mirror of
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Add Oracle23ai as a vector datasource (#5342)
Co-authored-by: walter from vm <walter.jin@oracle.com>
This commit is contained in:
tmuife
GitHub
parent
27f0ae8416
commit
6a09409ec9
4
.github/workflows/api-tests.yml
vendored
4
.github/workflows/api-tests.yml
vendored
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@ -68,6 +68,7 @@ jobs:
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docker/docker-compose.pgvecto-rs.yaml
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docker/docker-compose.pgvector.yaml
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docker/docker-compose.chroma.yaml
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docker/docker-compose.oracle.yaml
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services: |
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weaviate
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qdrant
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@ -77,6 +78,7 @@ jobs:
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pgvecto-rs
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pgvector
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chroma
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oracle
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- name: Test Vector Stores
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run: dev/pytest/pytest_vdb.sh
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@ -145,6 +147,7 @@ jobs:
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docker/docker-compose.pgvecto-rs.yaml
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docker/docker-compose.pgvector.yaml
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docker/docker-compose.chroma.yaml
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docker/docker-compose.oracle.yaml
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services: |
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weaviate
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qdrant
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@ -154,6 +157,7 @@ jobs:
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pgvecto-rs
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pgvector
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chroma
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oracle
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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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@ -6,6 +6,7 @@ from configs.middleware.redis_configs import RedisConfigs
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from configs.middleware.vdb.chroma_configs import ChromaConfigs
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from configs.middleware.vdb.milvus_configs import MilvusConfigs
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from configs.middleware.vdb.opensearch_configs import OpenSearchConfigs
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from configs.middleware.vdb.oracle_configs import OracleConfigs
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from configs.middleware.vdb.pgvector_configs import PGVectorConfigs
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from configs.middleware.vdb.pgvectors_configs import PGVectoRSConfigs
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from configs.middleware.vdb.qdrant_configs import QdrantConfigs
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@ -61,5 +62,6 @@ class MiddlewareConfigs(
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TencentVectorDBConfigs,
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TiDBVectorConfigs,
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WeaviateConfigs,
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OracleConfigs,
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):
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pass
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34
api/configs/middleware/vdb/oracle_configs.py
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34
api/configs/middleware/vdb/oracle_configs.py
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@ -0,0 +1,34 @@
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from typing import Optional
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from pydantic import BaseModel, Field, PositiveInt
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class OracleConfigs(BaseModel):
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"""
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ORACLE configs
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"""
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ORACLE_HOST: Optional[str] = Field(
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description='ORACLE host',
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default=None,
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)
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ORACLE_PORT: Optional[PositiveInt] = Field(
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description='ORACLE port',
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default=None,
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)
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ORACLE_USER: Optional[str] = Field(
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description='ORACLE user',
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default=None,
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)
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ORACLE_PASSWORD: Optional[str] = Field(
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description='ORACLE password',
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default=None,
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)
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ORACLE_DATABASE: Optional[str] = Field(
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description='ORACLE database',
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default=None,
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)
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@ -498,7 +498,7 @@ class DatasetRetrievalSettingApi(Resource):
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def get(self):
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vector_type = current_app.config['VECTOR_STORE']
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match vector_type:
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case VectorType.MILVUS | VectorType.RELYT | VectorType.PGVECTOR | VectorType.TIDB_VECTOR | VectorType.CHROMA | VectorType.TENCENT:
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case VectorType.MILVUS | VectorType.RELYT | VectorType.PGVECTOR | VectorType.TIDB_VECTOR | VectorType.CHROMA | VectorType.TENCENT | VectorType.ORACLE:
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return {
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'retrieval_method': [
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RetrievalMethod.SEMANTIC_SEARCH
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@ -522,7 +522,7 @@ class DatasetRetrievalSettingMockApi(Resource):
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@account_initialization_required
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def get(self, vector_type):
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match vector_type:
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case VectorType.MILVUS | VectorType.RELYT | VectorType.PGVECTOR | VectorType.TIDB_VECTOR | VectorType.CHROMA | VectorType.TENCEN:
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case VectorType.MILVUS | VectorType.RELYT | VectorType.PGVECTOR | VectorType.TIDB_VECTOR | VectorType.CHROMA | VectorType.TENCENT | VectorType.ORACLE:
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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/oracle/__init__.py
Normal file
0
api/core/rag/datasource/vdb/oracle/__init__.py
Normal file
239
api/core/rag/datasource/vdb/oracle/oraclevector.py
Normal file
239
api/core/rag/datasource/vdb/oracle/oraclevector.py
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@ -0,0 +1,239 @@
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import array
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import json
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import uuid
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from contextlib import contextmanager
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from typing import Any
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import numpy
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import oracledb
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from flask import current_app
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from pydantic import BaseModel, model_validator
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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 extensions.ext_redis import redis_client
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from models.dataset import Dataset
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oracledb.defaults.fetch_lobs = False
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class OracleVectorConfig(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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@model_validator(mode='before')
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def validate_config(cls, values: dict) -> dict:
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if not values["host"]:
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raise ValueError("config ORACLE_HOST is required")
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if not values["port"]:
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raise ValueError("config ORACLE_PORT is required")
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if not values["user"]:
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raise ValueError("config ORACLE_USER is required")
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if not values["password"]:
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raise ValueError("config ORACLE_PASSWORD is required")
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if not values["database"]:
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raise ValueError("config ORACLE_DB is required")
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return values
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SQL_CREATE_TABLE = """
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CREATE TABLE IF NOT EXISTS {table_name} (
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id varchar2(100)
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,text CLOB NOT NULL
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,meta JSON
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,embedding vector NOT NULL
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)
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"""
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class OracleVector(BaseVector):
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def __init__(self, collection_name: str, config: OracleVectorConfig):
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super().__init__(collection_name)
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self.pool = self._create_connection_pool(config)
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self.table_name = f"embedding_{collection_name}"
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def get_type(self) -> str:
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return VectorType.ORACLE
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def numpy_converter_in(self, value):
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if value.dtype == numpy.float64:
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dtype = "d"
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elif value.dtype == numpy.float32:
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dtype = "f"
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else:
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dtype = "b"
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return array.array(dtype, value)
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def input_type_handler(self, cursor, value, arraysize):
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if isinstance(value, numpy.ndarray):
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return cursor.var(
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oracledb.DB_TYPE_VECTOR,
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arraysize=arraysize,
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inconverter=self.numpy_converter_in,
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)
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def numpy_converter_out(self, value):
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if value.typecode == "b":
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dtype = numpy.int8
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elif value.typecode == "f":
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dtype = numpy.float32
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else:
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dtype = numpy.float64
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return numpy.array(value, copy=False, dtype=dtype)
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def output_type_handler(self, cursor, metadata):
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if metadata.type_code is oracledb.DB_TYPE_VECTOR:
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return cursor.var(
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metadata.type_code,
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arraysize=cursor.arraysize,
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outconverter=self.numpy_converter_out,
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)
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def _create_connection_pool(self, config: OracleVectorConfig):
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return oracledb.create_pool(user=config.user, password=config.password, dsn="{}:{}/{}".format(config.host, config.port, config.database), min=1, max=50, increment=1)
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@contextmanager
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def _get_cursor(self):
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conn = self.pool.acquire()
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conn.inputtypehandler = self.input_type_handler
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conn.outputtypehandler = self.output_type_handler
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cur = conn.cursor()
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try:
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yield cur
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finally:
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cur.close()
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conn.commit()
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conn.close()
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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(texts, embeddings)
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def add_texts(self, documents: list[Document], embeddings: list[list[float]], **kwargs):
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values = []
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pks = []
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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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pks.append(doc_id)
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values.append(
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(
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doc_id,
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doc.page_content,
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json.dumps(doc.metadata),
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#array.array("f", embeddings[i]),
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numpy.array(embeddings[i]),
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)
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)
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#print(f"INSERT INTO {self.table_name} (id, text, meta, embedding) VALUES (:1, :2, :3, :4)")
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with self._get_cursor() as cur:
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cur.executemany(f"INSERT INTO {self.table_name} (id, text, meta, embedding) VALUES (:1, :2, :3, :4)", values)
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return pks
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def text_exists(self, id: str) -> bool:
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with self._get_cursor() as cur:
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cur.execute(f"SELECT id FROM {self.table_name} WHERE id = '%s'" % (id,))
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return cur.fetchone() is not None
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def get_by_ids(self, ids: list[str]) -> list[Document]:
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with self._get_cursor() as cur:
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cur.execute(f"SELECT meta, text FROM {self.table_name} WHERE id IN %s", (tuple(ids),))
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docs = []
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for record in cur:
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docs.append(Document(page_content=record[1], metadata=record[0]))
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return docs
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#def get_ids_by_metadata_field(self, key: str, value: str):
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# with self._get_cursor() as cur:
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# cur.execute(f"SELECT id FROM {self.table_name} d WHERE d.meta.{key}='{value}'" )
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# idss = []
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# for record in cur:
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# idss.append(record[0])
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# return idss
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#def delete_by_document_id(self, document_id: str):
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# ids = self.get_ids_by_metadata_field('doc_id', document_id)
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# if len(ids)>0:
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# with self._get_cursor() as cur:
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# cur.execute(f"delete FROM {self.table_name} d WHERE d.meta.doc_id in '%s'" % ("','".join(ids),))
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def delete_by_ids(self, ids: list[str]) -> None:
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with self._get_cursor() as cur:
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cur.execute(f"DELETE FROM {self.table_name} WHERE id IN %s" % (tuple(ids),))
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def delete_by_metadata_field(self, key: str, value: str) -> None:
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with self._get_cursor() as cur:
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cur.execute(f"DELETE FROM {self.table_name} WHERE meta->>%s = %s", (key, value))
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def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]:
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"""
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Search the nearest neighbors to a vector.
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:param query_vector: The input vector to search for similar items.
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:param top_k: The number of nearest neighbors to return, default is 5.
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:return: List of Documents that are nearest to the query vector.
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"""
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top_k = kwargs.get("top_k", 5)
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with self._get_cursor() as cur:
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cur.execute(
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f"SELECT meta, text, vector_distance(embedding,:1) AS distance FROM {self.table_name} ORDER BY distance fetch first {top_k} rows only" ,[numpy.array(query_vector)]
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)
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docs = []
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score_threshold = kwargs.get("score_threshold") if kwargs.get("score_threshold") else 0.0
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for record in cur:
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metadata, text, distance = record
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score = 1 - distance
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metadata["score"] = score
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if score > score_threshold:
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docs.append(Document(page_content=text, metadata=metadata))
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return docs
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def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
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# do not support bm25 search
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return []
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def delete(self) -> None:
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with self._get_cursor() as cur:
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cur.execute(f"DROP TABLE IF EXISTS {self.table_name}")
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def _create_collection(self, dimension: int):
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cache_key = f"vector_indexing_{self._collection_name}"
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lock_name = f"{cache_key}_lock"
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with redis_client.lock(lock_name, timeout=20):
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collection_exist_cache_key = f"vector_indexing_{self._collection_name}"
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if redis_client.get(collection_exist_cache_key):
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return
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with self._get_cursor() as cur:
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cur.execute(SQL_CREATE_TABLE.format(table_name=self.table_name))
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redis_client.set(collection_exist_cache_key, 1, ex=3600)
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class OracleVectorFactory(AbstractVectorFactory):
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def init_vector(self, dataset: Dataset, attributes: list, embeddings: Embeddings) -> OracleVector:
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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
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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)
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dataset.index_struct = json.dumps(
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self.gen_index_struct_dict(VectorType.ORACLE, collection_name))
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config = current_app.config
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return OracleVector(
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collection_name=collection_name,
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config=OracleVectorConfig(
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host=config.get("ORACLE_HOST"),
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port=config.get("ORACLE_PORT"),
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user=config.get("ORACLE_USER"),
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password=config.get("ORACLE_PASSWORD"),
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database=config.get("ORACLE_DATABASE"),
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),
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)
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@ -78,6 +78,9 @@ class Vector:
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case VectorType.TENCENT:
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from core.rag.datasource.vdb.tencent.tencent_vector import TencentVectorFactory
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return TencentVectorFactory
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case VectorType.ORACLE:
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from core.rag.datasource.vdb.oracle.oraclevector import OracleVectorFactory
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return OracleVectorFactory
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case VectorType.OPENSEARCH:
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from core.rag.datasource.vdb.opensearch.opensearch_vector import OpenSearchVectorFactory
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return OpenSearchVectorFactory
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|
|
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@ -12,3 +12,4 @@ class VectorType(str, Enum):
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WEAVIATE = 'weaviate'
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OPENSEARCH = 'opensearch'
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TENCENT = 'tencent'
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ORACLE = 'oracle'
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|
|
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638
api/poetry.lock
generated
638
api/poetry.lock
generated
|
|
@ -572,54 +572,53 @@ crt = ["awscrt (==0.19.12)"]
|
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|
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[[package]]
|
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name = "bottleneck"
|
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version = "1.3.8"
|
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version = "1.4.0"
|
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description = "Fast NumPy array functions written in C"
|
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optional = false
|
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python-versions = "*"
|
||||
files = [
|
||||
{file = "Bottleneck-1.3.8-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:865c8ed5b798c0198b0b80553e09cc0d890c4f5feb3d81d31661517ca7819fa3"},
|
||||
{file = "Bottleneck-1.3.8-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d073a31e259d40b25e29dbba80f73abf38afe98fd730c79dad7edd9a0ad6cff5"},
|
||||
{file = "Bottleneck-1.3.8-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b806b277ab47495032822f55f43b8d336e4b7e73f8506ed34d3ea3da6d644abc"},
|
||||
{file = "Bottleneck-1.3.8-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:770b517609916adeb39d3b1a386a29bc316da03dd61e7ee6e8a38325b80cc327"},
|
||||
{file = "Bottleneck-1.3.8-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:2948502b0394ee419945b55b092585222a505c61d41a874c741be49f2cac056f"},
|
||||
{file = "Bottleneck-1.3.8-cp310-cp310-win32.whl", hash = "sha256:271b6333522beb8aee32e640ba49a2064491d2c10317baa58a5996be3dd443e4"},
|
||||
{file = "Bottleneck-1.3.8-cp310-cp310-win_amd64.whl", hash = "sha256:d41000ea7ca196b5fd39d6fccd34bf0704c8831731cedd2da2dcae3c6ac49c42"},
|
||||
{file = "Bottleneck-1.3.8-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:d0a7f454394cd3642498b6e077e70f4a6b9fd46a8eb908c83ac737fdc9f9a98c"},
|
||||
{file = "Bottleneck-1.3.8-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2c4ea8b9024dcb4e83b5c118a3c8faa863ace2ad572849da548a74a8ee4e8f2a"},
|
||||
{file = "Bottleneck-1.3.8-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f40724b6e965ff5b88b333d4a10097b1629e60c0db21bb3d08c24d7b1a904a16"},
|
||||
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]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1088,13 +1087,13 @@ numpy = "*"
|
|||
|
||||
[[package]]
|
||||
name = "chromadb"
|
||||
version = "0.5.1"
|
||||
version = "0.5.3"
|
||||
description = "Chroma."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
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||||
files = [
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||||
{file = "chromadb-0.5.1-py3-none-any.whl", hash = "sha256:61f1f75a672b6edce7f1c8875c67e2aaaaf130dc1c1684431fbc42ad7240d01d"},
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|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1841,19 +1840,19 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "duckduckgo-search"
|
||||
version = "6.1.6"
|
||||
version = "6.1.7"
|
||||
description = "Search for words, documents, images, news, maps and text translation using the DuckDuckGo.com search engine."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
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||||
files = [
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]
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||||
|
||||
[package.dependencies]
|
||||
click = ">=8.1.7"
|
||||
orjson = ">=3.10.4"
|
||||
pyreqwest-impersonate = ">=0.4.7"
|
||||
orjson = ">=3.10.5"
|
||||
pyreqwest-impersonate = ">=0.4.8"
|
||||
|
||||
[package.extras]
|
||||
dev = ["mypy (>=1.10.0)", "pytest (>=8.2.2)", "pytest-asyncio (>=0.23.7)", "ruff (>=0.4.8)"]
|
||||
|
|
@ -1861,13 +1860,13 @@ lxml = ["lxml (>=5.2.2)"]
|
|||
|
||||
[[package]]
|
||||
name = "email-validator"
|
||||
version = "2.1.1"
|
||||
version = "2.1.2"
|
||||
description = "A robust email address syntax and deliverability validation library."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "email_validator-2.1.1-py3-none-any.whl", hash = "sha256:97d882d174e2a65732fb43bfce81a3a834cbc1bde8bf419e30ef5ea976370a05"},
|
||||
{file = "email_validator-2.1.1.tar.gz", hash = "sha256:200a70680ba08904be6d1eef729205cc0d687634399a5924d842533efb824b84"},
|
||||
{file = "email_validator-2.1.2-py3-none-any.whl", hash = "sha256:d89f6324e13b1e39889eab7f9ca2f91dc9aebb6fa50a6d8bd4329ab50f251115"},
|
||||
{file = "email_validator-2.1.2.tar.gz", hash = "sha256:14c0f3d343c4beda37400421b39fa411bbe33a75df20825df73ad53e06a9f04c"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -2058,18 +2057,18 @@ sgmllib3k = "*"
|
|||
|
||||
[[package]]
|
||||
name = "filelock"
|
||||
version = "3.14.0"
|
||||
version = "3.15.3"
|
||||
description = "A platform independent file lock."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "filelock-3.14.0-py3-none-any.whl", hash = "sha256:43339835842f110ca7ae60f1e1c160714c5a6afd15a2873419ab185334975c0f"},
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|
||||
{file = "filelock-3.15.3.tar.gz", hash = "sha256:e1199bf5194a2277273dacd50269f0d87d0682088a3c561c15674ea9005d8635"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
|
||||
testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
|
||||
testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-asyncio (>=0.21)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)", "virtualenv (>=20.26.2)"]
|
||||
typing = ["typing-extensions (>=4.8)"]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -3904,32 +3903,32 @@ six = "*"
|
|||
|
||||
[[package]]
|
||||
name = "llvmlite"
|
||||
version = "0.42.0"
|
||||
version = "0.43.0"
|
||||
description = "lightweight wrapper around basic LLVM functionality"
|
||||
optional = false
|
||||
python-versions = ">=3.9"
|
||||
files = [
|
||||
{file = "llvmlite-0.42.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:3366938e1bf63d26c34fbfb4c8e8d2ded57d11e0567d5bb243d89aab1eb56098"},
|
||||
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||||
{file = "llvmlite-0.42.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:70f44ccc3c6220bd23e0ba698a63ec2a7d3205da0d848804807f37fc243e3f77"},
|
||||
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||||
{file = "llvmlite-0.42.0-cp310-cp310-win_amd64.whl", hash = "sha256:8d90edf400b4ceb3a0e776b6c6e4656d05c7187c439587e06f86afceb66d2be5"},
|
||||
{file = "llvmlite-0.42.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:ae511caed28beaf1252dbaf5f40e663f533b79ceb408c874c01754cafabb9cbf"},
|
||||
{file = "llvmlite-0.42.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:81e674c2fe85576e6c4474e8c7e7aba7901ac0196e864fe7985492b737dbab65"},
|
||||
{file = "llvmlite-0.42.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bb3975787f13eb97629052edb5017f6c170eebc1c14a0433e8089e5db43bcce6"},
|
||||
{file = "llvmlite-0.42.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c5bece0cdf77f22379f19b1959ccd7aee518afa4afbd3656c6365865f84903f9"},
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||||
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||||
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||||
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||||
{file = "llvmlite-0.42.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ebe66a86dc44634b59a3bc860c7b20d26d9aaffcd30364ebe8ba79161a9121f4"},
|
||||
{file = "llvmlite-0.42.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d47494552559e00d81bfb836cf1c4d5a5062e54102cc5767d5aa1e77ccd2505c"},
|
||||
{file = "llvmlite-0.42.0-cp312-cp312-win_amd64.whl", hash = "sha256:05cb7e9b6ce69165ce4d1b994fbdedca0c62492e537b0cc86141b6e2c78d5888"},
|
||||
{file = "llvmlite-0.42.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:bdd3888544538a94d7ec99e7c62a0cdd8833609c85f0c23fcb6c5c591aec60ad"},
|
||||
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|
||||
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||||
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||||
{file = "llvmlite-0.42.0-cp39-cp39-win_amd64.whl", hash = "sha256:43d65cc4e206c2e902c1004dd5418417c4efa6c1d04df05c6c5675a27e8ca90e"},
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||||
{file = "llvmlite-0.42.0.tar.gz", hash = "sha256:f92b09243c0cc3f457da8b983f67bd8e1295d0f5b3746c7a1861d7a99403854a"},
|
||||
{file = "llvmlite-0.43.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:a289af9a1687c6cf463478f0fa8e8aa3b6fb813317b0d70bf1ed0759eab6f761"},
|
||||
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|
||||
{file = "llvmlite-0.43.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7d434ec7e2ce3cc8f452d1cd9a28591745de022f931d67be688a737320dfcead"},
|
||||
{file = "llvmlite-0.43.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6912a87782acdff6eb8bf01675ed01d60ca1f2551f8176a300a886f09e836a6a"},
|
||||
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||||
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||||
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||||
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|
||||
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||||
{file = "llvmlite-0.43.0-cp311-cp311-win_amd64.whl", hash = "sha256:d5bd550001d26450bd90777736c69d68c487d17bf371438f975229b2b8241a91"},
|
||||
{file = "llvmlite-0.43.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:f99b600aa7f65235a5a05d0b9a9f31150c390f31261f2a0ba678e26823ec38f7"},
|
||||
{file = "llvmlite-0.43.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:35d80d61d0cda2d767f72de99450766250560399edc309da16937b93d3b676e7"},
|
||||
{file = "llvmlite-0.43.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:eccce86bba940bae0d8d48ed925f21dbb813519169246e2ab292b5092aba121f"},
|
||||
{file = "llvmlite-0.43.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:df6509e1507ca0760787a199d19439cc887bfd82226f5af746d6977bd9f66844"},
|
||||
{file = "llvmlite-0.43.0-cp312-cp312-win_amd64.whl", hash = "sha256:7a2872ee80dcf6b5dbdc838763d26554c2a18aa833d31a2635bff16aafefb9c9"},
|
||||
{file = "llvmlite-0.43.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9cd2a7376f7b3367019b664c21f0c61766219faa3b03731113ead75107f3b66c"},
|
||||
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|
||||
{file = "llvmlite-0.43.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:74937acd22dc11b33946b67dca7680e6d103d6e90eeaaaf932603bec6fe7b03a"},
|
||||
{file = "llvmlite-0.43.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc9efc739cc6ed760f795806f67889923f7274276f0eb45092a1473e40d9b867"},
|
||||
{file = "llvmlite-0.43.0-cp39-cp39-win_amd64.whl", hash = "sha256:47e147cdda9037f94b399bf03bfd8a6b6b1f2f90be94a454e3386f006455a9b4"},
|
||||
{file = "llvmlite-0.43.0.tar.gz", hash = "sha256:ae2b5b5c3ef67354824fb75517c8db5fbe93bc02cd9671f3c62271626bc041d5"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -4651,37 +4650,37 @@ requests = ">=2.27.1"
|
|||
|
||||
[[package]]
|
||||
name = "numba"
|
||||
version = "0.59.1"
|
||||
version = "0.60.0"
|
||||
description = "compiling Python code using LLVM"
|
||||
optional = false
|
||||
python-versions = ">=3.9"
|
||||
files = [
|
||||
{file = "numba-0.59.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:97385a7f12212c4f4bc28f648720a92514bee79d7063e40ef66c2d30600fd18e"},
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
llvmlite = "==0.42.*"
|
||||
numpy = ">=1.22,<1.27"
|
||||
llvmlite = "==0.43.*"
|
||||
numpy = ">=1.22,<2.1"
|
||||
|
||||
[[package]]
|
||||
name = "numexpr"
|
||||
|
|
@ -4879,13 +4878,13 @@ datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
|
|||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
version = "3.1.4"
|
||||
description = "A Python library to read/write Excel 2010 xlsx/xlsm files"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
python-versions = ">=3.8"
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||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -5077,59 +5076,102 @@ files = [
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|||
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||||
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||||
|
||||
[[package]]
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||||
name = "oracledb"
|
||||
version = "2.2.1"
|
||||
description = "Python interface to Oracle Database"
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||||
optional = false
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||||
python-versions = ">=3.7"
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||||
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||||
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|
||||
|
||||
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|
||||
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|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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]
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||||
[[package]]
|
||||
|
|
@ -5498,20 +5540,20 @@ wcwidth = "*"
|
|||
|
||||
[[package]]
|
||||
name = "proto-plus"
|
||||
version = "1.23.0"
|
||||
version = "1.24.0"
|
||||
description = "Beautiful, Pythonic protocol buffers."
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||||
optional = false
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||||
python-versions = ">=3.6"
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||||
python-versions = ">=3.7"
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files = [
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{file = "proto-plus-1.23.0.tar.gz", hash = "sha256:89075171ef11988b3fa157f5dbd8b9cf09d65fffee97e29ce403cd8defba19d2"},
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]
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||||
|
||||
[package.dependencies]
|
||||
protobuf = ">=3.19.0,<5.0.0dev"
|
||||
protobuf = ">=3.19.0,<6.0.0dev"
|
||||
|
||||
[package.extras]
|
||||
testing = ["google-api-core[grpc] (>=1.31.5)"]
|
||||
testing = ["google-api-core (>=1.31.5)"]
|
||||
|
||||
[[package]]
|
||||
name = "protobuf"
|
||||
|
|
@ -5862,13 +5904,13 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
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|||
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[[package]]
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||||
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[package.dependencies]
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|
@ -6071,59 +6113,59 @@ files = [
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[[package]]
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python-versions = ">=3.8"
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|
||||
]
|
||||
|
||||
[package.extras]
|
||||
|
|
@ -6683,13 +6725,13 @@ test = ["coveralls", "pycodestyle", "pyflakes", "pylint", "pytest", "pytest-benc
|
|||
|
||||
[[package]]
|
||||
name = "redis"
|
||||
version = "5.0.5"
|
||||
version = "5.0.6"
|
||||
description = "Python client for Redis database and key-value store"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
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||||
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{file = "redis-5.0.5.tar.gz", hash = "sha256:3417688621acf6ee368dec4a04dd95881be24efd34c79f00d31f62bb528800ae"},
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{file = "redis-5.0.6.tar.gz", hash = "sha256:38473cd7c6389ad3e44a91f4c3eaf6bcb8a9f746007f29bf4fb20824ff0b2197"},
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]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -6909,28 +6951,28 @@ pyasn1 = ">=0.1.3"
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|||
|
||||
[[package]]
|
||||
name = "ruff"
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||||
version = "0.4.8"
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||||
version = "0.4.9"
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||||
description = "An extremely fast Python linter and code formatter, written in Rust."
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optional = false
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||||
python-versions = ">=3.7"
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files = [
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{file = "ruff-0.4.9.tar.gz", hash = "sha256:f1cb0828ac9533ba0135d148d214e284711ede33640465e706772645483427e3"},
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||||
|
||||
[[package]]
|
||||
|
|
@ -7206,18 +7248,18 @@ tornado = ["tornado (>=5)"]
|
|||
|
||||
[[package]]
|
||||
name = "setuptools"
|
||||
version = "70.0.0"
|
||||
version = "70.1.0"
|
||||
description = "Easily download, build, install, upgrade, and uninstall Python packages"
|
||||
optional = false
|
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python-versions = ">=3.8"
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{file = "setuptools-70.0.0-py3-none-any.whl", hash = "sha256:54faa7f2e8d2d11bcd2c07bed282eef1046b5c080d1c32add737d7b5817b1ad4"},
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||||
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|
||||
|
||||
[package.extras]
|
||||
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
|
||||
testing = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "mypy (==1.9)", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.1)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy", "pytest-perf", "pytest-ruff (>=0.2.1)", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
|
||||
testing = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test", "mypy (==1.10.0)", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.1)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy", "pytest-perf", "pytest-ruff (>=0.3.2)", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
|
||||
|
||||
[[package]]
|
||||
name = "sgmllib3k"
|
||||
|
|
@ -7360,64 +7402,64 @@ files = [
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|||
|
||||
[[package]]
|
||||
name = "sqlalchemy"
|
||||
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|
||||
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|
||||
description = "Database Abstraction Library"
|
||||
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|
||||
python-versions = ">=3.7"
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||||
{file = "SQLAlchemy-2.0.30-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:408f8b0e2c04677e9c93f40eef3ab22f550fecb3011b187f66a096395ff3d9fd"},
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||||
{file = "SQLAlchemy-2.0.30-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:37a4b4fb0dd4d2669070fb05b8b8824afd0af57587393015baee1cf9890242d9"},
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||||
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||||
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{file = "SQLAlchemy-2.0.30.tar.gz", hash = "sha256:2b1708916730f4830bc69d6f49d37f7698b5bd7530aca7f04f785f8849e95255"},
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||||
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{file = "SQLAlchemy-2.0.31-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f3ad7f221d8a69d32d197e5968d798217a4feebe30144986af71ada8c548e9fa"},
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||||
{file = "SQLAlchemy-2.0.31-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9f2bee229715b6366f86a95d497c347c22ddffa2c7c96143b59a2aa5cc9eebbc"},
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||||
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||||
{file = "SQLAlchemy-2.0.31-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:750900a471d39a7eeba57580b11983030517a1f512c2cb287d5ad0fcf3aebd58"},
|
||||
{file = "SQLAlchemy-2.0.31-cp310-cp310-win32.whl", hash = "sha256:7bd112be780928c7f493c1a192cd8c5fc2a2a7b52b790bc5a84203fb4381c6be"},
|
||||
{file = "SQLAlchemy-2.0.31-cp310-cp310-win_amd64.whl", hash = "sha256:5a48ac4d359f058474fadc2115f78a5cdac9988d4f99eae44917f36aa1476327"},
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||||
{file = "SQLAlchemy-2.0.31-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:f68470edd70c3ac3b6cd5c2a22a8daf18415203ca1b036aaeb9b0fb6f54e8298"},
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{file = "SQLAlchemy-2.0.31-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2e2c38c2a4c5c634fe6c3c58a789712719fa1bf9b9d6ff5ebfce9a9e5b89c1ca"},
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{file = "SQLAlchemy-2.0.31-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bd15026f77420eb2b324dcb93551ad9c5f22fab2c150c286ef1dc1160f110203"},
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||||
{file = "SQLAlchemy-2.0.31-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2196208432deebdfe3b22185d46b08f00ac9d7b01284e168c212919891289396"},
|
||||
{file = "SQLAlchemy-2.0.31-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:352b2770097f41bff6029b280c0e03b217c2dcaddc40726f8f53ed58d8a85da4"},
|
||||
{file = "SQLAlchemy-2.0.31-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:56d51ae825d20d604583f82c9527d285e9e6d14f9a5516463d9705dab20c3740"},
|
||||
{file = "SQLAlchemy-2.0.31-cp311-cp311-win32.whl", hash = "sha256:6e2622844551945db81c26a02f27d94145b561f9d4b0c39ce7bfd2fda5776dac"},
|
||||
{file = "SQLAlchemy-2.0.31-cp311-cp311-win_amd64.whl", hash = "sha256:ccaf1b0c90435b6e430f5dd30a5aede4764942a695552eb3a4ab74ed63c5b8d3"},
|
||||
{file = "SQLAlchemy-2.0.31-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:3b74570d99126992d4b0f91fb87c586a574a5872651185de8297c6f90055ae42"},
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||||
{file = "SQLAlchemy-2.0.31-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6f77c4f042ad493cb8595e2f503c7a4fe44cd7bd59c7582fd6d78d7e7b8ec52c"},
|
||||
{file = "SQLAlchemy-2.0.31-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cd1591329333daf94467e699e11015d9c944f44c94d2091f4ac493ced0119449"},
|
||||
{file = "SQLAlchemy-2.0.31-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:74afabeeff415e35525bf7a4ecdab015f00e06456166a2eba7590e49f8db940e"},
|
||||
{file = "SQLAlchemy-2.0.31-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:b9c01990d9015df2c6f818aa8f4297d42ee71c9502026bb074e713d496e26b67"},
|
||||
{file = "SQLAlchemy-2.0.31-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:66f63278db425838b3c2b1c596654b31939427016ba030e951b292e32b99553e"},
|
||||
{file = "SQLAlchemy-2.0.31-cp312-cp312-win32.whl", hash = "sha256:0b0f658414ee4e4b8cbcd4a9bb0fd743c5eeb81fc858ca517217a8013d282c96"},
|
||||
{file = "SQLAlchemy-2.0.31-cp312-cp312-win_amd64.whl", hash = "sha256:fa4b1af3e619b5b0b435e333f3967612db06351217c58bfb50cee5f003db2a5a"},
|
||||
{file = "SQLAlchemy-2.0.31-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:f43e93057cf52a227eda401251c72b6fbe4756f35fa6bfebb5d73b86881e59b0"},
|
||||
{file = "SQLAlchemy-2.0.31-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d337bf94052856d1b330d5fcad44582a30c532a2463776e1651bd3294ee7e58b"},
|
||||
{file = "SQLAlchemy-2.0.31-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c06fb43a51ccdff3b4006aafee9fcf15f63f23c580675f7734245ceb6b6a9e05"},
|
||||
{file = "SQLAlchemy-2.0.31-cp37-cp37m-musllinux_1_2_aarch64.whl", hash = "sha256:b6e22630e89f0e8c12332b2b4c282cb01cf4da0d26795b7eae16702a608e7ca1"},
|
||||
{file = "SQLAlchemy-2.0.31-cp37-cp37m-musllinux_1_2_x86_64.whl", hash = "sha256:79a40771363c5e9f3a77f0e28b3302801db08040928146e6808b5b7a40749c88"},
|
||||
{file = "SQLAlchemy-2.0.31-cp37-cp37m-win32.whl", hash = "sha256:501ff052229cb79dd4c49c402f6cb03b5a40ae4771efc8bb2bfac9f6c3d3508f"},
|
||||
{file = "SQLAlchemy-2.0.31-cp37-cp37m-win_amd64.whl", hash = "sha256:597fec37c382a5442ffd471f66ce12d07d91b281fd474289356b1a0041bdf31d"},
|
||||
{file = "SQLAlchemy-2.0.31-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:dc6d69f8829712a4fd799d2ac8d79bdeff651c2301b081fd5d3fe697bd5b4ab9"},
|
||||
{file = "SQLAlchemy-2.0.31-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:23b9fbb2f5dd9e630db70fbe47d963c7779e9c81830869bd7d137c2dc1ad05fb"},
|
||||
{file = "SQLAlchemy-2.0.31-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2a21c97efcbb9f255d5c12a96ae14da873233597dfd00a3a0c4ce5b3e5e79704"},
|
||||
{file = "SQLAlchemy-2.0.31-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:26a6a9837589c42b16693cf7bf836f5d42218f44d198f9343dd71d3164ceeeac"},
|
||||
{file = "SQLAlchemy-2.0.31-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:dc251477eae03c20fae8db9c1c23ea2ebc47331bcd73927cdcaecd02af98d3c3"},
|
||||
{file = "SQLAlchemy-2.0.31-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:2fd17e3bb8058359fa61248c52c7b09a97cf3c820e54207a50af529876451808"},
|
||||
{file = "SQLAlchemy-2.0.31-cp38-cp38-win32.whl", hash = "sha256:c76c81c52e1e08f12f4b6a07af2b96b9b15ea67ccdd40ae17019f1c373faa227"},
|
||||
{file = "SQLAlchemy-2.0.31-cp38-cp38-win_amd64.whl", hash = "sha256:4b600e9a212ed59355813becbcf282cfda5c93678e15c25a0ef896b354423238"},
|
||||
{file = "SQLAlchemy-2.0.31-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:5b6cf796d9fcc9b37011d3f9936189b3c8074a02a4ed0c0fbbc126772c31a6d4"},
|
||||
{file = "SQLAlchemy-2.0.31-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:78fe11dbe37d92667c2c6e74379f75746dc947ee505555a0197cfba9a6d4f1a4"},
|
||||
{file = "SQLAlchemy-2.0.31-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2fc47dc6185a83c8100b37acda27658fe4dbd33b7d5e7324111f6521008ab4fe"},
|
||||
{file = "SQLAlchemy-2.0.31-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8a41514c1a779e2aa9a19f67aaadeb5cbddf0b2b508843fcd7bafdf4c6864005"},
|
||||
{file = "SQLAlchemy-2.0.31-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:afb6dde6c11ea4525318e279cd93c8734b795ac8bb5dda0eedd9ebaca7fa23f1"},
|
||||
{file = "SQLAlchemy-2.0.31-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:3f9faef422cfbb8fd53716cd14ba95e2ef655400235c3dfad1b5f467ba179c8c"},
|
||||
{file = "SQLAlchemy-2.0.31-cp39-cp39-win32.whl", hash = "sha256:fc6b14e8602f59c6ba893980bea96571dd0ed83d8ebb9c4479d9ed5425d562e9"},
|
||||
{file = "SQLAlchemy-2.0.31-cp39-cp39-win_amd64.whl", hash = "sha256:3cb8a66b167b033ec72c3812ffc8441d4e9f5f78f5e31e54dcd4c90a4ca5bebc"},
|
||||
{file = "SQLAlchemy-2.0.31-py3-none-any.whl", hash = "sha256:69f3e3c08867a8e4856e92d7afb618b95cdee18e0bc1647b77599722c9a28911"},
|
||||
{file = "SQLAlchemy-2.0.31.tar.gz", hash = "sha256:b607489dd4a54de56984a0c7656247504bd5523d9d0ba799aef59d4add009484"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
greenlet = {version = "!=0.4.17", markers = "platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\""}
|
||||
greenlet = {version = "!=0.4.17", markers = "python_version < \"3.13\" and (platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\")"}
|
||||
typing-extensions = ">=4.6.0"
|
||||
|
||||
[package.extras]
|
||||
|
|
@ -7537,13 +7579,13 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"]
|
|||
|
||||
[[package]]
|
||||
name = "tencentcloud-sdk-python-common"
|
||||
version = "3.0.1166"
|
||||
version = "3.0.1172"
|
||||
description = "Tencent Cloud Common SDK for Python"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "tencentcloud-sdk-python-common-3.0.1166.tar.gz", hash = "sha256:7e20a98f94cd82302f4f9a6c28cd1d1d90e1043767a9ff98eebe10def84ec7b9"},
|
||||
{file = "tencentcloud_sdk_python_common-3.0.1166-py2.py3-none-any.whl", hash = "sha256:e230159b275427c0ff95bd708df2ad625ab4a45ff495d9a89d4199d535ce68e9"},
|
||||
{file = "tencentcloud-sdk-python-common-3.0.1172.tar.gz", hash = "sha256:37b3b9f4a53caa070379afb6910ac989823eacd35169701405ddafb12ea14e9e"},
|
||||
{file = "tencentcloud_sdk_python_common-3.0.1172-py2.py3-none-any.whl", hash = "sha256:8915ddc713bcd7512e9d528ec36ad3e527990ab06f5e89f63941f2e5c23f4675"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -7551,17 +7593,17 @@ requests = ">=2.16.0"
|
|||
|
||||
[[package]]
|
||||
name = "tencentcloud-sdk-python-hunyuan"
|
||||
version = "3.0.1166"
|
||||
version = "3.0.1172"
|
||||
description = "Tencent Cloud Hunyuan SDK for Python"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "tencentcloud-sdk-python-hunyuan-3.0.1166.tar.gz", hash = "sha256:9be5f6ca91facdc40da91a0b9c300a0c54a83cf3792305d0e83c4216ca2a2e18"},
|
||||
{file = "tencentcloud_sdk_python_hunyuan-3.0.1166-py2.py3-none-any.whl", hash = "sha256:572d41d034a68a898ac74dd4d92f6b764cdb2b993cf71e6fbc52a40e65b0b4b4"},
|
||||
{file = "tencentcloud-sdk-python-hunyuan-3.0.1172.tar.gz", hash = "sha256:ae83b39c9da7302b10c4bffb7672ae95be72945b43e06a0b1ae9ac23bac2d43b"},
|
||||
{file = "tencentcloud_sdk_python_hunyuan-3.0.1172-py2.py3-none-any.whl", hash = "sha256:443908059ef1a00a798b7387f85e210d89c65b4f9db73629e53b3ec609b8528b"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
tencentcloud-sdk-python-common = "3.0.1166"
|
||||
tencentcloud-sdk-python-common = "3.0.1172"
|
||||
|
||||
[[package]]
|
||||
name = "threadpoolctl"
|
||||
|
|
@ -8998,4 +9040,4 @@ testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"]
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.10"
|
||||
content-hash = "5e63749820d62d42f8f0d38104ea135f68361bde660131a93fe7ad08141b51b1"
|
||||
content-hash = "cac196b2ddb59d7873fb3380d87b622d002613d6dc1d271a5c15e46817a38c55"
|
||||
|
|
|
|||
|
|
@ -187,6 +187,7 @@ tenacity = "~8.3.0"
|
|||
cos-python-sdk-v5 = "1.9.30"
|
||||
novita-client = "^0.5.6"
|
||||
opensearch-py = "2.4.0"
|
||||
oracledb = "~2.2.1"
|
||||
|
||||
[tool.poetry.group.dev]
|
||||
optional = true
|
||||
|
|
|
|||
|
|
@ -92,4 +92,5 @@ chromadb~=0.5.1
|
|||
novita_client~=0.5.6
|
||||
tenacity~=8.3.0
|
||||
opensearch-py==2.4.0
|
||||
cos-python-sdk-v5==1.9.30
|
||||
cos-python-sdk-v5==1.9.30
|
||||
oracledb~=2.2.1
|
||||
|
|
|
|||
0
api/tests/integration_tests/vdb/oracle/__init__.py
Normal file
0
api/tests/integration_tests/vdb/oracle/__init__.py
Normal file
30
api/tests/integration_tests/vdb/oracle/test_oraclevector.py
Normal file
30
api/tests/integration_tests/vdb/oracle/test_oraclevector.py
Normal file
|
|
@ -0,0 +1,30 @@
|
|||
from core.rag.datasource.vdb.oracle.oraclevector import OracleVector, OracleVectorConfig
|
||||
from core.rag.models.document import Document
|
||||
from tests.integration_tests.vdb.test_vector_store import (
|
||||
AbstractVectorTest,
|
||||
get_example_text,
|
||||
setup_mock_redis,
|
||||
)
|
||||
|
||||
|
||||
class OracleVectorTest(AbstractVectorTest):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.vector = OracleVector(
|
||||
collection_name=self.collection_name,
|
||||
config=OracleVectorConfig(
|
||||
host="localhost",
|
||||
port=1521,
|
||||
user="dify",
|
||||
password="dify",
|
||||
database="FREEPDB1",
|
||||
),
|
||||
)
|
||||
|
||||
def search_by_full_text(self):
|
||||
hits_by_full_text: list[Document] = self.vector.search_by_full_text(query=get_example_text())
|
||||
assert len(hits_by_full_text) == 0
|
||||
|
||||
|
||||
def test_oraclevector(setup_mock_redis):
|
||||
OracleVectorTest().run_all_tests()
|
||||
18
docker/docker-compose.oracle.yaml
Normal file
18
docker/docker-compose.oracle.yaml
Normal file
|
|
@ -0,0 +1,18 @@
|
|||
version: '3'
|
||||
services:
|
||||
# oracle 23 ai vector store.
|
||||
oracle:
|
||||
image: container-registry.oracle.com/database/free:latest
|
||||
restart: always
|
||||
ports:
|
||||
- 1521:1521
|
||||
volumes:
|
||||
- type: volume
|
||||
source: oradata_vector
|
||||
target: /opt/oracle/oradata
|
||||
- ./startupscripts:/opt/oracle/scripts/startup
|
||||
environment:
|
||||
- ORACLE_PWD=Dify123456
|
||||
- ORACLE_CHARACTERSET=AL32UTF8
|
||||
volumes:
|
||||
oradata_vector:
|
||||
|
|
@ -154,6 +154,12 @@ services:
|
|||
TIDB_VECTOR_USER: xxx.root
|
||||
TIDB_VECTOR_PASSWORD: xxxxxx
|
||||
TIDB_VECTOR_DATABASE: dify
|
||||
# oracle configurations
|
||||
ORACLE_HOST: oracle
|
||||
ORACLE_PORT: 1521
|
||||
ORACLE_USER: dify
|
||||
ORACLE_PASSWORD: dify
|
||||
ORACLE_DATABASE: FREEPDB1
|
||||
# Chroma configuration
|
||||
CHROMA_HOST: 127.0.0.1
|
||||
CHROMA_PORT: 8000
|
||||
|
|
@ -350,6 +356,12 @@ services:
|
|||
TIDB_VECTOR_USER: xxx.root
|
||||
TIDB_VECTOR_PASSWORD: xxxxxx
|
||||
TIDB_VECTOR_DATABASE: dify
|
||||
# oracle configurations
|
||||
ORACLE_HOST: oracle
|
||||
ORACLE_PORT: 1521
|
||||
ORACLE_USER: dify
|
||||
ORACLE_PASSWORD: dify
|
||||
ORACLE_DATABASE: FREEPDB1
|
||||
# Chroma configuration
|
||||
CHROMA_HOST: 127.0.0.1
|
||||
CHROMA_PORT: 8000
|
||||
|
|
@ -530,6 +542,22 @@ services:
|
|||
# timeout: 3s
|
||||
# retries: 30
|
||||
|
||||
# The oracle vector database.
|
||||
# Uncomment to use oracle23ai as vector store. Also need to Uncomment volumes block
|
||||
# oracle:
|
||||
# image: container-registry.oracle.com/database/free:latest
|
||||
# restart: always
|
||||
# ports:
|
||||
# - 1521:1521
|
||||
# volumes:
|
||||
# - type: volume
|
||||
# source: oradata
|
||||
# target: /opt/oracle/oradata
|
||||
# - ./startupscripts:/opt/oracle/scripts/startup
|
||||
# environment:
|
||||
# - ORACLE_PWD=Dify123456
|
||||
# - ORACLE_CHARACTERSET=AL32UTF8
|
||||
|
||||
|
||||
# The nginx reverse proxy.
|
||||
# used for reverse proxying the API service and Web service.
|
||||
|
|
@ -555,3 +583,6 @@ networks:
|
|||
ssrf_proxy_network:
|
||||
driver: bridge
|
||||
internal: true
|
||||
|
||||
#volumes:
|
||||
# oradata:
|
||||
|
|
|
|||
5
docker/startupscripts/create_user.sql
Executable file
5
docker/startupscripts/create_user.sql
Executable file
|
|
@ -0,0 +1,5 @@
|
|||
show pdbs;
|
||||
ALTER SYSTEM SET PROCESSES=500 SCOPE=SPFILE;
|
||||
alter session set container= freepdb1;
|
||||
create user dify identified by dify DEFAULT TABLESPACE users quota unlimited on users;
|
||||
grant DB_DEVELOPER_ROLE to dify;
|
||||
Loading…
Reference in New Issue
Block a user