add build task for release/e-3.0.2

Co-authored-by: siqiuchen <siqiu.chen2@dentsplysirona.com>

.github/workflows/build-push.yml

@@ -6,6 +6,7 @@ on:
       - "main"
       - "deploy/dev"
       - "deploy/enterprise"
+      - "release/e-*"
     tags:
       - "*"
 

api/configs/middleware/__init__.py

@@ -223,6 +223,10 @@ class CeleryConfig(DatabaseConfig):
         default=None,
     )
 
+    CELERY_SENTINEL_PASSWORD: Optional[str] = Field(
+        description="Password of the Redis Sentinel master.",
+        default=None,
+    )
     CELERY_SENTINEL_SOCKET_TIMEOUT: Optional[PositiveFloat] = Field(
         description="Timeout for Redis Sentinel socket operations in seconds.",
         default=0.1,

api/controllers/console/workspace/members.py

@@ -85,6 +85,7 @@ class MemberInviteEmailApi(Resource):
         return {
             "result": "success",
             "invitation_results": invitation_results,
+            "tenant_id": str(current_user.current_tenant.id),
         }, 201
 
 
@@ -110,7 +111,7 @@ class MemberCancelInviteApi(Resource):
             except Exception as e:
                 raise ValueError(str(e))
 
-        return {"result": "success"}, 204
+        return {"result": "success", "tenant_id": str(current_user.current_tenant.id)}, 200
 
 
 class MemberUpdateRoleApi(Resource):

api/controllers/console/workspace/plugin.py

@@ -13,6 +13,7 @@ from core.model_runtime.utils.encoders import jsonable_encoder
 from core.plugin.impl.exc import PluginDaemonClientSideError
 from libs.login import login_required
 from models.account import TenantPluginPermission
+from services.plugin.plugin_parameter_service import PluginParameterService
 from services.plugin.plugin_permission_service import PluginPermissionService
 from services.plugin.plugin_service import PluginService
 
@@ -497,6 +498,42 @@ class PluginFetchPermissionApi(Resource):
         )
 
 
+class PluginFetchDynamicSelectOptionsApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self):
+        # check if the user is admin or owner
+        if not current_user.is_admin_or_owner:
+            raise Forbidden()
+
+        tenant_id = current_user.current_tenant_id
+        user_id = current_user.id
+
+        parser = reqparse.RequestParser()
+        parser.add_argument("plugin_id", type=str, required=True, location="args")
+        parser.add_argument("provider", type=str, required=True, location="args")
+        parser.add_argument("action", type=str, required=True, location="args")
+        parser.add_argument("parameter", type=str, required=True, location="args")
+        parser.add_argument("provider_type", type=str, required=True, location="args")
+        args = parser.parse_args()
+
+        try:
+            options = PluginParameterService.get_dynamic_select_options(
+                tenant_id,
+                user_id,
+                args["plugin_id"],
+                args["provider"],
+                args["action"],
+                args["parameter"],
+                args["provider_type"],
+            )
+        except PluginDaemonClientSideError as e:
+            raise ValueError(e)
+
+        return jsonable_encoder({"options": options})
+
+
 api.add_resource(PluginDebuggingKeyApi, "/workspaces/current/plugin/debugging-key")
 api.add_resource(PluginListApi, "/workspaces/current/plugin/list")
 api.add_resource(PluginListLatestVersionsApi, "/workspaces/current/plugin/list/latest-versions")
@@ -521,3 +558,5 @@ api.add_resource(PluginFetchMarketplacePkgApi, "/workspaces/current/plugin/marke
 
 api.add_resource(PluginChangePermissionApi, "/workspaces/current/plugin/permission/change")
 api.add_resource(PluginFetchPermissionApi, "/workspaces/current/plugin/permission/fetch")
+
+api.add_resource(PluginFetchDynamicSelectOptionsApi, "/workspaces/current/plugin/parameters/dynamic-options")

api/controllers/inner_api/plugin/plugin.py

@@ -17,6 +17,7 @@ from core.plugin.entities.request import (
     RequestInvokeApp,
     RequestInvokeEncrypt,
     RequestInvokeLLM,
+    RequestInvokeLLMWithStructuredOutput,
     RequestInvokeModeration,
     RequestInvokeParameterExtractorNode,
     RequestInvokeQuestionClassifierNode,
@@ -47,6 +48,21 @@ class PluginInvokeLLMApi(Resource):
         return length_prefixed_response(0xF, generator())
 
 
+class PluginInvokeLLMWithStructuredOutputApi(Resource):
+    @setup_required
+    @plugin_inner_api_only
+    @get_user_tenant
+    @plugin_data(payload_type=RequestInvokeLLMWithStructuredOutput)
+    def post(self, user_model: Account | EndUser, tenant_model: Tenant, payload: RequestInvokeLLMWithStructuredOutput):
+        def generator():
+            response = PluginModelBackwardsInvocation.invoke_llm_with_structured_output(
+                user_model.id, tenant_model, payload
+            )
+            return PluginModelBackwardsInvocation.convert_to_event_stream(response)
+
+        return length_prefixed_response(0xF, generator())
+
+
 class PluginInvokeTextEmbeddingApi(Resource):
     @setup_required
     @plugin_inner_api_only
@@ -291,6 +307,7 @@ class PluginFetchAppInfoApi(Resource):
 
 
 api.add_resource(PluginInvokeLLMApi, "/invoke/llm")
+api.add_resource(PluginInvokeLLMWithStructuredOutputApi, "/invoke/llm/structured-output")
 api.add_resource(PluginInvokeTextEmbeddingApi, "/invoke/text-embedding")
 api.add_resource(PluginInvokeRerankApi, "/invoke/rerank")
 api.add_resource(PluginInvokeTTSApi, "/invoke/tts")

api/controllers/inner_api/workspace/workspace.py

@@ -29,7 +29,19 @@ class EnterpriseWorkspace(Resource):
 
         tenant_was_created.send(tenant)
 
-        return {"message": "enterprise workspace created."}
+        resp = {
+            "id": tenant.id,
+            "name": tenant.name,
+            "plan": tenant.plan,
+            "status": tenant.status,
+            "created_at": tenant.created_at.isoformat() + "Z" if tenant.created_at else None,
+            "updated_at": tenant.updated_at.isoformat() + "Z" if tenant.updated_at else None,
+        }
+
+        return {
+            "message": "enterprise workspace created.",
+            "tenant": resp,
+        }
 
 
 class EnterpriseWorkspaceNoOwnerEmail(Resource):

api/controllers/service_api/dataset/dataset.py

@@ -133,6 +133,22 @@ class DatasetListApi(DatasetApiResource):
         parser.add_argument("embedding_model_provider", type=str, required=False, nullable=True, location="json")
 
         args = parser.parse_args()
+
+        if args.get("embedding_model_provider"):
+            DatasetService.check_embedding_model_setting(
+                tenant_id, args.get("embedding_model_provider"), args.get("embedding_model")
+            )
+        if (
+            args.get("retrieval_model")
+            and args.get("retrieval_model").get("reranking_model")
+            and args.get("retrieval_model").get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                tenant_id,
+                args.get("retrieval_model").get("reranking_model").get("reranking_provider_name"),
+                args.get("retrieval_model").get("reranking_model").get("reranking_model_name"),
+            )
+
         try:
             dataset = DatasetService.create_empty_dataset(
                 tenant_id=tenant_id,
@@ -265,10 +281,20 @@ class DatasetApi(DatasetApiResource):
         data = request.get_json()
 
         # check embedding model setting
-        if data.get("indexing_technique") == "high_quality":
+        if data.get("indexing_technique") == "high_quality" or data.get("embedding_model_provider"):
             DatasetService.check_embedding_model_setting(
                 dataset.tenant_id, data.get("embedding_model_provider"), data.get("embedding_model")
             )
+        if (
+            data.get("retrieval_model")
+            and data.get("retrieval_model").get("reranking_model")
+            and data.get("retrieval_model").get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                dataset.tenant_id,
+                data.get("retrieval_model").get("reranking_model").get("reranking_provider_name"),
+                data.get("retrieval_model").get("reranking_model").get("reranking_model_name"),
+            )
 
         # The role of the current user in the ta table must be admin, owner, editor, or dataset_operator
         DatasetPermissionService.check_permission(

api/controllers/service_api/dataset/document.py

@@ -29,7 +29,7 @@ from extensions.ext_database import db
 from fields.document_fields import document_fields, document_status_fields
 from libs.login import current_user
 from models.dataset import Dataset, Document, DocumentSegment
-from services.dataset_service import DocumentService
+from services.dataset_service import DatasetService, DocumentService
 from services.entities.knowledge_entities.knowledge_entities import KnowledgeConfig
 from services.file_service import FileService
 
@@ -59,6 +59,7 @@ class DocumentAddByTextApi(DatasetApiResource):
         parser.add_argument("embedding_model_provider", type=str, required=False, nullable=True, location="json")
 
         args = parser.parse_args()
+
         dataset_id = str(dataset_id)
         tenant_id = str(tenant_id)
         dataset = db.session.query(Dataset).filter(Dataset.tenant_id == tenant_id, Dataset.id == dataset_id).first()
@@ -74,6 +75,21 @@ class DocumentAddByTextApi(DatasetApiResource):
         if text is None or name is None:
             raise ValueError("Both 'text' and 'name' must be non-null values.")
 
+        if args.get("embedding_model_provider"):
+            DatasetService.check_embedding_model_setting(
+                tenant_id, args.get("embedding_model_provider"), args.get("embedding_model")
+            )
+        if (
+            args.get("retrieval_model")
+            and args.get("retrieval_model").get("reranking_model")
+            and args.get("retrieval_model").get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                tenant_id,
+                args.get("retrieval_model").get("reranking_model").get("reranking_provider_name"),
+                args.get("retrieval_model").get("reranking_model").get("reranking_model_name"),
+            )
+
         upload_file = FileService.upload_text(text=str(text), text_name=str(name))
         data_source = {
             "type": "upload_file",
@@ -124,6 +140,17 @@ class DocumentUpdateByTextApi(DatasetApiResource):
         if not dataset:
             raise ValueError("Dataset does not exist.")
 
+        if (
+            args.get("retrieval_model")
+            and args.get("retrieval_model").get("reranking_model")
+            and args.get("retrieval_model").get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                tenant_id,
+                args.get("retrieval_model").get("reranking_model").get("reranking_provider_name"),
+                args.get("retrieval_model").get("reranking_model").get("reranking_model_name"),
+            )
+
         # indexing_technique is already set in dataset since this is an update
         args["indexing_technique"] = dataset.indexing_technique
 
@@ -188,6 +215,21 @@ class DocumentAddByFileApi(DatasetApiResource):
             raise ValueError("indexing_technique is required.")
         args["indexing_technique"] = indexing_technique
 
+        if "embedding_model_provider" in args:
+            DatasetService.check_embedding_model_setting(
+                tenant_id, args["embedding_model_provider"], args["embedding_model"]
+            )
+        if (
+            "retrieval_model" in args
+            and args["retrieval_model"].get("reranking_model")
+            and args["retrieval_model"].get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                tenant_id,
+                args["retrieval_model"].get("reranking_model").get("reranking_provider_name"),
+                args["retrieval_model"].get("reranking_model").get("reranking_model_name"),
+            )
+
         # save file info
         file = request.files["file"]
         # check file

api/core/app/apps/advanced_chat/app_generator.py

@@ -36,7 +36,6 @@ from libs.flask_utils import preserve_flask_contexts
 from models import Account, App, Conversation, EndUser, Message, Workflow, WorkflowNodeExecutionTriggeredFrom
 from models.enums import WorkflowRunTriggeredFrom
 from services.conversation_service import ConversationService
-from services.errors.message import MessageNotExistsError
 from services.workflow_draft_variable_service import DraftVarLoader, WorkflowDraftVariableService
 
 logger = logging.getLogger(__name__)
@@ -480,8 +479,6 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
                 # get conversation and message
                 conversation = self._get_conversation(conversation_id)
                 message = self._get_message(message_id)
-                if message is None:
-                    raise MessageNotExistsError("Message not exists")
 
                 # chatbot app
                 runner = AdvancedChatAppRunner(

api/core/app/apps/agent_chat/app_generator.py

@@ -26,7 +26,6 @@ from factories import file_factory
 from libs.flask_utils import preserve_flask_contexts
 from models import Account, App, EndUser
 from services.conversation_service import ConversationService
-from services.errors.message import MessageNotExistsError
 
 logger = logging.getLogger(__name__)
 
@@ -238,8 +237,6 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
                 # get conversation and message
                 conversation = self._get_conversation(conversation_id)
                 message = self._get_message(message_id)
-                if message is None:
-                    raise MessageNotExistsError("Message not exists")
 
                 # chatbot app
                 runner = AgentChatAppRunner()

api/core/app/apps/chat/app_generator.py

@@ -25,7 +25,6 @@ from factories import file_factory
 from models.account import Account
 from models.model import App, EndUser
 from services.conversation_service import ConversationService
-from services.errors.message import MessageNotExistsError
 
 logger = logging.getLogger(__name__)
 
@@ -224,8 +223,6 @@ class ChatAppGenerator(MessageBasedAppGenerator):
                 # get conversation and message
                 conversation = self._get_conversation(conversation_id)
                 message = self._get_message(message_id)
-                if message is None:
-                    raise MessageNotExistsError("Message not exists")
 
                 # chatbot app
                 runner = ChatAppRunner()

api/core/app/apps/completion/app_generator.py

@@ -201,8 +201,6 @@ class CompletionAppGenerator(MessageBasedAppGenerator):
             try:
                 # get message
                 message = self._get_message(message_id)
-                if message is None:
-                    raise MessageNotExistsError()
 
                 # chatbot app
                 runner = CompletionAppRunner()

api/core/app/apps/message_based_app_generator.py

@@ -29,6 +29,7 @@ from models.enums import CreatorUserRole
 from models.model import App, AppMode, AppModelConfig, Conversation, EndUser, Message, MessageFile
 from services.errors.app_model_config import AppModelConfigBrokenError
 from services.errors.conversation import ConversationNotExistsError
+from services.errors.message import MessageNotExistsError
 
 logger = logging.getLogger(__name__)
 
@@ -251,7 +252,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
 
         return introduction or ""
 
-    def _get_conversation(self, conversation_id: str):
+    def _get_conversation(self, conversation_id: str) -> Conversation:
         """
         Get conversation by conversation id
         :param conversation_id: conversation id
@@ -260,11 +261,11 @@ class MessageBasedAppGenerator(BaseAppGenerator):
         conversation = db.session.query(Conversation).filter(Conversation.id == conversation_id).first()
 
         if not conversation:
-            raise ConversationNotExistsError()
+            raise ConversationNotExistsError("Conversation not exists")
 
         return conversation
 
-    def _get_message(self, message_id: str) -> Optional[Message]:
+    def _get_message(self, message_id: str) -> Message:
         """
         Get message by message id
         :param message_id: message id
@@ -272,4 +273,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
         """
         message = db.session.query(Message).filter(Message.id == message_id).first()
 
+        if message is None:
+            raise MessageNotExistsError("Message not exists")
+
         return message

api/core/entities/parameter_entities.py

@@ -15,6 +15,11 @@ class CommonParameterType(StrEnum):
     MODEL_SELECTOR = "model-selector"
     TOOLS_SELECTOR = "array[tools]"
 
+    # Dynamic select parameter
+    # Once you are not sure about the available options until authorization is done
+    # eg: Select a Slack channel from a Slack workspace
+    DYNAMIC_SELECT = "dynamic-select"
+
     # TOOL_SELECTOR = "tool-selector"
 
 

api/core/indexing_runner.py

@@ -534,7 +534,7 @@ class IndexingRunner:
         # chunk nodes by chunk size
         indexing_start_at = time.perf_counter()
         tokens = 0
-        if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX:
+        if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX and dataset.indexing_technique == "economy":
             # create keyword index
             create_keyword_thread = threading.Thread(
                 target=self._process_keyword_index,
@@ -572,7 +572,7 @@ class IndexingRunner:
 
                 for future in futures:
                     tokens += future.result()
-        if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX:
+        if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX and dataset.indexing_technique == "economy":
             create_keyword_thread.join()
         indexing_end_at = time.perf_counter()
 

api/core/llm_generator/output_parser/structured_output.py

@@ -0,0 +1,374 @@
+import json
+from collections.abc import Generator, Mapping, Sequence
+from copy import deepcopy
+from enum import StrEnum
+from typing import Any, Literal, Optional, cast, overload
+
+import json_repair
+from pydantic import TypeAdapter, ValidationError
+
+from core.llm_generator.output_parser.errors import OutputParserError
+from core.llm_generator.prompts import STRUCTURED_OUTPUT_PROMPT
+from core.model_manager import ModelInstance
+from core.model_runtime.callbacks.base_callback import Callback
+from core.model_runtime.entities.llm_entities import (
+    LLMResult,
+    LLMResultChunk,
+    LLMResultChunkDelta,
+    LLMResultChunkWithStructuredOutput,
+    LLMResultWithStructuredOutput,
+)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageTool,
+    SystemPromptMessage,
+)
+from core.model_runtime.entities.model_entities import AIModelEntity, ParameterRule
+
+
+class ResponseFormat(StrEnum):
+    """Constants for model response formats"""
+
+    JSON_SCHEMA = "json_schema"  # model's structured output mode. some model like gemini, gpt-4o,  support this mode.
+    JSON = "JSON"  # model's json mode. some model like claude support this mode.
+    JSON_OBJECT = "json_object"  # json mode's another alias. some model like deepseek-chat, qwen use this alias.
+
+
+class SpecialModelType(StrEnum):
+    """Constants for identifying model types"""
+
+    GEMINI = "gemini"
+    OLLAMA = "ollama"
+
+
+@overload
+def invoke_llm_with_structured_output(
+    provider: str,
+    model_schema: AIModelEntity,
+    model_instance: ModelInstance,
+    prompt_messages: Sequence[PromptMessage],
+    json_schema: Mapping[str, Any],
+    model_parameters: Optional[Mapping] = None,
+    tools: Sequence[PromptMessageTool] | None = None,
+    stop: Optional[list[str]] = None,
+    stream: Literal[True] = True,
+    user: Optional[str] = None,
+    callbacks: Optional[list[Callback]] = None,
+) -> Generator[LLMResultChunkWithStructuredOutput, None, None]: ...
+
+
+@overload
+def invoke_llm_with_structured_output(
+    provider: str,
+    model_schema: AIModelEntity,
+    model_instance: ModelInstance,
+    prompt_messages: Sequence[PromptMessage],
+    json_schema: Mapping[str, Any],
+    model_parameters: Optional[Mapping] = None,
+    tools: Sequence[PromptMessageTool] | None = None,
+    stop: Optional[list[str]] = None,
+    stream: Literal[False] = False,
+    user: Optional[str] = None,
+    callbacks: Optional[list[Callback]] = None,
+) -> LLMResultWithStructuredOutput: ...
+
+
+@overload
+def invoke_llm_with_structured_output(
+    provider: str,
+    model_schema: AIModelEntity,
+    model_instance: ModelInstance,
+    prompt_messages: Sequence[PromptMessage],
+    json_schema: Mapping[str, Any],
+    model_parameters: Optional[Mapping] = None,
+    tools: Sequence[PromptMessageTool] | None = None,
+    stop: Optional[list[str]] = None,
+    stream: bool = True,
+    user: Optional[str] = None,
+    callbacks: Optional[list[Callback]] = None,
+) -> LLMResultWithStructuredOutput | Generator[LLMResultChunkWithStructuredOutput, None, None]: ...
+
+
+def invoke_llm_with_structured_output(
+    provider: str,
+    model_schema: AIModelEntity,
+    model_instance: ModelInstance,
+    prompt_messages: Sequence[PromptMessage],
+    json_schema: Mapping[str, Any],
+    model_parameters: Optional[Mapping] = None,
+    tools: Sequence[PromptMessageTool] | None = None,
+    stop: Optional[list[str]] = None,
+    stream: bool = True,
+    user: Optional[str] = None,
+    callbacks: Optional[list[Callback]] = None,
+) -> LLMResultWithStructuredOutput | Generator[LLMResultChunkWithStructuredOutput, None, None]:
+    """
+    Invoke large language model with structured output
+    1. This method invokes model_instance.invoke_llm with json_schema
+    2. Try to parse the result as structured output
+
+    :param prompt_messages: prompt messages
+    :param json_schema: json schema
+    :param model_parameters: model parameters
+    :param tools: tools for tool calling
+    :param stop: stop words
+    :param stream: is stream response
+    :param user: unique user id
+    :param callbacks: callbacks
+    :return: full response or stream response chunk generator result
+    """
+
+    # handle native json schema
+    model_parameters_with_json_schema: dict[str, Any] = {
+        **(model_parameters or {}),
+    }
+
+    if model_schema.support_structure_output:
+        model_parameters = _handle_native_json_schema(
+            provider, model_schema, json_schema, model_parameters_with_json_schema, model_schema.parameter_rules
+        )
+    else:
+        # Set appropriate response format based on model capabilities
+        _set_response_format(model_parameters_with_json_schema, model_schema.parameter_rules)
+
+        # handle prompt based schema
+        prompt_messages = _handle_prompt_based_schema(
+            prompt_messages=prompt_messages,
+            structured_output_schema=json_schema,
+        )
+
+    llm_result = model_instance.invoke_llm(
+        prompt_messages=list(prompt_messages),
+        model_parameters=model_parameters_with_json_schema,
+        tools=tools,
+        stop=stop,
+        stream=stream,
+        user=user,
+        callbacks=callbacks,
+    )
+
+    if isinstance(llm_result, LLMResult):
+        if not isinstance(llm_result.message.content, str):
+            raise OutputParserError(
+                f"Failed to parse structured output, LLM result is not a string: {llm_result.message.content}"
+            )
+
+        return LLMResultWithStructuredOutput(
+            structured_output=_parse_structured_output(llm_result.message.content),
+            model=llm_result.model,
+            message=llm_result.message,
+            usage=llm_result.usage,
+            system_fingerprint=llm_result.system_fingerprint,
+            prompt_messages=llm_result.prompt_messages,
+        )
+    else:
+
+        def generator() -> Generator[LLMResultChunkWithStructuredOutput, None, None]:
+            result_text: str = ""
+            prompt_messages: Sequence[PromptMessage] = []
+            system_fingerprint: Optional[str] = None
+            for event in llm_result:
+                if isinstance(event, LLMResultChunk):
+                    if isinstance(event.delta.message.content, str):
+                        result_text += event.delta.message.content
+                        prompt_messages = event.prompt_messages
+                        system_fingerprint = event.system_fingerprint
+
+                yield LLMResultChunkWithStructuredOutput(
+                    model=model_schema.model,
+                    prompt_messages=prompt_messages,
+                    system_fingerprint=system_fingerprint,
+                    delta=event.delta,
+                )
+
+            yield LLMResultChunkWithStructuredOutput(
+                structured_output=_parse_structured_output(result_text),
+                model=model_schema.model,
+                prompt_messages=prompt_messages,
+                system_fingerprint=system_fingerprint,
+                delta=LLMResultChunkDelta(
+                    index=0,
+                    message=AssistantPromptMessage(content=""),
+                    usage=None,
+                    finish_reason=None,
+                ),
+            )
+
+        return generator()
+
+
+def _handle_native_json_schema(
+    provider: str,
+    model_schema: AIModelEntity,
+    structured_output_schema: Mapping,
+    model_parameters: dict,
+    rules: list[ParameterRule],
+) -> dict:
+    """
+    Handle structured output for models with native JSON schema support.
+
+    :param model_parameters: Model parameters to update
+    :param rules: Model parameter rules
+    :return: Updated model parameters with JSON schema configuration
+    """
+    # Process schema according to model requirements
+    schema_json = _prepare_schema_for_model(provider, model_schema, structured_output_schema)
+
+    # Set JSON schema in parameters
+    model_parameters["json_schema"] = json.dumps(schema_json, ensure_ascii=False)
+
+    # Set appropriate response format if required by the model
+    for rule in rules:
+        if rule.name == "response_format" and ResponseFormat.JSON_SCHEMA.value in rule.options:
+            model_parameters["response_format"] = ResponseFormat.JSON_SCHEMA.value
+
+    return model_parameters
+
+
+def _set_response_format(model_parameters: dict, rules: list) -> None:
+    """
+    Set the appropriate response format parameter based on model rules.
+
+    :param model_parameters: Model parameters to update
+    :param rules: Model parameter rules
+    """
+    for rule in rules:
+        if rule.name == "response_format":
+            if ResponseFormat.JSON.value in rule.options:
+                model_parameters["response_format"] = ResponseFormat.JSON.value
+            elif ResponseFormat.JSON_OBJECT.value in rule.options:
+                model_parameters["response_format"] = ResponseFormat.JSON_OBJECT.value
+
+
+def _handle_prompt_based_schema(
+    prompt_messages: Sequence[PromptMessage], structured_output_schema: Mapping
+) -> list[PromptMessage]:
+    """
+    Handle structured output for models without native JSON schema support.
+    This function modifies the prompt messages to include schema-based output requirements.
+
+    Args:
+        prompt_messages: Original sequence of prompt messages
+
+    Returns:
+        list[PromptMessage]: Updated prompt messages with structured output requirements
+    """
+    # Convert schema to string format
+    schema_str = json.dumps(structured_output_schema, ensure_ascii=False)
+
+    # Find existing system prompt with schema placeholder
+    system_prompt = next(
+        (prompt for prompt in prompt_messages if isinstance(prompt, SystemPromptMessage)),
+        None,
+    )
+    structured_output_prompt = STRUCTURED_OUTPUT_PROMPT.replace("{{schema}}", schema_str)
+    # Prepare system prompt content
+    system_prompt_content = (
+        structured_output_prompt + "\n\n" + system_prompt.content
+        if system_prompt and isinstance(system_prompt.content, str)
+        else structured_output_prompt
+    )
+    system_prompt = SystemPromptMessage(content=system_prompt_content)
+
+    # Extract content from the last user message
+
+    filtered_prompts = [prompt for prompt in prompt_messages if not isinstance(prompt, SystemPromptMessage)]
+    updated_prompt = [system_prompt] + filtered_prompts
+
+    return updated_prompt
+
+
+def _parse_structured_output(result_text: str) -> Mapping[str, Any]:
+    structured_output: Mapping[str, Any] = {}
+    parsed: Mapping[str, Any] = {}
+    try:
+        parsed = TypeAdapter(Mapping).validate_json(result_text)
+        if not isinstance(parsed, dict):
+            raise OutputParserError(f"Failed to parse structured output: {result_text}")
+        structured_output = parsed
+    except ValidationError:
+        # if the result_text is not a valid json, try to repair it
+        temp_parsed = json_repair.loads(result_text)
+        if not isinstance(temp_parsed, dict):
+            # handle reasoning model like deepseek-r1 got '<think>\n\n</think>\n' prefix
+            if isinstance(temp_parsed, list):
+                temp_parsed = next((item for item in temp_parsed if isinstance(item, dict)), {})
+            else:
+                raise OutputParserError(f"Failed to parse structured output: {result_text}")
+        structured_output = cast(dict, temp_parsed)
+    return structured_output
+
+
+def _prepare_schema_for_model(provider: str, model_schema: AIModelEntity, schema: Mapping) -> dict:
+    """
+    Prepare JSON schema based on model requirements.
+
+    Different models have different requirements for JSON schema formatting.
+    This function handles these differences.
+
+    :param schema: The original JSON schema
+    :return: Processed schema compatible with the current model
+    """
+
+    # Deep copy to avoid modifying the original schema
+    processed_schema = dict(deepcopy(schema))
+
+    # Convert boolean types to string types (common requirement)
+    convert_boolean_to_string(processed_schema)
+
+    # Apply model-specific transformations
+    if SpecialModelType.GEMINI in model_schema.model:
+        remove_additional_properties(processed_schema)
+        return processed_schema
+    elif SpecialModelType.OLLAMA in provider:
+        return processed_schema
+    else:
+        # Default format with name field
+        return {"schema": processed_schema, "name": "llm_response"}
+
+
+def remove_additional_properties(schema: dict) -> None:
+    """
+    Remove additionalProperties fields from JSON schema.
+    Used for models like Gemini that don't support this property.
+
+    :param schema: JSON schema to modify in-place
+    """
+    if not isinstance(schema, dict):
+        return
+
+    # Remove additionalProperties at current level
+    schema.pop("additionalProperties", None)
+
+    # Process nested structures recursively
+    for value in schema.values():
+        if isinstance(value, dict):
+            remove_additional_properties(value)
+        elif isinstance(value, list):
+            for item in value:
+                if isinstance(item, dict):
+                    remove_additional_properties(item)
+
+
+def convert_boolean_to_string(schema: dict) -> None:
+    """
+    Convert boolean type specifications to string in JSON schema.
+
+    :param schema: JSON schema to modify in-place
+    """
+    if not isinstance(schema, dict):
+        return
+
+    # Check for boolean type at current level
+    if schema.get("type") == "boolean":
+        schema["type"] = "string"
+
+    # Process nested dictionaries and lists recursively
+    for value in schema.values():
+        if isinstance(value, dict):
+            convert_boolean_to_string(value)
+        elif isinstance(value, list):
+            for item in value:
+                if isinstance(item, dict):
+                    convert_boolean_to_string(item)

api/core/llm_generator/prompts.py

@@ -291,3 +291,21 @@ Your task is to convert simple user descriptions into properly formatted JSON Sc
 
 Now, generate a JSON Schema based on my description
 """  # noqa: E501
+
+STRUCTURED_OUTPUT_PROMPT = """You’re a helpful AI assistant. You could answer questions and output in JSON format.
+constraints:
+    - You must output in JSON format.
+    - Do not output boolean value, use string type instead.
+    - Do not output integer or float value, use number type instead.
+eg:
+    Here is the JSON schema:
+    {"additionalProperties": false, "properties": {"age": {"type": "number"}, "name": {"type": "string"}}, "required": ["name", "age"], "type": "object"}
+
+    Here is the user's question:
+    My name is John Doe and I am 30 years old.
+
+    output:
+    {"name": "John Doe", "age": 30}
+Here is the JSON schema:
+{{schema}}
+"""  # noqa: E501

api/core/model_runtime/entities/llm_entities.py

@@ -1,7 +1,7 @@
-from collections.abc import Sequence
+from collections.abc import Mapping, Sequence
 from decimal import Decimal
 from enum import StrEnum
-from typing import Optional
+from typing import Any, Optional
 
 from pydantic import BaseModel, Field
 
@@ -101,6 +101,20 @@ class LLMResult(BaseModel):
     system_fingerprint: Optional[str] = None
 
 
+class LLMStructuredOutput(BaseModel):
+    """
+    Model class for llm structured output.
+    """
+
+    structured_output: Optional[Mapping[str, Any]] = None
+
+
+class LLMResultWithStructuredOutput(LLMResult, LLMStructuredOutput):
+    """
+    Model class for llm result with structured output.
+    """
+
+
 class LLMResultChunkDelta(BaseModel):
     """
     Model class for llm result chunk delta.
@@ -123,6 +137,12 @@ class LLMResultChunk(BaseModel):
     delta: LLMResultChunkDelta
 
 
+class LLMResultChunkWithStructuredOutput(LLMResultChunk, LLMStructuredOutput):
+    """
+    Model class for llm result chunk with structured output.
+    """
+
+
 class NumTokensResult(PriceInfo):
     """
     Model class for number of tokens result.

api/core/plugin/backwards_invocation/model.py

@@ -2,8 +2,15 @@ import tempfile
 from binascii import hexlify, unhexlify
 from collections.abc import Generator
 
+from core.llm_generator.output_parser.structured_output import invoke_llm_with_structured_output
 from core.model_manager import ModelManager
-from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
+from core.model_runtime.entities.llm_entities import (
+    LLMResult,
+    LLMResultChunk,
+    LLMResultChunkDelta,
+    LLMResultChunkWithStructuredOutput,
+    LLMResultWithStructuredOutput,
+)
 from core.model_runtime.entities.message_entities import (
     PromptMessage,
     SystemPromptMessage,
@@ -12,6 +19,7 @@ from core.model_runtime.entities.message_entities import (
 from core.plugin.backwards_invocation.base import BaseBackwardsInvocation
 from core.plugin.entities.request import (
     RequestInvokeLLM,
+    RequestInvokeLLMWithStructuredOutput,
     RequestInvokeModeration,
     RequestInvokeRerank,
     RequestInvokeSpeech2Text,
@@ -81,6 +89,72 @@ class PluginModelBackwardsInvocation(BaseBackwardsInvocation):
 
             return handle_non_streaming(response)
 
+    @classmethod
+    def invoke_llm_with_structured_output(
+        cls, user_id: str, tenant: Tenant, payload: RequestInvokeLLMWithStructuredOutput
+    ):
+        """
+        invoke llm with structured output
+        """
+        model_instance = ModelManager().get_model_instance(
+            tenant_id=tenant.id,
+            provider=payload.provider,
+            model_type=payload.model_type,
+            model=payload.model,
+        )
+
+        model_schema = model_instance.model_type_instance.get_model_schema(payload.model, model_instance.credentials)
+
+        if not model_schema:
+            raise ValueError(f"Model schema not found for {payload.model}")
+
+        response = invoke_llm_with_structured_output(
+            provider=payload.provider,
+            model_schema=model_schema,
+            model_instance=model_instance,
+            prompt_messages=payload.prompt_messages,
+            json_schema=payload.structured_output_schema,
+            tools=payload.tools,
+            stop=payload.stop,
+            stream=True if payload.stream is None else payload.stream,
+            user=user_id,
+            model_parameters=payload.completion_params,
+        )
+
+        if isinstance(response, Generator):
+
+            def handle() -> Generator[LLMResultChunkWithStructuredOutput, None, None]:
+                for chunk in response:
+                    if chunk.delta.usage:
+                        llm_utils.deduct_llm_quota(
+                            tenant_id=tenant.id, model_instance=model_instance, usage=chunk.delta.usage
+                        )
+                    chunk.prompt_messages = []
+                    yield chunk
+
+            return handle()
+        else:
+            if response.usage:
+                llm_utils.deduct_llm_quota(tenant_id=tenant.id, model_instance=model_instance, usage=response.usage)
+
+            def handle_non_streaming(
+                response: LLMResultWithStructuredOutput,
+            ) -> Generator[LLMResultChunkWithStructuredOutput, None, None]:
+                yield LLMResultChunkWithStructuredOutput(
+                    model=response.model,
+                    prompt_messages=[],
+                    system_fingerprint=response.system_fingerprint,
+                    structured_output=response.structured_output,
+                    delta=LLMResultChunkDelta(
+                        index=0,
+                        message=response.message,
+                        usage=response.usage,
+                        finish_reason="",
+                    ),
+                )
+
+            return handle_non_streaming(response)
+
     @classmethod
     def invoke_text_embedding(cls, user_id: str, tenant: Tenant, payload: RequestInvokeTextEmbedding):
         """

api/core/plugin/entities/parameters.py

@@ -10,6 +10,9 @@ from core.tools.entities.common_entities import I18nObject
 class PluginParameterOption(BaseModel):
     value: str = Field(..., description="The value of the option")
     label: I18nObject = Field(..., description="The label of the option")
+    icon: Optional[str] = Field(
+        default=None, description="The icon of the option, can be a url or a base64 encoded image"
+    )
 
     @field_validator("value", mode="before")
     @classmethod
@@ -35,6 +38,7 @@ class PluginParameterType(enum.StrEnum):
     APP_SELECTOR = CommonParameterType.APP_SELECTOR.value
     MODEL_SELECTOR = CommonParameterType.MODEL_SELECTOR.value
     TOOLS_SELECTOR = CommonParameterType.TOOLS_SELECTOR.value
+    DYNAMIC_SELECT = CommonParameterType.DYNAMIC_SELECT.value
 
     # deprecated, should not use.
     SYSTEM_FILES = CommonParameterType.SYSTEM_FILES.value

api/core/plugin/entities/plugin_daemon.py

@@ -1,4 +1,4 @@
-from collections.abc import Mapping
+from collections.abc import Mapping, Sequence
 from datetime import datetime
 from enum import StrEnum
 from typing import Any, Generic, Optional, TypeVar
@@ -9,6 +9,7 @@ from core.agent.plugin_entities import AgentProviderEntityWithPlugin
 from core.model_runtime.entities.model_entities import AIModelEntity
 from core.model_runtime.entities.provider_entities import ProviderEntity
 from core.plugin.entities.base import BasePluginEntity
+from core.plugin.entities.parameters import PluginParameterOption
 from core.plugin.entities.plugin import PluginDeclaration, PluginEntity
 from core.tools.entities.common_entities import I18nObject
 from core.tools.entities.tool_entities import ToolProviderEntityWithPlugin
@@ -186,3 +187,7 @@ class PluginOAuthCredentialsResponse(BaseModel):
 class PluginListResponse(BaseModel):
     list: list[PluginEntity]
     total: int
+
+
+class PluginDynamicSelectOptionsResponse(BaseModel):
+    options: Sequence[PluginParameterOption] = Field(description="The options of the dynamic select.")

api/core/plugin/entities/request.py

@@ -82,6 +82,16 @@ class RequestInvokeLLM(BaseRequestInvokeModel):
         return v
 
 
+class RequestInvokeLLMWithStructuredOutput(RequestInvokeLLM):
+    """
+    Request to invoke LLM with structured output
+    """
+
+    structured_output_schema: dict[str, Any] = Field(
+        default_factory=dict, description="The schema of the structured output in JSON schema format"
+    )
+
+
 class RequestInvokeTextEmbedding(BaseRequestInvokeModel):
     """
     Request to invoke text embedding

api/core/plugin/impl/dynamic_select.py

@@ -0,0 +1,45 @@
+from collections.abc import Mapping
+from typing import Any
+
+from core.plugin.entities.plugin import GenericProviderID
+from core.plugin.entities.plugin_daemon import PluginDynamicSelectOptionsResponse
+from core.plugin.impl.base import BasePluginClient
+
+
+class DynamicSelectClient(BasePluginClient):
+    def fetch_dynamic_select_options(
+        self,
+        tenant_id: str,
+        user_id: str,
+        plugin_id: str,
+        provider: str,
+        action: str,
+        credentials: Mapping[str, Any],
+        parameter: str,
+    ) -> PluginDynamicSelectOptionsResponse:
+        """
+        Fetch dynamic select options for a plugin parameter.
+        """
+        response = self._request_with_plugin_daemon_response_stream(
+            "POST",
+            f"plugin/{tenant_id}/dispatch/dynamic_select/fetch_parameter_options",
+            PluginDynamicSelectOptionsResponse,
+            data={
+                "user_id": user_id,
+                "data": {
+                    "provider": GenericProviderID(provider).provider_name,
+                    "credentials": credentials,
+                    "provider_action": action,
+                    "parameter": parameter,
+                },
+            },
+            headers={
+                "X-Plugin-ID": plugin_id,
+                "Content-Type": "application/json",
+            },
+        )
+
+        for options in response:
+            return options
+
+        raise ValueError("Plugin service returned no options")

api/core/rag/index_processor/processor/paragraph_index_processor.py

@@ -76,6 +76,7 @@ class ParagraphIndexProcessor(BaseIndexProcessor):
         if dataset.indexing_technique == "high_quality":
             vector = Vector(dataset)
             vector.create(documents)
+            with_keywords = False
         if with_keywords:
             keywords_list = kwargs.get("keywords_list")
             keyword = Keyword(dataset)
@@ -91,6 +92,7 @@ class ParagraphIndexProcessor(BaseIndexProcessor):
                 vector.delete_by_ids(node_ids)
             else:
                 vector.delete()
+            with_keywords = False
         if with_keywords:
             keyword = Keyword(dataset)
             if node_ids:

api/core/tools/entities/tool_entities.py

@@ -240,6 +240,7 @@ class ToolParameter(PluginParameter):
         FILES = PluginParameterType.FILES.value
         APP_SELECTOR = PluginParameterType.APP_SELECTOR.value
         MODEL_SELECTOR = PluginParameterType.MODEL_SELECTOR.value
+        DYNAMIC_SELECT = PluginParameterType.DYNAMIC_SELECT.value
 
         # deprecated, should not use.
         SYSTEM_FILES = PluginParameterType.SYSTEM_FILES.value

api/core/tools/utils/configuration.py

@@ -86,6 +86,7 @@ class ProviderConfigEncrypter(BaseModel):
         cached_credentials = cache.get()
         if cached_credentials:
             return cached_credentials
+
         data = self._deep_copy(data)
         # get fields need to be decrypted
         fields = dict[str, BasicProviderConfig]()

api/core/workflow/nodes/llm/node.py

@@ -5,11 +5,11 @@ import logging
 from collections.abc import Generator, Mapping, Sequence
 from typing import TYPE_CHECKING, Any, Optional, cast
 
-import json_repair
-
 from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
 from core.file import FileType, file_manager
 from core.helper.code_executor import CodeExecutor, CodeLanguage
+from core.llm_generator.output_parser.errors import OutputParserError
+from core.llm_generator.output_parser.structured_output import invoke_llm_with_structured_output
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance, ModelManager
 from core.model_runtime.entities import (
@@ -18,7 +18,13 @@ from core.model_runtime.entities import (
     PromptMessageContentType,
     TextPromptMessageContent,
 )
-from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMUsage
+from core.model_runtime.entities.llm_entities import (
+    LLMResult,
+    LLMResultChunk,
+    LLMResultChunkWithStructuredOutput,
+    LLMStructuredOutput,
+    LLMUsage,
+)
 from core.model_runtime.entities.message_entities import (
     AssistantPromptMessage,
     PromptMessageContentUnionTypes,
@@ -31,7 +37,6 @@ from core.model_runtime.entities.model_entities import (
     ModelFeature,
     ModelPropertyKey,
     ModelType,
-    ParameterRule,
 )
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.utils.encoders import jsonable_encoder
@@ -62,11 +67,6 @@ from core.workflow.nodes.event import (
     RunRetrieverResourceEvent,
     RunStreamChunkEvent,
 )
-from core.workflow.utils.structured_output.entities import (
-    ResponseFormat,
-    SpecialModelType,
-)
-from core.workflow.utils.structured_output.prompt import STRUCTURED_OUTPUT_PROMPT
 from core.workflow.utils.variable_template_parser import VariableTemplateParser
 
 from . import llm_utils
@@ -143,12 +143,6 @@ class LLMNode(BaseNode[LLMNodeData]):
         return "1"
 
     def _run(self) -> Generator[NodeEvent | InNodeEvent, None, None]:
-        def process_structured_output(text: str) -> Optional[dict[str, Any]]:
-            """Process structured output if enabled"""
-            if not self.node_data.structured_output_enabled or not self.node_data.structured_output:
-                return None
-            return self._parse_structured_output(text)
-
         node_inputs: Optional[dict[str, Any]] = None
         process_data = None
         result_text = ""
@@ -244,6 +238,8 @@ class LLMNode(BaseNode[LLMNodeData]):
                 stop=stop,
             )
 
+            structured_output: LLMStructuredOutput | None = None
+
             for event in generator:
                 if isinstance(event, RunStreamChunkEvent):
                     yield event
@@ -254,10 +250,12 @@ class LLMNode(BaseNode[LLMNodeData]):
                     # deduct quota
                     llm_utils.deduct_llm_quota(tenant_id=self.tenant_id, model_instance=model_instance, usage=usage)
                     break
+                elif isinstance(event, LLMStructuredOutput):
+                    structured_output = event
+
             outputs = {"text": result_text, "usage": jsonable_encoder(usage), "finish_reason": finish_reason}
-            structured_output = process_structured_output(result_text)
             if structured_output:
-                outputs["structured_output"] = structured_output
+                outputs["structured_output"] = structured_output.structured_output
             if self._file_outputs is not None:
                 outputs["files"] = ArrayFileSegment(value=self._file_outputs)
 
@@ -302,20 +300,40 @@ class LLMNode(BaseNode[LLMNodeData]):
         model_instance: ModelInstance,
         prompt_messages: Sequence[PromptMessage],
         stop: Optional[Sequence[str]] = None,
-    ) -> Generator[NodeEvent, None, None]:
-        invoke_result = model_instance.invoke_llm(
-            prompt_messages=list(prompt_messages),
-            model_parameters=node_data_model.completion_params,
-            stop=list(stop or []),
-            stream=True,
-            user=self.user_id,
+    ) -> Generator[NodeEvent | LLMStructuredOutput, None, None]:
+        model_schema = model_instance.model_type_instance.get_model_schema(
+            node_data_model.name, model_instance.credentials
         )
+        if not model_schema:
+            raise ValueError(f"Model schema not found for {node_data_model.name}")
+
+        if self.node_data.structured_output_enabled:
+            output_schema = self._fetch_structured_output_schema()
+            invoke_result = invoke_llm_with_structured_output(
+                provider=model_instance.provider,
+                model_schema=model_schema,
+                model_instance=model_instance,
+                prompt_messages=prompt_messages,
+                json_schema=output_schema,
+                model_parameters=node_data_model.completion_params,
+                stop=list(stop or []),
+                stream=True,
+                user=self.user_id,
+            )
+        else:
+            invoke_result = model_instance.invoke_llm(
+                prompt_messages=list(prompt_messages),
+                model_parameters=node_data_model.completion_params,
+                stop=list(stop or []),
+                stream=True,
+                user=self.user_id,
+            )
 
         return self._handle_invoke_result(invoke_result=invoke_result)
 
     def _handle_invoke_result(
-        self, invoke_result: LLMResult | Generator[LLMResultChunk, None, None]
-    ) -> Generator[NodeEvent, None, None]:
+        self, invoke_result: LLMResult | Generator[LLMResultChunk | LLMStructuredOutput, None, None]
+    ) -> Generator[NodeEvent | LLMStructuredOutput, None, None]:
         # For blocking mode
         if isinstance(invoke_result, LLMResult):
             event = self._handle_blocking_result(invoke_result=invoke_result)
@@ -329,23 +347,32 @@ class LLMNode(BaseNode[LLMNodeData]):
         usage = LLMUsage.empty_usage()
         finish_reason = None
         full_text_buffer = io.StringIO()
-        for result in invoke_result:
-            contents = result.delta.message.content
-            for text_part in self._save_multimodal_output_and_convert_result_to_markdown(contents):
-                full_text_buffer.write(text_part)
-                yield RunStreamChunkEvent(chunk_content=text_part, from_variable_selector=[self.node_id, "text"])
+        # Consume the invoke result and handle generator exception
+        try:
+            for result in invoke_result:
+                if isinstance(result, LLMResultChunkWithStructuredOutput):
+                    yield result
+                if isinstance(result, LLMResultChunk):
+                    contents = result.delta.message.content
+                    for text_part in self._save_multimodal_output_and_convert_result_to_markdown(contents):
+                        full_text_buffer.write(text_part)
+                        yield RunStreamChunkEvent(
+                            chunk_content=text_part, from_variable_selector=[self.node_id, "text"]
+                        )
 
-            # Update the whole metadata
-            if not model and result.model:
-                model = result.model
-            if len(prompt_messages) == 0:
-                # TODO(QuantumGhost): it seems that this update has no visable effect.
-                # What's the purpose of the line below?
-                prompt_messages = list(result.prompt_messages)
-            if usage.prompt_tokens == 0 and result.delta.usage:
-                usage = result.delta.usage
-            if finish_reason is None and result.delta.finish_reason:
-                finish_reason = result.delta.finish_reason
+                    # Update the whole metadata
+                    if not model and result.model:
+                        model = result.model
+                    if len(prompt_messages) == 0:
+                        # TODO(QuantumGhost): it seems that this update has no visable effect.
+                        # What's the purpose of the line below?
+                        prompt_messages = list(result.prompt_messages)
+                    if usage.prompt_tokens == 0 and result.delta.usage:
+                        usage = result.delta.usage
+                    if finish_reason is None and result.delta.finish_reason:
+                        finish_reason = result.delta.finish_reason
+        except OutputParserError as e:
+            raise LLMNodeError(f"Failed to parse structured output: {e}")
 
         yield ModelInvokeCompletedEvent(text=full_text_buffer.getvalue(), usage=usage, finish_reason=finish_reason)
 
@@ -522,12 +549,6 @@ class LLMNode(BaseNode[LLMNodeData]):
         if not model_schema:
             raise ModelNotExistError(f"Model {node_data_model.name} not exist.")
 
-        if self.node_data.structured_output_enabled:
-            if model_schema.support_structure_output:
-                completion_params = self._handle_native_json_schema(completion_params, model_schema.parameter_rules)
-            else:
-                # Set appropriate response format based on model capabilities
-                self._set_response_format(completion_params, model_schema.parameter_rules)
         model_config_with_cred.parameters = completion_params
         # NOTE(-LAN-): This line modify the `self.node_data.model`, which is used in `_invoke_llm()`.
         node_data_model.completion_params = completion_params
@@ -719,32 +740,8 @@ class LLMNode(BaseNode[LLMNodeData]):
         )
         if not model_schema:
             raise ModelNotExistError(f"Model {model_config.model} not exist.")
-        if self.node_data.structured_output_enabled:
-            if not model_schema.support_structure_output:
-                filtered_prompt_messages = self._handle_prompt_based_schema(
-                    prompt_messages=filtered_prompt_messages,
-                )
         return filtered_prompt_messages, model_config.stop
 
-    def _parse_structured_output(self, result_text: str) -> dict[str, Any]:
-        structured_output: dict[str, Any] = {}
-        try:
-            parsed = json.loads(result_text)
-            if not isinstance(parsed, dict):
-                raise LLMNodeError(f"Failed to parse structured output: {result_text}")
-            structured_output = parsed
-        except json.JSONDecodeError as e:
-            # if the result_text is not a valid json, try to repair it
-            parsed = json_repair.loads(result_text)
-            if not isinstance(parsed, dict):
-                # handle reasoning model like deepseek-r1 got '<think>\n\n</think>\n' prefix
-                if isinstance(parsed, list):
-                    parsed = next((item for item in parsed if isinstance(item, dict)), {})
-                else:
-                    raise LLMNodeError(f"Failed to parse structured output: {result_text}")
-            structured_output = parsed
-        return structured_output
-
     @classmethod
     def _extract_variable_selector_to_variable_mapping(
         cls,
@@ -934,104 +931,6 @@ class LLMNode(BaseNode[LLMNodeData]):
         self._file_outputs.append(saved_file)
         return saved_file
 
-    def _handle_native_json_schema(self, model_parameters: dict, rules: list[ParameterRule]) -> dict:
-        """
-        Handle structured output for models with native JSON schema support.
-
-        :param model_parameters: Model parameters to update
-        :param rules: Model parameter rules
-        :return: Updated model parameters with JSON schema configuration
-        """
-        # Process schema according to model requirements
-        schema = self._fetch_structured_output_schema()
-        schema_json = self._prepare_schema_for_model(schema)
-
-        # Set JSON schema in parameters
-        model_parameters["json_schema"] = json.dumps(schema_json, ensure_ascii=False)
-
-        # Set appropriate response format if required by the model
-        for rule in rules:
-            if rule.name == "response_format" and ResponseFormat.JSON_SCHEMA.value in rule.options:
-                model_parameters["response_format"] = ResponseFormat.JSON_SCHEMA.value
-
-        return model_parameters
-
-    def _handle_prompt_based_schema(self, prompt_messages: Sequence[PromptMessage]) -> list[PromptMessage]:
-        """
-        Handle structured output for models without native JSON schema support.
-        This function modifies the prompt messages to include schema-based output requirements.
-
-        Args:
-            prompt_messages: Original sequence of prompt messages
-
-        Returns:
-            list[PromptMessage]: Updated prompt messages with structured output requirements
-        """
-        # Convert schema to string format
-        schema_str = json.dumps(self._fetch_structured_output_schema(), ensure_ascii=False)
-
-        # Find existing system prompt with schema placeholder
-        system_prompt = next(
-            (prompt for prompt in prompt_messages if isinstance(prompt, SystemPromptMessage)),
-            None,
-        )
-        structured_output_prompt = STRUCTURED_OUTPUT_PROMPT.replace("{{schema}}", schema_str)
-        # Prepare system prompt content
-        system_prompt_content = (
-            structured_output_prompt + "\n\n" + system_prompt.content
-            if system_prompt and isinstance(system_prompt.content, str)
-            else structured_output_prompt
-        )
-        system_prompt = SystemPromptMessage(content=system_prompt_content)
-
-        # Extract content from the last user message
-
-        filtered_prompts = [prompt for prompt in prompt_messages if not isinstance(prompt, SystemPromptMessage)]
-        updated_prompt = [system_prompt] + filtered_prompts
-
-        return updated_prompt
-
-    def _set_response_format(self, model_parameters: dict, rules: list) -> None:
-        """
-        Set the appropriate response format parameter based on model rules.
-
-        :param model_parameters: Model parameters to update
-        :param rules: Model parameter rules
-        """
-        for rule in rules:
-            if rule.name == "response_format":
-                if ResponseFormat.JSON.value in rule.options:
-                    model_parameters["response_format"] = ResponseFormat.JSON.value
-                elif ResponseFormat.JSON_OBJECT.value in rule.options:
-                    model_parameters["response_format"] = ResponseFormat.JSON_OBJECT.value
-
-    def _prepare_schema_for_model(self, schema: dict) -> dict:
-        """
-        Prepare JSON schema based on model requirements.
-
-        Different models have different requirements for JSON schema formatting.
-        This function handles these differences.
-
-        :param schema: The original JSON schema
-        :return: Processed schema compatible with the current model
-        """
-
-        # Deep copy to avoid modifying the original schema
-        processed_schema = schema.copy()
-
-        # Convert boolean types to string types (common requirement)
-        convert_boolean_to_string(processed_schema)
-
-        # Apply model-specific transformations
-        if SpecialModelType.GEMINI in self.node_data.model.name:
-            remove_additional_properties(processed_schema)
-            return processed_schema
-        elif SpecialModelType.OLLAMA in self.node_data.model.provider:
-            return processed_schema
-        else:
-            # Default format with name field
-            return {"schema": processed_schema, "name": "llm_response"}
-
     def _fetch_model_schema(self, provider: str) -> AIModelEntity | None:
         """
         Fetch model schema
@@ -1243,49 +1142,3 @@ def _handle_completion_template(
     )
     prompt_messages.append(prompt_message)
     return prompt_messages
-
-
-def remove_additional_properties(schema: dict) -> None:
-    """
-    Remove additionalProperties fields from JSON schema.
-    Used for models like Gemini that don't support this property.
-
-    :param schema: JSON schema to modify in-place
-    """
-    if not isinstance(schema, dict):
-        return
-
-    # Remove additionalProperties at current level
-    schema.pop("additionalProperties", None)
-
-    # Process nested structures recursively
-    for value in schema.values():
-        if isinstance(value, dict):
-            remove_additional_properties(value)
-        elif isinstance(value, list):
-            for item in value:
-                if isinstance(item, dict):
-                    remove_additional_properties(item)
-
-
-def convert_boolean_to_string(schema: dict) -> None:
-    """
-    Convert boolean type specifications to string in JSON schema.
-
-    :param schema: JSON schema to modify in-place
-    """
-    if not isinstance(schema, dict):
-        return
-
-    # Check for boolean type at current level
-    if schema.get("type") == "boolean":
-        schema["type"] = "string"
-
-    # Process nested dictionaries and lists recursively
-    for value in schema.values():
-        if isinstance(value, dict):
-            convert_boolean_to_string(value)
-        elif isinstance(value, list):
-            for item in value:
-                if isinstance(item, dict):
-                    convert_boolean_to_string(item)

api/core/workflow/utils/structured_output/entities.py

@@ -1,16 +0,0 @@
-from enum import StrEnum
-
-
-class ResponseFormat(StrEnum):
-    """Constants for model response formats"""
-
-    JSON_SCHEMA = "json_schema"  # model's structured output mode. some model like gemini, gpt-4o,  support this mode.
-    JSON = "JSON"  # model's json mode. some model like claude support this mode.
-    JSON_OBJECT = "json_object"  # json mode's another alias. some model like deepseek-chat, qwen use this alias.
-
-
-class SpecialModelType(StrEnum):
-    """Constants for identifying model types"""
-
-    GEMINI = "gemini"
-    OLLAMA = "ollama"

api/core/workflow/utils/structured_output/prompt.py

@@ -1,17 +0,0 @@
-STRUCTURED_OUTPUT_PROMPT = """You’re a helpful AI assistant. You could answer questions and output in JSON format.
-constraints:
-    - You must output in JSON format.
-    - Do not output boolean value, use string type instead.
-    - Do not output integer or float value, use number type instead.
-eg:
-    Here is the JSON schema:
-    {"additionalProperties": false, "properties": {"age": {"type": "number"}, "name": {"type": "string"}}, "required": ["name", "age"], "type": "object"}
-
-    Here is the user's question:
-    My name is John Doe and I am 30 years old.
-
-    output:
-    {"name": "John Doe", "age": 30}
-Here is the JSON schema:
-{{schema}}
-"""  # noqa: E501

api/core/workflow/utils/variable_utils.py

@@ -7,6 +7,7 @@ def append_variables_recursively(
 ):
     """
     Append variables recursively
+    :param pool: variable pool to append variables to
     :param node_id: node id
     :param variable_key_list: variable key list
     :param variable_value: variable value

api/core/workflow/workflow_entry.py

@@ -300,7 +300,7 @@ class WorkflowEntry:
             return node_instance, generator
         except Exception as e:
             logger.exception(
-                "error while running node_instance, workflow_id=%s, node_id=%s, type=%s, version=%s",
+                "error while running node_instance, node_id=%s, type=%s, version=%s",
                 node_instance.id,
                 node_instance.node_type,
                 node_instance.version(),

api/extensions/ext_celery.py

@@ -21,6 +21,7 @@ def init_app(app: DifyApp) -> Celery:
             "master_name": dify_config.CELERY_SENTINEL_MASTER_NAME,
             "sentinel_kwargs": {
                 "socket_timeout": dify_config.CELERY_SENTINEL_SOCKET_TIMEOUT,
+                "password": dify_config.CELERY_SENTINEL_PASSWORD,
             },
         }
 

api/factories/file_factory.py

@@ -384,7 +384,7 @@ def get_file_type_by_mime_type(mime_type: str) -> FileType:
 
 class StorageKeyLoader:
     """FileKeyLoader load the storage key from database for a list of files.
-    This loader is batched, the
+    This loader is batched, the database query count is constant regardless of the input size.
     """
 
     def __init__(self, session: Session, tenant_id: str) -> None:
@@ -445,10 +445,10 @@ class StorageKeyLoader:
             if file.transfer_method in (FileTransferMethod.LOCAL_FILE, FileTransferMethod.REMOTE_URL):
                 upload_file_row = upload_files.get(model_id)
                 if upload_file_row is None:
-                    raise ValueError(...)
+                    raise ValueError(f"Upload file not found for id: {model_id}")
                 file._storage_key = upload_file_row.key
             elif file.transfer_method == FileTransferMethod.TOOL_FILE:
                 tool_file_row = tool_files.get(model_id)
                 if tool_file_row is None:
-                    raise ValueError(...)
+                    raise ValueError(f"Tool file not found for id: {model_id}")
                 file._storage_key = tool_file_row.file_key

api/models/model.py

@@ -718,7 +718,6 @@ class Conversation(Base):
                 if "model" in override_model_configs:
                     app_model_config = AppModelConfig()
                     app_model_config = app_model_config.from_model_config_dict(override_model_configs)
-                    assert app_model_config is not None, "app model config not found"
                     model_config = app_model_config.to_dict()
                 else:
                     model_config["configs"] = override_model_configs

api/pyproject.toml

@@ -198,7 +198,7 @@ vdb = [
     "pymochow==1.3.1",
     "pyobvector~=0.1.6",
     "qdrant-client==1.9.0",
-    "tablestore==6.1.0",
+    "tablestore==6.2.0",
     "tcvectordb~=1.6.4",
     "tidb-vector==0.0.9",
     "upstash-vector==0.6.0",

api/services/dataset_service.py

@@ -278,6 +278,23 @@ class DatasetService:
         except ProviderTokenNotInitError as ex:
             raise ValueError(ex.description)
 
+    @staticmethod
+    def check_reranking_model_setting(tenant_id: str, reranking_model_provider: str, reranking_model: str):
+        try:
+            model_manager = ModelManager()
+            model_manager.get_model_instance(
+                tenant_id=tenant_id,
+                provider=reranking_model_provider,
+                model_type=ModelType.RERANK,
+                model=reranking_model,
+            )
+        except LLMBadRequestError:
+            raise ValueError(
+                "No Rerank Model available. Please configure a valid provider in the Settings -> Model Provider."
+            )
+        except ProviderTokenNotInitError as ex:
+            raise ValueError(ex.description)
+
     @staticmethod
     def update_dataset(dataset_id, data, user):
         """
@@ -586,6 +603,10 @@ class DatasetService:
             )
         except ProviderTokenNotInitError:
             # If we can't get the embedding model, preserve existing settings
+            logging.warning(
+                f"Failed to initialize embedding model {data['embedding_model_provider']}/{data['embedding_model']}, "
+                f"preserving existing settings"
+            )
             if dataset.embedding_model_provider and dataset.embedding_model:
                 filtered_data["embedding_model_provider"] = dataset.embedding_model_provider
                 filtered_data["embedding_model"] = dataset.embedding_model
@@ -2203,6 +2224,7 @@ class SegmentService:
 
                     # calc embedding use tokens
                     if document.doc_form == "qa_model":
+                        segment.answer = args.answer
                         tokens = embedding_model.get_text_embedding_num_tokens(texts=[content + segment.answer])[0]
                     else:
                         tokens = embedding_model.get_text_embedding_num_tokens(texts=[content])[0]

api/services/moderation_service.py

@@ -1,23 +0,0 @@
-from typing import Optional
-
-from core.moderation.factory import ModerationFactory, ModerationOutputsResult
-from extensions.ext_database import db
-from models.model import App, AppModelConfig
-
-
-class ModerationService:
-    def moderation_for_outputs(self, app_id: str, app_model: App, text: str) -> ModerationOutputsResult:
-        app_model_config: Optional[AppModelConfig] = None
-
-        app_model_config = (
-            db.session.query(AppModelConfig).filter(AppModelConfig.id == app_model.app_model_config_id).first()
-        )
-
-        if not app_model_config:
-            raise ValueError("app model config not found")
-
-        name = app_model_config.sensitive_word_avoidance_dict["type"]
-        config = app_model_config.sensitive_word_avoidance_dict["config"]
-
-        moderation = ModerationFactory(name, app_id, app_model.tenant_id, config)
-        return moderation.moderation_for_outputs(text)

api/services/plugin/plugin_parameter_service.py

@@ -0,0 +1,74 @@
+from collections.abc import Mapping, Sequence
+from typing import Any, Literal
+
+from sqlalchemy.orm import Session
+
+from core.plugin.entities.parameters import PluginParameterOption
+from core.plugin.impl.dynamic_select import DynamicSelectClient
+from core.tools.tool_manager import ToolManager
+from core.tools.utils.configuration import ProviderConfigEncrypter
+from extensions.ext_database import db
+from models.tools import BuiltinToolProvider
+
+
+class PluginParameterService:
+    @staticmethod
+    def get_dynamic_select_options(
+        tenant_id: str,
+        user_id: str,
+        plugin_id: str,
+        provider: str,
+        action: str,
+        parameter: str,
+        provider_type: Literal["tool"],
+    ) -> Sequence[PluginParameterOption]:
+        """
+        Get dynamic select options for a plugin parameter.
+
+        Args:
+            tenant_id: The tenant ID.
+            plugin_id: The plugin ID.
+            provider: The provider name.
+            action: The action name.
+            parameter: The parameter name.
+        """
+        credentials: Mapping[str, Any] = {}
+
+        match provider_type:
+            case "tool":
+                provider_controller = ToolManager.get_builtin_provider(provider, tenant_id)
+                # init tool configuration
+                tool_configuration = ProviderConfigEncrypter(
+                    tenant_id=tenant_id,
+                    config=[x.to_basic_provider_config() for x in provider_controller.get_credentials_schema()],
+                    provider_type=provider_controller.provider_type.value,
+                    provider_identity=provider_controller.entity.identity.name,
+                )
+
+                # check if credentials are required
+                if not provider_controller.need_credentials:
+                    credentials = {}
+                else:
+                    # fetch credentials from db
+                    with Session(db.engine) as session:
+                        db_record = (
+                            session.query(BuiltinToolProvider)
+                            .filter(
+                                BuiltinToolProvider.tenant_id == tenant_id,
+                                BuiltinToolProvider.provider == provider,
+                            )
+                            .first()
+                        )
+
+                    if db_record is None:
+                        raise ValueError(f"Builtin provider {provider} not found when fetching credentials")
+
+                    credentials = tool_configuration.decrypt(db_record.credentials)
+            case _:
+                raise ValueError(f"Invalid provider type: {provider_type}")
+
+        return (
+            DynamicSelectClient()
+            .fetch_dynamic_select_options(tenant_id, user_id, plugin_id, provider, action, credentials, parameter)
+            .options
+        )

api/services/vector_service.py

@@ -97,16 +97,16 @@ class VectorService:
             vector = Vector(dataset=dataset)
             vector.delete_by_ids([segment.index_node_id])
             vector.add_texts([document], duplicate_check=True)
-
-        # update keyword index
-        keyword = Keyword(dataset)
-        keyword.delete_by_ids([segment.index_node_id])
-
-        # save keyword index
-        if keywords and len(keywords) > 0:
-            keyword.add_texts([document], keywords_list=[keywords])
         else:
-            keyword.add_texts([document])
+            # update keyword index
+            keyword = Keyword(dataset)
+            keyword.delete_by_ids([segment.index_node_id])
+
+            # save keyword index
+            if keywords and len(keywords) > 0:
+                keyword.add_texts([document], keywords_list=[keywords])
+            else:
+                keyword.add_texts([document])
 
     @classmethod
     def generate_child_chunks(

api/tests/integration_tests/workflow/nodes/test_llm.py

@@ -9,6 +9,7 @@ from unittest.mock import MagicMock, patch
 import pytest
 
 from core.app.entities.app_invoke_entities import InvokeFrom
+from core.llm_generator.output_parser.structured_output import _parse_structured_output
 from core.model_runtime.entities.llm_entities import LLMResult, LLMUsage
 from core.model_runtime.entities.message_entities import AssistantPromptMessage
 from core.workflow.entities.variable_pool import VariablePool
@@ -277,29 +278,6 @@ def test_execute_llm_with_jinja2(flask_req_ctx, setup_code_executor_mock):
 
 
 def test_extract_json():
-    node = init_llm_node(
-        config={
-            "id": "llm",
-            "data": {
-                "title": "123",
-                "type": "llm",
-                "model": {"provider": "openai", "name": "gpt-3.5-turbo", "mode": "chat", "completion_params": {}},
-                "prompt_config": {
-                    "structured_output": {
-                        "enabled": True,
-                        "schema": {
-                            "type": "object",
-                            "properties": {"name": {"type": "string"}, "age": {"type": "number"}},
-                        },
-                    }
-                },
-                "prompt_template": [{"role": "user", "text": "{{#sys.query#}}"}],
-                "memory": None,
-                "context": {"enabled": False},
-                "vision": {"enabled": False},
-            },
-        },
-    )
     llm_texts = [
         '<think>\n\n</think>{"name": "test", "age": 123',  # resoning model (deepseek-r1)
         '{"name":"test","age":123}',  # json schema model (gpt-4o)
@@ -308,4 +286,4 @@ def test_extract_json():
         '{"name":"test",age:123}',  # without quotes (qwen-2.5-0.5b)
     ]
     result = {"name": "test", "age": 123}
-    assert all(node._parse_structured_output(item) == result for item in llm_texts)
+    assert all(_parse_structured_output(item) == result for item in llm_texts)

api/tests/unit_tests/services/test_dataset_permission.py

@@ -8,151 +8,298 @@ from services.dataset_service import DatasetService
 from services.errors.account import NoPermissionError
 
 
+class DatasetPermissionTestDataFactory:
+    """Factory class for creating test data and mock objects for dataset permission tests."""
+
+    @staticmethod
+    def create_dataset_mock(
+        dataset_id: str = "dataset-123",
+        tenant_id: str = "test-tenant-123",
+        created_by: str = "creator-456",
+        permission: DatasetPermissionEnum = DatasetPermissionEnum.ONLY_ME,
+        **kwargs,
+    ) -> Mock:
+        """Create a mock dataset with specified attributes."""
+        dataset = Mock(spec=Dataset)
+        dataset.id = dataset_id
+        dataset.tenant_id = tenant_id
+        dataset.created_by = created_by
+        dataset.permission = permission
+        for key, value in kwargs.items():
+            setattr(dataset, key, value)
+        return dataset
+
+    @staticmethod
+    def create_user_mock(
+        user_id: str = "user-789",
+        tenant_id: str = "test-tenant-123",
+        role: TenantAccountRole = TenantAccountRole.NORMAL,
+        **kwargs,
+    ) -> Mock:
+        """Create a mock user with specified attributes."""
+        user = Mock(spec=Account)
+        user.id = user_id
+        user.current_tenant_id = tenant_id
+        user.current_role = role
+        for key, value in kwargs.items():
+            setattr(user, key, value)
+        return user
+
+    @staticmethod
+    def create_dataset_permission_mock(
+        dataset_id: str = "dataset-123",
+        account_id: str = "user-789",
+        **kwargs,
+    ) -> Mock:
+        """Create a mock dataset permission record."""
+        permission = Mock(spec=DatasetPermission)
+        permission.dataset_id = dataset_id
+        permission.account_id = account_id
+        for key, value in kwargs.items():
+            setattr(permission, key, value)
+        return permission
+
+
 class TestDatasetPermissionService:
-    """Test cases for dataset permission checking functionality"""
+    """
+    Comprehensive unit tests for DatasetService.check_dataset_permission method.
 
-    def setup_method(self):
-        """Set up test fixtures"""
-        # Mock tenant and user
-        self.tenant_id = "test-tenant-123"
-        self.creator_id = "creator-456"
-        self.normal_user_id = "normal-789"
-        self.owner_user_id = "owner-999"
+    This test suite covers all permission scenarios including:
+    - Cross-tenant access restrictions
+    - Owner privilege checks
+    - Different permission levels (ONLY_ME, ALL_TEAM, PARTIAL_TEAM)
+    - Explicit permission checks for PARTIAL_TEAM
+    - Error conditions and logging
+    """
 
-        # Mock dataset
-        self.dataset = Mock(spec=Dataset)
-        self.dataset.id = "dataset-123"
-        self.dataset.tenant_id = self.tenant_id
-        self.dataset.created_by = self.creator_id
+    @pytest.fixture
+    def mock_dataset_service_dependencies(self):
+        """Common mock setup for dataset service dependencies."""
+        with patch("services.dataset_service.db.session") as mock_session:
+            yield {
+                "db_session": mock_session,
+            }
 
-        # Mock users
-        self.creator_user = Mock(spec=Account)
-        self.creator_user.id = self.creator_id
-        self.creator_user.current_tenant_id = self.tenant_id
-        self.creator_user.current_role = TenantAccountRole.EDITOR
-
-        self.normal_user = Mock(spec=Account)
-        self.normal_user.id = self.normal_user_id
-        self.normal_user.current_tenant_id = self.tenant_id
-        self.normal_user.current_role = TenantAccountRole.NORMAL
-
-        self.owner_user = Mock(spec=Account)
-        self.owner_user.id = self.owner_user_id
-        self.owner_user.current_tenant_id = self.tenant_id
-        self.owner_user.current_role = TenantAccountRole.OWNER
-
-    def test_permission_check_different_tenant_should_fail(self):
-        """Test that users from different tenants cannot access dataset"""
-        self.normal_user.current_tenant_id = "different-tenant"
-
-        with pytest.raises(NoPermissionError, match="You do not have permission to access this dataset."):
-            DatasetService.check_dataset_permission(self.dataset, self.normal_user)
-
-    def test_owner_can_access_any_dataset(self):
-        """Test that tenant owners can access any dataset regardless of permission"""
-        self.dataset.permission = DatasetPermissionEnum.ONLY_ME
+    @pytest.fixture
+    def mock_logging_dependencies(self):
+        """Mock setup for logging tests."""
+        with patch("services.dataset_service.logging") as mock_logging:
+            yield {
+                "logging": mock_logging,
+            }
 
+    def _assert_permission_check_passes(self, dataset: Mock, user: Mock):
+        """Helper method to verify that permission check passes without raising exceptions."""
         # Should not raise any exception
-        DatasetService.check_dataset_permission(self.dataset, self.owner_user)
+        DatasetService.check_dataset_permission(dataset, user)
 
-    def test_only_me_permission_creator_can_access(self):
-        """Test ONLY_ME permission allows only creator to access"""
-        self.dataset.permission = DatasetPermissionEnum.ONLY_ME
+    def _assert_permission_check_fails(
+        self, dataset: Mock, user: Mock, expected_message: str = "You do not have permission to access this dataset."
+    ):
+        """Helper method to verify that permission check fails with expected error."""
+        with pytest.raises(NoPermissionError, match=expected_message):
+            DatasetService.check_dataset_permission(dataset, user)
 
-        # Creator should be able to access
-        DatasetService.check_dataset_permission(self.dataset, self.creator_user)
+    def _assert_database_query_called(self, mock_session: Mock, dataset_id: str, account_id: str):
+        """Helper method to verify database query calls for permission checks."""
+        mock_session.query().filter_by.assert_called_with(dataset_id=dataset_id, account_id=account_id)
 
-    def test_only_me_permission_others_cannot_access(self):
-        """Test ONLY_ME permission denies access to non-creators"""
-        self.dataset.permission = DatasetPermissionEnum.ONLY_ME
-
-        with pytest.raises(NoPermissionError, match="You do not have permission to access this dataset."):
-            DatasetService.check_dataset_permission(self.dataset, self.normal_user)
-
-    def test_all_team_permission_allows_access(self):
-        """Test ALL_TEAM permission allows any team member to access"""
-        self.dataset.permission = DatasetPermissionEnum.ALL_TEAM
-
-        # Should not raise any exception for team members
-        DatasetService.check_dataset_permission(self.dataset, self.normal_user)
-        DatasetService.check_dataset_permission(self.dataset, self.creator_user)
-
-    @patch("services.dataset_service.db.session")
-    def test_partial_team_permission_creator_can_access(self, mock_session):
-        """Test PARTIAL_TEAM permission allows creator to access"""
-        self.dataset.permission = DatasetPermissionEnum.PARTIAL_TEAM
-
-        # Should not raise any exception for creator
-        DatasetService.check_dataset_permission(self.dataset, self.creator_user)
-
-        # Should not query database for creator
+    def _assert_database_query_not_called(self, mock_session: Mock):
+        """Helper method to verify that database query was not called."""
         mock_session.query.assert_not_called()
 
-    @patch("services.dataset_service.db.session")
-    def test_partial_team_permission_with_explicit_permission(self, mock_session):
-        """Test PARTIAL_TEAM permission allows users with explicit permission"""
-        self.dataset.permission = DatasetPermissionEnum.PARTIAL_TEAM
+    # ==================== Cross-Tenant Access Tests ====================
+
+    def test_permission_check_different_tenant_should_fail(self):
+        """Test that users from different tenants cannot access dataset regardless of other permissions."""
+        # Create dataset and user from different tenants
+        dataset = DatasetPermissionTestDataFactory.create_dataset_mock(
+            tenant_id="tenant-123", permission=DatasetPermissionEnum.ALL_TEAM
+        )
+        user = DatasetPermissionTestDataFactory.create_user_mock(
+            user_id="user-789", tenant_id="different-tenant-456", role=TenantAccountRole.EDITOR
+        )
+
+        # Should fail due to different tenant
+        self._assert_permission_check_fails(dataset, user)
+
+    # ==================== Owner Privilege Tests ====================
+
+    def test_owner_can_access_any_dataset(self):
+        """Test that tenant owners can access any dataset regardless of permission level."""
+        # Create dataset with restrictive permission
+        dataset = DatasetPermissionTestDataFactory.create_dataset_mock(permission=DatasetPermissionEnum.ONLY_ME)
+
+        # Create owner user
+        owner_user = DatasetPermissionTestDataFactory.create_user_mock(
+            user_id="owner-999", role=TenantAccountRole.OWNER
+        )
+
+        # Owner should have access regardless of dataset permission
+        self._assert_permission_check_passes(dataset, owner_user)
+
+    # ==================== ONLY_ME Permission Tests ====================
+
+    def test_only_me_permission_creator_can_access(self):
+        """Test ONLY_ME permission allows only the dataset creator to access."""
+        # Create dataset with ONLY_ME permission
+        dataset = DatasetPermissionTestDataFactory.create_dataset_mock(
+            created_by="creator-456", permission=DatasetPermissionEnum.ONLY_ME
+        )
+
+        # Create creator user
+        creator_user = DatasetPermissionTestDataFactory.create_user_mock(
+            user_id="creator-456", role=TenantAccountRole.EDITOR
+        )
+
+        # Creator should be able to access
+        self._assert_permission_check_passes(dataset, creator_user)
+
+    def test_only_me_permission_others_cannot_access(self):
+        """Test ONLY_ME permission denies access to non-creators."""
+        # Create dataset with ONLY_ME permission
+        dataset = DatasetPermissionTestDataFactory.create_dataset_mock(
+            created_by="creator-456", permission=DatasetPermissionEnum.ONLY_ME
+        )
+
+        # Create normal user (not the creator)
+        normal_user = DatasetPermissionTestDataFactory.create_user_mock(
+            user_id="normal-789", role=TenantAccountRole.NORMAL
+        )
+
+        # Non-creator should be denied access
+        self._assert_permission_check_fails(dataset, normal_user)
+
+    # ==================== ALL_TEAM Permission Tests ====================
+
+    def test_all_team_permission_allows_access(self):
+        """Test ALL_TEAM permission allows any team member to access the dataset."""
+        # Create dataset with ALL_TEAM permission
+        dataset = DatasetPermissionTestDataFactory.create_dataset_mock(permission=DatasetPermissionEnum.ALL_TEAM)
+
+        # Create different types of team members
+        normal_user = DatasetPermissionTestDataFactory.create_user_mock(
+            user_id="normal-789", role=TenantAccountRole.NORMAL
+        )
+        editor_user = DatasetPermissionTestDataFactory.create_user_mock(
+            user_id="editor-456", role=TenantAccountRole.EDITOR
+        )
+
+        # All team members should have access
+        self._assert_permission_check_passes(dataset, normal_user)
+        self._assert_permission_check_passes(dataset, editor_user)
+
+    # ==================== PARTIAL_TEAM Permission Tests ====================
+
+    def test_partial_team_permission_creator_can_access(self, mock_dataset_service_dependencies):
+        """Test PARTIAL_TEAM permission allows creator to access without database query."""
+        # Create dataset with PARTIAL_TEAM permission
+        dataset = DatasetPermissionTestDataFactory.create_dataset_mock(
+            created_by="creator-456", permission=DatasetPermissionEnum.PARTIAL_TEAM
+        )
+
+        # Create creator user
+        creator_user = DatasetPermissionTestDataFactory.create_user_mock(
+            user_id="creator-456", role=TenantAccountRole.EDITOR
+        )
+
+        # Creator should have access without database query
+        self._assert_permission_check_passes(dataset, creator_user)
+        self._assert_database_query_not_called(mock_dataset_service_dependencies["db_session"])
+
+    def test_partial_team_permission_with_explicit_permission(self, mock_dataset_service_dependencies):
+        """Test PARTIAL_TEAM permission allows users with explicit permission records."""
+        # Create dataset with PARTIAL_TEAM permission
+        dataset = DatasetPermissionTestDataFactory.create_dataset_mock(permission=DatasetPermissionEnum.PARTIAL_TEAM)
+
+        # Create normal user (not the creator)
+        normal_user = DatasetPermissionTestDataFactory.create_user_mock(
+            user_id="normal-789", role=TenantAccountRole.NORMAL
+        )
 
         # Mock database query to return a permission record
-        mock_permission = Mock(spec=DatasetPermission)
-        mock_session.query().filter_by().first.return_value = mock_permission
+        mock_permission = DatasetPermissionTestDataFactory.create_dataset_permission_mock(
+            dataset_id=dataset.id, account_id=normal_user.id
+        )
+        mock_dataset_service_dependencies["db_session"].query().filter_by().first.return_value = mock_permission
 
-        # Should not raise any exception
-        DatasetService.check_dataset_permission(self.dataset, self.normal_user)
+        # User with explicit permission should have access
+        self._assert_permission_check_passes(dataset, normal_user)
+        self._assert_database_query_called(mock_dataset_service_dependencies["db_session"], dataset.id, normal_user.id)
 
-        # Verify database was queried correctly
-        mock_session.query().filter_by.assert_called_with(dataset_id=self.dataset.id, account_id=self.normal_user.id)
+    def test_partial_team_permission_without_explicit_permission(self, mock_dataset_service_dependencies):
+        """Test PARTIAL_TEAM permission denies users without explicit permission records."""
+        # Create dataset with PARTIAL_TEAM permission
+        dataset = DatasetPermissionTestDataFactory.create_dataset_mock(permission=DatasetPermissionEnum.PARTIAL_TEAM)
 
-    @patch("services.dataset_service.db.session")
-    def test_partial_team_permission_without_explicit_permission(self, mock_session):
-        """Test PARTIAL_TEAM permission denies users without explicit permission"""
-        self.dataset.permission = DatasetPermissionEnum.PARTIAL_TEAM
+        # Create normal user (not the creator)
+        normal_user = DatasetPermissionTestDataFactory.create_user_mock(
+            user_id="normal-789", role=TenantAccountRole.NORMAL
+        )
 
         # Mock database query to return None (no permission record)
-        mock_session.query().filter_by().first.return_value = None
+        mock_dataset_service_dependencies["db_session"].query().filter_by().first.return_value = None
 
-        with pytest.raises(NoPermissionError, match="You do not have permission to access this dataset."):
-            DatasetService.check_dataset_permission(self.dataset, self.normal_user)
+        # User without explicit permission should be denied access
+        self._assert_permission_check_fails(dataset, normal_user)
+        self._assert_database_query_called(mock_dataset_service_dependencies["db_session"], dataset.id, normal_user.id)
 
-        # Verify database was queried correctly
-        mock_session.query().filter_by.assert_called_with(dataset_id=self.dataset.id, account_id=self.normal_user.id)
-
-    @patch("services.dataset_service.db.session")
-    def test_partial_team_permission_non_creator_without_permission_fails(self, mock_session):
-        """Test that non-creators without explicit permission are denied access"""
-        self.dataset.permission = DatasetPermissionEnum.PARTIAL_TEAM
+    def test_partial_team_permission_non_creator_without_permission_fails(self, mock_dataset_service_dependencies):
+        """Test that non-creators without explicit permission are denied access to PARTIAL_TEAM datasets."""
+        # Create dataset with PARTIAL_TEAM permission
+        dataset = DatasetPermissionTestDataFactory.create_dataset_mock(
+            created_by="creator-456", permission=DatasetPermissionEnum.PARTIAL_TEAM
+        )
 
         # Create a different user (not the creator)
-        other_user = Mock(spec=Account)
-        other_user.id = "other-user-123"
-        other_user.current_tenant_id = self.tenant_id
-        other_user.current_role = TenantAccountRole.NORMAL
+        other_user = DatasetPermissionTestDataFactory.create_user_mock(
+            user_id="other-user-123", role=TenantAccountRole.NORMAL
+        )
 
         # Mock database query to return None (no permission record)
-        mock_session.query().filter_by().first.return_value = None
+        mock_dataset_service_dependencies["db_session"].query().filter_by().first.return_value = None
 
-        with pytest.raises(NoPermissionError, match="You do not have permission to access this dataset."):
-            DatasetService.check_dataset_permission(self.dataset, other_user)
+        # Non-creator without explicit permission should be denied access
+        self._assert_permission_check_fails(dataset, other_user)
+        self._assert_database_query_called(mock_dataset_service_dependencies["db_session"], dataset.id, other_user.id)
+
+    # ==================== Enum Usage Tests ====================
 
     def test_partial_team_permission_uses_correct_enum(self):
-        """Test that the method correctly uses DatasetPermissionEnum.PARTIAL_TEAM"""
-        # This test ensures we're using the enum instead of string literals
-        self.dataset.permission = DatasetPermissionEnum.PARTIAL_TEAM
-
-        # Creator should always have access
-        DatasetService.check_dataset_permission(self.dataset, self.creator_user)
-
-    @patch("services.dataset_service.logging")
-    @patch("services.dataset_service.db.session")
-    def test_permission_denied_logs_debug_message(self, mock_session, mock_logging):
-        """Test that permission denied events are logged"""
-        self.dataset.permission = DatasetPermissionEnum.PARTIAL_TEAM
-        mock_session.query().filter_by().first.return_value = None
-
-        with pytest.raises(NoPermissionError):
-            DatasetService.check_dataset_permission(self.dataset, self.normal_user)
-
-        # Verify debug message was logged
-        mock_logging.debug.assert_called_with(
-            f"User {self.normal_user.id} does not have permission to access dataset {self.dataset.id}"
+        """Test that the method correctly uses DatasetPermissionEnum.PARTIAL_TEAM instead of string literals."""
+        # Create dataset with PARTIAL_TEAM permission using enum
+        dataset = DatasetPermissionTestDataFactory.create_dataset_mock(
+            created_by="creator-456", permission=DatasetPermissionEnum.PARTIAL_TEAM
+        )
+
+        # Create creator user
+        creator_user = DatasetPermissionTestDataFactory.create_user_mock(
+            user_id="creator-456", role=TenantAccountRole.EDITOR
+        )
+
+        # Creator should always have access regardless of permission level
+        self._assert_permission_check_passes(dataset, creator_user)
+
+    # ==================== Logging Tests ====================
+
+    def test_permission_denied_logs_debug_message(self, mock_dataset_service_dependencies, mock_logging_dependencies):
+        """Test that permission denied events are properly logged for debugging purposes."""
+        # Create dataset with PARTIAL_TEAM permission
+        dataset = DatasetPermissionTestDataFactory.create_dataset_mock(permission=DatasetPermissionEnum.PARTIAL_TEAM)
+
+        # Create normal user (not the creator)
+        normal_user = DatasetPermissionTestDataFactory.create_user_mock(
+            user_id="normal-789", role=TenantAccountRole.NORMAL
+        )
+
+        # Mock database query to return None (no permission record)
+        mock_dataset_service_dependencies["db_session"].query().filter_by().first.return_value = None
+
+        # Attempt permission check (should fail)
+        with pytest.raises(NoPermissionError):
+            DatasetService.check_dataset_permission(dataset, normal_user)
+
+        # Verify debug message was logged with correct user and dataset information
+        mock_logging_dependencies["logging"].debug.assert_called_with(
+            f"User {normal_user.id} does not have permission to access dataset {dataset.id}"
         )

docker/.env.example

@@ -285,6 +285,7 @@ BROKER_USE_SSL=false
 # If you are using Redis Sentinel for high availability, configure the following settings.
 CELERY_USE_SENTINEL=false
 CELERY_SENTINEL_MASTER_NAME=
+CELERY_SENTINEL_PASSWORD=
 CELERY_SENTINEL_SOCKET_TIMEOUT=0.1
 
 # ------------------------------

docker/docker-compose.yaml

@@ -79,6 +79,7 @@ x-shared-env: &shared-api-worker-env
   BROKER_USE_SSL: ${BROKER_USE_SSL:-false}
   CELERY_USE_SENTINEL: ${CELERY_USE_SENTINEL:-false}
   CELERY_SENTINEL_MASTER_NAME: ${CELERY_SENTINEL_MASTER_NAME:-}
+  CELERY_SENTINEL_PASSWORD: ${CELERY_SENTINEL_PASSWORD:-}
   CELERY_SENTINEL_SOCKET_TIMEOUT: ${CELERY_SENTINEL_SOCKET_TIMEOUT:-0.1}
   WEB_API_CORS_ALLOW_ORIGINS: ${WEB_API_CORS_ALLOW_ORIGINS:-*}
   CONSOLE_CORS_ALLOW_ORIGINS: ${CONSOLE_CORS_ALLOW_ORIGINS:-*}

web/app/(commonLayout)/apps/AppCard.tsx

@@ -36,6 +36,7 @@ import AccessControl from '@/app/components/app/app-access-control'
 import { AccessMode } from '@/models/access-control'
 import { useGlobalPublicStore } from '@/context/global-public-context'
 import { formatTime } from '@/utils/time'
+import { useGetUserCanAccessApp } from '@/service/access-control'
 
 export type AppCardProps = {
   app: App
@@ -190,6 +191,7 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => {
   }, [onRefresh, mutateApps, setShowAccessControl])
 
   const Operations = (props: HtmlContentProps) => {
+    const { data: userCanAccessApp, isLoading: isGettingUserCanAccessApp } = useGetUserCanAccessApp({ appId: app?.id, enabled: (!!props?.open && systemFeatures.webapp_auth.enabled) })
     const onMouseLeave = async () => {
       props.onClose?.()
     }
@@ -267,10 +269,14 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => {
             </button>
           </>
         )}
-        <Divider className="my-1" />
-        <button className='mx-1 flex h-8 cursor-pointer items-center gap-2 rounded-lg px-3 hover:bg-state-base-hover' onClick={onClickInstalledApp}>
-          <span className='system-sm-regular text-text-secondary'>{t('app.openInExplore')}</span>
-        </button>
+        {
+          (isGettingUserCanAccessApp || !userCanAccessApp?.result) ? null : <>
+            <Divider className="my-1" />
+            <button className='mx-1 flex h-8 cursor-pointer items-center gap-2 rounded-lg px-3 hover:bg-state-base-hover' onClick={onClickInstalledApp}>
+              <span className='system-sm-regular text-text-secondary'>{t('app.openInExplore')}</span>
+            </button>
+          </>
+        }
         <Divider className="my-1" />
         {
           systemFeatures.webapp_auth.enabled && isCurrentWorkspaceEditor && <>

web/app/components/app/log/list.tsx

@@ -191,6 +191,7 @@ function DetailPanel({ detail, onFeedback }: IDetailPanel) {
   const { userProfile: { timezone } } = useAppContext()
   const { formatTime } = useTimestamp()
   const { onClose, appDetail } = useContext(DrawerContext)
+  const { notify } = useContext(ToastContext)
   const { currentLogItem, setCurrentLogItem, showMessageLogModal, setShowMessageLogModal, showPromptLogModal, setShowPromptLogModal, currentLogModalActiveTab } = useAppStore(useShallow(state => ({
     currentLogItem: state.currentLogItem,
     setCurrentLogItem: state.setCurrentLogItem,
@@ -312,18 +313,34 @@ function DetailPanel({ detail, onFeedback }: IDetailPanel) {
       return item
     }))
   }, [allChatItems])
-  const handleAnnotationRemoved = useCallback((index: number) => {
-    setAllChatItems(allChatItems.map((item, i) => {
-      if (i === index) {
-        return {
-          ...item,
-          content: item.content,
-          annotation: undefined,
-        }
+  const handleAnnotationRemoved = useCallback(async (index: number): Promise<boolean> => {
+    const annotation = allChatItems[index]?.annotation
+
+    try {
+      if (annotation?.id) {
+        const { delAnnotation } = await import('@/service/annotation')
+        await delAnnotation(appDetail?.id || '', annotation.id)
       }
-      return item
-    }))
-  }, [allChatItems])
+
+      setAllChatItems(allChatItems.map((item, i) => {
+        if (i === index) {
+          return {
+            ...item,
+            content: item.content,
+            annotation: undefined,
+          }
+        }
+        return item
+      }))
+
+      notify({ type: 'success', message: t('common.actionMsg.modifiedSuccessfully') })
+      return true
+    }
+    catch {
+      notify({ type: 'error', message: t('common.actionMsg.modifiedUnsuccessfully') })
+      return false
+    }
+  }, [allChatItems, appDetail?.id, t])
 
   const fetchInitiated = useRef(false)
 

web/app/components/base/input-number/index.spec.tsx

@@ -18,7 +18,7 @@ describe('InputNumber Component', () => {
 
   it('renders input with default values', () => {
     render(<InputNumber {...defaultProps} />)
-    const input = screen.getByRole('textbox')
+    const input = screen.getByRole('spinbutton')
     expect(input).toBeInTheDocument()
   })
 
@@ -56,7 +56,7 @@ describe('InputNumber Component', () => {
 
   it('handles direct input changes', () => {
     render(<InputNumber {...defaultProps} />)
-    const input = screen.getByRole('textbox')
+    const input = screen.getByRole('spinbutton')
 
     fireEvent.change(input, { target: { value: '42' } })
     expect(defaultProps.onChange).toHaveBeenCalledWith(42)
@@ -64,7 +64,7 @@ describe('InputNumber Component', () => {
 
   it('handles empty input', () => {
     render(<InputNumber {...defaultProps} value={0} />)
-    const input = screen.getByRole('textbox')
+    const input = screen.getByRole('spinbutton')
 
     fireEvent.change(input, { target: { value: '' } })
     expect(defaultProps.onChange).toHaveBeenCalledWith(undefined)
@@ -72,7 +72,7 @@ describe('InputNumber Component', () => {
 
   it('handles invalid input', () => {
     render(<InputNumber {...defaultProps} />)
-    const input = screen.getByRole('textbox')
+    const input = screen.getByRole('spinbutton')
 
     fireEvent.change(input, { target: { value: 'abc' } })
     expect(defaultProps.onChange).not.toHaveBeenCalled()
@@ -86,7 +86,7 @@ describe('InputNumber Component', () => {
 
   it('disables controls when disabled prop is true', () => {
     render(<InputNumber {...defaultProps} disabled />)
-    const input = screen.getByRole('textbox')
+    const input = screen.getByRole('spinbutton')
     const incrementBtn = screen.getByRole('button', { name: /increment/i })
     const decrementBtn = screen.getByRole('button', { name: /decrement/i })
 

web/app/components/base/input-number/index.tsx

@@ -55,8 +55,8 @@ export const InputNumber: FC<InputNumberProps> = (props) => {
   return <div className={classNames('flex', wrapClassName)}>
     <Input {...rest}
       // disable default controller
-      type='text'
-      className={classNames('rounded-r-none', className)}
+      type='number'
+      className={classNames('no-spinner rounded-r-none', className)}
       value={value}
       max={max}
       min={min}
@@ -77,8 +77,8 @@ export const InputNumber: FC<InputNumberProps> = (props) => {
       size={size}
     />
     <div className={classNames(
-      'flex flex-col bg-components-input-bg-normal rounded-r-md border-l border-divider-subtle text-text-tertiary focus:shadow-xs',
-      disabled && 'opacity-50 cursor-not-allowed',
+      'flex flex-col rounded-r-md border-l border-divider-subtle bg-components-input-bg-normal text-text-tertiary focus:shadow-xs',
+      disabled && 'cursor-not-allowed opacity-50',
       controlWrapClassName)}
     >
       <button

web/app/components/base/popover/index.tsx

@@ -3,6 +3,7 @@ import { Fragment, cloneElement, useRef } from 'react'
 import cn from '@/utils/classnames'
 
 export type HtmlContentProps = {
+  open?: boolean
   onClose?: () => void
   onClick?: () => void
 }
@@ -100,7 +101,8 @@ export default function CustomPopover({
                       }
                     >
                       {cloneElement(htmlContent as React.ReactElement, {
-                        onClose: () => onMouseLeave(open),
+                        open,
+                        onClose: close,
                         ...(manualClose
                           ? {
                             onClick: close,

web/app/components/base/prompt-editor/plugins/component-picker-block/prompt-option.tsx

@@ -32,6 +32,10 @@ export const PromptMenuItem = memo(({
           return
         onMouseEnter()
       }}
+      onMouseDown={(e) => {
+        e.preventDefault()
+        e.stopPropagation()
+      }}
       onClick={() => {
         if (disabled)
           return

web/app/components/base/select/index.tsx

@@ -1,10 +1,10 @@
 'use client'
 import type { FC } from 'react'
-import React, { useEffect, useState } from 'react'
+import React, { useEffect, useRef, useState } from 'react'
 import { Combobox, ComboboxButton, ComboboxInput, ComboboxOption, ComboboxOptions, Listbox, ListboxButton, ListboxOption, ListboxOptions } from '@headlessui/react'
 import { ChevronDownIcon, ChevronUpIcon, XMarkIcon } from '@heroicons/react/20/solid'
 import Badge from '../badge/index'
-import { RiCheckLine } from '@remixicon/react'
+import { RiCheckLine, RiLoader4Line } from '@remixicon/react'
 import { useTranslation } from 'react-i18next'
 import classNames from '@/utils/classnames'
 import {
@@ -51,6 +51,8 @@ export type ISelectProps = {
     item: Item
     selected: boolean
   }) => React.ReactNode
+  isLoading?: boolean
+  onOpenChange?: (open: boolean) => void
 }
 const Select: FC<ISelectProps> = ({
   className,
@@ -178,17 +180,20 @@ const SimpleSelect: FC<ISelectProps> = ({
   defaultValue = 1,
   disabled = false,
   onSelect,
+  onOpenChange,
   placeholder,
   optionWrapClassName,
   optionClassName,
   hideChecked,
   notClearable,
   renderOption,
+  isLoading = false,
 }) => {
   const { t } = useTranslation()
   const localPlaceholder = placeholder || t('common.placeholder.select')
 
   const [selectedItem, setSelectedItem] = useState<Item | null>(null)
+
   useEffect(() => {
     let defaultSelect = null
     const existed = items.find((item: Item) => item.value === defaultValue)
@@ -199,8 +204,10 @@ const SimpleSelect: FC<ISelectProps> = ({
     // eslint-disable-next-line react-hooks/exhaustive-deps
   }, [defaultValue])
 
+  const listboxRef = useRef<HTMLDivElement>(null)
+
   return (
-    <Listbox
+    <Listbox ref={listboxRef}
       value={selectedItem}
       onChange={(value: Item) => {
         if (!disabled) {
@@ -212,10 +219,17 @@ const SimpleSelect: FC<ISelectProps> = ({
       <div className={classNames('group/simple-select relative h-9', wrapperClassName)}>
         {renderTrigger && <ListboxButton className='w-full'>{renderTrigger(selectedItem)}</ListboxButton>}
         {!renderTrigger && (
-          <ListboxButton className={classNames(`flex items-center w-full h-full rounded-lg border-0 bg-components-input-bg-normal pl-3 pr-10 sm:text-sm sm:leading-6 focus-visible:outline-none focus-visible:bg-state-base-hover-alt group-hover/simple-select:bg-state-base-hover-alt ${disabled ? 'cursor-not-allowed' : 'cursor-pointer'}`, className)}>
+          <ListboxButton onClick={() => {
+              // get data-open, use setTimeout to ensure the attribute is set
+              setTimeout(() => {
+                if (listboxRef.current)
+                  onOpenChange?.(listboxRef.current.getAttribute('data-open') !== null)
+              })
+          }} className={classNames(`flex items-center w-full h-full rounded-lg border-0 bg-components-input-bg-normal pl-3 pr-10 sm:text-sm sm:leading-6 focus-visible:outline-none focus-visible:bg-state-base-hover-alt group-hover/simple-select:bg-state-base-hover-alt ${disabled ? 'cursor-not-allowed' : 'cursor-pointer'}`, className)}>
             <span className={classNames('block truncate text-left system-sm-regular text-components-input-text-filled', !selectedItem?.name && 'text-components-input-text-placeholder')}>{selectedItem?.name ?? localPlaceholder}</span>
             <span className="absolute inset-y-0 right-0 flex items-center pr-2">
-              {(selectedItem && !notClearable)
+              {isLoading ? <RiLoader4Line className='h-3.5 w-3.5 animate-spin text-text-secondary' />
+              : (selectedItem && !notClearable)
                 ? (
                   <XMarkIcon
                     onClick={(e) => {
@@ -237,7 +251,7 @@ const SimpleSelect: FC<ISelectProps> = ({
           </ListboxButton>
         )}
 
-        {!disabled && (
+        {(!disabled) && (
           <ListboxOptions className={classNames('absolute z-10 mt-1 px-1 max-h-60 w-full overflow-auto rounded-xl bg-components-panel-bg-blur backdrop-blur-sm py-1 text-base shadow-lg border-components-panel-border border-[0.5px] focus:outline-none sm:text-sm', optionWrapClassName)}>
             {items.map((item: Item) => (
               <ListboxOption

web/app/components/base/tag-input/index.tsx

@@ -1,6 +1,5 @@
-import { useState } from 'react'
+import { useCallback, useState } from 'react'
 import type { ChangeEvent, FC, KeyboardEvent } from 'react'
-import { } from 'use-context-selector'
 import { useTranslation } from 'react-i18next'
 import AutosizeInput from 'react-18-input-autosize'
 import { RiAddLine, RiCloseLine } from '@remixicon/react'
@@ -40,6 +39,29 @@ const TagInput: FC<TagInputProps> = ({
     onChange(copyItems)
   }
 
+  const handleNewTag = useCallback((value: string) => {
+    const valueTrimmed = value.trim()
+    if (!valueTrimmed) {
+      notify({ type: 'error', message: t('datasetDocuments.segment.keywordEmpty') })
+      return
+    }
+
+    if ((items.find(item => item === valueTrimmed))) {
+      notify({ type: 'error', message: t('datasetDocuments.segment.keywordDuplicate') })
+      return
+    }
+
+    if (valueTrimmed.length > 20) {
+      notify({ type: 'error', message: t('datasetDocuments.segment.keywordError') })
+      return
+    }
+
+    onChange([...items, valueTrimmed])
+    setTimeout(() => {
+      setValue('')
+    })
+  }, [items, onChange, notify, t])
+
   const handleKeyDown = (e: KeyboardEvent) => {
     if (isSpecialMode && e.key === 'Enter')
       setValue(`${value}↵`)
@@ -48,24 +70,12 @@ const TagInput: FC<TagInputProps> = ({
       if (isSpecialMode)
         e.preventDefault()
 
-      const valueTrimmed = value.trim()
-      if (!valueTrimmed || (items.find(item => item === valueTrimmed)))
-        return
-
-      if (valueTrimmed.length > 20) {
-        notify({ type: 'error', message: t('datasetDocuments.segment.keywordError') })
-        return
-      }
-
-      onChange([...items, valueTrimmed])
-      setTimeout(() => {
-        setValue('')
-      })
+      handleNewTag(value)
     }
   }
 
   const handleBlur = () => {
-    setValue('')
+    handleNewTag(value)
     setFocused(false)
   }
 

web/app/components/datasets/create/step-three/index.tsx

@@ -52,8 +52,8 @@ const StepThree = ({ datasetId, datasetName, indexingType, creationCache, retrie
             datasetId={datasetId || creationCache?.dataset?.id || ''}
             batchId={creationCache?.batch || ''}
             documents={creationCache?.documents as FullDocumentDetail[]}
-            indexingType={indexingType || creationCache?.dataset?.indexing_technique}
-            retrievalMethod={retrievalMethod || creationCache?.dataset?.retrieval_model?.search_method}
+            indexingType={creationCache?.dataset?.indexing_technique || indexingType}
+            retrievalMethod={creationCache?.dataset?.retrieval_model_dict?.search_method || retrievalMethod}
           />
         </div>
       </div>

web/app/components/datasets/create/step-two/index.tsx

@@ -575,6 +575,7 @@ const StepTwo = ({
         onSuccess(data) {
           updateIndexingTypeCache && updateIndexingTypeCache(indexType as string)
           updateResultCache && updateResultCache(data)
+          updateRetrievalMethodCache && updateRetrievalMethodCache(retrievalConfig.search_method as string)
         },
       })
     }

web/app/components/datasets/documents/detail/completed/segment-detail.tsx

@@ -1,4 +1,4 @@
-import React, { type FC, useMemo, useState } from 'react'
+import React, { type FC, useCallback, useMemo, useState } from 'react'
 import { useTranslation } from 'react-i18next'
 import {
   RiCloseLine,
@@ -16,8 +16,10 @@ import { useSegmentListContext } from './index'
 import { ChunkingMode, type SegmentDetailModel } from '@/models/datasets'
 import { useEventEmitterContextContext } from '@/context/event-emitter'
 import { formatNumber } from '@/utils/format'
-import classNames from '@/utils/classnames'
+import cn from '@/utils/classnames'
 import Divider from '@/app/components/base/divider'
+import { useDatasetDetailContextWithSelector } from '@/context/dataset-detail'
+import { IndexingType } from '../../../create/step-two'
 
 type ISegmentDetailProps = {
   segInfo?: Partial<SegmentDetailModel> & { id: string }
@@ -48,6 +50,7 @@ const SegmentDetail: FC<ISegmentDetailProps> = ({
   const toggleFullScreen = useSegmentListContext(s => s.toggleFullScreen)
   const mode = useDocumentContext(s => s.mode)
   const parentMode = useDocumentContext(s => s.parentMode)
+  const indexingTechnique = useDatasetDetailContextWithSelector(s => s.dataset?.indexing_technique)
 
   eventEmitter?.useSubscription((v) => {
     if (v === 'update-segment')
@@ -56,56 +59,41 @@ const SegmentDetail: FC<ISegmentDetailProps> = ({
       setLoading(false)
   })
 
-  const handleCancel = () => {
+  const handleCancel = useCallback(() => {
     onCancel()
-  }
+  }, [onCancel])
 
-  const handleSave = () => {
+  const handleSave = useCallback(() => {
     onUpdate(segInfo?.id || '', question, answer, keywords)
-  }
+  }, [onUpdate, segInfo?.id, question, answer, keywords])
 
-  const handleRegeneration = () => {
+  const handleRegeneration = useCallback(() => {
     setShowRegenerationModal(true)
-  }
+  }, [])
 
-  const onCancelRegeneration = () => {
+  const onCancelRegeneration = useCallback(() => {
     setShowRegenerationModal(false)
-  }
+  }, [])
 
-  const onConfirmRegeneration = () => {
+  const onConfirmRegeneration = useCallback(() => {
     onUpdate(segInfo?.id || '', question, answer, keywords, true)
-  }
-
-  const isParentChildMode = useMemo(() => {
-    return mode === 'hierarchical'
-  }, [mode])
-
-  const isFullDocMode = useMemo(() => {
-    return mode === 'hierarchical' && parentMode === 'full-doc'
-  }, [mode, parentMode])
-
-  const titleText = useMemo(() => {
-    return isEditMode ? t('datasetDocuments.segment.editChunk') : t('datasetDocuments.segment.chunkDetail')
-  }, [isEditMode, t])
-
-  const isQAModel = useMemo(() => {
-    return docForm === ChunkingMode.qa
-  }, [docForm])
+  }, [onUpdate, segInfo?.id, question, answer, keywords])
 
   const wordCountText = useMemo(() => {
-    const contentLength = isQAModel ? (question.length + answer.length) : question.length
+    const contentLength = docForm === ChunkingMode.qa ? (question.length + answer.length) : question.length
     const total = formatNumber(isEditMode ? contentLength : segInfo!.word_count as number)
     const count = isEditMode ? contentLength : segInfo!.word_count as number
     return `${total} ${t('datasetDocuments.segment.characters', { count })}`
-  }, [isEditMode, question.length, answer.length, isQAModel, segInfo, t])
+  }, [isEditMode, question.length, answer.length, docForm, segInfo, t])
 
-  const labelPrefix = useMemo(() => {
-    return isParentChildMode ? t('datasetDocuments.segment.parentChunk') : t('datasetDocuments.segment.chunk')
-  }, [isParentChildMode, t])
+  const isFullDocMode = mode === 'hierarchical' && parentMode === 'full-doc'
+  const titleText = isEditMode ? t('datasetDocuments.segment.editChunk') : t('datasetDocuments.segment.chunkDetail')
+  const labelPrefix = mode === 'hierarchical' ? t('datasetDocuments.segment.parentChunk') : t('datasetDocuments.segment.chunk')
+  const isECOIndexing = indexingTechnique === IndexingType.ECONOMICAL
 
   return (
     <div className={'flex h-full flex-col'}>
-      <div className={classNames('flex items-center justify-between', fullScreen ? 'py-3 pr-4 pl-6 border border-divider-subtle' : 'pt-3 pr-3 pl-4')}>
+      <div className={cn('flex items-center justify-between', fullScreen ? 'border border-divider-subtle py-3 pl-6 pr-4' : 'pl-4 pr-3 pt-3')}>
         <div className='flex flex-col'>
           <div className='system-xl-semibold text-text-primary'>{titleText}</div>
           <div className='flex items-center gap-x-2'>
@@ -134,12 +122,12 @@ const SegmentDetail: FC<ISegmentDetailProps> = ({
           </div>
         </div>
       </div>
-      <div className={classNames(
+      <div className={cn(
         'flex grow',
-        fullScreen ? 'w-full flex-row justify-center px-6 pt-6 gap-x-8' : 'flex-col gap-y-1 py-3 px-4',
-        !isEditMode && 'pb-0 overflow-hidden',
+        fullScreen ? 'w-full flex-row justify-center gap-x-8 px-6 pt-6' : 'flex-col gap-y-1 px-4 py-3',
+        !isEditMode && 'overflow-hidden pb-0',
       )}>
-        <div className={classNames(isEditMode ? 'break-all whitespace-pre-line overflow-hidden' : 'overflow-y-auto', fullScreen ? 'w-1/2' : 'grow')}>
+        <div className={cn(isEditMode ? 'overflow-hidden whitespace-pre-line break-all' : 'overflow-y-auto', fullScreen ? 'w-1/2' : 'grow')}>
           <ChunkContent
             docForm={docForm}
             question={question}
@@ -149,7 +137,7 @@ const SegmentDetail: FC<ISegmentDetailProps> = ({
             isEditMode={isEditMode}
           />
         </div>
-        {mode === 'custom' && <Keywords
+        {isECOIndexing && <Keywords
           className={fullScreen ? 'w-1/5' : ''}
           actionType={isEditMode ? 'edit' : 'view'}
           segInfo={segInfo}

web/app/components/datasets/documents/detail/new-segment.tsx

@@ -1,4 +1,4 @@
-import { memo, useMemo, useRef, useState } from 'react'
+import { memo, useCallback, useMemo, useRef, useState } from 'react'
 import type { FC } from 'react'
 import { useTranslation } from 'react-i18next'
 import { useContext } from 'use-context-selector'
@@ -12,7 +12,6 @@ import Keywords from './completed/common/keywords'
 import ChunkContent from './completed/common/chunk-content'
 import AddAnother from './completed/common/add-another'
 import Dot from './completed/common/dot'
-import { useDocumentContext } from './index'
 import { useStore as useAppStore } from '@/app/components/app/store'
 import { ToastContext } from '@/app/components/base/toast'
 import { ChunkingMode, type SegmentUpdater } from '@/models/datasets'
@@ -20,6 +19,8 @@ import classNames from '@/utils/classnames'
 import { formatNumber } from '@/utils/format'
 import Divider from '@/app/components/base/divider'
 import { useAddSegment } from '@/service/knowledge/use-segment'
+import { useDatasetDetailContextWithSelector } from '@/context/dataset-detail'
+import { IndexingType } from '../../create/step-two'
 
 type NewSegmentModalProps = {
   onCancel: () => void
@@ -44,39 +45,37 @@ const NewSegmentModal: FC<NewSegmentModalProps> = ({
   const [addAnother, setAddAnother] = useState(true)
   const fullScreen = useSegmentListContext(s => s.fullScreen)
   const toggleFullScreen = useSegmentListContext(s => s.toggleFullScreen)
-  const mode = useDocumentContext(s => s.mode)
+  const indexingTechnique = useDatasetDetailContextWithSelector(s => s.dataset?.indexing_technique)
   const { appSidebarExpand } = useAppStore(useShallow(state => ({
     appSidebarExpand: state.appSidebarExpand,
   })))
   const refreshTimer = useRef<any>(null)
 
-  const CustomButton = <>
-    <Divider type='vertical' className='mx-1 h-3 bg-divider-regular' />
-    <button
-      type='button'
-      className='system-xs-semibold text-text-accent'
-      onClick={() => {
-        clearTimeout(refreshTimer.current)
-        viewNewlyAddedChunk()
-      }}>
-      {t('common.operation.view')}
-    </button>
-  </>
+  const CustomButton = useMemo(() => (
+    <>
+      <Divider type='vertical' className='mx-1 h-3 bg-divider-regular' />
+      <button
+        type='button'
+        className='system-xs-semibold text-text-accent'
+        onClick={() => {
+          clearTimeout(refreshTimer.current)
+          viewNewlyAddedChunk()
+        }}>
+        {t('common.operation.view')}
+      </button>
+    </>
+  ), [viewNewlyAddedChunk, t])
 
-  const isQAModel = useMemo(() => {
-    return docForm === ChunkingMode.qa
-  }, [docForm])
-
-  const handleCancel = (actionType: 'esc' | 'add' = 'esc') => {
+  const handleCancel = useCallback((actionType: 'esc' | 'add' = 'esc') => {
     if (actionType === 'esc' || !addAnother)
       onCancel()
-  }
+  }, [onCancel, addAnother])
 
   const { mutateAsync: addSegment } = useAddSegment()
 
-  const handleSave = async () => {
+  const handleSave = useCallback(async () => {
     const params: SegmentUpdater = { content: '' }
-    if (isQAModel) {
+    if (docForm === ChunkingMode.qa) {
       if (!question.trim()) {
         return notify({
           type: 'error',
@@ -129,21 +128,27 @@ const NewSegmentModal: FC<NewSegmentModalProps> = ({
         setLoading(false)
       },
     })
-  }
+  }, [docForm, keywords, addSegment, datasetId, documentId, question, answer, notify, t, appSidebarExpand, CustomButton, handleCancel, onSave])
 
   const wordCountText = useMemo(() => {
-    const count = isQAModel ? (question.length + answer.length) : question.length
+    const count = docForm === ChunkingMode.qa ? (question.length + answer.length) : question.length
     return `${formatNumber(count)} ${t('datasetDocuments.segment.characters', { count })}`
-    // eslint-disable-next-line react-hooks/exhaustive-deps
-  }, [question.length, answer.length, isQAModel])
+  }, [question.length, answer.length, docForm, t])
+
+  const isECOIndexing = indexingTechnique === IndexingType.ECONOMICAL
 
   return (
     <div className={'flex h-full flex-col'}>
-      <div className={classNames('flex items-center justify-between', fullScreen ? 'py-3 pr-4 pl-6 border border-divider-subtle' : 'pt-3 pr-3 pl-4')}>
+      <div
+        className={classNames(
+          'flex items-center justify-between',
+          fullScreen ? 'border border-divider-subtle py-3 pl-6 pr-4' : 'pl-4 pr-3 pt-3',
+        )}
+      >
         <div className='flex flex-col'>
-          <div className='system-xl-semibold text-text-primary'>{
-            t('datasetDocuments.segment.addChunk')
-          }</div>
+          <div className='system-xl-semibold text-text-primary'>
+            {t('datasetDocuments.segment.addChunk')}
+          </div>
           <div className='flex items-center gap-x-2'>
             <SegmentIndexTag label={t('datasetDocuments.segment.newChunk')!} />
             <Dot />
@@ -171,8 +176,8 @@ const NewSegmentModal: FC<NewSegmentModalProps> = ({
           </div>
         </div>
       </div>
-      <div className={classNames('flex grow', fullScreen ? 'w-full flex-row justify-center px-6 pt-6 gap-x-8' : 'flex-col gap-y-1 py-3 px-4')}>
-        <div className={classNames('break-all overflow-hidden whitespace-pre-line', fullScreen ? 'w-1/2' : 'grow')}>
+      <div className={classNames('flex grow', fullScreen ? 'w-full flex-row justify-center gap-x-8 px-6 pt-6' : 'flex-col gap-y-1 px-4 py-3')}>
+        <div className={classNames('overflow-hidden whitespace-pre-line break-all', fullScreen ? 'w-1/2' : 'grow')}>
           <ChunkContent
             docForm={docForm}
             question={question}
@@ -182,7 +187,7 @@ const NewSegmentModal: FC<NewSegmentModalProps> = ({
             isEditMode={true}
           />
         </div>
-        {mode === 'custom' && <Keywords
+        {isECOIndexing && <Keywords
           className={fullScreen ? 'w-1/5' : ''}
           actionType='add'
           keywords={keywords}

web/app/components/header/account-setting/model-provider-page/declarations.ts

@@ -19,12 +19,14 @@ export enum FormTypeEnum {
   toolSelector = 'tool-selector',
   multiToolSelector = 'array[tools]',
   appSelector = 'app-selector',
+  dynamicSelect = 'dynamic-select',
 }
 
 export type FormOption = {
   label: TypeWithI18N
   value: string
   show_on: FormShowOnObject[]
+  icon?: string
 }
 
 export enum ModelTypeEnum {

web/app/components/header/header-wrapper.tsx

@@ -30,7 +30,7 @@ const HeaderWrapper = ({
 
   return (
     <div className={classNames(
-      'sticky top-0 left-0 right-0 z-30 flex flex-col grow-0 shrink-0 basis-auto min-h-[56px]',
+      'sticky left-0 right-0 top-0 z-[15] flex min-h-[56px] shrink-0 grow-0 basis-auto flex-col',
       s.header,
       isBordered ? 'border-b border-divider-regular' : '',
     )}

web/app/components/plugins/plugin-detail-panel/multiple-tool-selector/index.tsx

@@ -117,6 +117,7 @@ const MultipleToolSelector = ({
         )}
         {!disabled && (
           <ActionButton className='mx-1' onClick={() => {
+            setCollapse(false)
             setOpen(!open)
             setPanelShowState(true)
           }}>
@@ -126,23 +127,6 @@ const MultipleToolSelector = ({
       </div>
       {!collapse && (
         <>
-          <ToolSelector
-            nodeId={nodeId}
-            nodeOutputVars={nodeOutputVars}
-            availableNodes={availableNodes}
-            scope={scope}
-            value={undefined}
-            selectedTools={value}
-            onSelect={handleAdd}
-            controlledState={open}
-            onControlledStateChange={setOpen}
-            trigger={
-              <div className=''></div>
-            }
-            panelShowState={panelShowState}
-            onPanelShowStateChange={setPanelShowState}
-            isEdit={false}
-          />
           {value.length === 0 && (
             <div className='system-xs-regular flex justify-center rounded-[10px] bg-background-section p-3 text-text-tertiary'>{t('plugin.detailPanel.toolSelector.empty')}</div>
           )}
@@ -164,6 +148,23 @@ const MultipleToolSelector = ({
           ))}
         </>
       )}
+      <ToolSelector
+        nodeId={nodeId}
+        nodeOutputVars={nodeOutputVars}
+        availableNodes={availableNodes}
+        scope={scope}
+        value={undefined}
+        selectedTools={value}
+        onSelect={handleAdd}
+        controlledState={open}
+        onControlledStateChange={setOpen}
+        trigger={
+          <div className=''></div>
+        }
+        panelShowState={panelShowState}
+        onPanelShowStateChange={setPanelShowState}
+        isEdit={false}
+      />
     </>
   )
 }

web/app/components/plugins/plugin-detail-panel/tool-selector/index.tsx

@@ -275,7 +275,7 @@ const ToolSelector: FC<Props> = ({
             />
           )}
         </PortalToFollowElemTrigger>
-        <PortalToFollowElemContent className='z-[1000]'>
+        <PortalToFollowElemContent>
           <div className={cn('relative max-h-[642px] min-h-20 w-[361px] rounded-xl border-[0.5px] border-components-panel-border bg-components-panel-bg-blur pb-4 shadow-lg backdrop-blur-sm', !isShowSettingAuth && 'overflow-y-auto pb-2')}>
             {!isShowSettingAuth && (
               <>

web/app/components/plugins/plugin-page/index.tsx

@@ -136,7 +136,7 @@ const PluginPage = ({
   const options = usePluginPageContext(v => v.options)
   const activeTab = usePluginPageContext(v => v.activeTab)
   const setActiveTab = usePluginPageContext(v => v.setActiveTab)
-  const { enable_marketplace, branding } = useGlobalPublicStore(s => s.systemFeatures)
+  const { enable_marketplace } = useGlobalPublicStore(s => s.systemFeatures)
 
   const isPluginsTab = useMemo(() => activeTab === PLUGIN_PAGE_TABS_MAP.plugins, [activeTab])
   const isExploringMarketplace = useMemo(() => {
@@ -225,7 +225,7 @@ const PluginPage = ({
               )
             }
             {
-              canSetPermissions && !branding.enabled && (
+              canSetPermissions && (
                 <Tooltip
                   popupContent={t('plugin.privilege.title')}
                 >

web/app/components/workflow/block-selector/market-place-plugin/list.tsx

@@ -6,9 +6,9 @@ import Item from './item'
 import type { Plugin } from '@/app/components/plugins/types.ts'
 import cn from '@/utils/classnames'
 import Link from 'next/link'
-import { MARKETPLACE_URL_PREFIX } from '@/config'
 import { RiArrowRightUpLine, RiSearchLine } from '@remixicon/react'
 import { noop } from 'lodash-es'
+import { getMarketplaceUrl } from '@/utils/var'
 
 export type ListProps = {
   wrapElemRef: React.RefObject<HTMLElement>
@@ -32,7 +32,7 @@ const List = forwardRef<ListRef, ListProps>(({
   const { t } = useTranslation()
   const hasFilter = !searchText
   const hasRes = list.length > 0
-  const urlWithSearchText = `${MARKETPLACE_URL_PREFIX}/?q=${searchText}&tags=${tags.join(',')}`
+  const urlWithSearchText = getMarketplaceUrl('', { q: searchText, tags: tags.join(',') })
   const nextToStickyELemRef = useRef<HTMLDivElement>(null)
 
   const { handleScroll, scrollPosition } = useStickyScroll({
@@ -71,7 +71,7 @@ const List = forwardRef<ListRef, ListProps>(({
     return (
       <Link
         className='system-sm-medium sticky bottom-0 z-10 flex h-8 cursor-pointer items-center rounded-b-lg border-[0.5px] border-t border-components-panel-border bg-components-panel-bg-blur px-4 py-1 text-text-accent-light-mode-only shadow-lg'
-        href={`${MARKETPLACE_URL_PREFIX}/`}
+        href={getMarketplaceUrl('')}
         target='_blank'
       >
         <span>{t('plugin.findMoreInMarketplace')}</span>

web/app/components/workflow/block-selector/types.ts

@@ -36,7 +36,7 @@ export type ToolValue = {
   provider_name: string
   tool_name: string
   tool_label: string
-  tool_description: string
+  tool_description?: string
   settings?: Record<string, any>
   parameters?: Record<string, any>
   enabled?: boolean

web/app/components/workflow/header/header-in-normal.tsx

@@ -33,6 +33,8 @@ const HeaderInNormal = ({
   const setShowWorkflowVersionHistoryPanel = useStore(s => s.setShowWorkflowVersionHistoryPanel)
   const setShowEnvPanel = useStore(s => s.setShowEnvPanel)
   const setShowDebugAndPreviewPanel = useStore(s => s.setShowDebugAndPreviewPanel)
+  const setShowVariableInspectPanel = useStore(s => s.setShowVariableInspectPanel)
+  const setShowChatVariablePanel = useStore(s => s.setShowChatVariablePanel)
   const nodes = useNodes<StartNodeType>()
   const selectedNode = nodes.find(node => node.data.selected)
   const { handleBackupDraft } = useWorkflowRun()
@@ -46,8 +48,10 @@ const HeaderInNormal = ({
     setShowWorkflowVersionHistoryPanel(true)
     setShowEnvPanel(false)
     setShowDebugAndPreviewPanel(false)
+    setShowVariableInspectPanel(false)
+    setShowChatVariablePanel(false)
   }, [handleBackupDraft, workflowStore, handleNodeSelect, selectedNode,
-    setShowWorkflowVersionHistoryPanel, setShowEnvPanel, setShowDebugAndPreviewPanel])
+    setShowWorkflowVersionHistoryPanel, setShowEnvPanel, setShowDebugAndPreviewPanel, setShowVariableInspectPanel])
 
   return (
     <>

web/app/components/workflow/nodes/_base/components/switch-plugin-version.tsx

@@ -15,7 +15,7 @@ import { pluginManifestToCardPluginProps } from '@/app/components/plugins/instal
 import { Badge as Badge2, BadgeState } from '@/app/components/base/badge/index'
 import Link from 'next/link'
 import { useTranslation } from 'react-i18next'
-import { MARKETPLACE_URL_PREFIX } from '@/config'
+import { getMarketplaceUrl } from '@/utils/var'
 
 export type SwitchPluginVersionProps = {
   uniqueIdentifier: string
@@ -82,7 +82,7 @@ export const SwitchPluginVersion: FC<SwitchPluginVersionProps> = (props) => {
         modalBottomLeft={
           <Link
             className='flex items-center justify-center gap-1'
-            href={`${MARKETPLACE_URL_PREFIX}/plugins/${pluginDetail.declaration.author}/${pluginDetail.declaration.name}`}
+            href={getMarketplaceUrl(`/plugins/${pluginDetail.declaration.author}/${pluginDetail.declaration.name}`)}
             target='_blank'
           >
             <span className='system-xs-regular text-xs text-text-accent'>

web/app/components/workflow/nodes/_base/components/variable/constant-field.tsx

@@ -13,6 +13,8 @@ type Props = {
   readonly: boolean
   value: string
   onChange: (value: string | number, varKindType: VarKindType, varInfo?: Var) => void
+  onOpenChange?: (open: boolean) => void
+  isLoading?: boolean
 }
 
 const DEFAULT_SCHEMA = {} as CredentialFormSchema
@@ -22,6 +24,8 @@ const ConstantField: FC<Props> = ({
   readonly,
   value,
   onChange,
+  onOpenChange,
+  isLoading,
 }) => {
   const language = useLanguage()
   const placeholder = (schema as CredentialFormSchemaSelect).placeholder
@@ -36,7 +40,7 @@ const ConstantField: FC<Props> = ({
 
   return (
     <>
-      {schema.type === FormTypeEnum.select && (
+      {(schema.type === FormTypeEnum.select || schema.type === FormTypeEnum.dynamicSelect) && (
         <SimpleSelect
           wrapperClassName='w-full !h-8'
           className='flex items-center'
@@ -45,6 +49,8 @@ const ConstantField: FC<Props> = ({
           items={(schema as CredentialFormSchemaSelect).options.map(option => ({ value: option.value, name: option.label[language] || option.label.en_US }))}
           onSelect={item => handleSelectChange(item.value)}
           placeholder={placeholder?.[language] || placeholder?.en_US}
+          onOpenChange={onOpenChange}
+          isLoading={isLoading}
         />
       )}
       {schema.type === FormTypeEnum.textNumber && (

web/app/components/workflow/nodes/_base/components/variable/utils.ts

@@ -1090,13 +1090,13 @@ export const getNodeUsedVarPassToServerKey = (node: Node, valueSelector: ValueSe
       break
     }
     case BlockEnum.Code: {
-      const targetVar = (data as CodeNodeType).variables?.find(v => v.value_selector.join('.') === valueSelector.join('.'))
+      const targetVar = (data as CodeNodeType).variables?.find(v => Array.isArray(v.value_selector) && v.value_selector && v.value_selector.join('.') === valueSelector.join('.'))
       if (targetVar)
         res = targetVar.variable
       break
     }
     case BlockEnum.TemplateTransform: {
-      const targetVar = (data as TemplateTransformNodeType).variables?.find(v => v.value_selector.join('.') === valueSelector.join('.'))
+      const targetVar = (data as TemplateTransformNodeType).variables?.find(v => Array.isArray(v.value_selector) && v.value_selector && v.value_selector.join('.') === valueSelector.join('.'))
       if (targetVar)
         res = targetVar.variable
       break

web/app/components/workflow/nodes/_base/components/variable/var-reference-picker.tsx

@@ -6,6 +6,7 @@ import {
   RiArrowDownSLine,
   RiCloseLine,
   RiErrorWarningFill,
+  RiLoader4Line,
   RiMoreLine,
 } from '@remixicon/react'
 import produce from 'immer'
@@ -16,8 +17,9 @@ import VarReferencePopup from './var-reference-popup'
 import { getNodeInfoById, isConversationVar, isENV, isSystemVar, varTypeToStructType } from './utils'
 import ConstantField from './constant-field'
 import cn from '@/utils/classnames'
-import type { Node, NodeOutPutVar, ValueSelector, Var } from '@/app/components/workflow/types'
-import type { CredentialFormSchema } from '@/app/components/header/account-setting/model-provider-page/declarations'
+import type { Node, NodeOutPutVar, ToolWithProvider, ValueSelector, Var } from '@/app/components/workflow/types'
+import type { CredentialFormSchemaSelect } from '@/app/components/header/account-setting/model-provider-page/declarations'
+import { type CredentialFormSchema, type FormOption, FormTypeEnum } from '@/app/components/header/account-setting/model-provider-page/declarations'
 import { BlockEnum } from '@/app/components/workflow/types'
 import { VarBlockIcon } from '@/app/components/workflow/block-icon'
 import { Line3 } from '@/app/components/base/icons/src/public/common'
@@ -40,6 +42,8 @@ import Tooltip from '@/app/components/base/tooltip'
 import { isExceptionVariable } from '@/app/components/workflow/utils'
 import VarFullPathPanel from './var-full-path-panel'
 import { noop } from 'lodash-es'
+import { useFetchDynamicOptions } from '@/service/use-plugins'
+import type { Tool } from '@/app/components/tools/types'
 
 const TRIGGER_DEFAULT_WIDTH = 227
 
@@ -68,6 +72,8 @@ type Props = {
   minWidth?: number
   popupFor?: 'assigned' | 'toAssigned'
   zIndex?: number
+  currentTool?: Tool
+  currentProvider?: ToolWithProvider
 }
 
 const DEFAULT_VALUE_SELECTOR: Props['value'] = []
@@ -97,6 +103,8 @@ const VarReferencePicker: FC<Props> = ({
   minWidth,
   popupFor,
   zIndex,
+  currentTool,
+  currentProvider,
 }) => {
   const { t } = useTranslation()
   const store = useStoreApi()
@@ -316,6 +324,42 @@ const VarReferencePicker: FC<Props> = ({
 
     return null
   }, [isValidVar, isShowAPart, hasValue, t, outputVarNode?.title, outputVarNode?.type, value, type])
+
+  const [dynamicOptions, setDynamicOptions] = useState<FormOption[] | null>(null)
+  const [isLoading, setIsLoading] = useState(false)
+  const { mutateAsync: fetchDynamicOptions } = useFetchDynamicOptions(
+    currentProvider?.plugin_id || '', currentProvider?.name || '', currentTool?.name || '', (schema as CredentialFormSchemaSelect)?.variable || '',
+    'tool',
+  )
+  const handleFetchDynamicOptions = async () => {
+    if (schema?.type !== FormTypeEnum.dynamicSelect || !currentTool || !currentProvider)
+      return
+    setIsLoading(true)
+    try {
+      const data = await fetchDynamicOptions()
+      setDynamicOptions(data?.options || [])
+    }
+ finally {
+      setIsLoading(false)
+    }
+  }
+  useEffect(() => {
+    handleFetchDynamicOptions()
+  }, [currentTool, currentProvider, schema])
+
+  const schemaWithDynamicSelect = useMemo(() => {
+    if (schema?.type !== FormTypeEnum.dynamicSelect)
+      return schema
+    // rewrite schema.options with dynamicOptions
+    if (dynamicOptions) {
+      return {
+        ...schema,
+        options: dynamicOptions,
+      }
+    }
+    return schema
+  }, [dynamicOptions])
+
   return (
     <div className={cn(className, !readonly && 'cursor-pointer')}>
       <PortalToFollowElem
@@ -366,8 +410,9 @@ const VarReferencePicker: FC<Props> = ({
                     <ConstantField
                       value={value as string}
                       onChange={onChange as ((value: string | number, varKindType: VarKindType, varInfo?: Var) => void)}
-                      schema={schema as CredentialFormSchema}
+                      schema={schemaWithDynamicSelect as CredentialFormSchema}
                       readonly={readonly}
+                      isLoading={isLoading}
                     />
                   )
                   : (
@@ -412,6 +457,7 @@ const VarReferencePicker: FC<Props> = ({
                                   )}
                                   <div className='flex items-center text-text-accent'>
                                     {!hasValue && <Variable02 className='h-3.5 w-3.5' />}
+                                    {isLoading && <RiLoader4Line className='h-3.5 w-3.5 animate-spin text-text-secondary' />}
                                     {isEnv && <Env className='h-3.5 w-3.5 text-util-colors-violet-violet-600' />}
                                     {isChatVar && <BubbleX className='h-3.5 w-3.5 text-util-colors-teal-teal-700' />}
                                     <div className={cn('ml-0.5 truncate text-xs font-medium', isEnv && '!text-text-secondary', isChatVar && 'text-util-colors-teal-teal-700', isException && 'text-text-warning')} title={varName} style={{
@@ -424,7 +470,16 @@ const VarReferencePicker: FC<Props> = ({
                                   {!isValidVar && <RiErrorWarningFill className='ml-0.5 h-3 w-3 text-text-destructive' />}
                                 </>
                               )
-                              : <div className={`overflow-hidden ${readonly ? 'text-components-input-text-disabled' : 'text-components-input-text-placeholder'} system-sm-regular text-ellipsis`}>{placeholder ?? t('workflow.common.setVarValuePlaceholder')}</div>}
+                              : <div className={`overflow-hidden ${readonly ? 'text-components-input-text-disabled' : 'text-components-input-text-placeholder'} system-sm-regular text-ellipsis`}>
+                                {isLoading ? (
+                                  <div className='flex items-center'>
+                                    <RiLoader4Line className='mr-1 h-3.5 w-3.5 animate-spin text-text-secondary' />
+                                    <span>{placeholder ?? t('workflow.common.setVarValuePlaceholder')}</span>
+                                  </div>
+                                ) : (
+                                  placeholder ?? t('workflow.common.setVarValuePlaceholder')
+                                )}
+                              </div>}
                           </div>
                         </Tooltip>
                       </div>

web/app/components/workflow/nodes/tool/components/input-var-list.tsx

@@ -6,7 +6,7 @@ import { useTranslation } from 'react-i18next'
 import type { ToolVarInputs } from '../types'
 import { VarType as VarKindType } from '../types'
 import cn from '@/utils/classnames'
-import type { ValueSelector, Var } from '@/app/components/workflow/types'
+import type { ToolWithProvider, ValueSelector, Var } from '@/app/components/workflow/types'
 import type { CredentialFormSchema } from '@/app/components/header/account-setting/model-provider-page/declarations'
 import { FormTypeEnum } from '@/app/components/header/account-setting/model-provider-page/declarations'
 import { useLanguage } from '@/app/components/header/account-setting/model-provider-page/hooks'
@@ -17,6 +17,7 @@ import { VarType } from '@/app/components/workflow/types'
 import AppSelector from '@/app/components/plugins/plugin-detail-panel/app-selector'
 import ModelParameterModal from '@/app/components/plugins/plugin-detail-panel/model-selector'
 import { noop } from 'lodash-es'
+import type { Tool } from '@/app/components/tools/types'
 
 type Props = {
   readOnly: boolean
@@ -27,6 +28,8 @@ type Props = {
   onOpen?: (index: number) => void
   isSupportConstantValue?: boolean
   filterVar?: (payload: Var, valueSelector: ValueSelector) => boolean
+  currentTool?: Tool
+  currentProvider?: ToolWithProvider
 }
 
 const InputVarList: FC<Props> = ({
@@ -38,6 +41,8 @@ const InputVarList: FC<Props> = ({
   onOpen = noop,
   isSupportConstantValue,
   filterVar,
+  currentTool,
+  currentProvider,
 }) => {
   const language = useLanguage()
   const { t } = useTranslation()
@@ -58,6 +63,8 @@ const InputVarList: FC<Props> = ({
       return 'ModelSelector'
     else if (type === FormTypeEnum.toolSelector)
       return 'ToolSelector'
+    else if (type === FormTypeEnum.dynamicSelect || type === FormTypeEnum.select)
+      return 'Select'
     else
       return 'String'
   }
@@ -149,6 +156,7 @@ const InputVarList: FC<Props> = ({
   const handleOpen = useCallback((index: number) => {
     return () => onOpen(index)
   }, [onOpen])
+
   return (
     <div className='space-y-3'>
       {
@@ -163,7 +171,8 @@ const InputVarList: FC<Props> = ({
           } = schema
           const varInput = value[variable]
           const isNumber = type === FormTypeEnum.textNumber
-          const isSelect = type === FormTypeEnum.select
+          const isDynamicSelect = type === FormTypeEnum.dynamicSelect
+          const isSelect = type === FormTypeEnum.select || type === FormTypeEnum.dynamicSelect
           const isFile = type === FormTypeEnum.file || type === FormTypeEnum.files
           const isAppSelector = type === FormTypeEnum.appSelector
           const isModelSelector = type === FormTypeEnum.modelSelector
@@ -198,11 +207,13 @@ const InputVarList: FC<Props> = ({
                   value={varInput?.type === VarKindType.constant ? (varInput?.value ?? '') : (varInput?.value ?? [])}
                   onChange={handleNotMixedTypeChange(variable)}
                   onOpen={handleOpen(index)}
-                  defaultVarKindType={varInput?.type || (isNumber ? VarKindType.constant : VarKindType.variable)}
+                  defaultVarKindType={varInput?.type || ((isNumber || isDynamicSelect) ? VarKindType.constant : VarKindType.variable)}
                   isSupportConstantValue={isSupportConstantValue}
                   filterVar={isNumber ? filterVar : undefined}
                   availableVars={isSelect ? availableVars : undefined}
                   schema={schema}
+                  currentTool={currentTool}
+                  currentProvider={currentProvider}
                 />
               )}
               {isFile && (

web/app/components/workflow/nodes/tool/panel.tsx

@@ -42,6 +42,7 @@ const Panel: FC<NodePanelProps<ToolNodeType>> = ({
     isLoading,
     outputSchema,
     hasObjectOutput,
+    currTool,
   } = useConfig(id, data)
 
   if (isLoading) {
@@ -80,6 +81,8 @@ const Panel: FC<NodePanelProps<ToolNodeType>> = ({
                 filterVar={filterVar}
                 isSupportConstantValue
                 onOpen={handleOnVarOpen}
+                currentProvider={currCollection}
+                currentTool={currTool}
               />
             </Field>
           )}

web/app/components/workflow/panel/index.tsx

@@ -1,5 +1,5 @@
 import type { FC } from 'react'
-import { memo, useEffect, useRef } from 'react'
+import { memo, useCallback, useEffect, useRef } from 'react'
 import { useNodes } from 'reactflow'
 import type { CommonNodeType } from '../types'
 import { Panel as NodePanel } from '../nodes'
@@ -13,6 +13,51 @@ export type PanelProps = {
     right?: React.ReactNode
   }
 }
+
+/**
+ * Reference MDN standard implementation：https://developer.mozilla.org/zh-CN/docs/Web/API/ResizeObserverEntry/borderBoxSize
+ */
+const getEntryWidth = (entry: ResizeObserverEntry, element: HTMLElement): number => {
+  if (entry.borderBoxSize?.length > 0)
+    return entry.borderBoxSize[0].inlineSize
+
+  if (entry.contentRect.width > 0)
+    return entry.contentRect.width
+
+  return element.getBoundingClientRect().width
+}
+
+const useResizeObserver = (
+  callback: (width: number) => void,
+  dependencies: React.DependencyList = [],
+) => {
+  const elementRef = useRef<HTMLDivElement>(null)
+
+  const stableCallback = useCallback(callback, [callback])
+
+  useEffect(() => {
+    const element = elementRef.current
+    if (!element) return
+
+    const resizeObserver = new ResizeObserver((entries) => {
+      for (const entry of entries) {
+        const width = getEntryWidth(entry, element)
+        stableCallback(width)
+      }
+    })
+
+    resizeObserver.observe(element)
+
+    const initialWidth = element.getBoundingClientRect().width
+    stableCallback(initialWidth)
+
+    return () => {
+      resizeObserver.disconnect()
+    }
+  }, [stableCallback, ...dependencies])
+  return elementRef
+}
+
 const Panel: FC<PanelProps> = ({
   components,
 }) => {
@@ -20,44 +65,21 @@ const Panel: FC<PanelProps> = ({
   const selectedNode = nodes.find(node => node.data.selected)
   const showEnvPanel = useStore(s => s.showEnvPanel)
   const isRestoring = useStore(s => s.isRestoring)
+  const showWorkflowVersionHistoryPanel = useStore(s => s.showWorkflowVersionHistoryPanel)
 
-  const rightPanelRef = useRef<HTMLDivElement>(null)
   const setRightPanelWidth = useStore(s => s.setRightPanelWidth)
-
-  // get right panel width
-  useEffect(() => {
-    if (rightPanelRef.current) {
-      const resizeRightPanelObserver = new ResizeObserver((entries) => {
-        for (const entry of entries) {
-          const { inlineSize } = entry.borderBoxSize[0]
-          setRightPanelWidth(inlineSize)
-        }
-      })
-      resizeRightPanelObserver.observe(rightPanelRef.current)
-      return () => {
-        resizeRightPanelObserver.disconnect()
-      }
-    }
-  }, [setRightPanelWidth])
-
-  const otherPanelRef = useRef<HTMLDivElement>(null)
   const setOtherPanelWidth = useStore(s => s.setOtherPanelWidth)
 
-  // get other panel width
-  useEffect(() => {
-    if (otherPanelRef.current) {
-      const resizeOtherPanelObserver = new ResizeObserver((entries) => {
-        for (const entry of entries) {
-          const { inlineSize } = entry.borderBoxSize[0]
-          setOtherPanelWidth(inlineSize)
-        }
-      })
-      resizeOtherPanelObserver.observe(otherPanelRef.current)
-      return () => {
-        resizeOtherPanelObserver.disconnect()
-      }
-    }
-  }, [setOtherPanelWidth])
+  const rightPanelRef = useResizeObserver(
+    setRightPanelWidth,
+    [setRightPanelWidth, selectedNode, showEnvPanel, showWorkflowVersionHistoryPanel],
+  )
+
+  const otherPanelRef = useResizeObserver(
+    setOtherPanelWidth,
+    [setOtherPanelWidth, showEnvPanel, showWorkflowVersionHistoryPanel],
+  )
+
   return (
     <div
       ref={rightPanelRef}
@@ -65,26 +87,14 @@ const Panel: FC<PanelProps> = ({
       className={cn('absolute bottom-1 right-0 top-14 z-10 flex outline-none')}
       key={`${isRestoring}`}
     >
-      {
-        components?.left
-      }
-      {
-        !!selectedNode && (
-          <NodePanel {...selectedNode!} />
-        )
-      }
+      {components?.left}
+      {!!selectedNode && <NodePanel {...selectedNode} />}
       <div
-        className='relative'
+        className="relative"
         ref={otherPanelRef}
       >
-        {
-          components?.right
-        }
-        {
-          showEnvPanel && (
-            <EnvPanel />
-          )
-        }
+        {components?.right}
+        {showEnvPanel && <EnvPanel />}
       </div>
     </div>
   )

web/app/components/workflow/run/node.tsx

@@ -29,6 +29,7 @@ import type {
 import ErrorHandleTip from '@/app/components/workflow/nodes/_base/components/error-handle/error-handle-tip'
 import { hasRetryNode } from '@/app/components/workflow/utils'
 import { useDocLink } from '@/context/i18n'
+import Tooltip from '@/app/components/base/tooltip'
 
 type Props = {
   className?: string
@@ -129,10 +130,16 @@ const NodePanel: FC<Props> = ({
             />
           )}
           <BlockIcon size={inMessage ? 'xs' : 'sm'} className={cn('mr-2 shrink-0', inMessage && '!mr-1')} type={nodeInfo.node_type} toolIcon={nodeInfo.extras?.icon || nodeInfo.extras} />
-          <div className={cn(
-            'system-xs-semibold-uppercase grow truncate text-text-secondary',
-            hideInfo && '!text-xs',
-          )} title={nodeInfo.title}>{nodeInfo.title}</div>
+          <Tooltip
+            popupContent={
+              <div className='max-w-xs'>{nodeInfo.title}</div>
+            }
+          >
+            <div className={cn(
+              'system-xs-semibold-uppercase grow truncate text-text-secondary',
+              hideInfo && '!text-xs',
+            )}>{nodeInfo.title}</div>
+          </Tooltip>
           {nodeInfo.status !== 'running' && !hideInfo && (
             <div className='system-xs-regular shrink-0 text-text-tertiary'>{nodeInfo.execution_metadata?.total_tokens ? `${getTokenCount(nodeInfo.execution_metadata?.total_tokens || 0)} tokens · ` : ''}{`${getTime(nodeInfo.elapsed_time || 0)}`}</div>
           )}

web/app/components/workflow/variable-inspect/empty.tsx

@@ -15,7 +15,7 @@ const Empty: FC = () => {
         <div className='system-xs-regular text-text-tertiary'>{t('workflow.debug.variableInspect.emptyTip')}</div>
         <a
           className='system-xs-regular cursor-pointer text-text-accent'
-          href='https://docs.dify.ai/guides/workflow/debug-and-preview/variable-inspect'
+          href='https://docs.dify.ai/en/guides/workflow/debug-and-preview/variable-inspect'
           target='_blank'
           rel='noopener noreferrer'>
             {t('workflow.debug.variableInspect.emptyLink')}

web/app/components/workflow/variable-inspect/trigger.tsx

@@ -12,6 +12,7 @@ import type { CommonNodeType } from '@/app/components/workflow/types'
 import { useEventEmitterContextContext } from '@/context/event-emitter'
 import { EVENT_WORKFLOW_STOP } from '@/app/components/workflow/variable-inspect/types'
 import cn from '@/utils/classnames'
+import { useNodesReadOnly } from '../hooks/use-workflow'
 
 const VariableInspectTrigger: FC = () => {
   const { t } = useTranslation()
@@ -32,7 +33,10 @@ const VariableInspectTrigger: FC = () => {
     const allVars = [...environmentVariables, ...conversationVars, ...systemVars, ...nodesWithInspectVars]
     return allVars
   }, [environmentVariables, conversationVars, systemVars, nodesWithInspectVars])
-
+  const {
+    nodesReadOnly,
+    getNodesReadOnly,
+  } = useNodesReadOnly()
   const workflowRunningData = useStore(s => s.workflowRunningData)
   const nodes = useNodes<CommonNodeType>()
   const isStepRunning = useMemo(() => nodes.some(node => node.data._singleRunningStatus === NodeRunningStatus.Running), [nodes])
@@ -61,8 +65,14 @@ const VariableInspectTrigger: FC = () => {
     <div className={cn('flex items-center gap-1')}>
       {!isRunning && !currentVars.length && (
         <div
-          className='system-2xs-semibold-uppercase flex h-5 cursor-pointer items-center gap-1 rounded-md border-[0.5px] border-effects-highlight bg-components-actionbar-bg px-2 text-text-tertiary shadow-lg backdrop-blur-sm hover:bg-background-default-hover'
-          onClick={() => setShowVariableInspectPanel(true)}
+          className={cn('system-2xs-semibold-uppercase flex h-5 cursor-pointer items-center gap-1 rounded-md border-[0.5px] border-effects-highlight bg-components-actionbar-bg px-2 text-text-tertiary shadow-lg backdrop-blur-sm hover:bg-background-default-hover',
+            nodesReadOnly && 'cursor-not-allowed text-text-disabled hover:bg-transparent hover:text-text-disabled',
+          )}
+          onClick={() => {
+            if (getNodesReadOnly())
+              return
+            setShowVariableInspectPanel(true)
+          }}
         >
           {t('workflow.debug.variableInspect.trigger.normal')}
         </div>
@@ -70,13 +80,21 @@ const VariableInspectTrigger: FC = () => {
       {!isRunning && currentVars.length > 0 && (
         <>
           <div
-            className='system-xs-medium flex h-6 cursor-pointer items-center gap-1 rounded-md border-[0.5px] border-effects-highlight bg-components-actionbar-bg px-2 text-text-accent shadow-lg backdrop-blur-sm hover:bg-components-actionbar-bg-accent'
-            onClick={() => setShowVariableInspectPanel(true)}
+            className={cn('system-xs-medium flex h-6 cursor-pointer items-center gap-1 rounded-md border-[0.5px] border-effects-highlight bg-components-actionbar-bg px-2 text-text-accent shadow-lg backdrop-blur-sm hover:bg-components-actionbar-bg-accent',
+              nodesReadOnly && 'cursor-not-allowed text-text-disabled hover:bg-transparent hover:text-text-disabled',
+            )}
+            onClick={() => {
+              if (getNodesReadOnly())
+                return
+              setShowVariableInspectPanel(true)
+            }}
           >
             {t('workflow.debug.variableInspect.trigger.cached')}
           </div>
           <div
-            className='system-xs-medium flex h-6 cursor-pointer items-center rounded-md border-[0.5px] border-effects-highlight bg-components-actionbar-bg px-1 text-text-tertiary shadow-lg backdrop-blur-sm hover:bg-components-actionbar-bg-accent hover:text-text-accent'
+            className={cn('system-xs-medium flex h-6 cursor-pointer items-center rounded-md border-[0.5px] border-effects-highlight bg-components-actionbar-bg px-1 text-text-tertiary shadow-lg backdrop-blur-sm hover:bg-components-actionbar-bg-accent hover:text-text-accent',
+              nodesReadOnly && 'cursor-not-allowed text-text-disabled hover:bg-transparent hover:text-text-disabled',
+            )}
             onClick={handleClearAll}
           >
             {t('workflow.debug.variableInspect.trigger.clear')}

web/app/styles/globals.css

@@ -697,4 +697,15 @@ button:focus-within {
     -ms-overflow-style: none;
     scrollbar-width: none;
   }
+
+  /* Hide arrows from number input */
+  .no-spinner::-webkit-outer-spin-button,
+  .no-spinner::-webkit-inner-spin-button {
+    -webkit-appearance: none;
+    margin: 0;
+  }
+
+  .no-spinner {
+    -moz-appearance: textfield;
+  }
 }

web/eslint.config.mjs

@@ -213,7 +213,7 @@ export default combine(
     settings: {
       tailwindcss: {
         // These are the default values but feel free to customize
-        callees: ['classnames', 'clsx', 'ctl', 'cn'],
+        callees: ['classnames', 'clsx', 'ctl', 'cn', 'classNames'],
         config: 'tailwind.config.js', // returned from `loadConfig()` utility if not provided
         cssFiles: [
           '**/*.css',

web/hooks/use-tab-searchparams.ts

@@ -29,9 +29,10 @@ export const useTabSearchParams = ({
   const router = useRouter()
   const pathName = pathnameFromHook || window?.location?.pathname
   const searchParams = useSearchParams()
+  const searchParamValue = searchParams.has(searchParamName) ? decodeURIComponent(searchParams.get(searchParamName)!) : defaultTab
   const [activeTab, setTab] = useState<string>(
     !disableSearchParams
-      ? (searchParams.get(searchParamName) || defaultTab)
+      ? searchParamValue
       : defaultTab,
   )
 
@@ -39,7 +40,7 @@ export const useTabSearchParams = ({
     setTab(newActiveTab)
     if (disableSearchParams)
       return
-    router[`${routingBehavior}`](`${pathName}?${searchParamName}=${newActiveTab}`)
+    router[`${routingBehavior}`](`${pathName}?${searchParamName}=${encodeURIComponent(newActiveTab)}`)
   }
 
   return [activeTab, setActiveTab] as const

web/i18n/en-US/app.ts

@@ -199,9 +199,9 @@ const translation = {
   accessControl: 'Web App Access Control',
   accessItemsDescription: {
     anyone: 'Anyone can access the web app (no login required)',
-    specific: 'Only specific members within the platform can access the Web application',
-    organization: 'All members within the platform can access the Web application',
-    external: 'Only authenticated external users can access the Web application',
+    specific: 'Only specific members within the platform can access the web app',
+    organization: 'All members within the platform can access the web app',
+    external: 'Only authenticated external users can access the web app',
   },
   accessControlDialog: {
     title: 'Web App Access Control',
@@ -218,7 +218,7 @@ const translation = {
     members_one: '{{count}} MEMBER',
     members_other: '{{count}} MEMBERS',
     noGroupsOrMembers: 'No groups or members selected',
-    webAppSSONotEnabledTip: 'Please contact your organization administrator to configure external authentication for the Web application.',
+    webAppSSONotEnabledTip: 'Please contact your organization administrator to configure external authentication for the web app.',
     operateGroupAndMember: {
       searchPlaceholder: 'Search groups and members',
       allMembers: 'All members',

web/i18n/en-US/dataset-documents.ts

@@ -355,7 +355,9 @@ const translation = {
     newChildChunk: 'New Child Chunk',
     keywords: 'KEYWORDS',
     addKeyWord: 'Add keyword',
+    keywordEmpty: 'The keyword cannot be empty',
     keywordError: 'The maximum length of keyword is 20',
+    keywordDuplicate: 'The keyword already exists',
     characters_one: 'character',
     characters_other: 'characters',
     hitCount: 'Retrieval count',

web/service/access-control.ts

@@ -86,5 +86,8 @@ export const useGetUserCanAccessApp = ({ appId, isInstalledApp = true, enabled }
     enabled: !!appId && enabled,
     staleTime: 0,
     gcTime: 0,
+    initialData: {
+      result: !enabled,
+    },
   })
 }

web/service/use-plugins.ts

@@ -1,5 +1,6 @@
 import { useCallback, useEffect } from 'react'
 import type {
+  FormOption,
   ModelProvider,
 } from '@/app/components/header/account-setting/model-provider-page/declarations'
 import { fetchModelProviderModelList } from '@/service/common'
@@ -477,7 +478,7 @@ export const usePluginTaskList = (category?: PluginType) => {
           refreshPluginList(category ? { category } as any : undefined, !category)
       }
     }
-  // eslint-disable-next-line react-hooks/exhaustive-deps
+    // eslint-disable-next-line react-hooks/exhaustive-deps
   }, [isRefetching])
 
   const handleRefetch = useCallback(() => {
@@ -571,3 +572,17 @@ export const usePluginInfo = (providerName?: string) => {
     enabled: !!providerName,
   })
 }
+
+export const useFetchDynamicOptions = (plugin_id: string, provider: string, action: string, parameter: string, provider_type: 'tool') => {
+  return useMutation({
+    mutationFn: () => get<{ options: FormOption[] }>('/workspaces/current/plugin/parameters/dynamic-options', {
+      params: {
+        plugin_id,
+        provider,
+        action,
+        parameter,
+        provider_type,
+      },
+    }),
+  })
+}