mirror of
https://github.com/langgenius/dify.git
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774 lines
31 KiB
Python
774 lines
31 KiB
Python
import base64
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import hashlib
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import logging
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import uuid
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from collections.abc import Mapping
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from enum import StrEnum
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from typing import Optional
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from urllib.parse import urlparse
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from uuid import uuid4
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import yaml # type: ignore
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from Crypto.Cipher import AES
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from Crypto.Util.Padding import pad, unpad
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from packaging import version
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from pydantic import BaseModel, Field
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from sqlalchemy import select
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from sqlalchemy.orm import Session
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from core.helper import ssrf_proxy
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from core.model_runtime.utils.encoders import jsonable_encoder
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from core.plugin.entities.plugin import PluginDependency
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from core.workflow.nodes.enums import NodeType
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from core.workflow.nodes.knowledge_retrieval.entities import KnowledgeRetrievalNodeData
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from core.workflow.nodes.llm.entities import LLMNodeData
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from core.workflow.nodes.parameter_extractor.entities import ParameterExtractorNodeData
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from core.workflow.nodes.question_classifier.entities import QuestionClassifierNodeData
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from core.workflow.nodes.tool.entities import ToolNodeData
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from events.app_event import app_model_config_was_updated, app_was_created
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from extensions.ext_redis import redis_client
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from factories import variable_factory
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from models import Account, App, AppMode
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from models.model import AppModelConfig
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from models.workflow import Workflow
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from services.plugin.dependencies_analysis import DependenciesAnalysisService
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from services.workflow_service import WorkflowService
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logger = logging.getLogger(__name__)
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IMPORT_INFO_REDIS_KEY_PREFIX = "app_import_info:"
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CHECK_DEPENDENCIES_REDIS_KEY_PREFIX = "app_check_dependencies:"
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IMPORT_INFO_REDIS_EXPIRY = 10 * 60 # 10 minutes
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DSL_MAX_SIZE = 10 * 1024 * 1024 # 10MB
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CURRENT_DSL_VERSION = "0.1.5"
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class ImportMode(StrEnum):
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YAML_CONTENT = "yaml-content"
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YAML_URL = "yaml-url"
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class ImportStatus(StrEnum):
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COMPLETED = "completed"
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COMPLETED_WITH_WARNINGS = "completed-with-warnings"
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PENDING = "pending"
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FAILED = "failed"
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class Import(BaseModel):
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id: str
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status: ImportStatus
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app_id: Optional[str] = None
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app_mode: Optional[str] = None
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current_dsl_version: str = CURRENT_DSL_VERSION
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imported_dsl_version: str = ""
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error: str = ""
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class CheckDependenciesResult(BaseModel):
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leaked_dependencies: list[PluginDependency] = Field(default_factory=list)
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def _check_version_compatibility(imported_version: str) -> ImportStatus:
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"""Determine import status based on version comparison"""
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try:
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current_ver = version.parse(CURRENT_DSL_VERSION)
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imported_ver = version.parse(imported_version)
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except version.InvalidVersion:
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return ImportStatus.FAILED
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# Compare major version and minor version
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if current_ver.major != imported_ver.major or current_ver.minor != imported_ver.minor:
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return ImportStatus.PENDING
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if current_ver.micro != imported_ver.micro:
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return ImportStatus.COMPLETED_WITH_WARNINGS
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return ImportStatus.COMPLETED
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class PendingData(BaseModel):
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import_mode: str
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yaml_content: str
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name: str | None
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description: str | None
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icon_type: str | None
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icon: str | None
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icon_background: str | None
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app_id: str | None
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class CheckDependenciesPendingData(BaseModel):
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dependencies: list[PluginDependency]
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app_id: str | None
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class AppDslService:
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def __init__(self, session: Session):
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self._session = session
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def import_app(
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self,
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*,
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account: Account,
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import_mode: str,
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yaml_content: Optional[str] = None,
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yaml_url: Optional[str] = None,
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name: Optional[str] = None,
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description: Optional[str] = None,
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icon_type: Optional[str] = None,
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icon: Optional[str] = None,
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icon_background: Optional[str] = None,
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app_id: Optional[str] = None,
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) -> Import:
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"""Import an app from YAML content or URL."""
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import_id = str(uuid.uuid4())
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# Validate import mode
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try:
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mode = ImportMode(import_mode)
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except ValueError:
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raise ValueError(f"Invalid import_mode: {import_mode}")
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# Get YAML content
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content: str = ""
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if mode == ImportMode.YAML_URL:
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if not yaml_url:
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error="yaml_url is required when import_mode is yaml-url",
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)
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try:
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parsed_url = urlparse(yaml_url)
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if (
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parsed_url.scheme == "https"
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and parsed_url.netloc == "github.com"
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and parsed_url.path.endswith((".yml", ".yaml"))
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):
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yaml_url = yaml_url.replace("https://github.com", "https://raw.githubusercontent.com")
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yaml_url = yaml_url.replace("/blob/", "/")
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response = ssrf_proxy.get(yaml_url.strip(), follow_redirects=True, timeout=(10, 10))
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response.raise_for_status()
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content = response.content.decode()
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if len(content) > DSL_MAX_SIZE:
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error="File size exceeds the limit of 10MB",
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)
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if not content:
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error="Empty content from url",
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)
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except Exception as e:
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error=f"Error fetching YAML from URL: {str(e)}",
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)
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elif mode == ImportMode.YAML_CONTENT:
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if not yaml_content:
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error="yaml_content is required when import_mode is yaml-content",
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)
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content = yaml_content
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# Process YAML content
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try:
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# Parse YAML to validate format
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data = yaml.safe_load(content)
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if not isinstance(data, dict):
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error="Invalid YAML format: content must be a mapping",
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)
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# Validate and fix DSL version
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if not data.get("version"):
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data["version"] = "0.1.0"
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if not data.get("kind") or data.get("kind") != "app":
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data["kind"] = "app"
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imported_version = data.get("version", "0.1.0")
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# check if imported_version is a float-like string
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if not isinstance(imported_version, str):
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raise ValueError(f"Invalid version type, expected str, got {type(imported_version)}")
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status = _check_version_compatibility(imported_version)
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# Extract app data
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app_data = data.get("app")
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if not app_data:
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error="Missing app data in YAML content",
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)
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# If app_id is provided, check if it exists
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app = None
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if app_id:
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stmt = select(App).where(App.id == app_id, App.tenant_id == account.current_tenant_id)
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app = self._session.scalar(stmt)
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if not app:
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error="App not found",
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)
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if app.mode not in [AppMode.WORKFLOW, AppMode.ADVANCED_CHAT]:
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error="Only workflow or advanced chat apps can be overwritten",
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)
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# If major version mismatch, store import info in Redis
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if status == ImportStatus.PENDING:
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pending_data = PendingData(
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import_mode=import_mode,
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yaml_content=content,
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name=name,
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description=description,
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icon_type=icon_type,
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icon=icon,
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icon_background=icon_background,
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app_id=app_id,
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)
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redis_client.setex(
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f"{IMPORT_INFO_REDIS_KEY_PREFIX}{import_id}",
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IMPORT_INFO_REDIS_EXPIRY,
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pending_data.model_dump_json(),
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)
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return Import(
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id=import_id,
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status=status,
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app_id=app_id,
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imported_dsl_version=imported_version,
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)
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# Extract dependencies
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dependencies = data.get("dependencies", [])
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check_dependencies_pending_data = None
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if dependencies:
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check_dependencies_pending_data = [PluginDependency.model_validate(d) for d in dependencies]
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elif imported_version <= "0.1.5":
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if "workflow" in data:
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graph = data.get("workflow", {}).get("graph", {})
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dependencies_list = self._extract_dependencies_from_workflow_graph(graph)
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else:
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dependencies_list = self._extract_dependencies_from_model_config(data.get("model_config", {}))
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check_dependencies_pending_data = DependenciesAnalysisService.generate_latest_dependencies(
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dependencies_list
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)
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# Create or update app
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app = self._create_or_update_app(
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app=app,
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data=data,
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account=account,
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name=name,
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description=description,
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icon_type=icon_type,
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icon=icon,
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icon_background=icon_background,
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dependencies=check_dependencies_pending_data,
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)
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return Import(
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id=import_id,
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status=status,
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app_id=app.id,
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app_mode=app.mode,
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imported_dsl_version=imported_version,
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)
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except yaml.YAMLError as e:
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error=f"Invalid YAML format: {str(e)}",
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)
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except Exception as e:
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logger.exception("Failed to import app")
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error=str(e),
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)
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def confirm_import(self, *, import_id: str, account: Account) -> Import:
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"""
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Confirm an import that requires confirmation
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"""
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redis_key = f"{IMPORT_INFO_REDIS_KEY_PREFIX}{import_id}"
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pending_data = redis_client.get(redis_key)
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if not pending_data:
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error="Import information expired or does not exist",
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)
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try:
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if not isinstance(pending_data, str | bytes):
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error="Invalid import information",
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)
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pending_data = PendingData.model_validate_json(pending_data)
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data = yaml.safe_load(pending_data.yaml_content)
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app = None
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if pending_data.app_id:
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stmt = select(App).where(App.id == pending_data.app_id, App.tenant_id == account.current_tenant_id)
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app = self._session.scalar(stmt)
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# Create or update app
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app = self._create_or_update_app(
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app=app,
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data=data,
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account=account,
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name=pending_data.name,
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description=pending_data.description,
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icon_type=pending_data.icon_type,
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icon=pending_data.icon,
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icon_background=pending_data.icon_background,
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)
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# Delete import info from Redis
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redis_client.delete(redis_key)
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return Import(
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id=import_id,
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status=ImportStatus.COMPLETED,
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app_id=app.id,
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app_mode=app.mode,
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current_dsl_version=CURRENT_DSL_VERSION,
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imported_dsl_version=data.get("version", "0.1.0"),
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)
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except Exception as e:
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logger.exception("Error confirming import")
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return Import(
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id=import_id,
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status=ImportStatus.FAILED,
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error=str(e),
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)
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def check_dependencies(
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self,
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*,
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app_model: App,
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) -> CheckDependenciesResult:
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"""Check dependencies"""
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# Get dependencies from Redis
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redis_key = f"{CHECK_DEPENDENCIES_REDIS_KEY_PREFIX}{app_model.id}"
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dependencies = redis_client.get(redis_key)
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if not dependencies:
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return CheckDependenciesResult()
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# Extract dependencies
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dependencies = CheckDependenciesPendingData.model_validate_json(dependencies)
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# Get leaked dependencies
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leaked_dependencies = DependenciesAnalysisService.get_leaked_dependencies(
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tenant_id=app_model.tenant_id, dependencies=dependencies.dependencies
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)
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return CheckDependenciesResult(
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leaked_dependencies=leaked_dependencies,
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)
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def _create_or_update_app(
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self,
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*,
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app: Optional[App],
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data: dict,
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account: Account,
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name: Optional[str] = None,
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description: Optional[str] = None,
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icon_type: Optional[str] = None,
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icon: Optional[str] = None,
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icon_background: Optional[str] = None,
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dependencies: Optional[list[PluginDependency]] = None,
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) -> App:
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"""Create a new app or update an existing one."""
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app_data = data.get("app", {})
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app_mode = app_data.get("mode")
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if not app_mode:
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raise ValueError("loss app mode")
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app_mode = AppMode(app_mode)
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# Set icon type
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icon_type_value = icon_type or app_data.get("icon_type")
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if icon_type_value in ["emoji", "link"]:
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icon_type = icon_type_value
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else:
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icon_type = "emoji"
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icon = icon or str(app_data.get("icon", ""))
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if app:
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# Update existing app
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app.name = name or app_data.get("name", app.name)
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app.description = description or app_data.get("description", app.description)
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app.icon_type = icon_type
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app.icon = icon
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app.icon_background = icon_background or app_data.get("icon_background", app.icon_background)
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app.updated_by = account.id
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else:
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if account.current_tenant_id is None:
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raise ValueError("Current tenant is not set")
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# Create new app
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app = App()
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app.id = str(uuid4())
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app.tenant_id = account.current_tenant_id
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app.mode = app_mode.value
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app.name = name or app_data.get("name", "")
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app.description = description or app_data.get("description", "")
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app.icon_type = icon_type
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app.icon = icon
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app.icon_background = icon_background or app_data.get("icon_background", "#FFFFFF")
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app.enable_site = True
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app.enable_api = True
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app.use_icon_as_answer_icon = app_data.get("use_icon_as_answer_icon", False)
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app.created_by = account.id
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app.updated_by = account.id
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self._session.add(app)
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self._session.commit()
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app_was_created.send(app, account=account)
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# save dependencies
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if dependencies:
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redis_client.setex(
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f"{CHECK_DEPENDENCIES_REDIS_KEY_PREFIX}{app.id}",
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IMPORT_INFO_REDIS_EXPIRY,
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CheckDependenciesPendingData(app_id=app.id, dependencies=dependencies).model_dump_json(),
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)
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# Initialize app based on mode
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if app_mode in {AppMode.ADVANCED_CHAT, AppMode.WORKFLOW}:
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workflow_data = data.get("workflow")
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if not workflow_data or not isinstance(workflow_data, dict):
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raise ValueError("Missing workflow data for workflow/advanced chat app")
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environment_variables_list = workflow_data.get("environment_variables", [])
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environment_variables = [
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variable_factory.build_environment_variable_from_mapping(obj) for obj in environment_variables_list
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]
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conversation_variables_list = workflow_data.get("conversation_variables", [])
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conversation_variables = [
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variable_factory.build_conversation_variable_from_mapping(obj) for obj in conversation_variables_list
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]
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workflow_service = WorkflowService()
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current_draft_workflow = workflow_service.get_draft_workflow(app_model=app)
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if current_draft_workflow:
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unique_hash = current_draft_workflow.unique_hash
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else:
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unique_hash = None
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graph = workflow_data.get("graph", {})
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for node in graph.get("nodes", []):
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if node.get("data", {}).get("type", "") == NodeType.KNOWLEDGE_RETRIEVAL.value:
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dataset_ids = node["data"].get("dataset_ids", [])
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node["data"]["dataset_ids"] = [
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decrypted_id
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for dataset_id in dataset_ids
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if (decrypted_id := self.decrypt_dataset_id(encrypted_data=dataset_id, tenant_id=app.tenant_id))
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]
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workflow_service.sync_draft_workflow(
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app_model=app,
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graph=workflow_data.get("graph", {}),
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features=workflow_data.get("features", {}),
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unique_hash=unique_hash,
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account=account,
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environment_variables=environment_variables,
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conversation_variables=conversation_variables,
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)
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elif app_mode in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.COMPLETION}:
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# Initialize model config
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model_config = data.get("model_config")
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if not model_config or not isinstance(model_config, dict):
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raise ValueError("Missing model_config for chat/agent-chat/completion app")
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# Initialize or update model config
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if not app.app_model_config:
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app_model_config = AppModelConfig().from_model_config_dict(model_config)
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app_model_config.id = str(uuid4())
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app_model_config.app_id = app.id
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app_model_config.created_by = account.id
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app_model_config.updated_by = account.id
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app.app_model_config_id = app_model_config.id
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|
|
self._session.add(app_model_config)
|
|
app_model_config_was_updated.send(app, app_model_config=app_model_config)
|
|
else:
|
|
raise ValueError("Invalid app mode")
|
|
return app
|
|
|
|
@classmethod
|
|
def export_dsl(cls, app_model: App, include_secret: bool = False) -> str:
|
|
"""
|
|
Export app
|
|
:param app_model: App instance
|
|
:param include_secret: Whether include secret variable
|
|
:return:
|
|
"""
|
|
app_mode = AppMode.value_of(app_model.mode)
|
|
|
|
export_data = {
|
|
"version": CURRENT_DSL_VERSION,
|
|
"kind": "app",
|
|
"app": {
|
|
"name": app_model.name,
|
|
"mode": app_model.mode,
|
|
"icon": "🤖" if app_model.icon_type == "image" else app_model.icon,
|
|
"icon_background": "#FFEAD5" if app_model.icon_type == "image" else app_model.icon_background,
|
|
"description": app_model.description,
|
|
"use_icon_as_answer_icon": app_model.use_icon_as_answer_icon,
|
|
},
|
|
}
|
|
|
|
if app_mode in {AppMode.ADVANCED_CHAT, AppMode.WORKFLOW}:
|
|
cls._append_workflow_export_data(
|
|
export_data=export_data, app_model=app_model, include_secret=include_secret
|
|
)
|
|
else:
|
|
cls._append_model_config_export_data(export_data, app_model)
|
|
|
|
return yaml.dump(export_data, allow_unicode=True) # type: ignore
|
|
|
|
@classmethod
|
|
def _append_workflow_export_data(cls, *, export_data: dict, app_model: App, include_secret: bool) -> None:
|
|
"""
|
|
Append workflow export data
|
|
:param export_data: export data
|
|
:param app_model: App instance
|
|
"""
|
|
workflow_service = WorkflowService()
|
|
workflow = workflow_service.get_draft_workflow(app_model)
|
|
if not workflow:
|
|
raise ValueError("Missing draft workflow configuration, please check.")
|
|
|
|
workflow_dict = workflow.to_dict(include_secret=include_secret)
|
|
for node in workflow_dict.get("graph", {}).get("nodes", []):
|
|
if node.get("data", {}).get("type", "") == NodeType.KNOWLEDGE_RETRIEVAL.value:
|
|
dataset_ids = node["data"].get("dataset_ids", [])
|
|
node["data"]["dataset_ids"] = [
|
|
cls.encrypt_dataset_id(dataset_id=dataset_id, tenant_id=app_model.tenant_id)
|
|
for dataset_id in dataset_ids
|
|
]
|
|
export_data["workflow"] = workflow_dict
|
|
dependencies = cls._extract_dependencies_from_workflow(workflow)
|
|
export_data["dependencies"] = [
|
|
jsonable_encoder(d.model_dump())
|
|
for d in DependenciesAnalysisService.generate_dependencies(
|
|
tenant_id=app_model.tenant_id, dependencies=dependencies
|
|
)
|
|
]
|
|
|
|
@classmethod
|
|
def _append_model_config_export_data(cls, export_data: dict, app_model: App) -> None:
|
|
"""
|
|
Append model config export data
|
|
:param export_data: export data
|
|
:param app_model: App instance
|
|
"""
|
|
app_model_config = app_model.app_model_config
|
|
if not app_model_config:
|
|
raise ValueError("Missing app configuration, please check.")
|
|
|
|
export_data["model_config"] = app_model_config.to_dict()
|
|
dependencies = cls._extract_dependencies_from_model_config(app_model_config.to_dict())
|
|
export_data["dependencies"] = [
|
|
jsonable_encoder(d.model_dump())
|
|
for d in DependenciesAnalysisService.generate_dependencies(
|
|
tenant_id=app_model.tenant_id, dependencies=dependencies
|
|
)
|
|
]
|
|
|
|
@classmethod
|
|
def _extract_dependencies_from_workflow(cls, workflow: Workflow) -> list[str]:
|
|
"""
|
|
Extract dependencies from workflow
|
|
:param workflow: Workflow instance
|
|
:return: dependencies list format like ["langgenius/google"]
|
|
"""
|
|
graph = workflow.graph_dict
|
|
dependencies = cls._extract_dependencies_from_workflow_graph(graph)
|
|
return dependencies
|
|
|
|
@classmethod
|
|
def _extract_dependencies_from_workflow_graph(cls, graph: Mapping) -> list[str]:
|
|
"""
|
|
Extract dependencies from workflow graph
|
|
:param graph: Workflow graph
|
|
:return: dependencies list format like ["langgenius/google"]
|
|
"""
|
|
dependencies = []
|
|
for node in graph.get("nodes", []):
|
|
try:
|
|
typ = node.get("data", {}).get("type")
|
|
match typ:
|
|
case NodeType.TOOL.value:
|
|
tool_entity = ToolNodeData(**node["data"])
|
|
dependencies.append(
|
|
DependenciesAnalysisService.analyze_tool_dependency(tool_entity.provider_id),
|
|
)
|
|
case NodeType.LLM.value:
|
|
llm_entity = LLMNodeData(**node["data"])
|
|
dependencies.append(
|
|
DependenciesAnalysisService.analyze_model_provider_dependency(llm_entity.model.provider),
|
|
)
|
|
case NodeType.QUESTION_CLASSIFIER.value:
|
|
question_classifier_entity = QuestionClassifierNodeData(**node["data"])
|
|
dependencies.append(
|
|
DependenciesAnalysisService.analyze_model_provider_dependency(
|
|
question_classifier_entity.model.provider
|
|
),
|
|
)
|
|
case NodeType.PARAMETER_EXTRACTOR.value:
|
|
parameter_extractor_entity = ParameterExtractorNodeData(**node["data"])
|
|
dependencies.append(
|
|
DependenciesAnalysisService.analyze_model_provider_dependency(
|
|
parameter_extractor_entity.model.provider
|
|
),
|
|
)
|
|
case NodeType.KNOWLEDGE_RETRIEVAL.value:
|
|
knowledge_retrieval_entity = KnowledgeRetrievalNodeData(**node["data"])
|
|
if knowledge_retrieval_entity.retrieval_mode == "multiple":
|
|
if knowledge_retrieval_entity.multiple_retrieval_config:
|
|
if (
|
|
knowledge_retrieval_entity.multiple_retrieval_config.reranking_mode
|
|
== "reranking_model"
|
|
):
|
|
if knowledge_retrieval_entity.multiple_retrieval_config.reranking_model:
|
|
dependencies.append(
|
|
DependenciesAnalysisService.analyze_model_provider_dependency(
|
|
knowledge_retrieval_entity.multiple_retrieval_config.reranking_model.provider
|
|
),
|
|
)
|
|
elif (
|
|
knowledge_retrieval_entity.multiple_retrieval_config.reranking_mode
|
|
== "weighted_score"
|
|
):
|
|
if knowledge_retrieval_entity.multiple_retrieval_config.weights:
|
|
vector_setting = (
|
|
knowledge_retrieval_entity.multiple_retrieval_config.weights.vector_setting
|
|
)
|
|
dependencies.append(
|
|
DependenciesAnalysisService.analyze_model_provider_dependency(
|
|
vector_setting.embedding_provider_name
|
|
),
|
|
)
|
|
elif knowledge_retrieval_entity.retrieval_mode == "single":
|
|
model_config = knowledge_retrieval_entity.single_retrieval_config
|
|
if model_config:
|
|
dependencies.append(
|
|
DependenciesAnalysisService.analyze_model_provider_dependency(
|
|
model_config.model.provider
|
|
),
|
|
)
|
|
case _:
|
|
# TODO: Handle default case or unknown node types
|
|
pass
|
|
except Exception as e:
|
|
logger.exception("Error extracting node dependency", exc_info=e)
|
|
|
|
return dependencies
|
|
|
|
@classmethod
|
|
def _extract_dependencies_from_model_config(cls, model_config: Mapping) -> list[str]:
|
|
"""
|
|
Extract dependencies from model config
|
|
:param model_config: model config dict
|
|
:return: dependencies list format like ["langgenius/google"]
|
|
"""
|
|
dependencies = []
|
|
|
|
try:
|
|
# completion model
|
|
model_dict = model_config.get("model", {})
|
|
if model_dict:
|
|
dependencies.append(
|
|
DependenciesAnalysisService.analyze_model_provider_dependency(model_dict.get("provider", ""))
|
|
)
|
|
|
|
# reranking model
|
|
dataset_configs = model_config.get("dataset_configs", {})
|
|
if dataset_configs:
|
|
for dataset_config in dataset_configs.get("datasets", {}).get("datasets", []):
|
|
if dataset_config.get("reranking_model"):
|
|
dependencies.append(
|
|
DependenciesAnalysisService.analyze_model_provider_dependency(
|
|
dataset_config.get("reranking_model", {})
|
|
.get("reranking_provider_name", {})
|
|
.get("provider")
|
|
)
|
|
)
|
|
|
|
# tools
|
|
agent_configs = model_config.get("agent_mode", {})
|
|
if agent_configs:
|
|
for agent_config in agent_configs.get("tools", []):
|
|
dependencies.append(
|
|
DependenciesAnalysisService.analyze_tool_dependency(agent_config.get("provider_id"))
|
|
)
|
|
|
|
except Exception as e:
|
|
logger.exception("Error extracting model config dependency", exc_info=e)
|
|
|
|
return dependencies
|
|
|
|
@classmethod
|
|
def get_leaked_dependencies(cls, tenant_id: str, dsl_dependencies: list[dict]) -> list[PluginDependency]:
|
|
"""
|
|
Returns the leaked dependencies in current workspace
|
|
"""
|
|
dependencies = [PluginDependency(**dep) for dep in dsl_dependencies]
|
|
if not dependencies:
|
|
return []
|
|
|
|
return DependenciesAnalysisService.get_leaked_dependencies(tenant_id=tenant_id, dependencies=dependencies)
|
|
|
|
@staticmethod
|
|
def _generate_aes_key(tenant_id: str) -> bytes:
|
|
"""Generate AES key based on tenant_id"""
|
|
return hashlib.sha256(tenant_id.encode()).digest()
|
|
|
|
@classmethod
|
|
def encrypt_dataset_id(cls, dataset_id: str, tenant_id: str) -> str:
|
|
"""Encrypt dataset_id using AES-CBC mode"""
|
|
key = cls._generate_aes_key(tenant_id)
|
|
iv = key[:16]
|
|
cipher = AES.new(key, AES.MODE_CBC, iv)
|
|
ct_bytes = cipher.encrypt(pad(dataset_id.encode(), AES.block_size))
|
|
return base64.b64encode(ct_bytes).decode()
|
|
|
|
@classmethod
|
|
def decrypt_dataset_id(cls, encrypted_data: str, tenant_id: str) -> str | None:
|
|
"""AES decryption"""
|
|
try:
|
|
key = cls._generate_aes_key(tenant_id)
|
|
iv = key[:16]
|
|
cipher = AES.new(key, AES.MODE_CBC, iv)
|
|
pt = unpad(cipher.decrypt(base64.b64decode(encrypted_data)), AES.block_size)
|
|
return pt.decode()
|
|
except Exception:
|
|
return None
|