f25eb773c3675f49353e0d7e6ef1205fc"},
|
||||
{file = "clickhouse_connect-0.7.16-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:faadaf206ea7753782db017daedbf592e4edc7c71cb985aad787eb9dc516bf21"},
|
||||
{file = "clickhouse_connect-0.7.16-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1db8f1168f33fda78adddb733913b211ddf648984d8fef8d934e30df876e5f23"},
|
||||
{file = "clickhouse_connect-0.7.16-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8fa630bf50fb064cc53b7ea5d862066476d3c6074003f6d39d2594fb1a7abf67"},
|
||||
{file = "clickhouse_connect-0.7.16-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2cba9547dad41b2d333458615208a3c7db6f56a63473ffea2c05c44225ffa020"},
|
||||
{file = "clickhouse_connect-0.7.16-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:480f7856fcf42a21f17886e0b42d70499067c865fc2a0ea7c0eb5c0bdca281a8"},
|
||||
{file = "clickhouse_connect-0.7.16-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:b65f3eb570cbcf9fa383b4e0925d1ceb3efd3deba42a435625cad75b3a9ff7f3"},
|
||||
{file = "clickhouse_connect-0.7.16-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:b78d3cc0fe42374bb9d5a05ba71578dc69f7e4b4c771e86dcf292ae0412265cc"},
|
||||
{file = "clickhouse_connect-0.7.16-cp310-cp310-win32.whl", hash = "sha256:1cb76b26fcde1ba6a8ae68e1db1f9e42d458879a0d4d2c9843cc998f42f445ac"},
|
||||
{file = "clickhouse_connect-0.7.16-cp310-cp310-win_amd64.whl", hash = "sha256:9298b344168271e952ea41021963ca1b81b9b3c38be8b036cb64a2556edbb4b7"},
|
||||
{file = "clickhouse_connect-0.7.16-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:8ae39a765735cc6e786e5f9a0dba799e7f8ee0bbd5dfc5d5ff755dfa9dd13855"},
|
||||
{file = "clickhouse_connect-0.7.16-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3f32546f65dd234a49310cda454713a5f7fbc8ba978744e070355c7ea8819a5a"},
|
||||
{file = "clickhouse_connect-0.7.16-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:20865c81a5b378625a528ac8960e08cdca316147f87fad6deb9f16c0d5e5f62f"},
|
||||
{file = "clickhouse_connect-0.7.16-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:609c076261d779703bf29e7a27dafc8283153403ceab1ec23d50eb2acabc4b9d"},
|
||||
{file = "clickhouse_connect-0.7.16-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e07862e75ac7419c5671384055f11ca5e76dc2c0be4a6f3aed7bf419997184bc"},
|
||||
{file = "clickhouse_connect-0.7.16-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d5db7da6f20b9a49b288063de9b3224a56634f8cb94d19d435af518ed81872c3"},
|
||||
{file = "clickhouse_connect-0.7.16-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:955c567ede68a10325045bb2adf1314ff569dfb7e52f6074c18182f3803279f6"},
|
||||
{file = "clickhouse_connect-0.7.16-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:df517bfe23d85f5aeeb17b262c06d0a5c24e0baea09688a96d02dc8589ef8b07"},
|
||||
{file = "clickhouse_connect-0.7.16-cp311-cp311-win32.whl", hash = "sha256:7f2c6132fc90df6a8318abb9f257c2b777404908b7d168ac08235d516f65a663"},
|
||||
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]
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||||
|
||||
[package.dependencies]
|
||||
certifi = "*"
|
||||
lz4 = "*"
|
||||
pytz = "*"
|
||||
urllib3 = ">=1.26"
|
||||
zstandard = "*"
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||||
|
||||
[package.extras]
|
||||
arrow = ["pyarrow"]
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||||
numpy = ["numpy"]
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||||
orjson = ["orjson"]
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||||
pandas = ["pandas"]
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||||
sqlalchemy = ["sqlalchemy (>1.3.21,<2.0)"]
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||||
tzlocal = ["tzlocal (>=4.0)"]
|
||||
|
||||
[[package]]
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||||
name = "clickhouse-driver"
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||||
version = "0.2.8"
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||||
@ -4259,6 +4349,56 @@ html5 = ["html5lib"]
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||||
htmlsoup = ["BeautifulSoup4"]
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source = ["Cython (>=3.0.7)"]
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||||
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[[package]]
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name = "lz4"
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version = "4.3.3"
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description = "LZ4 Bindings for Python"
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optional = false
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python-versions = ">=3.8"
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|
||||
{file = "lz4-4.3.3-cp39-cp39-win_amd64.whl", hash = "sha256:eac9af361e0d98335a02ff12fb56caeb7ea1196cf1a49dbf6f17828a131da807"},
|
||||
{file = "lz4-4.3.3.tar.gz", hash = "sha256:01fe674ef2889dbb9899d8a67361e0c4a2c833af5aeb37dd505727cf5d2a131e"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
docs = ["sphinx (>=1.6.0)", "sphinx-bootstrap-theme"]
|
||||
flake8 = ["flake8"]
|
||||
tests = ["psutil", "pytest (!=3.3.0)", "pytest-cov"]
|
||||
|
||||
[[package]]
|
||||
name = "mailchimp-transactional"
|
||||
version = "1.0.56"
|
||||
@ -9190,7 +9330,68 @@ docs = ["Sphinx", "repoze.sphinx.autointerface", "sphinx-rtd-theme"]
|
||||
test = ["coverage (>=5.0.3)", "zope.event", "zope.testing"]
|
||||
testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"]
|
||||
|
||||
[[package]]
|
||||
name = "zstandard"
|
||||
version = "0.22.0"
|
||||
description = "Zstandard bindings for Python"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "zstandard-0.22.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:275df437ab03f8c033b8a2c181e51716c32d831082d93ce48002a5227ec93019"},
|
||||
{file = "zstandard-0.22.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2ac9957bc6d2403c4772c890916bf181b2653640da98f32e04b96e4d6fb3252a"},
|
||||
{file = "zstandard-0.22.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fe3390c538f12437b859d815040763abc728955a52ca6ff9c5d4ac707c4ad98e"},
|
||||
{file = "zstandard-0.22.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1958100b8a1cc3f27fa21071a55cb2ed32e9e5df4c3c6e661c193437f171cba2"},
|
||||
{file = "zstandard-0.22.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:93e1856c8313bc688d5df069e106a4bc962eef3d13372020cc6e3ebf5e045202"},
|
||||
{file = "zstandard-0.22.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:1a90ba9a4c9c884bb876a14be2b1d216609385efb180393df40e5172e7ecf356"},
|
||||
{file = "zstandard-0.22.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:3db41c5e49ef73641d5111554e1d1d3af106410a6c1fb52cf68912ba7a343a0d"},
|
||||
{file = "zstandard-0.22.0-cp310-cp310-win32.whl", hash = "sha256:d8593f8464fb64d58e8cb0b905b272d40184eac9a18d83cf8c10749c3eafcd7e"},
|
||||
{file = "zstandard-0.22.0-cp310-cp310-win_amd64.whl", hash = "sha256:f1a4b358947a65b94e2501ce3e078bbc929b039ede4679ddb0460829b12f7375"},
|
||||
{file = "zstandard-0.22.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:589402548251056878d2e7c8859286eb91bd841af117dbe4ab000e6450987e08"},
|
||||
{file = "zstandard-0.22.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a97079b955b00b732c6f280d5023e0eefe359045e8b83b08cf0333af9ec78f26"},
|
||||
{file = "zstandard-0.22.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:445b47bc32de69d990ad0f34da0e20f535914623d1e506e74d6bc5c9dc40bb09"},
|
||||
{file = "zstandard-0.22.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:33591d59f4956c9812f8063eff2e2c0065bc02050837f152574069f5f9f17775"},
|
||||
{file = "zstandard-0.22.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:888196c9c8893a1e8ff5e89b8f894e7f4f0e64a5af4d8f3c410f0319128bb2f8"},
|
||||
{file = "zstandard-0.22.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:53866a9d8ab363271c9e80c7c2e9441814961d47f88c9bc3b248142c32141d94"},
|
||||
{file = "zstandard-0.22.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:4ac59d5d6910b220141c1737b79d4a5aa9e57466e7469a012ed42ce2d3995e88"},
|
||||
{file = "zstandard-0.22.0-cp311-cp311-win32.whl", hash = "sha256:2b11ea433db22e720758cba584c9d661077121fcf60ab43351950ded20283440"},
|
||||
{file = "zstandard-0.22.0-cp311-cp311-win_amd64.whl", hash = "sha256:11f0d1aab9516a497137b41e3d3ed4bbf7b2ee2abc79e5c8b010ad286d7464bd"},
|
||||
{file = "zstandard-0.22.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:6c25b8eb733d4e741246151d895dd0308137532737f337411160ff69ca24f93a"},
|
||||
{file = "zstandard-0.22.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f9b2cde1cd1b2a10246dbc143ba49d942d14fb3d2b4bccf4618d475c65464912"},
|
||||
{file = "zstandard-0.22.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a88b7df61a292603e7cd662d92565d915796b094ffb3d206579aaebac6b85d5f"},
|
||||
{file = "zstandard-0.22.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:466e6ad8caefb589ed281c076deb6f0cd330e8bc13c5035854ffb9c2014b118c"},
|
||||
{file = "zstandard-0.22.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a1d67d0d53d2a138f9e29d8acdabe11310c185e36f0a848efa104d4e40b808e4"},
|
||||
{file = "zstandard-0.22.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:39b2853efc9403927f9065cc48c9980649462acbdf81cd4f0cb773af2fd734bc"},
|
||||
{file = "zstandard-0.22.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8a1b2effa96a5f019e72874969394edd393e2fbd6414a8208fea363a22803b45"},
|
||||
{file = "zstandard-0.22.0-cp312-cp312-win32.whl", hash = "sha256:88c5b4b47a8a138338a07fc94e2ba3b1535f69247670abfe422de4e0b344aae2"},
|
||||
{file = "zstandard-0.22.0-cp312-cp312-win_amd64.whl", hash = "sha256:de20a212ef3d00d609d0b22eb7cc798d5a69035e81839f549b538eff4105d01c"},
|
||||
{file = "zstandard-0.22.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:d75f693bb4e92c335e0645e8845e553cd09dc91616412d1d4650da835b5449df"},
|
||||
{file = "zstandard-0.22.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:36a47636c3de227cd765e25a21dc5dace00539b82ddd99ee36abae38178eff9e"},
|
||||
{file = "zstandard-0.22.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:68953dc84b244b053c0d5f137a21ae8287ecf51b20872eccf8eaac0302d3e3b0"},
|
||||
{file = "zstandard-0.22.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2612e9bb4977381184bb2463150336d0f7e014d6bb5d4a370f9a372d21916f69"},
|
||||
{file = "zstandard-0.22.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:23d2b3c2b8e7e5a6cb7922f7c27d73a9a615f0a5ab5d0e03dd533c477de23004"},
|
||||
{file = "zstandard-0.22.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:1d43501f5f31e22baf822720d82b5547f8a08f5386a883b32584a185675c8fbf"},
|
||||
{file = "zstandard-0.22.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:a493d470183ee620a3df1e6e55b3e4de8143c0ba1b16f3ded83208ea8ddfd91d"},
|
||||
{file = "zstandard-0.22.0-cp38-cp38-win32.whl", hash = "sha256:7034d381789f45576ec3f1fa0e15d741828146439228dc3f7c59856c5bcd3292"},
|
||||
{file = "zstandard-0.22.0-cp38-cp38-win_amd64.whl", hash = "sha256:d8fff0f0c1d8bc5d866762ae95bd99d53282337af1be9dc0d88506b340e74b73"},
|
||||
{file = "zstandard-0.22.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:2fdd53b806786bd6112d97c1f1e7841e5e4daa06810ab4b284026a1a0e484c0b"},
|
||||
{file = "zstandard-0.22.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:73a1d6bd01961e9fd447162e137ed949c01bdb830dfca487c4a14e9742dccc93"},
|
||||
{file = "zstandard-0.22.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9501f36fac6b875c124243a379267d879262480bf85b1dbda61f5ad4d01b75a3"},
|
||||
{file = "zstandard-0.22.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:48f260e4c7294ef275744210a4010f116048e0c95857befb7462e033f09442fe"},
|
||||
{file = "zstandard-0.22.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:959665072bd60f45c5b6b5d711f15bdefc9849dd5da9fb6c873e35f5d34d8cfb"},
|
||||
{file = "zstandard-0.22.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:d22fdef58976457c65e2796e6730a3ea4a254f3ba83777ecfc8592ff8d77d303"},
|
||||
{file = "zstandard-0.22.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:a7ccf5825fd71d4542c8ab28d4d482aace885f5ebe4b40faaa290eed8e095a4c"},
|
||||
{file = "zstandard-0.22.0-cp39-cp39-win32.whl", hash = "sha256:f058a77ef0ece4e210bb0450e68408d4223f728b109764676e1a13537d056bb0"},
|
||||
{file = "zstandard-0.22.0-cp39-cp39-win_amd64.whl", hash = "sha256:e9e9d4e2e336c529d4c435baad846a181e39a982f823f7e4495ec0b0ec8538d2"},
|
||||
{file = "zstandard-0.22.0.tar.gz", hash = "sha256:8226a33c542bcb54cd6bd0a366067b610b41713b64c9abec1bc4533d69f51e70"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
cffi = {version = ">=1.11", markers = "platform_python_implementation == \"PyPy\""}
|
||||
|
||||
[package.extras]
|
||||
cffi = ["cffi (>=1.11)"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.10"
|
||||
content-hash = "7dc35227a8e2545597f7a9660850e9adb2569d38f97d72dbfdcdff88f3a38bdb"
|
||||
content-hash = "76374a3483905c3219821ec31cefd75c64e0ccb3f0c5424acf1b8a1322587411"
|
||||
|
||||
@ -211,6 +211,7 @@ qdrant-client = "1.7.3"
|
||||
weaviate-client = "~3.21.0"
|
||||
alibabacloud_gpdb20160503 = "~3.8.0"
|
||||
alibabacloud_tea_openapi = "~0.3.9"
|
||||
clickhouse-connect = "~0.7.16"
|
||||
|
||||
############################################################
|
||||
# Transparent dependencies required by main dependencies
|
||||
|
||||
0
api/tests/integration_tests/vdb/myscale/__init__.py
Normal file
0
api/tests/integration_tests/vdb/myscale/__init__.py
Normal file
29
api/tests/integration_tests/vdb/myscale/test_myscale.py
Normal file
29
api/tests/integration_tests/vdb/myscale/test_myscale.py
Normal file
@ -0,0 +1,29 @@
|
||||
from core.rag.datasource.vdb.myscale.myscale_vector import MyScaleConfig, MyScaleVector
|
||||
from tests.integration_tests.vdb.test_vector_store import (
|
||||
AbstractVectorTest,
|
||||
setup_mock_redis,
|
||||
)
|
||||
|
||||
|
||||
class MyScaleVectorTest(AbstractVectorTest):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.vector = MyScaleVector(
|
||||
collection_name=self.collection_name,
|
||||
config=MyScaleConfig(
|
||||
host="localhost",
|
||||
port=8123,
|
||||
user="default",
|
||||
password="",
|
||||
database="dify",
|
||||
fts_params="",
|
||||
),
|
||||
)
|
||||
|
||||
def get_ids_by_metadata_field(self):
|
||||
ids = self.vector.get_ids_by_metadata_field(key='document_id', value=self.example_doc_id)
|
||||
assert len(ids) == 1
|
||||
|
||||
|
||||
def test_myscale_vector(setup_mock_redis):
|
||||
MyScaleVectorTest().run_all_tests()
|
||||
@ -3,6 +3,7 @@ set -x
|
||||
|
||||
pytest api/tests/integration_tests/vdb/chroma \
|
||||
api/tests/integration_tests/vdb/milvus \
|
||||
api/tests/integration_tests/vdb/myscale \
|
||||
api/tests/integration_tests/vdb/pgvecto_rs \
|
||||
api/tests/integration_tests/vdb/pgvector \
|
||||
api/tests/integration_tests/vdb/qdrant \
|
||||
|
||||
@ -243,7 +243,7 @@ TENCENT_COS_SCHEME=your-scheme
|
||||
# ------------------------------
|
||||
|
||||
# The type of vector store to use.
|
||||
# Supported values are `weaviate`, `qdrant`, `milvus`, `relyt`, `pgvector`, `chroma`, `opensearch`, `tidb_vector`, `oracle`, `tencent`.
|
||||
# Supported values are `weaviate`, `qdrant`, `milvus`, `myscale`, `relyt`, `pgvector`, `chroma`, `opensearch`, `tidb_vector`, `oracle`, `tencent`.
|
||||
VECTOR_STORE=weaviate
|
||||
|
||||
# The Weaviate endpoint URL. Only available when VECTOR_STORE is `weaviate`.
|
||||
@ -274,6 +274,16 @@ MILVUS_PASSWORD=Milvus
|
||||
# The milvus tls switch.
|
||||
MILVUS_SECURE=false
|
||||
|
||||
# MyScale configuration, only available when VECTOR_STORE is `myscale`
|
||||
# For multi-language support, please set MYSCALE_FTS_PARAMS with referring to:
|
||||
# https://myscale.com/docs/en/text-search/#understanding-fts-index-parameters
|
||||
MYSCALE_HOST=myscale
|
||||
MYSCALE_PORT=8123
|
||||
MYSCALE_USER=default
|
||||
MYSCALE_PASSWORD=
|
||||
MYSCALE_DATABASE=dify
|
||||
MYSCALE_FTS_PARAMS=
|
||||
|
||||
# pgvector configurations, only available when VECTOR_STORE is `pgvecto-rs or pgvector`
|
||||
PGVECTOR_HOST=pgvector
|
||||
PGVECTOR_PORT=5432
|
||||
|
||||
@ -83,6 +83,12 @@ x-shared-env: &shared-api-worker-env
|
||||
MILVUS_USER: ${MILVUS_USER:-root}
|
||||
MILVUS_PASSWORD: ${MILVUS_PASSWORD:-Milvus}
|
||||
MILVUS_SECURE: ${MILVUS_SECURE:-false}
|
||||
MYSCALE_HOST: ${MYSCALE_HOST:-myscale}
|
||||
MYSCALE_PORT: ${MYSCALE_PORT:-8123}
|
||||
MYSCALE_USER: ${MYSCALE_USER:-default}
|
||||
MYSCALE_PASSWORD: ${MYSCALE_PASSWORD:-}
|
||||
MYSCALE_DATABASE: ${MYSCALE_DATABASE:-dify}
|
||||
MYSCALE_FTS_PARAMS: ${MYSCALE_FTS_PARAMS:-}
|
||||
RELYT_HOST: ${RELYT_HOST:-db}
|
||||
RELYT_PORT: ${RELYT_PORT:-5432}
|
||||
RELYT_USER: ${RELYT_USER:-postgres}
|
||||
@ -532,6 +538,21 @@ services:
|
||||
depends_on:
|
||||
- opensearch
|
||||
|
||||
# MyScale vector database
|
||||
myscale:
|
||||
container_name: myscale
|
||||
image: myscale/myscaledb:1.6
|
||||
profiles:
|
||||
- myscale
|
||||
restart: always
|
||||
tty: true
|
||||
volumes:
|
||||
- ./volumes/myscale/data:/var/lib/clickhouse
|
||||
- ./volumes/myscale/log:/var/log/clickhouse-server
|
||||
- ./volumes/myscale/config/users.d/custom_users_config.xml:/etc/clickhouse-server/users.d/custom_users_config.xml
|
||||
ports:
|
||||
- "${MYSCALE_PORT:-8123}:${MYSCALE_PORT:-8123}"
|
||||
|
||||
networks:
|
||||
# create a network between sandbox, api and ssrf_proxy, and can not access outside.
|
||||
ssrf_proxy_network:
|
||||
|
||||
@ -0,0 +1,17 @@
|
||||
<clickhouse>
|
||||
<users>
|
||||
<default>
|
||||
<password></password>
|
||||
<networks>
|
||||
<ip>::1</ip> <!-- change to ::/0 to allow access from all addresses -->
|
||||
<ip>127.0.0.1</ip>
|
||||
<ip>10.0.0.0/8</ip>
|
||||
<ip>172.16.0.0/12</ip>
|
||||
<ip>192.168.0.0/16</ip>
|
||||
</networks>
|
||||
<profile>default</profile>
|
||||
<quota>default</quota>
|
||||
<access_management>1</access_management>
|
||||
</default>
|
||||
</users>
|
||||
</clickhouse>
|
||||
Loading…
Reference in New Issue
Block a user