Merge branch 'main' into feat/r2
# Conflicts: # api/core/plugin/impl/oauth.py # api/core/workflow/entities/variable_pool.py # api/models/workflow.py # api/services/dataset_service.pyfeat/r2
jyong
7 months ago
commit
540096a8d8
@ -0,0 +1,421 @@
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import logging
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from typing import Any, NoReturn
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from flask import Response
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from flask_restful import Resource, fields, inputs, marshal, marshal_with, reqparse
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from sqlalchemy.orm import Session
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from werkzeug.exceptions import Forbidden
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from controllers.console import api
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from controllers.console.app.error import (
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DraftWorkflowNotExist,
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)
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from controllers.console.app.wraps import get_app_model
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from controllers.console.wraps import account_initialization_required, setup_required
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from controllers.web.error import InvalidArgumentError, NotFoundError
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from core.variables.segment_group import SegmentGroup
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from core.variables.segments import ArrayFileSegment, FileSegment, Segment
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from core.variables.types import SegmentType
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from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID, SYSTEM_VARIABLE_NODE_ID
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from factories.file_factory import build_from_mapping, build_from_mappings
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from factories.variable_factory import build_segment_with_type
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from libs.login import current_user, login_required
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from models import App, AppMode, db
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from models.workflow import WorkflowDraftVariable
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from services.workflow_draft_variable_service import WorkflowDraftVariableList, WorkflowDraftVariableService
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from services.workflow_service import WorkflowService
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logger = logging.getLogger(__name__)
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def _convert_values_to_json_serializable_object(value: Segment) -> Any:
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if isinstance(value, FileSegment):
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return value.value.model_dump()
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elif isinstance(value, ArrayFileSegment):
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return [i.model_dump() for i in value.value]
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elif isinstance(value, SegmentGroup):
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return [_convert_values_to_json_serializable_object(i) for i in value.value]
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else:
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return value.value
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def _serialize_var_value(variable: WorkflowDraftVariable) -> Any:
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value = variable.get_value()
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# create a copy of the value to avoid affecting the model cache.
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value = value.model_copy(deep=True)
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# Refresh the url signature before returning it to client.
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if isinstance(value, FileSegment):
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file = value.value
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file.remote_url = file.generate_url()
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elif isinstance(value, ArrayFileSegment):
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files = value.value
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for file in files:
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file.remote_url = file.generate_url()
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return _convert_values_to_json_serializable_object(value)
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def _create_pagination_parser():
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parser = reqparse.RequestParser()
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parser.add_argument(
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"page",
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type=inputs.int_range(1, 100_000),
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required=False,
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default=1,
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location="args",
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help="the page of data requested",
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)
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parser.add_argument("limit", type=inputs.int_range(1, 100), required=False, default=20, location="args")
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return parser
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_WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS = {
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"id": fields.String,
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"type": fields.String(attribute=lambda model: model.get_variable_type()),
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"name": fields.String,
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"description": fields.String,
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"selector": fields.List(fields.String, attribute=lambda model: model.get_selector()),
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"value_type": fields.String,
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"edited": fields.Boolean(attribute=lambda model: model.edited),
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"visible": fields.Boolean,
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}
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_WORKFLOW_DRAFT_VARIABLE_FIELDS = dict(
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_WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS,
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value=fields.Raw(attribute=_serialize_var_value),
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)
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_WORKFLOW_DRAFT_ENV_VARIABLE_FIELDS = {
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"id": fields.String,
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"type": fields.String(attribute=lambda _: "env"),
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"name": fields.String,
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"description": fields.String,
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"selector": fields.List(fields.String, attribute=lambda model: model.get_selector()),
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"value_type": fields.String,
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"edited": fields.Boolean(attribute=lambda model: model.edited),
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"visible": fields.Boolean,
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}
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_WORKFLOW_DRAFT_ENV_VARIABLE_LIST_FIELDS = {
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"items": fields.List(fields.Nested(_WORKFLOW_DRAFT_ENV_VARIABLE_FIELDS)),
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}
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def _get_items(var_list: WorkflowDraftVariableList) -> list[WorkflowDraftVariable]:
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return var_list.variables
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_WORKFLOW_DRAFT_VARIABLE_LIST_WITHOUT_VALUE_FIELDS = {
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"items": fields.List(fields.Nested(_WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS), attribute=_get_items),
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"total": fields.Raw(),
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}
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_WORKFLOW_DRAFT_VARIABLE_LIST_FIELDS = {
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"items": fields.List(fields.Nested(_WORKFLOW_DRAFT_VARIABLE_FIELDS), attribute=_get_items),
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}
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def _api_prerequisite(f):
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"""Common prerequisites for all draft workflow variable APIs.
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It ensures the following conditions are satisfied:
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- Dify has been property setup.
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- The request user has logged in and initialized.
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- The requested app is a workflow or a chat flow.
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- The request user has the edit permission for the app.
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"""
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@setup_required
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@login_required
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@account_initialization_required
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@get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
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def wrapper(*args, **kwargs):
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if not current_user.is_editor:
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raise Forbidden()
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return f(*args, **kwargs)
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return wrapper
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class WorkflowVariableCollectionApi(Resource):
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@_api_prerequisite
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@marshal_with(_WORKFLOW_DRAFT_VARIABLE_LIST_WITHOUT_VALUE_FIELDS)
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def get(self, app_model: App):
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"""
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Get draft workflow
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"""
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parser = _create_pagination_parser()
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args = parser.parse_args()
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# fetch draft workflow by app_model
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workflow_service = WorkflowService()
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workflow_exist = workflow_service.is_workflow_exist(app_model=app_model)
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if not workflow_exist:
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raise DraftWorkflowNotExist()
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# fetch draft workflow by app_model
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with Session(bind=db.engine, expire_on_commit=False) as session:
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draft_var_srv = WorkflowDraftVariableService(
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session=session,
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)
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workflow_vars = draft_var_srv.list_variables_without_values(
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app_id=app_model.id,
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page=args.page,
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limit=args.limit,
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)
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return workflow_vars
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@_api_prerequisite
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def delete(self, app_model: App):
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draft_var_srv = WorkflowDraftVariableService(
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session=db.session(),
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)
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draft_var_srv.delete_workflow_variables(app_model.id)
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db.session.commit()
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return Response("", 204)
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def validate_node_id(node_id: str) -> NoReturn | None:
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if node_id in [
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CONVERSATION_VARIABLE_NODE_ID,
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SYSTEM_VARIABLE_NODE_ID,
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]:
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# NOTE(QuantumGhost): While we store the system and conversation variables as node variables
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# with specific `node_id` in database, we still want to make the API separated. By disallowing
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# accessing system and conversation variables in `WorkflowDraftNodeVariableListApi`,
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# we mitigate the risk that user of the API depending on the implementation detail of the API.
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#
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# ref: [Hyrum's Law](https://www.hyrumslaw.com/)
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raise InvalidArgumentError(
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f"invalid node_id, please use correspond api for conversation and system variables, node_id={node_id}",
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)
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return None
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class NodeVariableCollectionApi(Resource):
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@_api_prerequisite
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@marshal_with(_WORKFLOW_DRAFT_VARIABLE_LIST_FIELDS)
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def get(self, app_model: App, node_id: str):
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validate_node_id(node_id)
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with Session(bind=db.engine, expire_on_commit=False) as session:
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draft_var_srv = WorkflowDraftVariableService(
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session=session,
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)
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node_vars = draft_var_srv.list_node_variables(app_model.id, node_id)
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return node_vars
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@_api_prerequisite
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def delete(self, app_model: App, node_id: str):
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validate_node_id(node_id)
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srv = WorkflowDraftVariableService(db.session())
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srv.delete_node_variables(app_model.id, node_id)
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db.session.commit()
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return Response("", 204)
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class VariableApi(Resource):
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_PATCH_NAME_FIELD = "name"
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_PATCH_VALUE_FIELD = "value"
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@_api_prerequisite
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@marshal_with(_WORKFLOW_DRAFT_VARIABLE_FIELDS)
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def get(self, app_model: App, variable_id: str):
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draft_var_srv = WorkflowDraftVariableService(
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session=db.session(),
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)
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variable = draft_var_srv.get_variable(variable_id=variable_id)
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if variable is None:
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raise NotFoundError(description=f"variable not found, id={variable_id}")
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if variable.app_id != app_model.id:
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raise NotFoundError(description=f"variable not found, id={variable_id}")
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return variable
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@_api_prerequisite
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@marshal_with(_WORKFLOW_DRAFT_VARIABLE_FIELDS)
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def patch(self, app_model: App, variable_id: str):
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# Request payload for file types:
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#
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# Local File:
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#
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# {
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# "type": "image",
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# "transfer_method": "local_file",
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# "url": "",
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# "upload_file_id": "daded54f-72c7-4f8e-9d18-9b0abdd9f190"
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# }
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#
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# Remote File:
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#
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#
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# {
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# "type": "image",
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# "transfer_method": "remote_url",
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# "url": "http://127.0.0.1:5001/files/1602650a-4fe4-423c-85a2-af76c083e3c4/file-preview?timestamp=1750041099&nonce=...&sign=...=",
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# "upload_file_id": "1602650a-4fe4-423c-85a2-af76c083e3c4"
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# }
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parser = reqparse.RequestParser()
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parser.add_argument(self._PATCH_NAME_FIELD, type=str, required=False, nullable=True, location="json")
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# Parse 'value' field as-is to maintain its original data structure
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parser.add_argument(self._PATCH_VALUE_FIELD, type=lambda x: x, required=False, nullable=True, location="json")
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draft_var_srv = WorkflowDraftVariableService(
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session=db.session(),
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)
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args = parser.parse_args(strict=True)
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variable = draft_var_srv.get_variable(variable_id=variable_id)
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if variable is None:
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raise NotFoundError(description=f"variable not found, id={variable_id}")
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if variable.app_id != app_model.id:
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raise NotFoundError(description=f"variable not found, id={variable_id}")
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new_name = args.get(self._PATCH_NAME_FIELD, None)
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raw_value = args.get(self._PATCH_VALUE_FIELD, None)
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if new_name is None and raw_value is None:
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return variable
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new_value = None
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if raw_value is not None:
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if variable.value_type == SegmentType.FILE:
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if not isinstance(raw_value, dict):
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raise InvalidArgumentError(description=f"expected dict for file, got {type(raw_value)}")
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raw_value = build_from_mapping(mapping=raw_value, tenant_id=app_model.tenant_id)
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elif variable.value_type == SegmentType.ARRAY_FILE:
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if not isinstance(raw_value, list):
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raise InvalidArgumentError(description=f"expected list for files, got {type(raw_value)}")
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if len(raw_value) > 0 and not isinstance(raw_value[0], dict):
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raise InvalidArgumentError(description=f"expected dict for files[0], got {type(raw_value)}")
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raw_value = build_from_mappings(mappings=raw_value, tenant_id=app_model.tenant_id)
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new_value = build_segment_with_type(variable.value_type, raw_value)
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draft_var_srv.update_variable(variable, name=new_name, value=new_value)
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db.session.commit()
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return variable
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@_api_prerequisite
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def delete(self, app_model: App, variable_id: str):
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draft_var_srv = WorkflowDraftVariableService(
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session=db.session(),
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)
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variable = draft_var_srv.get_variable(variable_id=variable_id)
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if variable is None:
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raise NotFoundError(description=f"variable not found, id={variable_id}")
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if variable.app_id != app_model.id:
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raise NotFoundError(description=f"variable not found, id={variable_id}")
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draft_var_srv.delete_variable(variable)
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db.session.commit()
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return Response("", 204)
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class VariableResetApi(Resource):
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@_api_prerequisite
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def put(self, app_model: App, variable_id: str):
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draft_var_srv = WorkflowDraftVariableService(
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session=db.session(),
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)
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workflow_srv = WorkflowService()
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draft_workflow = workflow_srv.get_draft_workflow(app_model)
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if draft_workflow is None:
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raise NotFoundError(
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f"Draft workflow not found, app_id={app_model.id}",
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)
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variable = draft_var_srv.get_variable(variable_id=variable_id)
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if variable is None:
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raise NotFoundError(description=f"variable not found, id={variable_id}")
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if variable.app_id != app_model.id:
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raise NotFoundError(description=f"variable not found, id={variable_id}")
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resetted = draft_var_srv.reset_variable(draft_workflow, variable)
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db.session.commit()
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if resetted is None:
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return Response("", 204)
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else:
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return marshal(resetted, _WORKFLOW_DRAFT_VARIABLE_FIELDS)
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def _get_variable_list(app_model: App, node_id) -> WorkflowDraftVariableList:
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with Session(bind=db.engine, expire_on_commit=False) as session:
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draft_var_srv = WorkflowDraftVariableService(
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session=session,
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)
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if node_id == CONVERSATION_VARIABLE_NODE_ID:
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draft_vars = draft_var_srv.list_conversation_variables(app_model.id)
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elif node_id == SYSTEM_VARIABLE_NODE_ID:
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draft_vars = draft_var_srv.list_system_variables(app_model.id)
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else:
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draft_vars = draft_var_srv.list_node_variables(app_id=app_model.id, node_id=node_id)
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return draft_vars
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|
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|
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class ConversationVariableCollectionApi(Resource):
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@_api_prerequisite
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@marshal_with(_WORKFLOW_DRAFT_VARIABLE_LIST_FIELDS)
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def get(self, app_model: App):
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# NOTE(QuantumGhost): Prefill conversation variables into the draft variables table
|
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# so their IDs can be returned to the caller.
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workflow_srv = WorkflowService()
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draft_workflow = workflow_srv.get_draft_workflow(app_model)
|
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if draft_workflow is None:
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raise NotFoundError(description=f"draft workflow not found, id={app_model.id}")
|
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draft_var_srv = WorkflowDraftVariableService(db.session())
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draft_var_srv.prefill_conversation_variable_default_values(draft_workflow)
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db.session.commit()
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return _get_variable_list(app_model, CONVERSATION_VARIABLE_NODE_ID)
|
||||
|
||||
|
||||
class SystemVariableCollectionApi(Resource):
|
||||
@_api_prerequisite
|
||||
@marshal_with(_WORKFLOW_DRAFT_VARIABLE_LIST_FIELDS)
|
||||
def get(self, app_model: App):
|
||||
return _get_variable_list(app_model, SYSTEM_VARIABLE_NODE_ID)
|
||||
|
||||
|
||||
class EnvironmentVariableCollectionApi(Resource):
|
||||
@_api_prerequisite
|
||||
def get(self, app_model: App):
|
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"""
|
||||
Get draft workflow
|
||||
"""
|
||||
# fetch draft workflow by app_model
|
||||
workflow_service = WorkflowService()
|
||||
workflow = workflow_service.get_draft_workflow(app_model=app_model)
|
||||
if workflow is None:
|
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raise DraftWorkflowNotExist()
|
||||
|
||||
env_vars = workflow.environment_variables
|
||||
env_vars_list = []
|
||||
for v in env_vars:
|
||||
env_vars_list.append(
|
||||
{
|
||||
"id": v.id,
|
||||
"type": "env",
|
||||
"name": v.name,
|
||||
"description": v.description,
|
||||
"selector": v.selector,
|
||||
"value_type": v.value_type.value,
|
||||
"value": v.value,
|
||||
# Do not track edited for env vars.
|
||||
"edited": False,
|
||||
"visible": True,
|
||||
"editable": True,
|
||||
}
|
||||
)
|
||||
|
||||
return {"items": env_vars_list}
|
||||
|
||||
|
||||
api.add_resource(
|
||||
WorkflowVariableCollectionApi,
|
||||
"/apps/<uuid:app_id>/workflows/draft/variables",
|
||||
)
|
||||
api.add_resource(NodeVariableCollectionApi, "/apps/<uuid:app_id>/workflows/draft/nodes/<string:node_id>/variables")
|
||||
api.add_resource(VariableApi, "/apps/<uuid:app_id>/workflows/draft/variables/<uuid:variable_id>")
|
||||
api.add_resource(VariableResetApi, "/apps/<uuid:app_id>/workflows/draft/variables/<uuid:variable_id>/reset")
|
||||
|
||||
api.add_resource(ConversationVariableCollectionApi, "/apps/<uuid:app_id>/workflows/draft/conversation-variables")
|
||||
api.add_resource(SystemVariableCollectionApi, "/apps/<uuid:app_id>/workflows/draft/system-variables")
|
||||
api.add_resource(EnvironmentVariableCollectionApi, "/apps/<uuid:app_id>/workflows/draft/environment-variables")
|
||||
@ -1 +1,11 @@
|
||||
from typing import Any
|
||||
|
||||
# TODO(QuantumGhost): Refactor variable type identification. Instead of directly
|
||||
# comparing `dify_model_identity` with constants throughout the codebase, extract
|
||||
# this logic into a dedicated function. This would encapsulate the implementation
|
||||
# details of how different variable types are identified.
|
||||
FILE_MODEL_IDENTITY = "__dify__file__"
|
||||
|
||||
|
||||
def maybe_file_object(o: Any) -> bool:
|
||||
return isinstance(o, dict) and o.get("dify_model_identity") == FILE_MODEL_IDENTITY
|
||||
|
||||
@ -1,8 +1,26 @@
|
||||
import json
|
||||
from collections.abc import Iterable, Sequence
|
||||
|
||||
from .segment_group import SegmentGroup
|
||||
from .segments import ArrayFileSegment, FileSegment, Segment
|
||||
|
||||
|
||||
def to_selector(node_id: str, name: str, paths: Iterable[str] = ()) -> Sequence[str]:
|
||||
selectors = [node_id, name]
|
||||
if paths:
|
||||
selectors.extend(paths)
|
||||
return selectors
|
||||
|
||||
|
||||
class SegmentJSONEncoder(json.JSONEncoder):
|
||||
def default(self, o):
|
||||
if isinstance(o, ArrayFileSegment):
|
||||
return [v.model_dump() for v in o.value]
|
||||
elif isinstance(o, FileSegment):
|
||||
return o.value.model_dump()
|
||||
elif isinstance(o, SegmentGroup):
|
||||
return [self.default(seg) for seg in o.value]
|
||||
elif isinstance(o, Segment):
|
||||
return o.value
|
||||
else:
|
||||
super().default(o)
|
||||
|
||||
@ -0,0 +1,39 @@
|
||||
import abc
|
||||
from typing import Protocol
|
||||
|
||||
from core.variables import Variable
|
||||
|
||||
|
||||
class ConversationVariableUpdater(Protocol):
|
||||
"""
|
||||
ConversationVariableUpdater defines an abstraction for updating conversation variable values.
|
||||
|
||||
It is intended for use by `v1.VariableAssignerNode` and `v2.VariableAssignerNode` when updating
|
||||
conversation variables.
|
||||
|
||||
Implementations may choose to batch updates. If batching is used, the `flush` method
|
||||
should be implemented to persist buffered changes, and `update`
|
||||
should handle buffering accordingly.
|
||||
|
||||
Note: Since implementations may buffer updates, instances of ConversationVariableUpdater
|
||||
are not thread-safe. Each VariableAssignerNode should create its own instance during execution.
|
||||
"""
|
||||
|
||||
@abc.abstractmethod
|
||||
def update(self, conversation_id: str, variable: "Variable") -> None:
|
||||
"""
|
||||
Updates the value of the specified conversation variable in the underlying storage.
|
||||
|
||||
:param conversation_id: The ID of the conversation to update. Typically references `ConversationVariable.id`.
|
||||
:param variable: The `Variable` instance containing the updated value.
|
||||
"""
|
||||
pass
|
||||
|
||||
@abc.abstractmethod
|
||||
def flush(self):
|
||||
"""
|
||||
Flushes all pending updates to the underlying storage system.
|
||||
|
||||
If the implementation does not buffer updates, this method can be a no-op.
|
||||
"""
|
||||
pass
|
||||
@ -1,19 +1,55 @@
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.orm import Session
|
||||
from collections.abc import Mapping, MutableMapping, Sequence
|
||||
from typing import Any, TypeVar
|
||||
|
||||
from core.variables import Variable
|
||||
from core.workflow.nodes.variable_assigner.common.exc import VariableOperatorNodeError
|
||||
from extensions.ext_database import db
|
||||
from models import ConversationVariable
|
||||
from pydantic import BaseModel
|
||||
|
||||
from core.variables import Segment
|
||||
from core.variables.consts import MIN_SELECTORS_LENGTH
|
||||
from core.variables.types import SegmentType
|
||||
|
||||
def update_conversation_variable(conversation_id: str, variable: Variable):
|
||||
stmt = select(ConversationVariable).where(
|
||||
ConversationVariable.id == variable.id, ConversationVariable.conversation_id == conversation_id
|
||||
# Use double underscore (`__`) prefix for internal variables
|
||||
# to minimize risk of collision with user-defined variable names.
|
||||
_UPDATED_VARIABLES_KEY = "__updated_variables"
|
||||
|
||||
|
||||
class UpdatedVariable(BaseModel):
|
||||
name: str
|
||||
selector: Sequence[str]
|
||||
value_type: SegmentType
|
||||
new_value: Any
|
||||
|
||||
|
||||
_T = TypeVar("_T", bound=MutableMapping[str, Any])
|
||||
|
||||
|
||||
def variable_to_processed_data(selector: Sequence[str], seg: Segment) -> UpdatedVariable:
|
||||
if len(selector) < MIN_SELECTORS_LENGTH:
|
||||
raise Exception("selector too short")
|
||||
node_id, var_name = selector[:2]
|
||||
return UpdatedVariable(
|
||||
name=var_name,
|
||||
selector=list(selector[:2]),
|
||||
value_type=seg.value_type,
|
||||
new_value=seg.value,
|
||||
)
|
||||
with Session(db.engine) as session:
|
||||
row = session.scalar(stmt)
|
||||
if not row:
|
||||
raise VariableOperatorNodeError("conversation variable not found in the database")
|
||||
row.data = variable.model_dump_json()
|
||||
session.commit()
|
||||
|
||||
|
||||
def set_updated_variables(m: _T, updates: Sequence[UpdatedVariable]) -> _T:
|
||||
m[_UPDATED_VARIABLES_KEY] = updates
|
||||
return m
|
||||
|
||||
|
||||
def get_updated_variables(m: Mapping[str, Any]) -> Sequence[UpdatedVariable] | None:
|
||||
updated_values = m.get(_UPDATED_VARIABLES_KEY, None)
|
||||
if updated_values is None:
|
||||
return None
|
||||
result = []
|
||||
for items in updated_values:
|
||||
if isinstance(items, UpdatedVariable):
|
||||
result.append(items)
|
||||
elif isinstance(items, dict):
|
||||
items = UpdatedVariable.model_validate(items)
|
||||
result.append(items)
|
||||
else:
|
||||
raise TypeError(f"Invalid updated variable: {items}, type={type(items)}")
|
||||
return result
|
||||
|
||||
@ -0,0 +1,38 @@
|
||||
from sqlalchemy import Engine, select
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from core.variables.variables import Variable
|
||||
from models.engine import db
|
||||
from models.workflow import ConversationVariable
|
||||
|
||||
from .exc import VariableOperatorNodeError
|
||||
|
||||
|
||||
class ConversationVariableUpdaterImpl:
|
||||
_engine: Engine | None
|
||||
|
||||
def __init__(self, engine: Engine | None = None) -> None:
|
||||
self._engine = engine
|
||||
|
||||
def _get_engine(self) -> Engine:
|
||||
if self._engine:
|
||||
return self._engine
|
||||
return db.engine
|
||||
|
||||
def update(self, conversation_id: str, variable: Variable):
|
||||
stmt = select(ConversationVariable).where(
|
||||
ConversationVariable.id == variable.id, ConversationVariable.conversation_id == conversation_id
|
||||
)
|
||||
with Session(self._get_engine()) as session:
|
||||
row = session.scalar(stmt)
|
||||
if not row:
|
||||
raise VariableOperatorNodeError("conversation variable not found in the database")
|
||||
row.data = variable.model_dump_json()
|
||||
session.commit()
|
||||
|
||||
def flush(self):
|
||||
pass
|
||||
|
||||
|
||||
def conversation_variable_updater_factory() -> ConversationVariableUpdaterImpl:
|
||||
return ConversationVariableUpdaterImpl()
|
||||
@ -0,0 +1,28 @@
|
||||
from core.variables.segments import ObjectSegment, Segment
|
||||
from core.workflow.entities.variable_pool import VariablePool, VariableValue
|
||||
|
||||
|
||||
def append_variables_recursively(
|
||||
pool: VariablePool, node_id: str, variable_key_list: list[str], variable_value: VariableValue | Segment
|
||||
):
|
||||
"""
|
||||
Append variables recursively
|
||||
:param node_id: node id
|
||||
:param variable_key_list: variable key list
|
||||
:param variable_value: variable value
|
||||
:return:
|
||||
"""
|
||||
pool.add([node_id] + variable_key_list, variable_value)
|
||||
|
||||
# if variable_value is a dict, then recursively append variables
|
||||
if isinstance(variable_value, ObjectSegment):
|
||||
variable_dict = variable_value.value
|
||||
elif isinstance(variable_value, dict):
|
||||
variable_dict = variable_value
|
||||
else:
|
||||
return
|
||||
|
||||
for key, value in variable_dict.items():
|
||||
# construct new key list
|
||||
new_key_list = variable_key_list + [key]
|
||||
append_variables_recursively(pool, node_id=node_id, variable_key_list=new_key_list, variable_value=value)
|
||||
@ -0,0 +1,84 @@
|
||||
import abc
|
||||
from collections.abc import Mapping, Sequence
|
||||
from typing import Any, Protocol
|
||||
|
||||
from core.variables import Variable
|
||||
from core.variables.consts import MIN_SELECTORS_LENGTH
|
||||
from core.workflow.entities.variable_pool import VariablePool
|
||||
from core.workflow.utils import variable_utils
|
||||
|
||||
|
||||
class VariableLoader(Protocol):
|
||||
"""Interface for loading variables based on selectors.
|
||||
|
||||
A `VariableLoader` is responsible for retrieving additional variables required during the execution
|
||||
of a single node, which are not provided as user inputs.
|
||||
|
||||
NOTE(QuantumGhost): Typically, all variables loaded by a `VariableLoader` should belong to the same
|
||||
application and share the same `app_id`. However, this interface does not enforce that constraint,
|
||||
and the `app_id` parameter is intentionally omitted from `load_variables` to achieve separation of
|
||||
concern and allow for flexible implementations.
|
||||
|
||||
Implementations of `VariableLoader` should almost always have an `app_id` parameter in
|
||||
their constructor.
|
||||
|
||||
TODO(QuantumGhost): this is a temporally workaround. If we can move the creation of node instance into
|
||||
`WorkflowService.single_step_run`, we may get rid of this interface.
|
||||
"""
|
||||
|
||||
@abc.abstractmethod
|
||||
def load_variables(self, selectors: list[list[str]]) -> list[Variable]:
|
||||
"""Load variables based on the provided selectors. If the selectors are empty,
|
||||
this method should return an empty list.
|
||||
|
||||
The order of the returned variables is not guaranteed. If the caller wants to ensure
|
||||
a specific order, they should sort the returned list themselves.
|
||||
|
||||
:param: selectors: a list of string list, each inner list should have at least two elements:
|
||||
- the first element is the node ID,
|
||||
- the second element is the variable name.
|
||||
:return: a list of Variable objects that match the provided selectors.
|
||||
"""
|
||||
pass
|
||||
|
||||
|
||||
class _DummyVariableLoader(VariableLoader):
|
||||
"""A dummy implementation of VariableLoader that does not load any variables.
|
||||
Serves as a placeholder when no variable loading is needed.
|
||||
"""
|
||||
|
||||
def load_variables(self, selectors: list[list[str]]) -> list[Variable]:
|
||||
return []
|
||||
|
||||
|
||||
DUMMY_VARIABLE_LOADER = _DummyVariableLoader()
|
||||
|
||||
|
||||
def load_into_variable_pool(
|
||||
variable_loader: VariableLoader,
|
||||
variable_pool: VariablePool,
|
||||
variable_mapping: Mapping[str, Sequence[str]],
|
||||
user_inputs: Mapping[str, Any],
|
||||
):
|
||||
# Loading missing variable from draft var here, and set it into
|
||||
# variable_pool.
|
||||
variables_to_load: list[list[str]] = []
|
||||
for key, selector in variable_mapping.items():
|
||||
# NOTE(QuantumGhost): this logic needs to be in sync with
|
||||
# `WorkflowEntry.mapping_user_inputs_to_variable_pool`.
|
||||
node_variable_list = key.split(".")
|
||||
if len(node_variable_list) < 1:
|
||||
raise ValueError(f"Invalid variable key: {key}. It should have at least one element.")
|
||||
if key in user_inputs:
|
||||
continue
|
||||
node_variable_key = ".".join(node_variable_list[1:])
|
||||
if node_variable_key in user_inputs:
|
||||
continue
|
||||
if variable_pool.get(selector) is None:
|
||||
variables_to_load.append(list(selector))
|
||||
loaded = variable_loader.load_variables(variables_to_load)
|
||||
for var in loaded:
|
||||
assert len(var.selector) >= MIN_SELECTORS_LENGTH, f"Invalid variable {var}"
|
||||
variable_utils.append_variables_recursively(
|
||||
variable_pool, node_id=var.selector[0], variable_key_list=list(var.selector[1:]), variable_value=var
|
||||
)
|
||||
@ -0,0 +1,49 @@
|
||||
import json
|
||||
from collections.abc import Mapping
|
||||
from typing import Any
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from core.file.models import File
|
||||
from core.variables import Segment
|
||||
|
||||
|
||||
class WorkflowRuntimeTypeEncoder(json.JSONEncoder):
|
||||
def default(self, o: Any):
|
||||
if isinstance(o, Segment):
|
||||
return o.value
|
||||
elif isinstance(o, File):
|
||||
return o.to_dict()
|
||||
elif isinstance(o, BaseModel):
|
||||
return o.model_dump(mode="json")
|
||||
else:
|
||||
return super().default(o)
|
||||
|
||||
|
||||
class WorkflowRuntimeTypeConverter:
|
||||
def to_json_encodable(self, value: Mapping[str, Any] | None) -> Mapping[str, Any] | None:
|
||||
result = self._to_json_encodable_recursive(value)
|
||||
return result if isinstance(result, Mapping) or result is None else dict(result)
|
||||
|
||||
def _to_json_encodable_recursive(self, value: Any) -> Any:
|
||||
if value is None:
|
||||
return value
|
||||
if isinstance(value, (bool, int, str, float)):
|
||||
return value
|
||||
if isinstance(value, Segment):
|
||||
return self._to_json_encodable_recursive(value.value)
|
||||
if isinstance(value, File):
|
||||
return value.to_dict()
|
||||
if isinstance(value, BaseModel):
|
||||
return value.model_dump(mode="json")
|
||||
if isinstance(value, dict):
|
||||
res = {}
|
||||
for k, v in value.items():
|
||||
res[k] = self._to_json_encodable_recursive(v)
|
||||
return res
|
||||
if isinstance(value, list):
|
||||
res_list = []
|
||||
for item in value:
|
||||
res_list.append(self._to_json_encodable_recursive(item))
|
||||
return res_list
|
||||
return value
|
||||
@ -0,0 +1,22 @@
|
||||
import abc
|
||||
import datetime
|
||||
from typing import Protocol
|
||||
|
||||
|
||||
class _NowFunction(Protocol):
|
||||
@abc.abstractmethod
|
||||
def __call__(self, tz: datetime.timezone | None) -> datetime.datetime:
|
||||
pass
|
||||
|
||||
|
||||
# _now_func is a callable with the _NowFunction signature.
|
||||
# Its sole purpose is to abstract time retrieval, enabling
|
||||
# developers to mock this behavior in tests and time-dependent scenarios.
|
||||
_now_func: _NowFunction = datetime.datetime.now
|
||||
|
||||
|
||||
def naive_utc_now() -> datetime.datetime:
|
||||
"""Return a naive datetime object (without timezone information)
|
||||
representing current UTC time.
|
||||
"""
|
||||
return _now_func(datetime.UTC).replace(tzinfo=None)
|
||||
@ -0,0 +1,11 @@
|
||||
import json
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
|
||||
class PydanticModelEncoder(json.JSONEncoder):
|
||||
def default(self, o):
|
||||
if isinstance(o, BaseModel):
|
||||
return o.model_dump()
|
||||
else:
|
||||
super().default(o)
|
||||
@ -0,0 +1,66 @@
|
||||
"""remove sequence_number from workflow_runs
|
||||
|
||||
Revision ID: 0ab65e1cc7fa
|
||||
Revises: 4474872b0ee6
|
||||
Create Date: 2025-06-19 16:33:13.377215
|
||||
|
||||
"""
|
||||
from alembic import op
|
||||
import models as models
|
||||
import sqlalchemy as sa
|
||||
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision = '0ab65e1cc7fa'
|
||||
down_revision = '4474872b0ee6'
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade():
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
with op.batch_alter_table('workflow_runs', schema=None) as batch_op:
|
||||
batch_op.drop_index(batch_op.f('workflow_run_tenant_app_sequence_idx'))
|
||||
batch_op.drop_column('sequence_number')
|
||||
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
def downgrade():
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
|
||||
# WARNING: This downgrade CANNOT recover the original sequence_number values!
|
||||
# The original sequence numbers are permanently lost after the upgrade.
|
||||
# This downgrade will regenerate sequence numbers based on created_at order,
|
||||
# which may result in different values than the original sequence numbers.
|
||||
#
|
||||
# If you need to preserve original sequence numbers, use the alternative
|
||||
# migration approach that creates a backup table before removal.
|
||||
|
||||
# Step 1: Add sequence_number column as nullable first
|
||||
with op.batch_alter_table('workflow_runs', schema=None) as batch_op:
|
||||
batch_op.add_column(sa.Column('sequence_number', sa.INTEGER(), autoincrement=False, nullable=True))
|
||||
|
||||
# Step 2: Populate sequence_number values based on created_at order within each app
|
||||
# NOTE: This recreates sequence numbering logic but values will be different
|
||||
# from the original sequence numbers that were removed in the upgrade
|
||||
connection = op.get_bind()
|
||||
connection.execute(sa.text("""
|
||||
UPDATE workflow_runs
|
||||
SET sequence_number = subquery.row_num
|
||||
FROM (
|
||||
SELECT id, ROW_NUMBER() OVER (
|
||||
PARTITION BY tenant_id, app_id
|
||||
ORDER BY created_at, id
|
||||
) as row_num
|
||||
FROM workflow_runs
|
||||
) subquery
|
||||
WHERE workflow_runs.id = subquery.id
|
||||
"""))
|
||||
|
||||
# Step 3: Make the column NOT NULL and add the index
|
||||
with op.batch_alter_table('workflow_runs', schema=None) as batch_op:
|
||||
batch_op.alter_column('sequence_number', nullable=False)
|
||||
batch_op.create_index(batch_op.f('workflow_run_tenant_app_sequence_idx'), ['tenant_id', 'app_id', 'sequence_number'], unique=False)
|
||||
|
||||
# ### end Alembic commands ###
|
||||
@ -0,0 +1,20 @@
|
||||
"""All these exceptions are not meant to be caught by callers."""
|
||||
|
||||
|
||||
class WorkflowDataError(Exception):
|
||||
"""Base class for all workflow data related exceptions.
|
||||
|
||||
This should be used to indicate issues with workflow data integrity, such as
|
||||
no `graph` configuration, missing `nodes` field in `graph` configuration, or
|
||||
similar issues.
|
||||
"""
|
||||
|
||||
pass
|
||||
|
||||
|
||||
class NodeNotFoundError(WorkflowDataError):
|
||||
"""Raised when a node with the specified ID is not found in the workflow."""
|
||||
|
||||
def __init__(self, node_id: str):
|
||||
super().__init__(f"Node with ID '{node_id}' not found in the workflow.")
|
||||
self.node_id = node_id
|
||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue