Merge branch 'feat/r2' into deploy/rag-dev
# Conflicts: # web/i18n/zh-Hans/app.tsfeat/datasource
jyong
11 months ago
commit
9620d6bcd8
@ -0,0 +1,14 @@
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from pydantic import BaseModel, Field
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class MatrixoneConfig(BaseModel):
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"""Matrixone vector database configuration."""
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MATRIXONE_HOST: str = Field(default="localhost", description="Host address of the Matrixone server")
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MATRIXONE_PORT: int = Field(default=6001, description="Port number of the Matrixone server")
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MATRIXONE_USER: str = Field(default="dump", description="Username for authenticating with Matrixone")
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MATRIXONE_PASSWORD: str = Field(default="111", description="Password for authenticating with Matrixone")
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MATRIXONE_DATABASE: str = Field(default="dify", description="Name of the Matrixone database to connect to")
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MATRIXONE_METRIC: str = Field(
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default="l2", description="Distance metric type for vector similarity search (cosine or l2)"
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)
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@ -0,0 +1,233 @@
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import json
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import logging
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import uuid
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from functools import wraps
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from typing import Any, Optional
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from mo_vector.client import MoVectorClient # type: ignore
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from pydantic import BaseModel, model_validator
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from configs import dify_config
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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.embedding.embedding_base import Embeddings
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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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logger = logging.getLogger(__name__)
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class MatrixoneConfig(BaseModel):
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host: str = "localhost"
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port: int = 6001
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user: str = "dump"
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password: str = "111"
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database: str = "dify"
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metric: str = "l2"
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@model_validator(mode="before")
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@classmethod
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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 host is required")
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if not values["port"]:
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raise ValueError("config port is required")
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if not values["user"]:
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raise ValueError("config user is required")
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if not values["password"]:
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raise ValueError("config password is required")
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if not values["database"]:
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raise ValueError("config database is required")
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return values
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def ensure_client(func):
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@wraps(func)
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def wrapper(self, *args, **kwargs):
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if self.client is None:
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self.client = self._get_client(None, False)
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return func(self, *args, **kwargs)
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return wrapper
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class MatrixoneVector(BaseVector):
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"""
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Matrixone vector storage implementation.
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"""
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def __init__(self, collection_name: str, config: MatrixoneConfig):
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super().__init__(collection_name)
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self.config = config
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self.collection_name = collection_name.lower()
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self.client = None
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@property
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def collection_name(self):
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return self._collection_name
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@collection_name.setter
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def collection_name(self, value):
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self._collection_name = value
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def get_type(self) -> str:
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return VectorType.MATRIXONE
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def create(self, texts: list[Document], embeddings: list[list[float]], **kwargs):
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if self.client is None:
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self.client = self._get_client(len(embeddings[0]), True)
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return self.add_texts(texts, embeddings)
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def _get_client(self, dimension: Optional[int] = None, create_table: bool = False) -> MoVectorClient:
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"""
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Create a new client for the collection.
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The collection will be created if it doesn't exist.
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"""
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lock_name = f"vector_indexing_lock_{self._collection_name}"
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with redis_client.lock(lock_name, timeout=20):
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client = MoVectorClient(
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connection_string=f"mysql+pymysql://{self.config.user}:{self.config.password}@{self.config.host}:{self.config.port}/{self.config.database}",
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table_name=self.collection_name,
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vector_dimension=dimension,
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create_table=create_table,
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)
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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 client
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try:
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client.create_full_text_index()
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except Exception as e:
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logger.exception("Failed to create full text index")
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redis_client.set(collection_exist_cache_key, 1, ex=3600)
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return client
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def add_texts(self, documents: list[Document], embeddings: list[list[float]], **kwargs):
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if self.client is None:
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self.client = self._get_client(len(embeddings[0]), True)
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assert self.client is not None
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ids = []
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for _, doc in enumerate(documents):
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if doc.metadata is not None:
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doc_id = doc.metadata.get("doc_id", str(uuid.uuid4()))
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ids.append(doc_id)
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self.client.insert(
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texts=[doc.page_content for doc in documents],
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embeddings=embeddings,
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metadatas=[doc.metadata for doc in documents],
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ids=ids,
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)
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return ids
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@ensure_client
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def text_exists(self, id: str) -> bool:
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assert self.client is not None
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result = self.client.get(ids=[id])
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return len(result) > 0
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@ensure_client
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def delete_by_ids(self, ids: list[str]) -> None:
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assert self.client is not None
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if not ids:
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return
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self.client.delete(ids=ids)
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@ensure_client
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def get_ids_by_metadata_field(self, key: str, value: str):
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assert self.client is not None
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results = self.client.query_by_metadata(filter={key: value})
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return [result.id for result in results]
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@ensure_client
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def delete_by_metadata_field(self, key: str, value: str) -> None:
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assert self.client is not None
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self.client.delete(filter={key: value})
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@ensure_client
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def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]:
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assert self.client is not None
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top_k = kwargs.get("top_k", 5)
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document_ids_filter = kwargs.get("document_ids_filter")
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filter = None
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if document_ids_filter:
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filter = {"document_id": {"$in": document_ids_filter}}
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results = self.client.query(
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query_vector=query_vector,
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k=top_k,
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filter=filter,
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)
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docs = []
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# TODO: add the score threshold to the query
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for result in results:
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metadata = result.metadata
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docs.append(
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Document(
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page_content=result.document,
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metadata=metadata,
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)
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)
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return docs
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@ensure_client
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def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
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assert self.client is not None
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top_k = kwargs.get("top_k", 5)
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document_ids_filter = kwargs.get("document_ids_filter")
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filter = None
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if document_ids_filter:
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filter = {"document_id": {"$in": document_ids_filter}}
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score_threshold = float(kwargs.get("score_threshold", 0.0))
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results = self.client.full_text_query(
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keywords=[query],
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k=top_k,
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filter=filter,
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)
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docs = []
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for result in results:
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metadata = result.metadata
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if isinstance(metadata, str):
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import json
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metadata = json.loads(metadata)
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score = 1 - result.distance
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if score >= score_threshold:
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metadata["score"] = score
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docs.append(
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Document(
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page_content=result.document,
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metadata=metadata,
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)
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)
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return docs
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@ensure_client
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def delete(self) -> None:
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assert self.client is not None
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self.client.delete()
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class MatrixoneVectorFactory(AbstractVectorFactory):
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def init_vector(self, dataset: Dataset, attributes: list, embeddings: Embeddings) -> MatrixoneVector:
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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(self.gen_index_struct_dict(VectorType.MATRIXONE, collection_name))
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|
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config = MatrixoneConfig(
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host=dify_config.MATRIXONE_HOST or "localhost",
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port=dify_config.MATRIXONE_PORT or 6001,
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|
user=dify_config.MATRIXONE_USER or "dump",
|
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|
password=dify_config.MATRIXONE_PASSWORD or "111",
|
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database=dify_config.MATRIXONE_DATABASE or "dify",
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metric=dify_config.MATRIXONE_METRIC or "l2",
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|
)
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return MatrixoneVector(collection_name=collection_name, config=config)
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@ -0,0 +1,42 @@
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|
import logging
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|
|
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|
import sendgrid # type: ignore
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|
from python_http_client.exceptions import ForbiddenError, UnauthorizedError
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|
from sendgrid.helpers.mail import Content, Email, Mail, To # type: ignore
|
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|
|
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|
|
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|
class SendGridClient:
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|
def __init__(self, sendgrid_api_key: str, _from: str):
|
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|
self.sendgrid_api_key = sendgrid_api_key
|
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|
self._from = _from
|
||||||
|
|
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|
def send(self, mail: dict):
|
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|
logging.debug("Sending email with SendGrid")
|
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|
|
||||||
|
try:
|
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|
_to = mail["to"]
|
||||||
|
|
||||||
|
if not _to:
|
||||||
|
raise ValueError("SendGridClient: Cannot send email: recipient address is missing.")
|
||||||
|
|
||||||
|
sg = sendgrid.SendGridAPIClient(api_key=self.sendgrid_api_key)
|
||||||
|
from_email = Email(self._from)
|
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|
to_email = To(_to)
|
||||||
|
subject = mail["subject"]
|
||||||
|
content = Content("text/html", mail["html"])
|
||||||
|
mail = Mail(from_email, to_email, subject, content)
|
||||||
|
mail_json = mail.get() # type: ignore
|
||||||
|
response = sg.client.mail.send.post(request_body=mail_json)
|
||||||
|
logging.debug(response.status_code)
|
||||||
|
logging.debug(response.body)
|
||||||
|
logging.debug(response.headers)
|
||||||
|
|
||||||
|
except TimeoutError as e:
|
||||||
|
logging.exception("SendGridClient Timeout occurred while sending email")
|
||||||
|
raise
|
||||||
|
except (UnauthorizedError, ForbiddenError) as e:
|
||||||
|
logging.exception("SendGridClient Authentication failed. Verify that your credentials and the 'from")
|
||||||
|
raise
|
||||||
|
except Exception as e:
|
||||||
|
logging.exception(f"SendGridClient Unexpected error occurred while sending email to {_to}")
|
||||||
|
raise
|
||||||
@ -0,0 +1,5 @@
|
|||||||
|
from services.errors.base import BaseServiceError
|
||||||
|
|
||||||
|
|
||||||
|
class PluginInstallationForbiddenError(BaseServiceError):
|
||||||
|
pass
|
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@ -0,0 +1,25 @@
|
|||||||
|
from core.rag.datasource.vdb.matrixone.matrixone_vector import MatrixoneConfig, MatrixoneVector
|
||||||
|
from tests.integration_tests.vdb.test_vector_store import (
|
||||||
|
AbstractVectorTest,
|
||||||
|
get_example_text,
|
||||||
|
setup_mock_redis,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
class MatrixoneVectorTest(AbstractVectorTest):
|
||||||
|
def __init__(self):
|
||||||
|
super().__init__()
|
||||||
|
self.vector = MatrixoneVector(
|
||||||
|
collection_name=self.collection_name,
|
||||||
|
config=MatrixoneConfig(
|
||||||
|
host="localhost", port=6001, user="dump", password="111", database="dify", metric="l2"
|
||||||
|
),
|
||||||
|
)
|
||||||
|
|
||||||
|
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_matrixone_vector(setup_mock_redis):
|
||||||
|
MatrixoneVectorTest().run_all_tests()
|
||||||
@ -1,49 +0,0 @@
|
|||||||
import time
|
|
||||||
|
|
||||||
import pymysql
|
|
||||||
|
|
||||||
|
|
||||||
def check_oceanbase_ready() -> bool:
|
|
||||||
try:
|
|
||||||
connection = pymysql.connect(
|
|
||||||
host="localhost",
|
|
||||||
port=2881,
|
|
||||||
user="root",
|
|
||||||
password="difyai123456",
|
|
||||||
)
|
|
||||||
affected_rows = connection.query("SELECT 1")
|
|
||||||
return affected_rows == 1
|
|
||||||
except Exception as e:
|
|
||||||
print(f"Oceanbase is not ready. Exception: {e}")
|
|
||||||
return False
|
|
||||||
finally:
|
|
||||||
if connection:
|
|
||||||
connection.close()
|
|
||||||
|
|
||||||
|
|
||||||
def main():
|
|
||||||
max_attempts = 50
|
|
||||||
retry_interval_seconds = 2
|
|
||||||
is_oceanbase_ready = False
|
|
||||||
for attempt in range(max_attempts):
|
|
||||||
try:
|
|
||||||
is_oceanbase_ready = check_oceanbase_ready()
|
|
||||||
except Exception as e:
|
|
||||||
print(f"Oceanbase is not ready. Exception: {e}")
|
|
||||||
is_oceanbase_ready = False
|
|
||||||
|
|
||||||
if is_oceanbase_ready:
|
|
||||||
break
|
|
||||||
else:
|
|
||||||
print(f"Attempt {attempt + 1} failed, retry in {retry_interval_seconds} seconds...")
|
|
||||||
time.sleep(retry_interval_seconds)
|
|
||||||
|
|
||||||
if is_oceanbase_ready:
|
|
||||||
print("Oceanbase is ready.")
|
|
||||||
else:
|
|
||||||
print(f"Oceanbase is not ready after {max_attempts} attempting checks.")
|
|
||||||
exit(1)
|
|
||||||
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
|
||||||
main()
|
|
||||||
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,72 @@
|
|||||||
|
import { useEffect, useState } from 'react'
|
||||||
|
|
||||||
|
type DSLDragDropHookProps = {
|
||||||
|
onDSLFileDropped: (file: File) => void
|
||||||
|
containerRef: React.RefObject<HTMLDivElement>
|
||||||
|
enabled?: boolean
|
||||||
|
}
|
||||||
|
|
||||||
|
export const useDSLDragDrop = ({ onDSLFileDropped, containerRef, enabled = true }: DSLDragDropHookProps) => {
|
||||||
|
const [dragging, setDragging] = useState(false)
|
||||||
|
|
||||||
|
const handleDragEnter = (e: DragEvent) => {
|
||||||
|
e.preventDefault()
|
||||||
|
e.stopPropagation()
|
||||||
|
if (e.dataTransfer?.types.includes('Files'))
|
||||||
|
setDragging(true)
|
||||||
|
}
|
||||||
|
|
||||||
|
const handleDragOver = (e: DragEvent) => {
|
||||||
|
e.preventDefault()
|
||||||
|
e.stopPropagation()
|
||||||
|
}
|
||||||
|
|
||||||
|
const handleDragLeave = (e: DragEvent) => {
|
||||||
|
e.preventDefault()
|
||||||
|
e.stopPropagation()
|
||||||
|
if (e.relatedTarget === null || !containerRef.current?.contains(e.relatedTarget as Node))
|
||||||
|
setDragging(false)
|
||||||
|
}
|
||||||
|
|
||||||
|
const handleDrop = (e: DragEvent) => {
|
||||||
|
e.preventDefault()
|
||||||
|
e.stopPropagation()
|
||||||
|
setDragging(false)
|
||||||
|
|
||||||
|
if (!e.dataTransfer)
|
||||||
|
return
|
||||||
|
|
||||||
|
const files = [...e.dataTransfer.files]
|
||||||
|
if (files.length === 0)
|
||||||
|
return
|
||||||
|
|
||||||
|
const file = files[0]
|
||||||
|
if (file.name.toLowerCase().endsWith('.yaml') || file.name.toLowerCase().endsWith('.yml'))
|
||||||
|
onDSLFileDropped(file)
|
||||||
|
}
|
||||||
|
|
||||||
|
useEffect(() => {
|
||||||
|
if (!enabled)
|
||||||
|
return
|
||||||
|
|
||||||
|
const current = containerRef.current
|
||||||
|
if (current) {
|
||||||
|
current.addEventListener('dragenter', handleDragEnter)
|
||||||
|
current.addEventListener('dragover', handleDragOver)
|
||||||
|
current.addEventListener('dragleave', handleDragLeave)
|
||||||
|
current.addEventListener('drop', handleDrop)
|
||||||
|
}
|
||||||
|
return () => {
|
||||||
|
if (current) {
|
||||||
|
current.removeEventListener('dragenter', handleDragEnter)
|
||||||
|
current.removeEventListener('dragover', handleDragOver)
|
||||||
|
current.removeEventListener('dragleave', handleDragLeave)
|
||||||
|
current.removeEventListener('drop', handleDrop)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}, [containerRef, enabled])
|
||||||
|
|
||||||
|
return {
|
||||||
|
dragging: enabled ? dragging : false,
|
||||||
|
}
|
||||||
|
}
|
||||||
@ -0,0 +1,46 @@
|
|||||||
|
import { useGlobalPublicStore } from '@/context/global-public-context'
|
||||||
|
import type { SystemFeatures } from '@/types/feature'
|
||||||
|
import { InstallationScope } from '@/types/feature'
|
||||||
|
import type { Plugin, PluginManifestInMarket } from '../../types'
|
||||||
|
|
||||||
|
type PluginProps = (Plugin | PluginManifestInMarket) & { from: 'github' | 'marketplace' | 'package' }
|
||||||
|
|
||||||
|
export function pluginInstallLimit(plugin: PluginProps, systemFeatures: SystemFeatures) {
|
||||||
|
if (systemFeatures.plugin_installation_permission.restrict_to_marketplace_only) {
|
||||||
|
if (plugin.from === 'github' || plugin.from === 'package')
|
||||||
|
return { canInstall: false }
|
||||||
|
}
|
||||||
|
|
||||||
|
if (systemFeatures.plugin_installation_permission.plugin_installation_scope === InstallationScope.ALL) {
|
||||||
|
return {
|
||||||
|
canInstall: true,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
if (systemFeatures.plugin_installation_permission.plugin_installation_scope === InstallationScope.NONE) {
|
||||||
|
return {
|
||||||
|
canInstall: false,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
const verification = plugin.verification || {}
|
||||||
|
if (!plugin.verification || !plugin.verification.authorized_category)
|
||||||
|
verification.authorized_category = 'langgenius'
|
||||||
|
|
||||||
|
if (systemFeatures.plugin_installation_permission.plugin_installation_scope === InstallationScope.OFFICIAL_ONLY) {
|
||||||
|
return {
|
||||||
|
canInstall: verification.authorized_category === 'langgenius',
|
||||||
|
}
|
||||||
|
}
|
||||||
|
if (systemFeatures.plugin_installation_permission.plugin_installation_scope === InstallationScope.OFFICIAL_AND_PARTNER) {
|
||||||
|
return {
|
||||||
|
canInstall: verification.authorized_category === 'langgenius' || verification.authorized_category === 'partner',
|
||||||
|
}
|
||||||
|
}
|
||||||
|
return {
|
||||||
|
canInstall: true,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export default function usePluginInstallLimit(plugin: PluginProps) {
|
||||||
|
const systemFeatures = useGlobalPublicStore(s => s.systemFeatures)
|
||||||
|
return pluginInstallLimit(plugin, systemFeatures)
|
||||||
|
}
|
||||||
@ -1,30 +0,0 @@
|
|||||||
'use client'
|
|
||||||
import type { FC } from 'react'
|
|
||||||
import classNames from '@/utils/classnames'
|
|
||||||
import { useGlobalPublicStore } from '@/context/global-public-context'
|
|
||||||
import { useTheme } from 'next-themes'
|
|
||||||
|
|
||||||
type LoginLogoProps = {
|
|
||||||
className?: string
|
|
||||||
}
|
|
||||||
|
|
||||||
const LoginLogo: FC<LoginLogoProps> = ({
|
|
||||||
className,
|
|
||||||
}) => {
|
|
||||||
const { systemFeatures } = useGlobalPublicStore()
|
|
||||||
const { theme } = useTheme()
|
|
||||||
|
|
||||||
let src = theme === 'light' ? '/logo/logo-site.png' : `/logo/logo-site-${theme}.png`
|
|
||||||
if (systemFeatures.branding.enabled)
|
|
||||||
src = systemFeatures.branding.login_page_logo
|
|
||||||
|
|
||||||
return (
|
|
||||||
<img
|
|
||||||
src={src}
|
|
||||||
className={classNames('block w-auto h-10', className)}
|
|
||||||
alt='logo'
|
|
||||||
/>
|
|
||||||
)
|
|
||||||
}
|
|
||||||
|
|
||||||
export default LoginLogo
|
|
||||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue