merge main

.github/workflows/api-tests.yml

@@ -45,7 +45,17 @@ jobs:
         run: uv sync --project api --dev
 
       - name: Run Unit tests
-        run: uv run --project api bash dev/pytest/pytest_unit_tests.sh
+        run: |
+          uv run --project api bash dev/pytest/pytest_unit_tests.sh
+          # Extract coverage percentage and create a summary
+          TOTAL_COVERAGE=$(python -c 'import json; print(json.load(open("coverage.json"))["totals"]["percent_covered_display"])')
+
+          # Create a detailed coverage summary
+          echo "### Test Coverage Summary :test_tube:" >> $GITHUB_STEP_SUMMARY
+          echo "Total Coverage: ${TOTAL_COVERAGE}%" >> $GITHUB_STEP_SUMMARY
+          echo "\`\`\`" >> $GITHUB_STEP_SUMMARY
+          uv run --project api coverage report >> $GITHUB_STEP_SUMMARY
+          echo "\`\`\`" >> $GITHUB_STEP_SUMMARY
 
       - name: Run dify config tests
         run: uv run --project api dev/pytest/pytest_config_tests.py

.gitignore

@@ -46,6 +46,7 @@ htmlcov/
 .cache
 nosetests.xml
 coverage.xml
+coverage.json
 *.cover
 *.py,cover
 .hypothesis/

api/.env.example

@@ -165,6 +165,7 @@ MILVUS_URI=http://127.0.0.1:19530
 MILVUS_TOKEN=
 MILVUS_USER=root
 MILVUS_PASSWORD=Milvus
+MILVUS_ANALYZER_PARAMS=
 
 # MyScale configuration
 MYSCALE_HOST=127.0.0.1
@@ -423,6 +424,12 @@ WORKFLOW_CALL_MAX_DEPTH=5
 WORKFLOW_PARALLEL_DEPTH_LIMIT=3
 MAX_VARIABLE_SIZE=204800
 
+# Workflow storage configuration
+# Options: rdbms, hybrid
+# rdbms: Use only the relational database (default)
+# hybrid: Save new data to object storage, read from both object storage and RDBMS
+WORKFLOW_NODE_EXECUTION_STORAGE=rdbms
+
 # App configuration
 APP_MAX_EXECUTION_TIME=1200
 APP_MAX_ACTIVE_REQUESTS=0

api/app_factory.py

@@ -54,6 +54,7 @@ def initialize_extensions(app: DifyApp):
         ext_otel,
         ext_proxy_fix,
         ext_redis,
+        ext_repositories,
         ext_sentry,
         ext_set_secretkey,
         ext_storage,
@@ -74,6 +75,7 @@ def initialize_extensions(app: DifyApp):
         ext_migrate,
         ext_redis,
         ext_storage,
+        ext_repositories,
         ext_celery,
         ext_login,
         ext_mail,

api/configs/feature/__init__.py

@@ -12,7 +12,7 @@ from pydantic import (
 )
 from pydantic_settings import BaseSettings
 
-from configs.feature.hosted_service import HostedServiceConfig
+from .hosted_service import HostedServiceConfig
 
 
 class SecurityConfig(BaseSettings):
@@ -519,6 +519,11 @@ class WorkflowNodeExecutionConfig(BaseSettings):
         default=100,
     )
 
+    WORKFLOW_NODE_EXECUTION_STORAGE: str = Field(
+        default="rdbms",
+        description="Storage backend for WorkflowNodeExecution. Options: 'rdbms', 'hybrid'",
+    )
+
 
 class AuthConfig(BaseSettings):
     """

api/configs/middleware/vdb/milvus_config.py

@@ -39,3 +39,8 @@ class MilvusConfig(BaseSettings):
         "older versions",
         default=True,
     )
+
+    MILVUS_ANALYZER_PARAMS: Optional[str] = Field(
+        description='Milvus text analyzer parameters, e.g., {"type": "chinese"} for Chinese segmentation support.',
+        default=None,
+    )

api/controllers/common/helpers.py

@@ -4,14 +4,10 @@ import platform
 import re
 import urllib.parse
 import warnings
-from collections.abc import Mapping
-from typing import Any
 from uuid import uuid4
 
 import httpx
 
-from constants import DEFAULT_FILE_NUMBER_LIMITS
-
 try:
     import magic
 except ImportError:
@@ -31,8 +27,6 @@ except ImportError:
 
 from pydantic import BaseModel
 
-from configs import dify_config
-
 
 class FileInfo(BaseModel):
     filename: str
@@ -89,38 +83,3 @@ def guess_file_info_from_response(response: httpx.Response):
         mimetype=mimetype,
         size=int(response.headers.get("Content-Length", -1)),
     )
-
-
-def get_parameters_from_feature_dict(*, features_dict: Mapping[str, Any], user_input_form: list[dict[str, Any]]):
-    return {
-        "opening_statement": features_dict.get("opening_statement"),
-        "suggested_questions": features_dict.get("suggested_questions", []),
-        "suggested_questions_after_answer": features_dict.get("suggested_questions_after_answer", {"enabled": False}),
-        "speech_to_text": features_dict.get("speech_to_text", {"enabled": False}),
-        "text_to_speech": features_dict.get("text_to_speech", {"enabled": False}),
-        "retriever_resource": features_dict.get("retriever_resource", {"enabled": False}),
-        "annotation_reply": features_dict.get("annotation_reply", {"enabled": False}),
-        "more_like_this": features_dict.get("more_like_this", {"enabled": False}),
-        "user_input_form": user_input_form,
-        "sensitive_word_avoidance": features_dict.get(
-            "sensitive_word_avoidance", {"enabled": False, "type": "", "configs": []}
-        ),
-        "file_upload": features_dict.get(
-            "file_upload",
-            {
-                "image": {
-                    "enabled": False,
-                    "number_limits": DEFAULT_FILE_NUMBER_LIMITS,
-                    "detail": "high",
-                    "transfer_methods": ["remote_url", "local_file"],
-                }
-            },
-        ),
-        "system_parameters": {
-            "image_file_size_limit": dify_config.UPLOAD_IMAGE_FILE_SIZE_LIMIT,
-            "video_file_size_limit": dify_config.UPLOAD_VIDEO_FILE_SIZE_LIMIT,
-            "audio_file_size_limit": dify_config.UPLOAD_AUDIO_FILE_SIZE_LIMIT,
-            "file_size_limit": dify_config.UPLOAD_FILE_SIZE_LIMIT,
-            "workflow_file_upload_limit": dify_config.WORKFLOW_FILE_UPLOAD_LIMIT,
-        },
-    }

api/controllers/console/app/generator.py

@@ -85,5 +85,35 @@ class RuleCodeGenerateApi(Resource):
         return code_result
 
 
+class RuleStructuredOutputGenerateApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def post(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("instruction", type=str, required=True, nullable=False, location="json")
+        parser.add_argument("model_config", type=dict, required=True, nullable=False, location="json")
+        args = parser.parse_args()
+
+        account = current_user
+        try:
+            structured_output = LLMGenerator.generate_structured_output(
+                tenant_id=account.current_tenant_id,
+                instruction=args["instruction"],
+                model_config=args["model_config"],
+            )
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
+        except QuotaExceededError:
+            raise ProviderQuotaExceededError()
+        except ModelCurrentlyNotSupportError:
+            raise ProviderModelCurrentlyNotSupportError()
+        except InvokeError as e:
+            raise CompletionRequestError(e.description)
+
+        return structured_output
+
+
 api.add_resource(RuleGenerateApi, "/rule-generate")
 api.add_resource(RuleCodeGenerateApi, "/rule-code-generate")
+api.add_resource(RuleStructuredOutputGenerateApi, "/rule-structured-output-generate")

api/controllers/console/app/workflow_app_log.py

@@ -1,5 +1,4 @@
-from datetime import datetime
-
+from dateutil.parser import isoparse
 from flask_restful import Resource, marshal_with, reqparse  # type: ignore
 from flask_restful.inputs import int_range  # type: ignore
 from sqlalchemy.orm import Session
@@ -41,10 +40,10 @@ class WorkflowAppLogApi(Resource):
 
         args.status = WorkflowRunStatus(args.status) if args.status else None
         if args.created_at__before:
-            args.created_at__before = datetime.fromisoformat(args.created_at__before.replace("Z", "+00:00"))
+            args.created_at__before = isoparse(args.created_at__before)
 
         if args.created_at__after:
-            args.created_at__after = datetime.fromisoformat(args.created_at__after.replace("Z", "+00:00"))
+            args.created_at__after = isoparse(args.created_at__after)
 
         # get paginate workflow app logs
         workflow_app_service = WorkflowAppService()

api/controllers/console/auth/data_source_oauth.py

@@ -74,7 +74,9 @@ class OAuthDataSourceBinding(Resource):
         if not oauth_provider:
             return {"error": "Invalid provider"}, 400
         if "code" in request.args:
-            code = request.args.get("code")
+            code = request.args.get("code", "")
+            if not code:
+                return {"error": "Invalid code"}, 400
             try:
                 oauth_provider.get_access_token(code)
             except requests.exceptions.HTTPError as e:

api/controllers/console/auth/forgot_password.py

@@ -16,7 +16,7 @@ from controllers.console.auth.error import (
     PasswordMismatchError,
 )
 from controllers.console.error import AccountInFreezeError, AccountNotFound, EmailSendIpLimitError
-from controllers.console.wraps import setup_required
+from controllers.console.wraps import email_password_login_enabled, setup_required
 from events.tenant_event import tenant_was_created
 from extensions.ext_database import db
 from libs.helper import email, extract_remote_ip
@@ -30,6 +30,7 @@ from services.feature_service import FeatureService
 
 class ForgotPasswordSendEmailApi(Resource):
     @setup_required
+    @email_password_login_enabled
     def post(self):
         parser = reqparse.RequestParser()
         parser.add_argument("email", type=email, required=True, location="json")
@@ -62,6 +63,7 @@ class ForgotPasswordSendEmailApi(Resource):
 
 class ForgotPasswordCheckApi(Resource):
     @setup_required
+    @email_password_login_enabled
     def post(self):
         parser = reqparse.RequestParser()
         parser.add_argument("email", type=str, required=True, location="json")
@@ -86,12 +88,21 @@ class ForgotPasswordCheckApi(Resource):
             AccountService.add_forgot_password_error_rate_limit(args["email"])
             raise EmailCodeError()
 
+        # Verified, revoke the first token
+        AccountService.revoke_reset_password_token(args["token"])
+
+        # Refresh token data by generating a new token
+        _, new_token = AccountService.generate_reset_password_token(
+            user_email, code=args["code"], additional_data={"phase": "reset"}
+        )
+
         AccountService.reset_forgot_password_error_rate_limit(args["email"])
-        return {"is_valid": True, "email": token_data.get("email")}
+        return {"is_valid": True, "email": token_data.get("email"), "token": new_token}
 
 
 class ForgotPasswordResetApi(Resource):
     @setup_required
+    @email_password_login_enabled
     def post(self):
         parser = reqparse.RequestParser()
         parser.add_argument("token", type=str, required=True, nullable=False, location="json")
@@ -107,6 +118,9 @@ class ForgotPasswordResetApi(Resource):
         reset_data = AccountService.get_reset_password_data(args["token"])
         if not reset_data:
             raise InvalidTokenError()
+        # Must use token in reset phase
+        if reset_data.get("phase", "") != "reset":
+            raise InvalidTokenError()
 
         # Revoke token to prevent reuse
         AccountService.revoke_reset_password_token(args["token"])

api/controllers/console/auth/login.py

@@ -22,7 +22,7 @@ from controllers.console.error import (
     EmailSendIpLimitError,
     NotAllowedCreateWorkspace,
 )
-from controllers.console.wraps import setup_required
+from controllers.console.wraps import email_password_login_enabled, setup_required
 from events.tenant_event import tenant_was_created
 from libs.helper import email, extract_remote_ip
 from libs.password import valid_password
@@ -38,6 +38,7 @@ class LoginApi(Resource):
     """Resource for user login."""
 
     @setup_required
+    @email_password_login_enabled
     def post(self):
         """Authenticate user and login."""
         parser = reqparse.RequestParser()
@@ -110,6 +111,7 @@ class LogoutApi(Resource):
 
 class ResetPasswordSendEmailApi(Resource):
     @setup_required
+    @email_password_login_enabled
     def post(self):
         parser = reqparse.RequestParser()
         parser.add_argument("email", type=email, required=True, location="json")

api/controllers/console/explore/parameter.py

@@ -1,10 +1,10 @@
 from flask_restful import marshal_with  # type: ignore
 
 from controllers.common import fields
-from controllers.common import helpers as controller_helpers
 from controllers.console import api
 from controllers.console.app.error import AppUnavailableError
 from controllers.console.explore.wraps import InstalledAppResource
+from core.app.app_config.common.parameters_mapping import get_parameters_from_feature_dict
 from models.model import AppMode, InstalledApp
 from services.app_service import AppService
 
@@ -36,9 +36,7 @@ class AppParameterApi(InstalledAppResource):
 
             user_input_form = features_dict.get("user_input_form", [])
 
-        return controller_helpers.get_parameters_from_feature_dict(
-            features_dict=features_dict, user_input_form=user_input_form
-        )
+        return get_parameters_from_feature_dict(features_dict=features_dict, user_input_form=user_input_form)
 
 
 class ExploreAppMetaApi(InstalledAppResource):

api/controllers/console/wraps.py

@@ -210,3 +210,16 @@ def enterprise_license_required(view):
         return view(*args, **kwargs)
 
     return decorated
+
+
+def email_password_login_enabled(view):
+    @wraps(view)
+    def decorated(*args, **kwargs):
+        features = FeatureService.get_system_features()
+        if features.enable_email_password_login:
+            return view(*args, **kwargs)
+
+        # otherwise, return 403
+        abort(403)
+
+    return decorated

api/controllers/inner_api/plugin/plugin.py

@@ -13,6 +13,7 @@ from core.plugin.backwards_invocation.model import PluginModelBackwardsInvocatio
 from core.plugin.backwards_invocation.node import PluginNodeBackwardsInvocation
 from core.plugin.backwards_invocation.tool import PluginToolBackwardsInvocation
 from core.plugin.entities.request import (
+    RequestFetchAppInfo,
     RequestInvokeApp,
     RequestInvokeEncrypt,
     RequestInvokeLLM,
@@ -278,6 +279,17 @@ class PluginUploadFileRequestApi(Resource):
         return BaseBackwardsInvocationResponse(data={"url": url}).model_dump()
 
 
+class PluginFetchAppInfoApi(Resource):
+    @setup_required
+    @plugin_inner_api_only
+    @get_user_tenant
+    @plugin_data(payload_type=RequestFetchAppInfo)
+    def post(self, user_model: Account | EndUser, tenant_model: Tenant, payload: RequestFetchAppInfo):
+        return BaseBackwardsInvocationResponse(
+            data=PluginAppBackwardsInvocation.fetch_app_info(payload.app_id, tenant_model.id)
+        ).model_dump()
+
+
 api.add_resource(PluginInvokeLLMApi, "/invoke/llm")
 api.add_resource(PluginInvokeTextEmbeddingApi, "/invoke/text-embedding")
 api.add_resource(PluginInvokeRerankApi, "/invoke/rerank")
@@ -291,3 +303,4 @@ api.add_resource(PluginInvokeAppApi, "/invoke/app")
 api.add_resource(PluginInvokeEncryptApi, "/invoke/encrypt")
 api.add_resource(PluginInvokeSummaryApi, "/invoke/summary")
 api.add_resource(PluginUploadFileRequestApi, "/upload/file/request")
+api.add_resource(PluginFetchAppInfoApi, "/fetch/app/info")

api/controllers/service_api/app/app.py

@@ -1,10 +1,10 @@
 from flask_restful import Resource, marshal_with  # type: ignore
 
 from controllers.common import fields
-from controllers.common import helpers as controller_helpers
 from controllers.service_api import api
 from controllers.service_api.app.error import AppUnavailableError
 from controllers.service_api.wraps import validate_app_token
+from core.app.app_config.common.parameters_mapping import get_parameters_from_feature_dict
 from models.model import App, AppMode
 from services.app_service import AppService
 
@@ -32,9 +32,7 @@ class AppParameterApi(Resource):
 
             user_input_form = features_dict.get("user_input_form", [])
 
-        return controller_helpers.get_parameters_from_feature_dict(
-            features_dict=features_dict, user_input_form=user_input_form
-        )
+        return get_parameters_from_feature_dict(features_dict=features_dict, user_input_form=user_input_form)
 
 
 class AppMetaApi(Resource):

api/controllers/service_api/app/workflow.py

@@ -1,6 +1,6 @@
 import logging
-from datetime import datetime
 
+from dateutil.parser import isoparse
 from flask_restful import Resource, fields, marshal_with, reqparse  # type: ignore
 from flask_restful.inputs import int_range  # type: ignore
 from sqlalchemy.orm import Session
@@ -140,10 +140,10 @@ class WorkflowAppLogApi(Resource):
 
         args.status = WorkflowRunStatus(args.status) if args.status else None
         if args.created_at__before:
-            args.created_at__before = datetime.fromisoformat(args.created_at__before.replace("Z", "+00:00"))
+            args.created_at__before = isoparse(args.created_at__before)
 
         if args.created_at__after:
-            args.created_at__after = datetime.fromisoformat(args.created_at__after.replace("Z", "+00:00"))
+            args.created_at__after = isoparse(args.created_at__after)
 
         # get paginate workflow app logs
         workflow_app_service = WorkflowAppService()

api/controllers/service_api/dataset/dataset.py

@@ -139,7 +139,9 @@ class DatasetListApi(DatasetApiResource):
                 external_knowledge_id=args["external_knowledge_id"],
                 embedding_model_provider=args["embedding_model_provider"],
                 embedding_model_name=args["embedding_model"],
-                retrieval_model=RetrievalModel(**args["retrieval_model"]),
+                retrieval_model=RetrievalModel(**args["retrieval_model"])
+                if args["retrieval_model"] is not None
+                else None,
             )
         except services.errors.dataset.DatasetNameDuplicateError:
             raise DatasetNameDuplicateError()

api/controllers/service_api/dataset/segment.py

@@ -122,6 +122,8 @@ class SegmentApi(DatasetApiResource):
             tenant_id=current_user.current_tenant_id,
             status_list=args["status"],
             keyword=args["keyword"],
+            page=page,
+            limit=limit,
         )
 
         response = {

api/controllers/web/app.py

@@ -1,10 +1,10 @@
 from flask_restful import marshal_with  # type: ignore
 
 from controllers.common import fields
-from controllers.common import helpers as controller_helpers
 from controllers.web import api
 from controllers.web.error import AppUnavailableError
 from controllers.web.wraps import WebApiResource
+from core.app.app_config.common.parameters_mapping import get_parameters_from_feature_dict
 from models.model import App, AppMode
 from services.app_service import AppService
 
@@ -31,9 +31,7 @@ class AppParameterApi(WebApiResource):
 
             user_input_form = features_dict.get("user_input_form", [])
 
-        return controller_helpers.get_parameters_from_feature_dict(
-            features_dict=features_dict, user_input_form=user_input_form
-        )
+        return get_parameters_from_feature_dict(features_dict=features_dict, user_input_form=user_input_form)
 
 
 class AppMeta(WebApiResource):

api/controllers/web/message.py

@@ -46,6 +46,7 @@ class MessageListApi(WebApiResource):
         "retriever_resources": fields.List(fields.Nested(retriever_resource_fields)),
         "created_at": TimestampField,
         "agent_thoughts": fields.List(fields.Nested(agent_thought_fields)),
+        "metadata": fields.Raw(attribute="message_metadata_dict"),
         "status": fields.String,
         "error": fields.String,
     }

api/core/agent/plugin_entities.py

@@ -52,6 +52,7 @@ class AgentStrategyParameter(PluginParameter):
             return cast_parameter_value(self, value)
 
     type: AgentStrategyParameterType = Field(..., description="The type of the parameter")
+    help: Optional[I18nObject] = None
 
     def init_frontend_parameter(self, value: Any):
         return init_frontend_parameter(self, self.type, value)

api/core/app/app_config/common/parameters_mapping/__init__.py

@@ -0,0 +1,45 @@
+from collections.abc import Mapping
+from typing import Any
+
+from configs import dify_config
+from constants import DEFAULT_FILE_NUMBER_LIMITS
+
+
+def get_parameters_from_feature_dict(
+    *, features_dict: Mapping[str, Any], user_input_form: list[dict[str, Any]]
+) -> Mapping[str, Any]:
+    """
+    Mapping from feature dict to webapp parameters
+    """
+    return {
+        "opening_statement": features_dict.get("opening_statement"),
+        "suggested_questions": features_dict.get("suggested_questions", []),
+        "suggested_questions_after_answer": features_dict.get("suggested_questions_after_answer", {"enabled": False}),
+        "speech_to_text": features_dict.get("speech_to_text", {"enabled": False}),
+        "text_to_speech": features_dict.get("text_to_speech", {"enabled": False}),
+        "retriever_resource": features_dict.get("retriever_resource", {"enabled": False}),
+        "annotation_reply": features_dict.get("annotation_reply", {"enabled": False}),
+        "more_like_this": features_dict.get("more_like_this", {"enabled": False}),
+        "user_input_form": user_input_form,
+        "sensitive_word_avoidance": features_dict.get(
+            "sensitive_word_avoidance", {"enabled": False, "type": "", "configs": []}
+        ),
+        "file_upload": features_dict.get(
+            "file_upload",
+            {
+                "image": {
+                    "enabled": False,
+                    "number_limits": DEFAULT_FILE_NUMBER_LIMITS,
+                    "detail": "high",
+                    "transfer_methods": ["remote_url", "local_file"],
+                }
+            },
+        ),
+        "system_parameters": {
+            "image_file_size_limit": dify_config.UPLOAD_IMAGE_FILE_SIZE_LIMIT,
+            "video_file_size_limit": dify_config.UPLOAD_VIDEO_FILE_SIZE_LIMIT,
+            "audio_file_size_limit": dify_config.UPLOAD_AUDIO_FILE_SIZE_LIMIT,
+            "file_size_limit": dify_config.UPLOAD_FILE_SIZE_LIMIT,
+            "workflow_file_upload_limit": dify_config.WORKFLOW_FILE_UPLOAD_LIMIT,
+        },
+    }

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

@@ -320,10 +320,9 @@ class AdvancedChatAppGenerateTaskPipeline:
                         session=session, workflow_run_id=self._workflow_run_id
                     )
                     workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_retried(
-                        session=session, workflow_run=workflow_run, event=event
+                        workflow_run=workflow_run, event=event
                     )
                     node_retry_resp = self._workflow_cycle_manager._workflow_node_retry_to_stream_response(
-                        session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
                         workflow_node_execution=workflow_node_execution,
@@ -341,11 +340,10 @@ class AdvancedChatAppGenerateTaskPipeline:
                         session=session, workflow_run_id=self._workflow_run_id
                     )
                     workflow_node_execution = self._workflow_cycle_manager._handle_node_execution_start(
-                        session=session, workflow_run=workflow_run, event=event
+                        workflow_run=workflow_run, event=event
                     )
 
                     node_start_resp = self._workflow_cycle_manager._workflow_node_start_to_stream_response(
-                        session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
                         workflow_node_execution=workflow_node_execution,
@@ -363,11 +361,10 @@ class AdvancedChatAppGenerateTaskPipeline:
 
                 with Session(db.engine, expire_on_commit=False) as session:
                     workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_success(
-                        session=session, event=event
+                        event=event
                     )
 
                     node_finish_resp = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
-                        session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
                         workflow_node_execution=workflow_node_execution,
@@ -383,18 +380,15 @@ class AdvancedChatAppGenerateTaskPipeline:
                 | QueueNodeInLoopFailedEvent
                 | QueueNodeExceptionEvent,
             ):
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_failed(
-                        session=session, event=event
-                    )
+                workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_failed(
+                    event=event
+                )
 
-                    node_finish_resp = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
-                        session=session,
-                        event=event,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_node_execution=workflow_node_execution,
-                    )
-                    session.commit()
+                node_finish_resp = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
+                    event=event,
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_node_execution=workflow_node_execution,
+                )
 
                 if node_finish_resp:
                     yield node_finish_resp

api/core/app/apps/base_app_generator.py

@@ -17,6 +17,7 @@ class BaseAppGenerator:
         user_inputs: Optional[Mapping[str, Any]],
         variables: Sequence["VariableEntity"],
         tenant_id: str,
+        strict_type_validation: bool = False,
     ) -> Mapping[str, Any]:
         user_inputs = user_inputs or {}
         # Filter input variables from form configuration, handle required fields, default values, and option values
@@ -37,6 +38,7 @@ class BaseAppGenerator:
                     allowed_file_extensions=entity_dictionary[k].allowed_file_extensions,
                     allowed_file_upload_methods=entity_dictionary[k].allowed_file_upload_methods,
                 ),
+                strict_type_validation=strict_type_validation,
             )
             for k, v in user_inputs.items()
             if isinstance(v, dict) and entity_dictionary[k].type == VariableEntityType.FILE

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

@@ -92,6 +92,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
             mappings=files,
             tenant_id=app_model.tenant_id,
             config=file_extra_config,
+            strict_type_validation=True if invoke_from == InvokeFrom.SERVICE_API else False,
         )
 
         # convert to app config
@@ -114,7 +115,10 @@ class WorkflowAppGenerator(BaseAppGenerator):
             app_config=app_config,
             file_upload_config=file_extra_config,
             inputs=self._prepare_user_inputs(
-                user_inputs=inputs, variables=app_config.variables, tenant_id=app_model.tenant_id
+                user_inputs=inputs,
+                variables=app_config.variables,
+                tenant_id=app_model.tenant_id,
+                strict_type_validation=True if invoke_from == InvokeFrom.SERVICE_API else False,
             ),
             files=list(system_files),
             user_id=user.id,

api/core/app/apps/workflow/generate_task_pipeline.py

@@ -279,10 +279,9 @@ class WorkflowAppGenerateTaskPipeline:
                         session=session, workflow_run_id=self._workflow_run_id
                     )
                     workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_retried(
-                        session=session, workflow_run=workflow_run, event=event
+                        workflow_run=workflow_run, event=event
                     )
                     response = self._workflow_cycle_manager._workflow_node_retry_to_stream_response(
-                        session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
                         workflow_node_execution=workflow_node_execution,
@@ -300,10 +299,9 @@ class WorkflowAppGenerateTaskPipeline:
                         session=session, workflow_run_id=self._workflow_run_id
                     )
                     workflow_node_execution = self._workflow_cycle_manager._handle_node_execution_start(
-                        session=session, workflow_run=workflow_run, event=event
+                        workflow_run=workflow_run, event=event
                     )
                     node_start_response = self._workflow_cycle_manager._workflow_node_start_to_stream_response(
-                        session=session,
                         event=event,
                         task_id=self._application_generate_entity.task_id,
                         workflow_node_execution=workflow_node_execution,
@@ -313,17 +311,14 @@ class WorkflowAppGenerateTaskPipeline:
                 if node_start_response:
                     yield node_start_response
             elif isinstance(event, QueueNodeSucceededEvent):
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_success(
-                        session=session, event=event
-                    )
-                    node_success_response = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
-                        session=session,
-                        event=event,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_node_execution=workflow_node_execution,
-                    )
-                    session.commit()
+                workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_success(
+                    event=event
+                )
+                node_success_response = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
+                    event=event,
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_node_execution=workflow_node_execution,
+                )
 
                 if node_success_response:
                     yield node_success_response
@@ -334,18 +329,14 @@ class WorkflowAppGenerateTaskPipeline:
                 | QueueNodeInLoopFailedEvent
                 | QueueNodeExceptionEvent,
             ):
-                with Session(db.engine, expire_on_commit=False) as session:
-                    workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_failed(
-                        session=session,
-                        event=event,
-                    )
-                    node_failed_response = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
-                        session=session,
-                        event=event,
-                        task_id=self._application_generate_entity.task_id,
-                        workflow_node_execution=workflow_node_execution,
-                    )
-                    session.commit()
+                workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_failed(
+                    event=event,
+                )
+                node_failed_response = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
+                    event=event,
+                    task_id=self._application_generate_entity.task_id,
+                    workflow_node_execution=workflow_node_execution,
+                )
 
                 if node_failed_response:
                     yield node_failed_response
@@ -627,6 +618,7 @@ class WorkflowAppGenerateTaskPipeline:
         workflow_app_log.created_by = self._user_id
 
         session.add(workflow_app_log)
+        session.commit()
 
     def _text_chunk_to_stream_response(
         self, text: str, from_variable_selector: Optional[list[str]] = None

api/core/app/task_pipeline/workflow_cycle_manage.py

@@ -6,7 +6,7 @@ from typing import Any, Optional, Union, cast
 from uuid import uuid4
 
 from sqlalchemy import func, select
-from sqlalchemy.orm import Session
+from sqlalchemy.orm import Session, sessionmaker
 
 from core.app.entities.app_invoke_entities import AdvancedChatAppGenerateEntity, InvokeFrom, WorkflowAppGenerateEntity
 from core.app.entities.queue_entities import (
@@ -49,12 +49,14 @@ from core.file import FILE_MODEL_IDENTITY, File
 from core.model_runtime.utils.encoders import jsonable_encoder
 from core.ops.entities.trace_entity import TraceTaskName
 from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
+from core.repository import RepositoryFactory
 from core.tools.tool_manager import ToolManager
 from core.workflow.entities.node_entities import NodeRunMetadataKey
 from core.workflow.enums import SystemVariableKey
 from core.workflow.nodes import NodeType
 from core.workflow.nodes.tool.entities import ToolNodeData
 from core.workflow.workflow_entry import WorkflowEntry
+from extensions.ext_database import db
 from models.account import Account
 from models.enums import CreatedByRole, WorkflowRunTriggeredFrom
 from models.model import EndUser
@@ -80,6 +82,21 @@ class WorkflowCycleManage:
         self._application_generate_entity = application_generate_entity
         self._workflow_system_variables = workflow_system_variables
 
+        # Initialize the session factory and repository
+        # We use the global db engine instead of the session passed to methods
+        # Disable expire_on_commit to avoid the need for merging objects
+        self._session_factory = sessionmaker(bind=db.engine, expire_on_commit=False)
+        self._workflow_node_execution_repository = RepositoryFactory.create_workflow_node_execution_repository(
+            params={
+                "tenant_id": self._application_generate_entity.app_config.tenant_id,
+                "app_id": self._application_generate_entity.app_config.app_id,
+                "session_factory": self._session_factory,
+            }
+        )
+
+        # We'll still keep the cache for backward compatibility and performance
+        # but use the repository for database operations
+
     def _handle_workflow_run_start(
         self,
         *,
@@ -254,19 +271,15 @@ class WorkflowCycleManage:
         workflow_run.finished_at = datetime.now(UTC).replace(tzinfo=None)
         workflow_run.exceptions_count = exceptions_count
 
-        stmt = select(WorkflowNodeExecution.node_execution_id).where(
-            WorkflowNodeExecution.tenant_id == workflow_run.tenant_id,
-            WorkflowNodeExecution.app_id == workflow_run.app_id,
-            WorkflowNodeExecution.workflow_id == workflow_run.workflow_id,
-            WorkflowNodeExecution.triggered_from == WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN.value,
-            WorkflowNodeExecution.workflow_run_id == workflow_run.id,
-            WorkflowNodeExecution.status == WorkflowNodeExecutionStatus.RUNNING.value,
+        # Use the instance repository to find running executions for a workflow run
+        running_workflow_node_executions = self._workflow_node_execution_repository.get_running_executions(
+            workflow_run_id=workflow_run.id
         )
-        ids = session.scalars(stmt).all()
-        # Use self._get_workflow_node_execution here to make sure the cache is updated
-        running_workflow_node_executions = [
-            self._get_workflow_node_execution(session=session, node_execution_id=id) for id in ids if id
-        ]
+
+        # Update the cache with the retrieved executions
+        for execution in running_workflow_node_executions:
+            if execution.node_execution_id:
+                self._workflow_node_executions[execution.node_execution_id] = execution
 
         for workflow_node_execution in running_workflow_node_executions:
             now = datetime.now(UTC).replace(tzinfo=None)
@@ -288,7 +301,7 @@ class WorkflowCycleManage:
         return workflow_run
 
     def _handle_node_execution_start(
-        self, *, session: Session, workflow_run: WorkflowRun, event: QueueNodeStartedEvent
+        self, *, workflow_run: WorkflowRun, event: QueueNodeStartedEvent
     ) -> WorkflowNodeExecution:
         workflow_node_execution = WorkflowNodeExecution()
         workflow_node_execution.id = str(uuid4())
@@ -315,17 +328,14 @@ class WorkflowCycleManage:
         )
         workflow_node_execution.created_at = datetime.now(UTC).replace(tzinfo=None)
 
-        session.add(workflow_node_execution)
+        # Use the instance repository to save the workflow node execution
+        self._workflow_node_execution_repository.save(workflow_node_execution)
 
         self._workflow_node_executions[event.node_execution_id] = workflow_node_execution
         return workflow_node_execution
 
-    def _handle_workflow_node_execution_success(
-        self, *, session: Session, event: QueueNodeSucceededEvent
-    ) -> WorkflowNodeExecution:
-        workflow_node_execution = self._get_workflow_node_execution(
-            session=session, node_execution_id=event.node_execution_id
-        )
+    def _handle_workflow_node_execution_success(self, *, event: QueueNodeSucceededEvent) -> WorkflowNodeExecution:
+        workflow_node_execution = self._get_workflow_node_execution(node_execution_id=event.node_execution_id)
         inputs = WorkflowEntry.handle_special_values(event.inputs)
         process_data = WorkflowEntry.handle_special_values(event.process_data)
         outputs = WorkflowEntry.handle_special_values(event.outputs)
@@ -344,13 +354,13 @@ class WorkflowCycleManage:
         workflow_node_execution.finished_at = finished_at
         workflow_node_execution.elapsed_time = elapsed_time
 
-        workflow_node_execution = session.merge(workflow_node_execution)
+        # Use the instance repository to update the workflow node execution
+        self._workflow_node_execution_repository.update(workflow_node_execution)
         return workflow_node_execution
 
     def _handle_workflow_node_execution_failed(
         self,
         *,
-        session: Session,
         event: QueueNodeFailedEvent
         | QueueNodeInIterationFailedEvent
         | QueueNodeInLoopFailedEvent
@@ -361,9 +371,7 @@ class WorkflowCycleManage:
         :param event: queue node failed event
         :return:
         """
-        workflow_node_execution = self._get_workflow_node_execution(
-            session=session, node_execution_id=event.node_execution_id
-        )
+        workflow_node_execution = self._get_workflow_node_execution(node_execution_id=event.node_execution_id)
 
         inputs = WorkflowEntry.handle_special_values(event.inputs)
         process_data = WorkflowEntry.handle_special_values(event.process_data)
@@ -387,14 +395,14 @@ class WorkflowCycleManage:
         workflow_node_execution.elapsed_time = elapsed_time
         workflow_node_execution.execution_metadata = execution_metadata
 
-        workflow_node_execution = session.merge(workflow_node_execution)
         return workflow_node_execution
 
     def _handle_workflow_node_execution_retried(
-        self, *, session: Session, workflow_run: WorkflowRun, event: QueueNodeRetryEvent
+        self, *, workflow_run: WorkflowRun, event: QueueNodeRetryEvent
     ) -> WorkflowNodeExecution:
         """
         Workflow node execution failed
+        :param workflow_run: workflow run
         :param event: queue node failed event
         :return:
         """
@@ -439,15 +447,12 @@ class WorkflowCycleManage:
         workflow_node_execution.execution_metadata = execution_metadata
         workflow_node_execution.index = event.node_run_index
 
-        session.add(workflow_node_execution)
+        # Use the instance repository to save the workflow node execution
+        self._workflow_node_execution_repository.save(workflow_node_execution)
 
         self._workflow_node_executions[event.node_execution_id] = workflow_node_execution
         return workflow_node_execution
 
-    #################################################
-    #             to stream responses               #
-    #################################################
-
     def _workflow_start_to_stream_response(
         self,
         *,
@@ -455,7 +460,6 @@ class WorkflowCycleManage:
         task_id: str,
         workflow_run: WorkflowRun,
     ) -> WorkflowStartStreamResponse:
-        # receive session to make sure the workflow_run won't be expired, need a more elegant way to handle this
         _ = session
         return WorkflowStartStreamResponse(
             task_id=task_id,
@@ -521,14 +525,10 @@ class WorkflowCycleManage:
     def _workflow_node_start_to_stream_response(
         self,
         *,
-        session: Session,
         event: QueueNodeStartedEvent,
         task_id: str,
         workflow_node_execution: WorkflowNodeExecution,
     ) -> Optional[NodeStartStreamResponse]:
-        # receive session to make sure the workflow_run won't be expired, need a more elegant way to handle this
-        _ = session
-
         if workflow_node_execution.node_type in {NodeType.ITERATION.value, NodeType.LOOP.value}:
             return None
         if not workflow_node_execution.workflow_run_id:
@@ -571,7 +571,6 @@ class WorkflowCycleManage:
     def _workflow_node_finish_to_stream_response(
         self,
         *,
-        session: Session,
         event: QueueNodeSucceededEvent
         | QueueNodeFailedEvent
         | QueueNodeInIterationFailedEvent
@@ -580,8 +579,6 @@ class WorkflowCycleManage:
         task_id: str,
         workflow_node_execution: WorkflowNodeExecution,
     ) -> Optional[NodeFinishStreamResponse]:
-        # receive session to make sure the workflow_run won't be expired, need a more elegant way to handle this
-        _ = session
         if workflow_node_execution.node_type in {NodeType.ITERATION.value, NodeType.LOOP.value}:
             return None
         if not workflow_node_execution.workflow_run_id:
@@ -621,13 +618,10 @@ class WorkflowCycleManage:
     def _workflow_node_retry_to_stream_response(
         self,
         *,
-        session: Session,
         event: QueueNodeRetryEvent,
         task_id: str,
         workflow_node_execution: WorkflowNodeExecution,
     ) -> Optional[Union[NodeRetryStreamResponse, NodeFinishStreamResponse]]:
-        # receive session to make sure the workflow_run won't be expired, need a more elegant way to handle this
-        _ = session
         if workflow_node_execution.node_type in {NodeType.ITERATION.value, NodeType.LOOP.value}:
             return None
         if not workflow_node_execution.workflow_run_id:
@@ -668,7 +662,6 @@ class WorkflowCycleManage:
     def _workflow_parallel_branch_start_to_stream_response(
         self, *, session: Session, task_id: str, workflow_run: WorkflowRun, event: QueueParallelBranchRunStartedEvent
     ) -> ParallelBranchStartStreamResponse:
-        # receive session to make sure the workflow_run won't be expired, need a more elegant way to handle this
         _ = session
         return ParallelBranchStartStreamResponse(
             task_id=task_id,
@@ -692,7 +685,6 @@ class WorkflowCycleManage:
         workflow_run: WorkflowRun,
         event: QueueParallelBranchRunSucceededEvent | QueueParallelBranchRunFailedEvent,
     ) -> ParallelBranchFinishedStreamResponse:
-        # receive session to make sure the workflow_run won't be expired, need a more elegant way to handle this
         _ = session
         return ParallelBranchFinishedStreamResponse(
             task_id=task_id,
@@ -713,7 +705,6 @@ class WorkflowCycleManage:
     def _workflow_iteration_start_to_stream_response(
         self, *, session: Session, task_id: str, workflow_run: WorkflowRun, event: QueueIterationStartEvent
     ) -> IterationNodeStartStreamResponse:
-        # receive session to make sure the workflow_run won't be expired, need a more elegant way to handle this
         _ = session
         return IterationNodeStartStreamResponse(
             task_id=task_id,
@@ -735,7 +726,6 @@ class WorkflowCycleManage:
     def _workflow_iteration_next_to_stream_response(
         self, *, session: Session, task_id: str, workflow_run: WorkflowRun, event: QueueIterationNextEvent
     ) -> IterationNodeNextStreamResponse:
-        # receive session to make sure the workflow_run won't be expired, need a more elegant way to handle this
         _ = session
         return IterationNodeNextStreamResponse(
             task_id=task_id,
@@ -759,7 +749,6 @@ class WorkflowCycleManage:
     def _workflow_iteration_completed_to_stream_response(
         self, *, session: Session, task_id: str, workflow_run: WorkflowRun, event: QueueIterationCompletedEvent
     ) -> IterationNodeCompletedStreamResponse:
-        # receive session to make sure the workflow_run won't be expired, need a more elegant way to handle this
         _ = session
         return IterationNodeCompletedStreamResponse(
             task_id=task_id,
@@ -790,7 +779,6 @@ class WorkflowCycleManage:
     def _workflow_loop_start_to_stream_response(
         self, *, session: Session, task_id: str, workflow_run: WorkflowRun, event: QueueLoopStartEvent
     ) -> LoopNodeStartStreamResponse:
-        # receive session to make sure the workflow_run won't be expired, need a more elegant way to handle this
         _ = session
         return LoopNodeStartStreamResponse(
             task_id=task_id,
@@ -812,7 +800,6 @@ class WorkflowCycleManage:
     def _workflow_loop_next_to_stream_response(
         self, *, session: Session, task_id: str, workflow_run: WorkflowRun, event: QueueLoopNextEvent
     ) -> LoopNodeNextStreamResponse:
-        # receive session to make sure the workflow_run won't be expired, need a more elegant way to handle this
         _ = session
         return LoopNodeNextStreamResponse(
             task_id=task_id,
@@ -836,7 +823,6 @@ class WorkflowCycleManage:
     def _workflow_loop_completed_to_stream_response(
         self, *, session: Session, task_id: str, workflow_run: WorkflowRun, event: QueueLoopCompletedEvent
     ) -> LoopNodeCompletedStreamResponse:
-        # receive session to make sure the workflow_run won't be expired, need a more elegant way to handle this
         _ = session
         return LoopNodeCompletedStreamResponse(
             task_id=task_id,
@@ -934,11 +920,22 @@ class WorkflowCycleManage:
 
         return workflow_run
 
-    def _get_workflow_node_execution(self, session: Session, node_execution_id: str) -> WorkflowNodeExecution:
-        if node_execution_id not in self._workflow_node_executions:
+    def _get_workflow_node_execution(self, node_execution_id: str) -> WorkflowNodeExecution:
+        # First check the cache for performance
+        if node_execution_id in self._workflow_node_executions:
+            cached_execution = self._workflow_node_executions[node_execution_id]
+            # No need to merge with session since expire_on_commit=False
+            return cached_execution
+
+        # If not in cache, use the instance repository to get by node_execution_id
+        execution = self._workflow_node_execution_repository.get_by_node_execution_id(node_execution_id)
+
+        if not execution:
             raise ValueError(f"Workflow node execution not found: {node_execution_id}")
-        cached_workflow_node_execution = self._workflow_node_executions[node_execution_id]
-        return session.merge(cached_workflow_node_execution)
+
+        # Update cache
+        self._workflow_node_executions[node_execution_id] = execution
+        return execution
 
     def _handle_agent_log(self, task_id: str, event: QueueAgentLogEvent) -> AgentLogStreamResponse:
         """

api/core/callback_handler/index_tool_callback_handler.py

@@ -6,7 +6,6 @@ from core.rag.models.document import Document
 from extensions.ext_database import db
 from models.dataset import ChildChunk, DatasetQuery, DocumentSegment
 from models.dataset import Document as DatasetDocument
-from models.model import DatasetRetrieverResource
 
 
 class DatasetIndexToolCallbackHandler:
@@ -71,29 +70,6 @@ class DatasetIndexToolCallbackHandler:
 
     def return_retriever_resource_info(self, resource: list):
         """Handle return_retriever_resource_info."""
-        if resource and len(resource) > 0:
-            for item in resource:
-                dataset_retriever_resource = DatasetRetrieverResource(
-                    message_id=self._message_id,
-                    position=item.get("position") or 0,
-                    dataset_id=item.get("dataset_id"),
-                    dataset_name=item.get("dataset_name"),
-                    document_id=item.get("document_id"),
-                    document_name=item.get("document_name"),
-                    data_source_type=item.get("data_source_type"),
-                    segment_id=item.get("segment_id"),
-                    score=item.get("score") if "score" in item else None,
-                    hit_count=item.get("hit_count") if "hit_count" in item else None,
-                    word_count=item.get("word_count") if "word_count" in item else None,
-                    segment_position=item.get("segment_position") if "segment_position" in item else None,
-                    index_node_hash=item.get("index_node_hash") if "index_node_hash" in item else None,
-                    content=item.get("content"),
-                    retriever_from=item.get("retriever_from"),
-                    created_by=self._user_id,
-                )
-                db.session.add(dataset_retriever_resource)
-                db.session.commit()
-
         self._queue_manager.publish(
             QueueRetrieverResourcesEvent(retriever_resources=resource), PublishFrom.APPLICATION_MANAGER
         )

api/core/helper/ssrf_proxy.py

@@ -48,25 +48,26 @@ def make_request(method, url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs):
             write=dify_config.SSRF_DEFAULT_WRITE_TIME_OUT,
         )
 
+    if "ssl_verify" not in kwargs:
+        kwargs["ssl_verify"] = HTTP_REQUEST_NODE_SSL_VERIFY
+
+    ssl_verify = kwargs.pop("ssl_verify")
+
     retries = 0
     while retries <= max_retries:
         try:
             if dify_config.SSRF_PROXY_ALL_URL:
-                with httpx.Client(proxy=dify_config.SSRF_PROXY_ALL_URL, verify=HTTP_REQUEST_NODE_SSL_VERIFY) as client:
+                with httpx.Client(proxy=dify_config.SSRF_PROXY_ALL_URL, verify=ssl_verify) as client:
                     response = client.request(method=method, url=url, **kwargs)
             elif dify_config.SSRF_PROXY_HTTP_URL and dify_config.SSRF_PROXY_HTTPS_URL:
                 proxy_mounts = {
-                    "http://": httpx.HTTPTransport(
-                        proxy=dify_config.SSRF_PROXY_HTTP_URL, verify=HTTP_REQUEST_NODE_SSL_VERIFY
-                    ),
-                    "https://": httpx.HTTPTransport(
-                        proxy=dify_config.SSRF_PROXY_HTTPS_URL, verify=HTTP_REQUEST_NODE_SSL_VERIFY
-                    ),
+                    "http://": httpx.HTTPTransport(proxy=dify_config.SSRF_PROXY_HTTP_URL, verify=ssl_verify),
+                    "https://": httpx.HTTPTransport(proxy=dify_config.SSRF_PROXY_HTTPS_URL, verify=ssl_verify),
                 }
-                with httpx.Client(mounts=proxy_mounts, verify=HTTP_REQUEST_NODE_SSL_VERIFY) as client:
+                with httpx.Client(mounts=proxy_mounts, verify=ssl_verify) as client:
                     response = client.request(method=method, url=url, **kwargs)
             else:
-                with httpx.Client(verify=HTTP_REQUEST_NODE_SSL_VERIFY) as client:
+                with httpx.Client(verify=ssl_verify) as client:
                     response = client.request(method=method, url=url, **kwargs)
 
             if response.status_code not in STATUS_FORCELIST:

api/core/llm_generator/llm_generator.py

@@ -10,6 +10,7 @@ from core.llm_generator.prompts import (
     GENERATOR_QA_PROMPT,
     JAVASCRIPT_CODE_GENERATOR_PROMPT_TEMPLATE,
     PYTHON_CODE_GENERATOR_PROMPT_TEMPLATE,
+    SYSTEM_STRUCTURED_OUTPUT_GENERATE,
     WORKFLOW_RULE_CONFIG_PROMPT_GENERATE_TEMPLATE,
 )
 from core.model_manager import ModelManager
@@ -340,3 +341,37 @@ class LLMGenerator:
 
         answer = cast(str, response.message.content)
         return answer.strip()
+
+    @classmethod
+    def generate_structured_output(cls, tenant_id: str, instruction: str, model_config: dict):
+        model_manager = ModelManager()
+        model_instance = model_manager.get_model_instance(
+            tenant_id=tenant_id,
+            model_type=ModelType.LLM,
+            provider=model_config.get("provider", ""),
+            model=model_config.get("name", ""),
+        )
+
+        prompt_messages = [
+            SystemPromptMessage(content=SYSTEM_STRUCTURED_OUTPUT_GENERATE),
+            UserPromptMessage(content=instruction),
+        ]
+        model_parameters = model_config.get("model_parameters", {})
+
+        try:
+            response = cast(
+                LLMResult,
+                model_instance.invoke_llm(
+                    prompt_messages=list(prompt_messages), model_parameters=model_parameters, stream=False
+                ),
+            )
+
+            generated_json_schema = cast(str, response.message.content)
+            return {"output": generated_json_schema, "error": ""}
+
+        except InvokeError as e:
+            error = str(e)
+            return {"output": "", "error": f"Failed to generate JSON Schema. Error: {error}"}
+        except Exception as e:
+            logging.exception(f"Failed to invoke LLM model, model: {model_config.get('name')}")
+            return {"output": "", "error": f"An unexpected error occurred: {str(e)}"}

api/core/llm_generator/prompts.py

@@ -220,3 +220,110 @@ Here is the task description: {{INPUT_TEXT}}
 
 You just need to generate the output
 """  # noqa: E501
+
+SYSTEM_STRUCTURED_OUTPUT_GENERATE = """
+Your task is to convert simple user descriptions into properly formatted JSON Schema definitions. When a user describes data fields they need, generate a complete, valid JSON Schema that accurately represents those fields with appropriate types and requirements.
+
+## Instructions:
+
+1. Analyze the user's description of their data needs
+2. Identify each property that should be included in the schema
+3. Determine the appropriate data type for each property
+4. Decide which properties should be required
+5. Generate a complete JSON Schema with proper syntax
+6. Include appropriate constraints when specified (min/max values, patterns, formats)
+7. Provide ONLY the JSON Schema without any additional explanations, comments, or markdown formatting.
+8. DO NOT use markdown code blocks (``` or ``` json). Return the raw JSON Schema directly.
+
+## Examples:
+
+### Example 1:
+**User Input:** I need name and age
+**JSON Schema Output:**
+{
+  "type": "object",
+  "properties": {
+    "name": { "type": "string" },
+    "age": { "type": "number" }
+  },
+  "required": ["name", "age"]
+}
+
+### Example 2:
+**User Input:** I want to store information about books including title, author, publication year and optional page count
+**JSON Schema Output:**
+{
+  "type": "object",
+  "properties": {
+    "title": { "type": "string" },
+    "author": { "type": "string" },
+    "publicationYear": { "type": "integer" },
+    "pageCount": { "type": "integer" }
+  },
+  "required": ["title", "author", "publicationYear"]
+}
+
+### Example 3:
+**User Input:** Create a schema for user profiles with email, password, and age (must be at least 18)
+**JSON Schema Output:**
+{
+  "type": "object",
+  "properties": {
+    "email": { 
+      "type": "string",
+      "format": "email"
+    },
+    "password": { 
+      "type": "string",
+      "minLength": 8
+    },
+    "age": { 
+      "type": "integer",
+      "minimum": 18
+    }
+  },
+  "required": ["email", "password", "age"]
+}
+
+### Example 4:
+**User Input:** I need album schema, the ablum has songs, and each song has name, duration, and artist.
+**JSON Schema Output:**
+{
+    "type": "object",
+    "properties": {
+        "properties": {
+            "songs": {
+                "type": "array",
+                "items": {
+                    "type": "object",
+                    "properties": {
+                        "name": {
+                            "type": "string"
+                        },
+                        "id": {
+                            "type": "string"
+                        },
+                        "duration": {
+                            "type": "string"
+                        },
+                        "aritst": {
+                            "type": "string"
+                        }
+                    },
+                    "required": [
+                        "name",
+                        "id",
+                        "duration",
+                        "aritst"
+                    ]
+                }
+            }
+        }
+    },
+    "required": [
+        "songs"
+    ]
+}
+
+Now, generate a JSON Schema based on my description
+"""  # noqa: E501

api/core/memory/token_buffer_memory.py

@@ -44,6 +44,7 @@ class TokenBufferMemory:
                 Message.created_at,
                 Message.workflow_run_id,
                 Message.parent_message_id,
+                Message.answer_tokens,
             )
             .filter(
                 Message.conversation_id == self.conversation.id,
@@ -63,7 +64,7 @@ class TokenBufferMemory:
         thread_messages = extract_thread_messages(messages)
 
         # for newly created message, its answer is temporarily empty, we don't need to add it to memory
-        if thread_messages and not thread_messages[0].answer:
+        if thread_messages and not thread_messages[0].answer and thread_messages[0].answer_tokens == 0:
             thread_messages.pop(0)
 
         messages = list(reversed(thread_messages))

api/core/model_runtime/entities/model_entities.py

@@ -2,7 +2,7 @@ from decimal import Decimal
 from enum import Enum, StrEnum
 from typing import Any, Optional
 
-from pydantic import BaseModel, ConfigDict
+from pydantic import BaseModel, ConfigDict, model_validator
 
 from core.model_runtime.entities.common_entities import I18nObject
 
@@ -85,6 +85,7 @@ class ModelFeature(Enum):
     DOCUMENT = "document"
     VIDEO = "video"
     AUDIO = "audio"
+    STRUCTURED_OUTPUT = "structured-output"
 
 
 class DefaultParameterName(StrEnum):
@@ -197,6 +198,19 @@ class AIModelEntity(ProviderModel):
     parameter_rules: list[ParameterRule] = []
     pricing: Optional[PriceConfig] = None
 
+    @model_validator(mode="after")
+    def validate_model(self):
+        supported_schema_keys = ["json_schema"]
+        schema_key = next((rule.name for rule in self.parameter_rules if rule.name in supported_schema_keys), None)
+        if not schema_key:
+            return self
+        if self.features is None:
+            self.features = [ModelFeature.STRUCTURED_OUTPUT]
+        else:
+            if ModelFeature.STRUCTURED_OUTPUT not in self.features:
+                self.features.append(ModelFeature.STRUCTURED_OUTPUT)
+        return self
+
 
 class ModelUsage(BaseModel):
     pass

api/core/model_runtime/model_providers/__base/large_language_model.py

@@ -1,5 +1,6 @@
 import logging
 import time
+import uuid
 from collections.abc import Generator, Sequence
 from typing import Optional, Union
 
@@ -24,6 +25,58 @@ from core.plugin.manager.model import PluginModelManager
 logger = logging.getLogger(__name__)
 
 
+def _gen_tool_call_id() -> str:
+    return f"chatcmpl-tool-{str(uuid.uuid4().hex)}"
+
+
+def _increase_tool_call(
+    new_tool_calls: list[AssistantPromptMessage.ToolCall], existing_tools_calls: list[AssistantPromptMessage.ToolCall]
+):
+    """
+    Merge incremental tool call updates into existing tool calls.
+
+    :param new_tool_calls: List of new tool call deltas to be merged.
+    :param existing_tools_calls: List of existing tool calls to be modified IN-PLACE.
+    """
+
+    def get_tool_call(tool_call_id: str):
+        """
+        Get or create a tool call by ID
+
+        :param tool_call_id: tool call ID
+        :return: existing or new tool call
+        """
+        if not tool_call_id:
+            return existing_tools_calls[-1]
+
+        _tool_call = next((_tool_call for _tool_call in existing_tools_calls if _tool_call.id == tool_call_id), None)
+        if _tool_call is None:
+            _tool_call = AssistantPromptMessage.ToolCall(
+                id=tool_call_id,
+                type="function",
+                function=AssistantPromptMessage.ToolCall.ToolCallFunction(name="", arguments=""),
+            )
+            existing_tools_calls.append(_tool_call)
+
+        return _tool_call
+
+    for new_tool_call in new_tool_calls:
+        # generate ID for tool calls with function name but no ID to track them
+        if new_tool_call.function.name and not new_tool_call.id:
+            new_tool_call.id = _gen_tool_call_id()
+        # get tool call
+        tool_call = get_tool_call(new_tool_call.id)
+        # update tool call
+        if new_tool_call.id:
+            tool_call.id = new_tool_call.id
+        if new_tool_call.type:
+            tool_call.type = new_tool_call.type
+        if new_tool_call.function.name:
+            tool_call.function.name = new_tool_call.function.name
+        if new_tool_call.function.arguments:
+            tool_call.function.arguments += new_tool_call.function.arguments
+
+
 class LargeLanguageModel(AIModel):
     """
     Model class for large language model.
@@ -109,44 +162,13 @@ class LargeLanguageModel(AIModel):
                 system_fingerprint = None
                 tools_calls: list[AssistantPromptMessage.ToolCall] = []
 
-                def increase_tool_call(new_tool_calls: list[AssistantPromptMessage.ToolCall]):
-                    def get_tool_call(tool_name: str):
-                        if not tool_name:
-                            return tools_calls[-1]
-
-                        tool_call = next(
-                            (tool_call for tool_call in tools_calls if tool_call.function.name == tool_name), None
-                        )
-                        if tool_call is None:
-                            tool_call = AssistantPromptMessage.ToolCall(
-                                id="",
-                                type="",
-                                function=AssistantPromptMessage.ToolCall.ToolCallFunction(name=tool_name, arguments=""),
-                            )
-                            tools_calls.append(tool_call)
-
-                        return tool_call
-
-                    for new_tool_call in new_tool_calls:
-                        # get tool call
-                        tool_call = get_tool_call(new_tool_call.function.name)
-                        # update tool call
-                        if new_tool_call.id:
-                            tool_call.id = new_tool_call.id
-                        if new_tool_call.type:
-                            tool_call.type = new_tool_call.type
-                        if new_tool_call.function.name:
-                            tool_call.function.name = new_tool_call.function.name
-                        if new_tool_call.function.arguments:
-                            tool_call.function.arguments += new_tool_call.function.arguments
-
                 for chunk in result:
                     if isinstance(chunk.delta.message.content, str):
                         content += chunk.delta.message.content
                     elif isinstance(chunk.delta.message.content, list):
                         content_list.extend(chunk.delta.message.content)
                     if chunk.delta.message.tool_calls:
-                        increase_tool_call(chunk.delta.message.tool_calls)
+                        _increase_tool_call(chunk.delta.message.tool_calls, tools_calls)
 
                     usage = chunk.delta.usage or LLMUsage.empty_usage()
                     system_fingerprint = chunk.system_fingerprint

api/core/ops/langfuse_trace/langfuse_trace.py

@@ -5,6 +5,7 @@ from datetime import datetime, timedelta
 from typing import Optional
 
 from langfuse import Langfuse  # type: ignore
+from sqlalchemy.orm import sessionmaker
 
 from core.ops.base_trace_instance import BaseTraceInstance
 from core.ops.entities.config_entity import LangfuseConfig
@@ -28,9 +29,9 @@ from core.ops.langfuse_trace.entities.langfuse_trace_entity import (
     UnitEnum,
 )
 from core.ops.utils import filter_none_values
+from core.repository.repository_factory import RepositoryFactory
 from extensions.ext_database import db
 from models.model import EndUser
-from models.workflow import WorkflowNodeExecution
 
 logger = logging.getLogger(__name__)
 
@@ -110,36 +111,18 @@ class LangFuseDataTrace(BaseTraceInstance):
             )
             self.add_trace(langfuse_trace_data=trace_data)
 
-        # through workflow_run_id get all_nodes_execution
-        workflow_nodes_execution_id_records = (
-            db.session.query(WorkflowNodeExecution.id)
-            .filter(WorkflowNodeExecution.workflow_run_id == trace_info.workflow_run_id)
-            .all()
+        # through workflow_run_id get all_nodes_execution using repository
+        session_factory = sessionmaker(bind=db.engine)
+        workflow_node_execution_repository = RepositoryFactory.create_workflow_node_execution_repository(
+            params={"tenant_id": trace_info.tenant_id, "session_factory": session_factory},
         )
 
-        for node_execution_id_record in workflow_nodes_execution_id_records:
-            node_execution = (
-                db.session.query(
-                    WorkflowNodeExecution.id,
-                    WorkflowNodeExecution.tenant_id,
-                    WorkflowNodeExecution.app_id,
-                    WorkflowNodeExecution.title,
-                    WorkflowNodeExecution.node_type,
-                    WorkflowNodeExecution.status,
-                    WorkflowNodeExecution.inputs,
-                    WorkflowNodeExecution.outputs,
-                    WorkflowNodeExecution.created_at,
-                    WorkflowNodeExecution.elapsed_time,
-                    WorkflowNodeExecution.process_data,
-                    WorkflowNodeExecution.execution_metadata,
-                )
-                .filter(WorkflowNodeExecution.id == node_execution_id_record.id)
-                .first()
-            )
-
-            if not node_execution:
-                continue
+        # Get all executions for this workflow run
+        workflow_node_executions = workflow_node_execution_repository.get_by_workflow_run(
+            workflow_run_id=trace_info.workflow_run_id
+        )
 
+        for node_execution in workflow_node_executions:
             node_execution_id = node_execution.id
             tenant_id = node_execution.tenant_id
             app_id = node_execution.app_id

api/core/ops/langsmith_trace/langsmith_trace.py

@@ -7,6 +7,7 @@ from typing import Optional, cast
 
 from langsmith import Client
 from langsmith.schemas import RunBase
+from sqlalchemy.orm import sessionmaker
 
 from core.ops.base_trace_instance import BaseTraceInstance
 from core.ops.entities.config_entity import LangSmithConfig
@@ -27,9 +28,9 @@ from core.ops.langsmith_trace.entities.langsmith_trace_entity import (
     LangSmithRunUpdateModel,
 )
 from core.ops.utils import filter_none_values, generate_dotted_order
+from core.repository.repository_factory import RepositoryFactory
 from extensions.ext_database import db
 from models.model import EndUser, MessageFile
-from models.workflow import WorkflowNodeExecution
 
 logger = logging.getLogger(__name__)
 
@@ -134,36 +135,22 @@ class LangSmithDataTrace(BaseTraceInstance):
 
         self.add_run(langsmith_run)
 
-        # through workflow_run_id get all_nodes_execution
-        workflow_nodes_execution_id_records = (
-            db.session.query(WorkflowNodeExecution.id)
-            .filter(WorkflowNodeExecution.workflow_run_id == trace_info.workflow_run_id)
-            .all()
+        # through workflow_run_id get all_nodes_execution using repository
+        session_factory = sessionmaker(bind=db.engine)
+        workflow_node_execution_repository = RepositoryFactory.create_workflow_node_execution_repository(
+            params={
+                "tenant_id": trace_info.tenant_id,
+                "app_id": trace_info.metadata.get("app_id"),
+                "session_factory": session_factory,
+            },
         )
 
-        for node_execution_id_record in workflow_nodes_execution_id_records:
-            node_execution = (
-                db.session.query(
-                    WorkflowNodeExecution.id,
-                    WorkflowNodeExecution.tenant_id,
-                    WorkflowNodeExecution.app_id,
-                    WorkflowNodeExecution.title,
-                    WorkflowNodeExecution.node_type,
-                    WorkflowNodeExecution.status,
-                    WorkflowNodeExecution.inputs,
-                    WorkflowNodeExecution.outputs,
-                    WorkflowNodeExecution.created_at,
-                    WorkflowNodeExecution.elapsed_time,
-                    WorkflowNodeExecution.process_data,
-                    WorkflowNodeExecution.execution_metadata,
-                )
-                .filter(WorkflowNodeExecution.id == node_execution_id_record.id)
-                .first()
-            )
-
-            if not node_execution:
-                continue
+        # Get all executions for this workflow run
+        workflow_node_executions = workflow_node_execution_repository.get_by_workflow_run(
+            workflow_run_id=trace_info.workflow_run_id
+        )
 
+        for node_execution in workflow_node_executions:
             node_execution_id = node_execution.id
             tenant_id = node_execution.tenant_id
             app_id = node_execution.app_id

api/core/ops/opik_trace/opik_trace.py

@@ -7,6 +7,7 @@ from typing import Optional, cast
 
 from opik import Opik, Trace
 from opik.id_helpers import uuid4_to_uuid7
+from sqlalchemy.orm import sessionmaker
 
 from core.ops.base_trace_instance import BaseTraceInstance
 from core.ops.entities.config_entity import OpikConfig
@@ -21,9 +22,9 @@ from core.ops.entities.trace_entity import (
     TraceTaskName,
     WorkflowTraceInfo,
 )
+from core.repository.repository_factory import RepositoryFactory
 from extensions.ext_database import db
 from models.model import EndUser, MessageFile
-from models.workflow import WorkflowNodeExecution
 
 logger = logging.getLogger(__name__)
 
@@ -147,36 +148,22 @@ class OpikDataTrace(BaseTraceInstance):
             }
             self.add_trace(trace_data)
 
-        # through workflow_run_id get all_nodes_execution
-        workflow_nodes_execution_id_records = (
-            db.session.query(WorkflowNodeExecution.id)
-            .filter(WorkflowNodeExecution.workflow_run_id == trace_info.workflow_run_id)
-            .all()
+        # through workflow_run_id get all_nodes_execution using repository
+        session_factory = sessionmaker(bind=db.engine)
+        workflow_node_execution_repository = RepositoryFactory.create_workflow_node_execution_repository(
+            params={
+                "tenant_id": trace_info.tenant_id,
+                "app_id": trace_info.metadata.get("app_id"),
+                "session_factory": session_factory,
+            },
         )
 
-        for node_execution_id_record in workflow_nodes_execution_id_records:
-            node_execution = (
-                db.session.query(
-                    WorkflowNodeExecution.id,
-                    WorkflowNodeExecution.tenant_id,
-                    WorkflowNodeExecution.app_id,
-                    WorkflowNodeExecution.title,
-                    WorkflowNodeExecution.node_type,
-                    WorkflowNodeExecution.status,
-                    WorkflowNodeExecution.inputs,
-                    WorkflowNodeExecution.outputs,
-                    WorkflowNodeExecution.created_at,
-                    WorkflowNodeExecution.elapsed_time,
-                    WorkflowNodeExecution.process_data,
-                    WorkflowNodeExecution.execution_metadata,
-                )
-                .filter(WorkflowNodeExecution.id == node_execution_id_record.id)
-                .first()
-            )
-
-            if not node_execution:
-                continue
+        # Get all executions for this workflow run
+        workflow_node_executions = workflow_node_execution_repository.get_by_workflow_run(
+            workflow_run_id=trace_info.workflow_run_id
+        )
 
+        for node_execution in workflow_node_executions:
             node_execution_id = node_execution.id
             tenant_id = node_execution.tenant_id
             app_id = node_execution.app_id

api/core/plugin/backwards_invocation/app.py

@@ -2,6 +2,7 @@ from collections.abc import Generator, Mapping
 from typing import Optional, Union
 
 from controllers.service_api.wraps import create_or_update_end_user_for_user_id
+from core.app.app_config.common.parameters_mapping import get_parameters_from_feature_dict
 from core.app.apps.advanced_chat.app_generator import AdvancedChatAppGenerator
 from core.app.apps.agent_chat.app_generator import AgentChatAppGenerator
 from core.app.apps.chat.app_generator import ChatAppGenerator
@@ -15,6 +16,34 @@ from models.model import App, AppMode, EndUser
 
 
 class PluginAppBackwardsInvocation(BaseBackwardsInvocation):
+    @classmethod
+    def fetch_app_info(cls, app_id: str, tenant_id: str) -> Mapping:
+        """
+        Fetch app info
+        """
+        app = cls._get_app(app_id, tenant_id)
+
+        """Retrieve app parameters."""
+        if app.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}:
+            workflow = app.workflow
+            if workflow is None:
+                raise ValueError("unexpected app type")
+
+            features_dict = workflow.features_dict
+            user_input_form = workflow.user_input_form(to_old_structure=True)
+        else:
+            app_model_config = app.app_model_config
+            if app_model_config is None:
+                raise ValueError("unexpected app type")
+
+            features_dict = app_model_config.to_dict()
+
+            user_input_form = features_dict.get("user_input_form", [])
+
+        return {
+            "data": get_parameters_from_feature_dict(features_dict=features_dict, user_input_form=user_input_form),
+        }
+
     @classmethod
     def invoke_app(
         cls,

api/core/plugin/backwards_invocation/node.py

@@ -39,6 +39,7 @@ class PluginNodeBackwardsInvocation(BaseBackwardsInvocation):
         :param query: str
         :return: dict
         """
+        # FIXME(-LAN-): Avoid import service into core
         workflow_service = WorkflowService()
         node_id = "1919810"
         node_data = ParameterExtractorNodeData(
@@ -89,6 +90,7 @@ class PluginNodeBackwardsInvocation(BaseBackwardsInvocation):
         :param query: str
         :return: dict
         """
+        # FIXME(-LAN-): Avoid import service into core
         workflow_service = WorkflowService()
         node_id = "1919810"
         node_data = QuestionClassifierNodeData(

api/core/plugin/entities/request.py

@@ -204,3 +204,11 @@ class RequestRequestUploadFile(BaseModel):
 
     filename: str
     mimetype: str
+
+
+class RequestFetchAppInfo(BaseModel):
+    """
+    Request to fetch app info
+    """
+
+    app_id: str

api/core/provider_manager.py

@@ -124,6 +124,15 @@ class ProviderManager:
 
         # Get All preferred provider types of the workspace
         provider_name_to_preferred_model_provider_records_dict = self._get_all_preferred_model_providers(tenant_id)
+        # Ensure that both the original provider name and its ModelProviderID string representation
+        # are present in the dictionary to handle cases where either form might be used
+        for provider_name in list(provider_name_to_preferred_model_provider_records_dict.keys()):
+            provider_id = ModelProviderID(provider_name)
+            if str(provider_id) not in provider_name_to_preferred_model_provider_records_dict:
+                # Add the ModelProviderID string representation if it's not already present
+                provider_name_to_preferred_model_provider_records_dict[str(provider_id)] = (
+                    provider_name_to_preferred_model_provider_records_dict[provider_name]
+                )
 
         # Get All provider model settings
         provider_name_to_provider_model_settings_dict = self._get_all_provider_model_settings(tenant_id)
@@ -497,8 +506,8 @@ class ProviderManager:
 
     @staticmethod
     def _init_trial_provider_records(
-        tenant_id: str, provider_name_to_provider_records_dict: dict[str, list]
-    ) -> dict[str, list]:
+        tenant_id: str, provider_name_to_provider_records_dict: dict[str, list[Provider]]
+    ) -> dict[str, list[Provider]]:
         """
         Initialize trial provider records if not exists.
 
@@ -532,7 +541,7 @@ class ProviderManager:
                     if ProviderQuotaType.TRIAL not in provider_quota_to_provider_record_dict:
                         try:
                             # FIXME ignore the type errork, onyl TrialHostingQuota has limit need to change the logic
-                            provider_record = Provider(
+                            new_provider_record = Provider(
                                 tenant_id=tenant_id,
                                 # TODO: Use provider name with prefix after the data migration.
                                 provider_name=ModelProviderID(provider_name).provider_name,
@@ -542,11 +551,12 @@ class ProviderManager:
                                 quota_used=0,
                                 is_valid=True,
                             )
-                            db.session.add(provider_record)
+                            db.session.add(new_provider_record)
                             db.session.commit()
+                            provider_name_to_provider_records_dict[provider_name].append(new_provider_record)
                         except IntegrityError:
                             db.session.rollback()
-                            provider_record = (
+                            existed_provider_record = (
                                 db.session.query(Provider)
                                 .filter(
                                     Provider.tenant_id == tenant_id,
@@ -556,11 +566,14 @@ class ProviderManager:
                                 )
                                 .first()
                             )
-                            if provider_record and not provider_record.is_valid:
-                                provider_record.is_valid = True
+                            if not existed_provider_record:
+                                continue
+
+                            if not existed_provider_record.is_valid:
+                                existed_provider_record.is_valid = True
                                 db.session.commit()
 
-                        provider_name_to_provider_records_dict[provider_name].append(provider_record)
+                            provider_name_to_provider_records_dict[provider_name].append(existed_provider_record)
 
         return provider_name_to_provider_records_dict
 

api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py

@@ -246,7 +246,7 @@ class AnalyticdbVectorBySql:
                 ts_rank(to_tsvector, to_tsquery_from_text(%s, 'zh_cn'), 32) AS score
                 FROM {self.table_name}
                 WHERE to_tsvector@@to_tsquery_from_text(%s, 'zh_cn') {where_clause}
-                ORDER BY (score,id) DESC
+                ORDER BY score DESC, id DESC
                 LIMIT {top_k}""",
                 (f"'{query}'", f"'{query}'"),
             )

api/core/rag/datasource/vdb/milvus/milvus_vector.py

@@ -32,6 +32,7 @@ class MilvusConfig(BaseModel):
     batch_size: int = 100  # Batch size for operations
     database: str = "default"  # Database name
     enable_hybrid_search: bool = False  # Flag to enable hybrid search
+    analyzer_params: Optional[str] = None  # Analyzer params
 
     @model_validator(mode="before")
     @classmethod
@@ -58,6 +59,7 @@ class MilvusConfig(BaseModel):
             "user": self.user,
             "password": self.password,
             "db_name": self.database,
+            "analyzer_params": self.analyzer_params,
         }
 
 
@@ -300,14 +302,19 @@ class MilvusVector(BaseVector):
 
                 # Create the text field, enable_analyzer will be set True to support milvus automatically
                 # transfer text to sparse_vector, reference: https://milvus.io/docs/full-text-search.md
-                fields.append(
-                    FieldSchema(
-                        Field.CONTENT_KEY.value,
-                        DataType.VARCHAR,
-                        max_length=65_535,
-                        enable_analyzer=self._hybrid_search_enabled,
-                    )
-                )
+                content_field_kwargs: dict[str, Any] = {
+                    "max_length": 65_535,
+                    "enable_analyzer": self._hybrid_search_enabled,
+                }
+                if (
+                    self._hybrid_search_enabled
+                    and self._client_config.analyzer_params is not None
+                    and self._client_config.analyzer_params.strip()
+                ):
+                    content_field_kwargs["analyzer_params"] = self._client_config.analyzer_params
+
+                fields.append(FieldSchema(Field.CONTENT_KEY.value, DataType.VARCHAR, **content_field_kwargs))
+
                 # Create the primary key field
                 fields.append(FieldSchema(Field.PRIMARY_KEY.value, DataType.INT64, is_primary=True, auto_id=True))
                 # Create the vector field, supports binary or float vectors
@@ -383,5 +390,6 @@ class MilvusVectorFactory(AbstractVectorFactory):
                 password=dify_config.MILVUS_PASSWORD or "",
                 database=dify_config.MILVUS_DATABASE or "",
                 enable_hybrid_search=dify_config.MILVUS_ENABLE_HYBRID_SEARCH or False,
+                analyzer_params=dify_config.MILVUS_ANALYZER_PARAMS or "",
             ),
         )

api/core/rag/extractor/word_extractor.py

@@ -126,9 +126,7 @@ class WordExtractor(BaseExtractor):
 
                 db.session.add(upload_file)
                 db.session.commit()
-                image_map[rel.target_part] = (
-                    f"![image]({dify_config.CONSOLE_API_URL}/files/{upload_file.id}/file-preview)"
-                )
+                image_map[rel.target_part] = f"![image]({dify_config.FILES_URL}/files/{upload_file.id}/file-preview)"
 
         return image_map
 

api/core/rag/splitter/fixed_text_splitter.py

@@ -39,6 +39,12 @@ class EnhanceRecursiveCharacterTextSplitter(RecursiveCharacterTextSplitter):
             else:
                 return [GPT2Tokenizer.get_num_tokens(text) for text in texts]
 
+        def _character_encoder(texts: list[str]) -> list[int]:
+            if not texts:
+                return []
+
+            return [len(text) for text in texts]
+
         if issubclass(cls, TokenTextSplitter):
             extra_kwargs = {
                 "model_name": embedding_model_instance.model if embedding_model_instance else "gpt2",
@@ -47,7 +53,7 @@ class EnhanceRecursiveCharacterTextSplitter(RecursiveCharacterTextSplitter):
             }
             kwargs = {**kwargs, **extra_kwargs}
 
-        return cls(length_function=_token_encoder, **kwargs)
+        return cls(length_function=_character_encoder, **kwargs)
 
 
 class FixedRecursiveCharacterTextSplitter(EnhanceRecursiveCharacterTextSplitter):
@@ -103,7 +109,7 @@ class FixedRecursiveCharacterTextSplitter(EnhanceRecursiveCharacterTextSplitter)
         _good_splits_lengths = []  # cache the lengths of the splits
         _separator = "" if self._keep_separator else separator
         s_lens = self._length_function(splits)
-        if _separator != "":
+        if separator != "":
             for s, s_len in zip(splits, s_lens):
                 if s_len < self._chunk_size:
                     _good_splits.append(s)

api/core/repository/__init__.py

@@ -0,0 +1,15 @@
+"""
+Repository interfaces for data access.
+
+This package contains repository interfaces that define the contract
+for accessing and manipulating data, regardless of the underlying
+storage mechanism.
+"""
+
+from core.repository.repository_factory import RepositoryFactory
+from core.repository.workflow_node_execution_repository import WorkflowNodeExecutionRepository
+
+__all__ = [
+    "RepositoryFactory",
+    "WorkflowNodeExecutionRepository",
+]

api/core/repository/repository_factory.py

@@ -0,0 +1,97 @@
+"""
+Repository factory for creating repository instances.
+
+This module provides a simple factory interface for creating repository instances.
+It does not contain any implementation details or dependencies on specific repositories.
+"""
+
+from collections.abc import Callable, Mapping
+from typing import Any, Literal, Optional, cast
+
+from core.repository.workflow_node_execution_repository import WorkflowNodeExecutionRepository
+
+# Type for factory functions - takes a dict of parameters and returns any repository type
+RepositoryFactoryFunc = Callable[[Mapping[str, Any]], Any]
+
+# Type for workflow node execution factory function
+WorkflowNodeExecutionFactoryFunc = Callable[[Mapping[str, Any]], WorkflowNodeExecutionRepository]
+
+# Repository type literals
+_RepositoryType = Literal["workflow_node_execution"]
+
+
+class RepositoryFactory:
+    """
+    Factory class for creating repository instances.
+
+    This factory delegates the actual repository creation to implementation-specific
+    factory functions that are registered with the factory at runtime.
+    """
+
+    # Dictionary to store factory functions
+    _factory_functions: dict[str, RepositoryFactoryFunc] = {}
+
+    @classmethod
+    def _register_factory(cls, repository_type: _RepositoryType, factory_func: RepositoryFactoryFunc) -> None:
+        """
+        Register a factory function for a specific repository type.
+        This is a private method and should not be called directly.
+
+        Args:
+            repository_type: The type of repository (e.g., 'workflow_node_execution')
+            factory_func: A function that takes parameters and returns a repository instance
+        """
+        cls._factory_functions[repository_type] = factory_func
+
+    @classmethod
+    def _create_repository(cls, repository_type: _RepositoryType, params: Optional[Mapping[str, Any]] = None) -> Any:
+        """
+        Create a new repository instance with the provided parameters.
+        This is a private method and should not be called directly.
+
+        Args:
+            repository_type: The type of repository to create
+            params: A dictionary of parameters to pass to the factory function
+
+        Returns:
+            A new instance of the requested repository
+
+        Raises:
+            ValueError: If no factory function is registered for the repository type
+        """
+        if repository_type not in cls._factory_functions:
+            raise ValueError(f"No factory function registered for repository type '{repository_type}'")
+
+        # Use empty dict if params is None
+        params = params or {}
+
+        return cls._factory_functions[repository_type](params)
+
+    @classmethod
+    def register_workflow_node_execution_factory(cls, factory_func: WorkflowNodeExecutionFactoryFunc) -> None:
+        """
+        Register a factory function for the workflow node execution repository.
+
+        Args:
+            factory_func: A function that takes parameters and returns a WorkflowNodeExecutionRepository instance
+        """
+        cls._register_factory("workflow_node_execution", factory_func)
+
+    @classmethod
+    def create_workflow_node_execution_repository(
+        cls, params: Optional[Mapping[str, Any]] = None
+    ) -> WorkflowNodeExecutionRepository:
+        """
+        Create a new WorkflowNodeExecutionRepository instance with the provided parameters.
+
+        Args:
+            params: A dictionary of parameters to pass to the factory function
+
+        Returns:
+            A new instance of the WorkflowNodeExecutionRepository
+
+        Raises:
+            ValueError: If no factory function is registered for the workflow_node_execution repository type
+        """
+        # We can safely cast here because we've registered a WorkflowNodeExecutionFactoryFunc
+        return cast(WorkflowNodeExecutionRepository, cls._create_repository("workflow_node_execution", params))

api/core/repository/workflow_node_execution_repository.py

@@ -0,0 +1,97 @@
+from collections.abc import Sequence
+from dataclasses import dataclass
+from typing import Literal, Optional, Protocol
+
+from models.workflow import WorkflowNodeExecution
+
+
+@dataclass
+class OrderConfig:
+    """Configuration for ordering WorkflowNodeExecution instances."""
+
+    order_by: list[str]
+    order_direction: Optional[Literal["asc", "desc"]] = None
+
+
+class WorkflowNodeExecutionRepository(Protocol):
+    """
+    Repository interface for WorkflowNodeExecution.
+
+    This interface defines the contract for accessing and manipulating
+    WorkflowNodeExecution data, regardless of the underlying storage mechanism.
+
+    Note: Domain-specific concepts like multi-tenancy (tenant_id), application context (app_id),
+    and trigger sources (triggered_from) should be handled at the implementation level, not in
+    the core interface. This keeps the core domain model clean and independent of specific
+    application domains or deployment scenarios.
+    """
+
+    def save(self, execution: WorkflowNodeExecution) -> None:
+        """
+        Save a WorkflowNodeExecution instance.
+
+        Args:
+            execution: The WorkflowNodeExecution instance to save
+        """
+        ...
+
+    def get_by_node_execution_id(self, node_execution_id: str) -> Optional[WorkflowNodeExecution]:
+        """
+        Retrieve a WorkflowNodeExecution by its node_execution_id.
+
+        Args:
+            node_execution_id: The node execution ID
+
+        Returns:
+            The WorkflowNodeExecution instance if found, None otherwise
+        """
+        ...
+
+    def get_by_workflow_run(
+        self,
+        workflow_run_id: str,
+        order_config: Optional[OrderConfig] = None,
+    ) -> Sequence[WorkflowNodeExecution]:
+        """
+        Retrieve all WorkflowNodeExecution instances for a specific workflow run.
+
+        Args:
+            workflow_run_id: The workflow run ID
+            order_config: Optional configuration for ordering results
+                order_config.order_by: List of fields to order by (e.g., ["index", "created_at"])
+                order_config.order_direction: Direction to order ("asc" or "desc")
+
+        Returns:
+            A list of WorkflowNodeExecution instances
+        """
+        ...
+
+    def get_running_executions(self, workflow_run_id: str) -> Sequence[WorkflowNodeExecution]:
+        """
+        Retrieve all running WorkflowNodeExecution instances for a specific workflow run.
+
+        Args:
+            workflow_run_id: The workflow run ID
+
+        Returns:
+            A list of running WorkflowNodeExecution instances
+        """
+        ...
+
+    def update(self, execution: WorkflowNodeExecution) -> None:
+        """
+        Update an existing WorkflowNodeExecution instance.
+
+        Args:
+            execution: The WorkflowNodeExecution instance to update
+        """
+        ...
+
+    def clear(self) -> None:
+        """
+        Clear all WorkflowNodeExecution records based on implementation-specific criteria.
+
+        This method is intended to be used for bulk deletion operations, such as removing
+        all records associated with a specific app_id and tenant_id in multi-tenant implementations.
+        """
+        ...

api/core/tools/utils/dataset_retriever/dataset_retriever_tool.py

@@ -94,7 +94,7 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool):
                         "title": item.metadata.get("title"),
                         "content": item.page_content,
                     }
-                context_list.append(source)
+                    context_list.append(source)
             for hit_callback in self.hit_callbacks:
                 hit_callback.return_retriever_resource_info(context_list)
 

api/core/workflow/nodes/agent/agent_node.py

@@ -16,7 +16,7 @@ from core.variables.segments import StringSegment
 from core.workflow.entities.node_entities import NodeRunResult
 from core.workflow.entities.variable_pool import VariablePool
 from core.workflow.enums import SystemVariableKey
-from core.workflow.nodes.agent.entities import AgentNodeData, ParamsAutoGenerated
+from core.workflow.nodes.agent.entities import AgentNodeData, AgentOldVersionModelFeatures, ParamsAutoGenerated
 from core.workflow.nodes.base.entities import BaseNodeData
 from core.workflow.nodes.enums import NodeType
 from core.workflow.nodes.event.event import RunCompletedEvent
@@ -251,7 +251,12 @@ class AgentNode(ToolNode):
                                 prompt_message.model_dump(mode="json") for prompt_message in prompt_messages
                             ]
                     value["history_prompt_messages"] = history_prompt_messages
-                    value["entity"] = model_schema.model_dump(mode="json") if model_schema else None
+                    if model_schema:
+                        # remove structured output feature to support old version agent plugin
+                        model_schema = self._remove_unsupported_model_features_for_old_version(model_schema)
+                        value["entity"] = model_schema.model_dump(mode="json")
+                    else:
+                        value["entity"] = None
             result[parameter_name] = value
 
         return result
@@ -348,3 +353,10 @@ class AgentNode(ToolNode):
         )
         model_schema = model_type_instance.get_model_schema(model_name, model_credentials)
         return model_instance, model_schema
+
+    def _remove_unsupported_model_features_for_old_version(self, model_schema: AIModelEntity) -> AIModelEntity:
+        if model_schema.features:
+            for feature in model_schema.features:
+                if feature.value not in AgentOldVersionModelFeatures:
+                    model_schema.features.remove(feature)
+        return model_schema

api/core/workflow/nodes/agent/entities.py

@@ -24,3 +24,18 @@ class AgentNodeData(BaseNodeData):
 class ParamsAutoGenerated(Enum):
     CLOSE = 0
     OPEN = 1
+
+
+class AgentOldVersionModelFeatures(Enum):
+    """
+    Enum class for old SDK version llm feature.
+    """
+
+    TOOL_CALL = "tool-call"
+    MULTI_TOOL_CALL = "multi-tool-call"
+    AGENT_THOUGHT = "agent-thought"
+    VISION = "vision"
+    STREAM_TOOL_CALL = "stream-tool-call"
+    DOCUMENT = "document"
+    VIDEO = "video"
+    AUDIO = "audio"

api/core/workflow/nodes/answer/answer_stream_processor.py

@@ -155,9 +155,28 @@ class AnswerStreamProcessor(StreamProcessor):
         for answer_node_id, route_position in self.route_position.items():
             if answer_node_id not in self.rest_node_ids:
                 continue
-            # exclude current node id
+            # Remove current node id from answer dependencies to support stream output if it is a success branch
             answer_dependencies = self.generate_routes.answer_dependencies
-            if event.node_id in answer_dependencies[answer_node_id]:
+            edge_mapping = self.graph.edge_mapping.get(event.node_id)
+            success_edge = (
+                next(
+                    (
+                        edge
+                        for edge in edge_mapping
+                        if edge.run_condition
+                        and edge.run_condition.type == "branch_identify"
+                        and edge.run_condition.branch_identify == "success-branch"
+                    ),
+                    None,
+                )
+                if edge_mapping
+                else None
+            )
+            if (
+                event.node_id in answer_dependencies[answer_node_id]
+                and success_edge
+                and success_edge.target_node_id == answer_node_id
+            ):
                 answer_dependencies[answer_node_id].remove(event.node_id)
             answer_dependencies_ids = answer_dependencies.get(answer_node_id, [])
             # all depends on answer node id not in rest node ids

api/core/workflow/nodes/http_request/entities.py

@@ -90,6 +90,7 @@ class HttpRequestNodeData(BaseNodeData):
     params: str
     body: Optional[HttpRequestNodeBody] = None
     timeout: Optional[HttpRequestNodeTimeout] = None
+    ssl_verify: Optional[bool] = dify_config.HTTP_REQUEST_NODE_SSL_VERIFY
 
 
 class Response:

api/core/workflow/nodes/http_request/executor.py

@@ -88,6 +88,7 @@ class Executor:
         self.method = node_data.method
         self.auth = node_data.authorization
         self.timeout = timeout
+        self.ssl_verify = node_data.ssl_verify
         self.params = []
         self.headers = {}
         self.content = None
@@ -316,6 +317,7 @@ class Executor:
             "headers": headers,
             "params": self.params,
             "timeout": (self.timeout.connect, self.timeout.read, self.timeout.write),
+            "ssl_verify": self.ssl_verify,
             "follow_redirects": True,
             "max_retries": self.max_retries,
         }

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

@@ -51,6 +51,7 @@ class HttpRequestNode(BaseNode[HttpRequestNodeData]):
                     "max_read_timeout": dify_config.HTTP_REQUEST_MAX_READ_TIMEOUT,
                     "max_write_timeout": dify_config.HTTP_REQUEST_MAX_WRITE_TIMEOUT,
                 },
+                "ssl_verify": dify_config.HTTP_REQUEST_NODE_SSL_VERIFY,
             },
             "retry_config": {
                 "max_retries": dify_config.SSRF_DEFAULT_MAX_RETRIES,

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

@@ -149,7 +149,10 @@ class ListOperatorNode(BaseNode[ListOperatorNodeData]):
     def _extract_slice(
         self, variable: Union[ArrayFileSegment, ArrayNumberSegment, ArrayStringSegment]
     ) -> Union[ArrayFileSegment, ArrayNumberSegment, ArrayStringSegment]:
-        value = int(self.graph_runtime_state.variable_pool.convert_template(self.node_data.extract_by.serial).text) - 1
+        value = int(self.graph_runtime_state.variable_pool.convert_template(self.node_data.extract_by.serial).text)
+        if value < 1:
+            raise ValueError(f"Invalid serial index: must be >= 1, got {value}")
+        value -= 1
         if len(variable.value) > int(value):
             result = variable.value[value]
         else:

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

@@ -65,6 +65,8 @@ class LLMNodeData(BaseNodeData):
     memory: Optional[MemoryConfig] = None
     context: ContextConfig
     vision: VisionConfig = Field(default_factory=VisionConfig)
+    structured_output: dict | None = None
+    structured_output_enabled: bool = False
 
     @field_validator("prompt_config", mode="before")
     @classmethod

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

@@ -4,6 +4,8 @@ from collections.abc import Generator, Mapping, Sequence
 from datetime import UTC, datetime
 from typing import TYPE_CHECKING, Any, Optional, cast
 
+import json_repair
+
 from configs import dify_config
 from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
 from core.entities.model_entities import ModelStatus
@@ -27,7 +29,13 @@ from core.model_runtime.entities.message_entities import (
     SystemPromptMessage,
     UserPromptMessage,
 )
-from core.model_runtime.entities.model_entities import ModelFeature, ModelPropertyKey, ModelType
+from core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    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
 from core.plugin.entities.plugin import ModelProviderID
@@ -57,6 +65,12 @@ from core.workflow.nodes.event import (
     RunRetrieverResourceEvent,
     RunStreamChunkEvent,
 )
+from core.workflow.utils.structured_output.entities import (
+    ResponseFormat,
+    SpecialModelType,
+    SupportStructuredOutputStatus,
+)
+from core.workflow.utils.structured_output.prompt import STRUCTURED_OUTPUT_PROMPT
 from core.workflow.utils.variable_template_parser import VariableTemplateParser
 from extensions.ext_database import db
 from models.model import Conversation
@@ -92,6 +106,12 @@ class LLMNode(BaseNode[LLMNodeData]):
     _node_type = NodeType.LLM
 
     def _run(self) -> Generator[NodeEvent | InNodeEvent, None, None]:
+        def process_structured_output(text: str) -> Optional[dict[str, Any] | list[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 = ""
@@ -130,7 +150,6 @@ class LLMNode(BaseNode[LLMNodeData]):
                 if isinstance(event, RunRetrieverResourceEvent):
                     context = event.context
                     yield event
-
             if context:
                 node_inputs["#context#"] = context
 
@@ -192,7 +211,9 @@ class LLMNode(BaseNode[LLMNodeData]):
                     self.deduct_llm_quota(tenant_id=self.tenant_id, model_instance=model_instance, usage=usage)
                     break
             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
             yield RunCompletedEvent(
                 run_result=NodeRunResult(
                     status=WorkflowNodeExecutionStatus.SUCCEEDED,
@@ -513,7 +534,12 @@ class LLMNode(BaseNode[LLMNodeData]):
 
         if not model_schema:
             raise ModelNotExistError(f"Model {model_name} not exist.")
-
+        support_structured_output = self._check_model_structured_output_support()
+        if support_structured_output == SupportStructuredOutputStatus.SUPPORTED:
+            completion_params = self._handle_native_json_schema(completion_params, model_schema.parameter_rules)
+        elif support_structured_output == SupportStructuredOutputStatus.UNSUPPORTED:
+            # Set appropriate response format based on model capabilities
+            self._set_response_format(completion_params, model_schema.parameter_rules)
         return model_instance, ModelConfigWithCredentialsEntity(
             provider=provider_name,
             model=model_name,
@@ -724,10 +750,29 @@ class LLMNode(BaseNode[LLMNodeData]):
                 "No prompt found in the LLM configuration. "
                 "Please ensure a prompt is properly configured before proceeding."
             )
-
+        support_structured_output = self._check_model_structured_output_support()
+        if support_structured_output == SupportStructuredOutputStatus.UNSUPPORTED:
+            filtered_prompt_messages = self._handle_prompt_based_schema(
+                prompt_messages=filtered_prompt_messages,
+            )
         stop = model_config.stop
         return filtered_prompt_messages, stop
 
+    def _parse_structured_output(self, result_text: str) -> dict[str, Any] | list[Any]:
+        structured_output: dict[str, Any] | list[Any] = {}
+        try:
+            parsed = json.loads(result_text)
+            if not isinstance(parsed, (dict | list)):
+                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 | list)):
+                raise LLMNodeError(f"Failed to parse structured output: {result_text}")
+            structured_output = parsed
+        return structured_output
+
     @classmethod
     def deduct_llm_quota(cls, tenant_id: str, model_instance: ModelInstance, usage: LLMUsage) -> None:
         provider_model_bundle = model_instance.provider_model_bundle
@@ -926,6 +971,166 @@ class LLMNode(BaseNode[LLMNodeData]):
 
         return prompt_messages
 
+    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
+        """
+        model_name = self.node_data.model.name
+        model_manager = ModelManager()
+        model_instance = model_manager.get_model_instance(
+            tenant_id=self.tenant_id, model_type=ModelType.LLM, provider=provider, model=model_name
+        )
+        model_type_instance = model_instance.model_type_instance
+        model_type_instance = cast(LargeLanguageModel, model_type_instance)
+        model_credentials = model_instance.credentials
+        model_schema = model_type_instance.get_model_schema(model_name, model_credentials)
+        return model_schema
+
+    def _fetch_structured_output_schema(self) -> dict[str, Any]:
+        """
+        Fetch the structured output schema from the node data.
+
+        Returns:
+            dict[str, Any]: The structured output schema
+        """
+        if not self.node_data.structured_output:
+            raise LLMNodeError("Please provide a valid structured output schema")
+        structured_output_schema = json.dumps(self.node_data.structured_output.get("schema", {}), ensure_ascii=False)
+        if not structured_output_schema:
+            raise LLMNodeError("Please provide a valid structured output schema")
+
+        try:
+            schema = json.loads(structured_output_schema)
+            if not isinstance(schema, dict):
+                raise LLMNodeError("structured_output_schema must be a JSON object")
+            return schema
+        except json.JSONDecodeError:
+            raise LLMNodeError("structured_output_schema is not valid JSON format")
+
+    def _check_model_structured_output_support(self) -> SupportStructuredOutputStatus:
+        """
+        Check if the current model supports structured output.
+
+        Returns:
+            SupportStructuredOutput: The support status of structured output
+        """
+        # Early return if structured output is disabled
+        if (
+            not isinstance(self.node_data, LLMNodeData)
+            or not self.node_data.structured_output_enabled
+            or not self.node_data.structured_output
+        ):
+            return SupportStructuredOutputStatus.DISABLED
+        # Get model schema and check if it exists
+        model_schema = self._fetch_model_schema(self.node_data.model.provider)
+        if not model_schema:
+            return SupportStructuredOutputStatus.DISABLED
+
+        # Check if model supports structured output feature
+        return (
+            SupportStructuredOutputStatus.SUPPORTED
+            if bool(model_schema.features and ModelFeature.STRUCTURED_OUTPUT in model_schema.features)
+            else SupportStructuredOutputStatus.UNSUPPORTED
+        )
+
 
 def _combine_message_content_with_role(*, contents: Sequence[PromptMessageContent], role: PromptMessageRole):
     match role:
@@ -1064,3 +1269,49 @@ 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

@@ -0,0 +1,24 @@
+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"
+
+
+class SupportStructuredOutputStatus(StrEnum):
+    """Constants for structured output support status"""
+
+    SUPPORTED = "supported"
+    UNSUPPORTED = "unsupported"
+    DISABLED = "disabled"

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

@@ -0,0 +1,17 @@
+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/extensions/ext_logging.py

@@ -26,9 +26,12 @@ def init_app(app: DifyApp):
 
     # Always add StreamHandler to log to console
     sh = logging.StreamHandler(sys.stdout)
-    sh.addFilter(RequestIdFilter())
     log_handlers.append(sh)
 
+    # Apply RequestIdFilter to all handlers
+    for handler in log_handlers:
+        handler.addFilter(RequestIdFilter())
+
     logging.basicConfig(
         level=dify_config.LOG_LEVEL,
         format=dify_config.LOG_FORMAT,

api/extensions/ext_repositories.py

@@ -0,0 +1,18 @@
+"""
+Extension for initializing repositories.
+
+This extension registers repository implementations with the RepositoryFactory.
+"""
+
+from dify_app import DifyApp
+from repositories.repository_registry import register_repositories
+
+
+def init_app(_app: DifyApp) -> None:
+    """
+    Initialize repository implementations.
+
+    Args:
+        _app: The Flask application instance (unused)
+    """
+    register_repositories()

api/extensions/ext_storage.py

@@ -73,11 +73,7 @@ class Storage:
                 raise ValueError(f"unsupported storage type {storage_type}")
 
     def save(self, filename, data):
-        try:
-            self.storage_runner.save(filename, data)
-        except Exception as e:
-            logger.exception(f"Failed to save file {filename}")
-            raise e
+        self.storage_runner.save(filename, data)
 
     @overload
     def load(self, filename: str, /, *, stream: Literal[False] = False) -> bytes: ...
@@ -86,49 +82,25 @@ class Storage:
     def load(self, filename: str, /, *, stream: Literal[True]) -> Generator: ...
 
     def load(self, filename: str, /, *, stream: bool = False) -> Union[bytes, Generator]:
-        try:
-            if stream:
-                return self.load_stream(filename)
-            else:
-                return self.load_once(filename)
-        except Exception as e:
-            logger.exception(f"Failed to load file {filename}")
-            raise e
+        if stream:
+            return self.load_stream(filename)
+        else:
+            return self.load_once(filename)
 
     def load_once(self, filename: str) -> bytes:
-        try:
-            return self.storage_runner.load_once(filename)
-        except Exception as e:
-            logger.exception(f"Failed to load_once file {filename}")
-            raise e
+        return self.storage_runner.load_once(filename)
 
     def load_stream(self, filename: str) -> Generator:
-        try:
-            return self.storage_runner.load_stream(filename)
-        except Exception as e:
-            logger.exception(f"Failed to load_stream file {filename}")
-            raise e
+        return self.storage_runner.load_stream(filename)
 
     def download(self, filename, target_filepath):
-        try:
-            self.storage_runner.download(filename, target_filepath)
-        except Exception as e:
-            logger.exception(f"Failed to download file {filename}")
-            raise e
+        self.storage_runner.download(filename, target_filepath)
 
     def exists(self, filename):
-        try:
-            return self.storage_runner.exists(filename)
-        except Exception as e:
-            logger.exception(f"Failed to check file exists {filename}")
-            raise e
+        return self.storage_runner.exists(filename)
 
     def delete(self, filename):
-        try:
-            return self.storage_runner.delete(filename)
-        except Exception as e:
-            logger.exception(f"Failed to delete file {filename}")
-            raise e
+        return self.storage_runner.delete(filename)
 
 
 storage = Storage()

api/factories/file_factory.py

@@ -52,6 +52,7 @@ def build_from_mapping(
     mapping: Mapping[str, Any],
     tenant_id: str,
     config: FileUploadConfig | None = None,
+    strict_type_validation: bool = False,
 ) -> File:
     transfer_method = FileTransferMethod.value_of(mapping.get("transfer_method"))
 
@@ -69,6 +70,7 @@ def build_from_mapping(
         mapping=mapping,
         tenant_id=tenant_id,
         transfer_method=transfer_method,
+        strict_type_validation=strict_type_validation,
     )
 
     if config and not _is_file_valid_with_config(
@@ -87,12 +89,14 @@ def build_from_mappings(
     mappings: Sequence[Mapping[str, Any]],
     config: FileUploadConfig | None = None,
     tenant_id: str,
+    strict_type_validation: bool = False,
 ) -> Sequence[File]:
     files = [
         build_from_mapping(
             mapping=mapping,
             tenant_id=tenant_id,
             config=config,
+            strict_type_validation=strict_type_validation,
         )
         for mapping in mappings
     ]
@@ -116,6 +120,7 @@ def _build_from_local_file(
     mapping: Mapping[str, Any],
     tenant_id: str,
     transfer_method: FileTransferMethod,
+    strict_type_validation: bool = False,
 ) -> File:
     upload_file_id = mapping.get("upload_file_id")
     if not upload_file_id:
@@ -134,10 +139,16 @@ def _build_from_local_file(
     if row is None:
         raise ValueError("Invalid upload file")
 
-    file_type = _standardize_file_type(extension="." + row.extension, mime_type=row.mime_type)
-    if file_type.value != mapping.get("type", "custom"):
+    detected_file_type = _standardize_file_type(extension="." + row.extension, mime_type=row.mime_type)
+    specified_type = mapping.get("type", "custom")
+
+    if strict_type_validation and detected_file_type.value != specified_type:
         raise ValueError("Detected file type does not match the specified type. Please verify the file.")
 
+    file_type = (
+        FileType(specified_type) if specified_type and specified_type != FileType.CUSTOM.value else detected_file_type
+    )
+
     return File(
         id=mapping.get("id"),
         filename=row.name,
@@ -158,6 +169,7 @@ def _build_from_remote_url(
     mapping: Mapping[str, Any],
     tenant_id: str,
     transfer_method: FileTransferMethod,
+    strict_type_validation: bool = False,
 ) -> File:
     upload_file_id = mapping.get("upload_file_id")
     if upload_file_id:
@@ -174,10 +186,21 @@ def _build_from_remote_url(
         if upload_file is None:
             raise ValueError("Invalid upload file")
 
-        file_type = _standardize_file_type(extension="." + upload_file.extension, mime_type=upload_file.mime_type)
-        if file_type.value != mapping.get("type", "custom"):
+        detected_file_type = _standardize_file_type(
+            extension="." + upload_file.extension, mime_type=upload_file.mime_type
+        )
+
+        specified_type = mapping.get("type")
+
+        if strict_type_validation and specified_type and detected_file_type.value != specified_type:
             raise ValueError("Detected file type does not match the specified type. Please verify the file.")
 
+        file_type = (
+            FileType(specified_type)
+            if specified_type and specified_type != FileType.CUSTOM.value
+            else detected_file_type
+        )
+
         return File(
             id=mapping.get("id"),
             filename=upload_file.name,
@@ -237,6 +260,7 @@ def _build_from_tool_file(
     mapping: Mapping[str, Any],
     tenant_id: str,
     transfer_method: FileTransferMethod,
+    strict_type_validation: bool = False,
 ) -> File:
     tool_file = (
         db.session.query(ToolFile)
@@ -252,7 +276,16 @@ def _build_from_tool_file(
 
     extension = "." + tool_file.file_key.split(".")[-1] if "." in tool_file.file_key else ".bin"
 
-    file_type = _standardize_file_type(extension=extension, mime_type=tool_file.mimetype)
+    detected_file_type = _standardize_file_type(extension="." + extension, mime_type=tool_file.mimetype)
+
+    specified_type = mapping.get("type")
+
+    if strict_type_validation and specified_type and detected_file_type.value != specified_type:
+        raise ValueError("Detected file type does not match the specified type. Please verify the file.")
+
+    file_type = (
+        FileType(specified_type) if specified_type and specified_type != FileType.CUSTOM.value else detected_file_type
+    )
 
     return File(
         id=mapping.get("id"),

api/fields/conversation_fields.py

@@ -42,6 +42,7 @@ message_file_fields = {
     "size": fields.Integer,
     "transfer_method": fields.String,
     "belongs_to": fields.String(default="user"),
+    "upload_file_id": fields.String(default=None),
 }
 
 agent_thought_fields = {

api/models/model.py

@@ -1091,12 +1091,7 @@ class Message(db.Model):  # type: ignore[name-defined]
 
     @property
     def retriever_resources(self):
-        return (
-            db.session.query(DatasetRetrieverResource)
-            .filter(DatasetRetrieverResource.message_id == self.id)
-            .order_by(DatasetRetrieverResource.position.asc())
-            .all()
-        )
+        return self.message_metadata_dict.get("retriever_resources") if self.message_metadata else []
 
     @property
     def message_files(self):
@@ -1155,7 +1150,7 @@ class Message(db.Model):  # type: ignore[name-defined]
             files.append(file)
 
         result = [
-            {"belongs_to": message_file.belongs_to, **file.to_dict()}
+            {"belongs_to": message_file.belongs_to, "upload_file_id": message_file.upload_file_id, **file.to_dict()}
             for (file, message_file) in zip(files, message_files)
         ]
 

api/models/workflow.py

@@ -510,7 +510,7 @@ class WorkflowRun(Base):
         )
 
 
-class WorkflowNodeExecutionTriggeredFrom(Enum):
+class WorkflowNodeExecutionTriggeredFrom(StrEnum):
     """
     Workflow Node Execution Triggered From Enum
     """
@@ -518,21 +518,8 @@ class WorkflowNodeExecutionTriggeredFrom(Enum):
     SINGLE_STEP = "single-step"
     WORKFLOW_RUN = "workflow-run"
 
-    @classmethod
-    def value_of(cls, value: str) -> "WorkflowNodeExecutionTriggeredFrom":
-        """
-        Get value of given mode.
 
-        :param value: mode value
-        :return: mode
-        """
-        for mode in cls:
-            if mode.value == value:
-                return mode
-        raise ValueError(f"invalid workflow node execution triggered from value {value}")
-
-
-class WorkflowNodeExecutionStatus(Enum):
+class WorkflowNodeExecutionStatus(StrEnum):
     """
     Workflow Node Execution Status Enum
     """
@@ -543,19 +530,6 @@ class WorkflowNodeExecutionStatus(Enum):
     EXCEPTION = "exception"
     RETRY = "retry"
 
-    @classmethod
-    def value_of(cls, value: str) -> "WorkflowNodeExecutionStatus":
-        """
-        Get value of given mode.
-
-        :param value: mode value
-        :return: mode
-        """
-        for mode in cls:
-            if mode.value == value:
-                return mode
-        raise ValueError(f"invalid workflow node execution status value {value}")
-
 
 class WorkflowNodeExecution(Base):
     """
@@ -656,6 +630,7 @@ class WorkflowNodeExecution(Base):
     @property
     def created_by_account(self):
         created_by_role = CreatedByRole(self.created_by_role)
+        # TODO(-LAN-): Avoid using db.session.get() here.
         return db.session.get(Account, self.created_by) if created_by_role == CreatedByRole.ACCOUNT else None
 
     @property
@@ -663,6 +638,7 @@ class WorkflowNodeExecution(Base):
         from models.model import EndUser
 
         created_by_role = CreatedByRole(self.created_by_role)
+        # TODO(-LAN-): Avoid using db.session.get() here.
         return db.session.get(EndUser, self.created_by) if created_by_role == CreatedByRole.END_USER else None
 
     @property

api/poetry.toml

@@ -1,4 +0,0 @@
-[virtualenvs]
-in-project = true
-create = true
-prefer-active-python = true

api/pyproject.toml

@@ -30,6 +30,7 @@ dependencies = [
     "gunicorn~=23.0.0",
     "httpx[socks]~=0.27.0",
     "jieba==0.42.1",
+    "json-repair>=0.41.1",
     "langfuse~=2.51.3",
     "langsmith~=0.1.77",
     "mailchimp-transactional~=1.0.50",
@@ -104,6 +105,7 @@ dev = [
     "ruff~=0.11.5",
     "pytest~=8.3.2",
     "pytest-benchmark~=4.0.0",
+    "pytest-cov~=4.1.0",
     "pytest-env~=1.1.3",
     "pytest-mock~=3.14.0",
     "types-aiofiles~=24.1.0",
@@ -162,10 +164,7 @@ storage = [
 ############################################################
 # [ Tools ] dependency group
 ############################################################
-tools = [
-    "cloudscraper~=1.2.71",
-    "nltk~=3.9.1",
-]
+tools = ["cloudscraper~=1.2.71", "nltk~=3.9.1"]
 
 ############################################################
 # [ VDB ] dependency group

api/pytest.ini

@@ -1,5 +1,6 @@
 [pytest]
 continue-on-collection-errors = true
+addopts = --cov=./api --cov-report=json --cov-report=xml
 env =
     ANTHROPIC_API_KEY = sk-ant-api11-IamNotARealKeyJustForMockTestKawaiiiiiiiiii-NotBaka-ASkksz
     AZURE_OPENAI_API_BASE = https://difyai-openai.openai.azure.com

api/repositories/__init__.py

@@ -0,0 +1,6 @@
+"""
+Repository implementations for data access.
+
+This package contains concrete implementations of the repository interfaces
+defined in the core.repository package.
+"""

api/repositories/repository_registry.py

@@ -0,0 +1,87 @@
+"""
+Registry for repository implementations.
+
+This module is responsible for registering factory functions with the repository factory.
+"""
+
+import logging
+from collections.abc import Mapping
+from typing import Any
+
+from sqlalchemy.orm import sessionmaker
+
+from configs import dify_config
+from core.repository.repository_factory import RepositoryFactory
+from extensions.ext_database import db
+from repositories.workflow_node_execution import SQLAlchemyWorkflowNodeExecutionRepository
+
+logger = logging.getLogger(__name__)
+
+# Storage type constants
+STORAGE_TYPE_RDBMS = "rdbms"
+STORAGE_TYPE_HYBRID = "hybrid"
+
+
+def register_repositories() -> None:
+    """
+    Register repository factory functions with the RepositoryFactory.
+
+    This function reads configuration settings to determine which repository
+    implementations to register.
+    """
+    # Configure WorkflowNodeExecutionRepository factory based on configuration
+    workflow_node_execution_storage = dify_config.WORKFLOW_NODE_EXECUTION_STORAGE
+
+    # Check storage type and register appropriate implementation
+    if workflow_node_execution_storage == STORAGE_TYPE_RDBMS:
+        # Register SQLAlchemy implementation for RDBMS storage
+        logger.info("Registering WorkflowNodeExecution repository with RDBMS storage")
+        RepositoryFactory.register_workflow_node_execution_factory(create_workflow_node_execution_repository)
+    elif workflow_node_execution_storage == STORAGE_TYPE_HYBRID:
+        # Hybrid storage is not yet implemented
+        raise NotImplementedError("Hybrid storage for WorkflowNodeExecution repository is not yet implemented")
+    else:
+        # Unknown storage type
+        raise ValueError(
+            f"Unknown storage type '{workflow_node_execution_storage}' for WorkflowNodeExecution repository. "
+            f"Supported types: {STORAGE_TYPE_RDBMS}"
+        )
+
+
+def create_workflow_node_execution_repository(params: Mapping[str, Any]) -> SQLAlchemyWorkflowNodeExecutionRepository:
+    """
+    Create a WorkflowNodeExecutionRepository instance using SQLAlchemy implementation.
+
+    This factory function creates a repository for the RDBMS storage type.
+
+    Args:
+        params: Parameters for creating the repository, including:
+            - tenant_id: Required. The tenant ID for multi-tenancy.
+            - app_id: Optional. The application ID for filtering.
+            - session_factory: Optional. A SQLAlchemy sessionmaker instance. If not provided,
+              a new sessionmaker will be created using the global database engine.
+
+    Returns:
+        A WorkflowNodeExecutionRepository instance
+
+    Raises:
+        ValueError: If required parameters are missing
+    """
+    # Extract required parameters
+    tenant_id = params.get("tenant_id")
+    if tenant_id is None:
+        raise ValueError("tenant_id is required for WorkflowNodeExecution repository with RDBMS storage")
+
+    # Extract optional parameters
+    app_id = params.get("app_id")
+
+    # Use the session_factory from params if provided, otherwise create one using the global db engine
+    session_factory = params.get("session_factory")
+    if session_factory is None:
+        # Create a sessionmaker using the same engine as the global db session
+        session_factory = sessionmaker(bind=db.engine)
+
+    # Create and return the repository
+    return SQLAlchemyWorkflowNodeExecutionRepository(
+        session_factory=session_factory, tenant_id=tenant_id, app_id=app_id
+    )

api/repositories/workflow_node_execution/__init__.py

@@ -0,0 +1,9 @@
+"""
+WorkflowNodeExecution repository implementations.
+"""
+
+from repositories.workflow_node_execution.sqlalchemy_repository import SQLAlchemyWorkflowNodeExecutionRepository
+
+__all__ = [
+    "SQLAlchemyWorkflowNodeExecutionRepository",
+]

api/repositories/workflow_node_execution/sqlalchemy_repository.py

@@ -0,0 +1,192 @@
+"""
+SQLAlchemy implementation of the WorkflowNodeExecutionRepository.
+"""
+
+import logging
+from collections.abc import Sequence
+from typing import Optional
+
+from sqlalchemy import UnaryExpression, asc, delete, desc, select
+from sqlalchemy.engine import Engine
+from sqlalchemy.orm import sessionmaker
+
+from core.repository.workflow_node_execution_repository import OrderConfig
+from models.workflow import WorkflowNodeExecution, WorkflowNodeExecutionStatus, WorkflowNodeExecutionTriggeredFrom
+
+logger = logging.getLogger(__name__)
+
+
+class SQLAlchemyWorkflowNodeExecutionRepository:
+    """
+    SQLAlchemy implementation of the WorkflowNodeExecutionRepository interface.
+
+    This implementation supports multi-tenancy by filtering operations based on tenant_id.
+    Each method creates its own session, handles the transaction, and commits changes
+    to the database. This prevents long-running connections in the workflow core.
+    """
+
+    def __init__(self, session_factory: sessionmaker | Engine, tenant_id: str, app_id: Optional[str] = None):
+        """
+        Initialize the repository with a SQLAlchemy sessionmaker or engine and tenant context.
+
+        Args:
+            session_factory: SQLAlchemy sessionmaker or engine for creating sessions
+            tenant_id: Tenant ID for multi-tenancy
+            app_id: Optional app ID for filtering by application
+        """
+        # If an engine is provided, create a sessionmaker from it
+        if isinstance(session_factory, Engine):
+            self._session_factory = sessionmaker(bind=session_factory, expire_on_commit=False)
+        else:
+            self._session_factory = session_factory
+
+        self._tenant_id = tenant_id
+        self._app_id = app_id
+
+    def save(self, execution: WorkflowNodeExecution) -> None:
+        """
+        Save a WorkflowNodeExecution instance and commit changes to the database.
+
+        Args:
+            execution: The WorkflowNodeExecution instance to save
+        """
+        with self._session_factory() as session:
+            # Ensure tenant_id is set
+            if not execution.tenant_id:
+                execution.tenant_id = self._tenant_id
+
+            # Set app_id if provided and not already set
+            if self._app_id and not execution.app_id:
+                execution.app_id = self._app_id
+
+            session.add(execution)
+            session.commit()
+
+    def get_by_node_execution_id(self, node_execution_id: str) -> Optional[WorkflowNodeExecution]:
+        """
+        Retrieve a WorkflowNodeExecution by its node_execution_id.
+
+        Args:
+            node_execution_id: The node execution ID
+
+        Returns:
+            The WorkflowNodeExecution instance if found, None otherwise
+        """
+        with self._session_factory() as session:
+            stmt = select(WorkflowNodeExecution).where(
+                WorkflowNodeExecution.node_execution_id == node_execution_id,
+                WorkflowNodeExecution.tenant_id == self._tenant_id,
+            )
+
+            if self._app_id:
+                stmt = stmt.where(WorkflowNodeExecution.app_id == self._app_id)
+
+            return session.scalar(stmt)
+
+    def get_by_workflow_run(
+        self,
+        workflow_run_id: str,
+        order_config: Optional[OrderConfig] = None,
+    ) -> Sequence[WorkflowNodeExecution]:
+        """
+        Retrieve all WorkflowNodeExecution instances for a specific workflow run.
+
+        Args:
+            workflow_run_id: The workflow run ID
+            order_config: Optional configuration for ordering results
+                order_config.order_by: List of fields to order by (e.g., ["index", "created_at"])
+                order_config.order_direction: Direction to order ("asc" or "desc")
+
+        Returns:
+            A list of WorkflowNodeExecution instances
+        """
+        with self._session_factory() as session:
+            stmt = select(WorkflowNodeExecution).where(
+                WorkflowNodeExecution.workflow_run_id == workflow_run_id,
+                WorkflowNodeExecution.tenant_id == self._tenant_id,
+                WorkflowNodeExecution.triggered_from == WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN,
+            )
+
+            if self._app_id:
+                stmt = stmt.where(WorkflowNodeExecution.app_id == self._app_id)
+
+            # Apply ordering if provided
+            if order_config and order_config.order_by:
+                order_columns: list[UnaryExpression] = []
+                for field in order_config.order_by:
+                    column = getattr(WorkflowNodeExecution, field, None)
+                    if not column:
+                        continue
+                    if order_config.order_direction == "desc":
+                        order_columns.append(desc(column))
+                    else:
+                        order_columns.append(asc(column))
+
+                if order_columns:
+                    stmt = stmt.order_by(*order_columns)
+
+            return session.scalars(stmt).all()
+
+    def get_running_executions(self, workflow_run_id: str) -> Sequence[WorkflowNodeExecution]:
+        """
+        Retrieve all running WorkflowNodeExecution instances for a specific workflow run.
+
+        Args:
+            workflow_run_id: The workflow run ID
+
+        Returns:
+            A list of running WorkflowNodeExecution instances
+        """
+        with self._session_factory() as session:
+            stmt = select(WorkflowNodeExecution).where(
+                WorkflowNodeExecution.workflow_run_id == workflow_run_id,
+                WorkflowNodeExecution.tenant_id == self._tenant_id,
+                WorkflowNodeExecution.status == WorkflowNodeExecutionStatus.RUNNING,
+                WorkflowNodeExecution.triggered_from == WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN,
+            )
+
+            if self._app_id:
+                stmt = stmt.where(WorkflowNodeExecution.app_id == self._app_id)
+
+            return session.scalars(stmt).all()
+
+    def update(self, execution: WorkflowNodeExecution) -> None:
+        """
+        Update an existing WorkflowNodeExecution instance and commit changes to the database.
+
+        Args:
+            execution: The WorkflowNodeExecution instance to update
+        """
+        with self._session_factory() as session:
+            # Ensure tenant_id is set
+            if not execution.tenant_id:
+                execution.tenant_id = self._tenant_id
+
+            # Set app_id if provided and not already set
+            if self._app_id and not execution.app_id:
+                execution.app_id = self._app_id
+
+            session.merge(execution)
+            session.commit()
+
+    def clear(self) -> None:
+        """
+        Clear all WorkflowNodeExecution records for the current tenant_id and app_id.
+
+        This method deletes all WorkflowNodeExecution records that match the tenant_id
+        and app_id (if provided) associated with this repository instance.
+        """
+        with self._session_factory() as session:
+            stmt = delete(WorkflowNodeExecution).where(WorkflowNodeExecution.tenant_id == self._tenant_id)
+
+            if self._app_id:
+                stmt = stmt.where(WorkflowNodeExecution.app_id == self._app_id)
+
+            result = session.execute(stmt)
+            session.commit()
+
+            deleted_count = result.rowcount
+            logger.info(
+                f"Cleared {deleted_count} workflow node execution records for tenant {self._tenant_id}"
+                + (f" and app {self._app_id}" if self._app_id else "")
+            )

api/services/account_service.py

@@ -407,10 +407,8 @@ class AccountService:
 
             raise PasswordResetRateLimitExceededError()
 
-        code = "".join([str(random.randint(0, 9)) for _ in range(6)])
-        token = TokenManager.generate_token(
-            account=account, email=email, token_type="reset_password", additional_data={"code": code}
-        )
+        code, token = cls.generate_reset_password_token(account_email, account)
+
         send_reset_password_mail_task.delay(
             language=language,
             to=account_email,
@@ -419,6 +417,22 @@ class AccountService:
         cls.reset_password_rate_limiter.increment_rate_limit(account_email)
         return token
 
+    @classmethod
+    def generate_reset_password_token(
+        cls,
+        email: str,
+        account: Optional[Account] = None,
+        code: Optional[str] = None,
+        additional_data: dict[str, Any] = {},
+    ):
+        if not code:
+            code = "".join([str(random.randint(0, 9)) for _ in range(6)])
+        additional_data["code"] = code
+        token = TokenManager.generate_token(
+            account=account, email=email, token_type="reset_password", additional_data=additional_data
+        )
+        return code, token
+
     @classmethod
     def revoke_reset_password_token(cls, token: str):
         TokenManager.revoke_token(token, "reset_password")

api/services/dataset_service.py

@@ -553,7 +553,7 @@ class DocumentService:
                 {"id": "remove_extra_spaces", "enabled": True},
                 {"id": "remove_urls_emails", "enabled": False},
             ],
-            "segmentation": {"delimiter": "\n", "max_tokens": 500, "chunk_overlap": 50},
+            "segmentation": {"delimiter": "\n", "max_tokens": 1024, "chunk_overlap": 50},
         },
         "limits": {
             "indexing_max_segmentation_tokens_length": dify_config.INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH,
@@ -2025,7 +2025,7 @@ class SegmentService:
                 dataset_id=dataset.id,
                 document_id=document.id,
                 segment_id=segment.id,
-                position=max_position + 1,
+                position=max_position + 1 if max_position else 1,
                 index_node_id=index_node_id,
                 index_node_hash=index_node_hash,
                 content=content,
@@ -2175,7 +2175,13 @@ class SegmentService:
 
     @classmethod
     def get_segments(
-        cls, document_id: str, tenant_id: str, status_list: list[str] | None = None, keyword: str | None = None
+        cls,
+        document_id: str,
+        tenant_id: str,
+        status_list: list[str] | None = None,
+        keyword: str | None = None,
+        page: int = 1,
+        limit: int = 20,
     ):
         """Get segments for a document with optional filtering."""
         query = DocumentSegment.query.filter(
@@ -2188,10 +2194,11 @@ class SegmentService:
         if keyword:
             query = query.filter(DocumentSegment.content.ilike(f"%{keyword}%"))
 
-        segments = query.order_by(DocumentSegment.position.asc()).all()
-        total = len(segments)
+        paginated_segments = query.order_by(DocumentSegment.position.asc()).paginate(
+            page=page, per_page=limit, max_per_page=100, error_out=False
+        )
 
-        return segments, total
+        return paginated_segments.items, paginated_segments.total
 
     @classmethod
     def update_segment_by_id(

api/services/plugin/dependencies_analysis.py

@@ -1,3 +1,4 @@
+from configs import dify_config
 from core.helper import marketplace
 from core.plugin.entities.plugin import ModelProviderID, PluginDependency, PluginInstallationSource, ToolProviderID
 from core.plugin.manager.plugin import PluginInstallationManager
@@ -111,6 +112,8 @@ class DependenciesAnalysisService:
         Generate the latest version of dependencies
         """
         dependencies = list(set(dependencies))
+        if not dify_config.MARKETPLACE_ENABLED:
+            return []
         deps = marketplace.batch_fetch_plugin_manifests(dependencies)
         return [
             PluginDependency(

api/services/workflow_run_service.py

@@ -2,13 +2,14 @@ import threading
 from typing import Optional
 
 import contexts
+from core.repository import RepositoryFactory
+from core.repository.workflow_node_execution_repository import OrderConfig
 from extensions.ext_database import db
 from libs.infinite_scroll_pagination import InfiniteScrollPagination
 from models.enums import WorkflowRunTriggeredFrom
 from models.model import App
 from models.workflow import (
     WorkflowNodeExecution,
-    WorkflowNodeExecutionTriggeredFrom,
     WorkflowRun,
 )
 
@@ -127,17 +128,17 @@ class WorkflowRunService:
         if not workflow_run:
             return []
 
-        node_executions = (
-            db.session.query(WorkflowNodeExecution)
-            .filter(
-                WorkflowNodeExecution.tenant_id == app_model.tenant_id,
-                WorkflowNodeExecution.app_id == app_model.id,
-                WorkflowNodeExecution.workflow_id == workflow_run.workflow_id,
-                WorkflowNodeExecution.triggered_from == WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN.value,
-                WorkflowNodeExecution.workflow_run_id == run_id,
-            )
-            .order_by(WorkflowNodeExecution.index.desc())
-            .all()
+        # Use the repository to get the node executions
+        repository = RepositoryFactory.create_workflow_node_execution_repository(
+            params={
+                "tenant_id": app_model.tenant_id,
+                "app_id": app_model.id,
+                "session_factory": db.session.get_bind,
+            }
         )
 
-        return node_executions
+        # Use the repository to get the node executions with ordering
+        order_config = OrderConfig(order_by=["index"], order_direction="desc")
+        node_executions = repository.get_by_workflow_run(workflow_run_id=run_id, order_config=order_config)
+
+        return list(node_executions)

api/services/workflow_service.py

@@ -11,6 +11,7 @@ from sqlalchemy.orm import Session
 from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfigManager
 from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager
 from core.model_runtime.utils.encoders import jsonable_encoder
+from core.repository import RepositoryFactory
 from core.variables import Variable
 from core.workflow.entities.node_entities import NodeRunResult
 from core.workflow.errors import WorkflowNodeRunFailedError
@@ -282,8 +283,15 @@ class WorkflowService:
         workflow_node_execution.created_by = account.id
         workflow_node_execution.workflow_id = draft_workflow.id
 
-        db.session.add(workflow_node_execution)
-        db.session.commit()
+        # Use the repository to save the workflow node execution
+        repository = RepositoryFactory.create_workflow_node_execution_repository(
+            params={
+                "tenant_id": app_model.tenant_id,
+                "app_id": app_model.id,
+                "session_factory": db.session.get_bind,
+            }
+        )
+        repository.save(workflow_node_execution)
 
         return workflow_node_execution
 

api/tasks/remove_app_and_related_data_task.py

@@ -7,6 +7,7 @@ from celery import shared_task  # type: ignore
 from sqlalchemy import delete
 from sqlalchemy.exc import SQLAlchemyError
 
+from core.repository import RepositoryFactory
 from extensions.ext_database import db
 from models.dataset import AppDatasetJoin
 from models.model import (
@@ -30,7 +31,7 @@ from models.model import (
 )
 from models.tools import WorkflowToolProvider
 from models.web import PinnedConversation, SavedMessage
-from models.workflow import ConversationVariable, Workflow, WorkflowAppLog, WorkflowNodeExecution, WorkflowRun
+from models.workflow import ConversationVariable, Workflow, WorkflowAppLog, WorkflowRun
 
 
 @shared_task(queue="app_deletion", bind=True, max_retries=3)
@@ -187,18 +188,20 @@ def _delete_app_workflow_runs(tenant_id: str, app_id: str):
 
 
 def _delete_app_workflow_node_executions(tenant_id: str, app_id: str):
-    def del_workflow_node_execution(workflow_node_execution_id: str):
-        db.session.query(WorkflowNodeExecution).filter(WorkflowNodeExecution.id == workflow_node_execution_id).delete(
-            synchronize_session=False
-        )
-
-    _delete_records(
-        """select id from workflow_node_executions where tenant_id=:tenant_id and app_id=:app_id limit 1000""",
-        {"tenant_id": tenant_id, "app_id": app_id},
-        del_workflow_node_execution,
-        "workflow node execution",
+    # Create a repository instance for WorkflowNodeExecution
+    repository = RepositoryFactory.create_workflow_node_execution_repository(
+        params={
+            "tenant_id": tenant_id,
+            "app_id": app_id,
+            "session_factory": db.session.get_bind,
+        }
     )
 
+    # Use the clear method to delete all records for this tenant_id and app_id
+    repository.clear()
+
+    logging.info(click.style(f"Deleted workflow node executions for tenant {tenant_id} and app {app_id}", fg="green"))
+
 
 def _delete_app_workflow_app_logs(tenant_id: str, app_id: str):
     def del_workflow_app_log(workflow_app_log_id: str):

api/tests/unit_tests/core/model_runtime/__base/test_increase_tool_call.py

@@ -0,0 +1,99 @@
+from unittest.mock import MagicMock, patch
+
+from core.model_runtime.entities.message_entities import AssistantPromptMessage
+from core.model_runtime.model_providers.__base.large_language_model import _increase_tool_call
+
+ToolCall = AssistantPromptMessage.ToolCall
+
+# CASE 1: Single tool call
+INPUTS_CASE_1 = [
+    ToolCall(id="1", type="function", function=ToolCall.ToolCallFunction(name="func_foo", arguments="")),
+    ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="", arguments='{"arg1": ')),
+    ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="", arguments='"value"}')),
+]
+EXPECTED_CASE_1 = [
+    ToolCall(
+        id="1", type="function", function=ToolCall.ToolCallFunction(name="func_foo", arguments='{"arg1": "value"}')
+    ),
+]
+
+# CASE 2: Tool call sequences where IDs are anchored to the first chunk (vLLM/SiliconFlow ...)
+INPUTS_CASE_2 = [
+    ToolCall(id="1", type="function", function=ToolCall.ToolCallFunction(name="func_foo", arguments="")),
+    ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="", arguments='{"arg1": ')),
+    ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="", arguments='"value"}')),
+    ToolCall(id="2", type="function", function=ToolCall.ToolCallFunction(name="func_bar", arguments="")),
+    ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="", arguments='{"arg2": ')),
+    ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="", arguments='"value"}')),
+]
+EXPECTED_CASE_2 = [
+    ToolCall(
+        id="1", type="function", function=ToolCall.ToolCallFunction(name="func_foo", arguments='{"arg1": "value"}')
+    ),
+    ToolCall(
+        id="2", type="function", function=ToolCall.ToolCallFunction(name="func_bar", arguments='{"arg2": "value"}')
+    ),
+]
+
+# CASE 3: Tool call sequences where IDs are anchored to every chunk (SGLang ...)
+INPUTS_CASE_3 = [
+    ToolCall(id="1", type="function", function=ToolCall.ToolCallFunction(name="func_foo", arguments="")),
+    ToolCall(id="1", type="function", function=ToolCall.ToolCallFunction(name="", arguments='{"arg1": ')),
+    ToolCall(id="1", type="function", function=ToolCall.ToolCallFunction(name="", arguments='"value"}')),
+    ToolCall(id="2", type="function", function=ToolCall.ToolCallFunction(name="func_bar", arguments="")),
+    ToolCall(id="2", type="function", function=ToolCall.ToolCallFunction(name="", arguments='{"arg2": ')),
+    ToolCall(id="2", type="function", function=ToolCall.ToolCallFunction(name="", arguments='"value"}')),
+]
+EXPECTED_CASE_3 = [
+    ToolCall(
+        id="1", type="function", function=ToolCall.ToolCallFunction(name="func_foo", arguments='{"arg1": "value"}')
+    ),
+    ToolCall(
+        id="2", type="function", function=ToolCall.ToolCallFunction(name="func_bar", arguments='{"arg2": "value"}')
+    ),
+]
+
+# CASE 4: Tool call sequences with no IDs
+INPUTS_CASE_4 = [
+    ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="func_foo", arguments="")),
+    ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="", arguments='{"arg1": ')),
+    ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="", arguments='"value"}')),
+    ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="func_bar", arguments="")),
+    ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="", arguments='{"arg2": ')),
+    ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="", arguments='"value"}')),
+]
+EXPECTED_CASE_4 = [
+    ToolCall(
+        id="RANDOM_ID_1",
+        type="function",
+        function=ToolCall.ToolCallFunction(name="func_foo", arguments='{"arg1": "value"}'),
+    ),
+    ToolCall(
+        id="RANDOM_ID_2",
+        type="function",
+        function=ToolCall.ToolCallFunction(name="func_bar", arguments='{"arg2": "value"}'),
+    ),
+]
+
+
+def _run_case(inputs: list[ToolCall], expected: list[ToolCall]):
+    actual = []
+    _increase_tool_call(inputs, actual)
+    assert actual == expected
+
+
+def test__increase_tool_call():
+    # case 1:
+    _run_case(INPUTS_CASE_1, EXPECTED_CASE_1)
+
+    # case 2:
+    _run_case(INPUTS_CASE_2, EXPECTED_CASE_2)
+
+    # case 3:
+    _run_case(INPUTS_CASE_3, EXPECTED_CASE_3)
+
+    # case 4:
+    mock_id_generator = MagicMock()
+    mock_id_generator.side_effect = [_exp_case.id for _exp_case in EXPECTED_CASE_4]
+    with patch("core.model_runtime.model_providers.__base.large_language_model._gen_tool_call_id", mock_id_generator):
+        _run_case(INPUTS_CASE_4, EXPECTED_CASE_4)

api/tests/unit_tests/core/workflow/nodes/test_continue_on_error.py

@@ -1,14 +1,20 @@
+from unittest.mock import patch
+
 from core.app.entities.app_invoke_entities import InvokeFrom
+from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult
 from core.workflow.enums import SystemVariableKey
 from core.workflow.graph_engine.entities.event import (
     GraphRunPartialSucceededEvent,
     NodeRunExceptionEvent,
+    NodeRunFailedEvent,
     NodeRunStreamChunkEvent,
 )
 from core.workflow.graph_engine.entities.graph import Graph
 from core.workflow.graph_engine.graph_engine import GraphEngine
+from core.workflow.nodes.event.event import RunCompletedEvent, RunStreamChunkEvent
+from core.workflow.nodes.llm.node import LLMNode
 from models.enums import UserFrom
-from models.workflow import WorkflowType
+from models.workflow import WorkflowNodeExecutionStatus, WorkflowType
 
 
 class ContinueOnErrorTestHelper:
@@ -492,10 +498,7 @@ def test_no_node_in_fail_branch_continue_on_error():
         "edges": FAIL_BRANCH_EDGES[:-1],
         "nodes": [
             {"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
-            {
-                "data": {"title": "success", "type": "answer", "answer": "HTTP request successful"},
-                "id": "success",
-            },
+            {"data": {"title": "success", "type": "answer", "answer": "HTTP request successful"}, "id": "success"},
             ContinueOnErrorTestHelper.get_http_node(),
         ],
     }
@@ -506,3 +509,47 @@ def test_no_node_in_fail_branch_continue_on_error():
     assert any(isinstance(e, NodeRunExceptionEvent) for e in events)
     assert any(isinstance(e, GraphRunPartialSucceededEvent) and e.outputs == {} for e in events)
     assert sum(1 for e in events if isinstance(e, NodeRunStreamChunkEvent)) == 0
+
+
+def test_stream_output_with_fail_branch_continue_on_error():
+    """Test stream output with fail-branch error strategy"""
+    graph_config = {
+        "edges": FAIL_BRANCH_EDGES,
+        "nodes": [
+            {"data": {"title": "Start", "type": "start", "variables": []}, "id": "start"},
+            {
+                "data": {"title": "success", "type": "answer", "answer": "LLM request successful"},
+                "id": "success",
+            },
+            {
+                "data": {"title": "error", "type": "answer", "answer": "{{#node.text#}}"},
+                "id": "error",
+            },
+            ContinueOnErrorTestHelper.get_llm_node(),
+        ],
+    }
+    graph_engine = ContinueOnErrorTestHelper.create_test_graph_engine(graph_config)
+
+    def llm_generator(self):
+        contents = ["hi", "bye", "good morning"]
+
+        yield RunStreamChunkEvent(chunk_content=contents[0], from_variable_selector=[self.node_id, "text"])
+
+        yield RunCompletedEvent(
+            run_result=NodeRunResult(
+                status=WorkflowNodeExecutionStatus.SUCCEEDED,
+                inputs={},
+                process_data={},
+                outputs={},
+                metadata={
+                    NodeRunMetadataKey.TOTAL_TOKENS: 1,
+                    NodeRunMetadataKey.TOTAL_PRICE: 1,
+                    NodeRunMetadataKey.CURRENCY: "USD",
+                },
+            )
+        )
+
+    with patch.object(LLMNode, "_run", new=llm_generator):
+        events = list(graph_engine.run())
+        assert sum(isinstance(e, NodeRunStreamChunkEvent) for e in events) == 1
+        assert all(not isinstance(e, NodeRunFailedEvent | NodeRunExceptionEvent) for e in events)

api/tests/unit_tests/factories/test_build_from_mapping.py

@@ -0,0 +1,198 @@
+import uuid
+from unittest.mock import MagicMock, patch
+
+import pytest
+from httpx import Response
+
+from factories.file_factory import (
+    File,
+    FileTransferMethod,
+    FileType,
+    FileUploadConfig,
+    build_from_mapping,
+)
+from models import ToolFile, UploadFile
+
+# Test Data
+TEST_TENANT_ID = "test_tenant_id"
+TEST_UPLOAD_FILE_ID = str(uuid.uuid4())
+TEST_TOOL_FILE_ID = str(uuid.uuid4())
+TEST_REMOTE_URL = "http://example.com/test.jpg"
+
+# Test Config
+TEST_CONFIG = FileUploadConfig(
+    allowed_file_types=["image", "document"],
+    allowed_file_extensions=[".jpg", ".pdf"],
+    allowed_file_upload_methods=[FileTransferMethod.LOCAL_FILE, FileTransferMethod.TOOL_FILE],
+    number_limits=10,
+)
+
+
+# Fixtures
+@pytest.fixture
+def mock_upload_file():
+    mock = MagicMock(spec=UploadFile)
+    mock.id = TEST_UPLOAD_FILE_ID
+    mock.tenant_id = TEST_TENANT_ID
+    mock.name = "test.jpg"
+    mock.extension = "jpg"
+    mock.mime_type = "image/jpeg"
+    mock.source_url = TEST_REMOTE_URL
+    mock.size = 1024
+    mock.key = "test_key"
+    with patch("factories.file_factory.db.session.scalar", return_value=mock) as m:
+        yield m
+
+
+@pytest.fixture
+def mock_tool_file():
+    mock = MagicMock(spec=ToolFile)
+    mock.id = TEST_TOOL_FILE_ID
+    mock.tenant_id = TEST_TENANT_ID
+    mock.name = "tool_file.pdf"
+    mock.file_key = "tool_file.pdf"
+    mock.mimetype = "application/pdf"
+    mock.original_url = "http://example.com/tool.pdf"
+    mock.size = 2048
+    with patch("factories.file_factory.db.session.query") as mock_query:
+        mock_query.return_value.filter.return_value.first.return_value = mock
+        yield mock
+
+
+@pytest.fixture
+def mock_http_head():
+    def _mock_response(filename, size, content_type):
+        return Response(
+            status_code=200,
+            headers={
+                "Content-Disposition": f'attachment; filename="{filename}"',
+                "Content-Length": str(size),
+                "Content-Type": content_type,
+            },
+        )
+
+    with patch("factories.file_factory.ssrf_proxy.head") as mock_head:
+        mock_head.return_value = _mock_response("remote_test.jpg", 2048, "image/jpeg")
+        yield mock_head
+
+
+# Helper functions
+def local_file_mapping(file_type="image"):
+    return {
+        "transfer_method": "local_file",
+        "upload_file_id": TEST_UPLOAD_FILE_ID,
+        "type": file_type,
+    }
+
+
+def tool_file_mapping(file_type="document"):
+    return {
+        "transfer_method": "tool_file",
+        "tool_file_id": TEST_TOOL_FILE_ID,
+        "type": file_type,
+    }
+
+
+# Tests
+def test_build_from_mapping_backward_compatibility(mock_upload_file):
+    mapping = local_file_mapping(file_type="image")
+    file = build_from_mapping(mapping=mapping, tenant_id=TEST_TENANT_ID)
+    assert isinstance(file, File)
+    assert file.transfer_method == FileTransferMethod.LOCAL_FILE
+    assert file.type == FileType.IMAGE
+    assert file.related_id == TEST_UPLOAD_FILE_ID
+
+
+@pytest.mark.parametrize(
+    ("file_type", "should_pass", "expected_error"),
+    [
+        ("image", True, None),
+        ("document", False, "Detected file type does not match"),
+    ],
+)
+def test_build_from_local_file_strict_validation(mock_upload_file, file_type, should_pass, expected_error):
+    mapping = local_file_mapping(file_type=file_type)
+    if should_pass:
+        file = build_from_mapping(mapping=mapping, tenant_id=TEST_TENANT_ID, strict_type_validation=True)
+        assert file.type == FileType(file_type)
+    else:
+        with pytest.raises(ValueError, match=expected_error):
+            build_from_mapping(mapping=mapping, tenant_id=TEST_TENANT_ID, strict_type_validation=True)
+
+
+@pytest.mark.parametrize(
+    ("file_type", "should_pass", "expected_error"),
+    [
+        ("document", True, None),
+        ("image", False, "Detected file type does not match"),
+    ],
+)
+def test_build_from_tool_file_strict_validation(mock_tool_file, file_type, should_pass, expected_error):
+    """Strict type validation for tool_file."""
+    mapping = tool_file_mapping(file_type=file_type)
+    if should_pass:
+        file = build_from_mapping(mapping=mapping, tenant_id=TEST_TENANT_ID, strict_type_validation=True)
+        assert file.type == FileType(file_type)
+    else:
+        with pytest.raises(ValueError, match=expected_error):
+            build_from_mapping(mapping=mapping, tenant_id=TEST_TENANT_ID, strict_type_validation=True)
+
+
+def test_build_from_remote_url(mock_http_head):
+    mapping = {
+        "transfer_method": "remote_url",
+        "url": TEST_REMOTE_URL,
+        "type": "image",
+    }
+    file = build_from_mapping(mapping=mapping, tenant_id=TEST_TENANT_ID)
+    assert file.transfer_method == FileTransferMethod.REMOTE_URL
+    assert file.type == FileType.IMAGE
+    assert file.filename == "remote_test.jpg"
+    assert file.size == 2048
+
+
+def test_tool_file_not_found():
+    """Test ToolFile not found in database."""
+    with patch("factories.file_factory.db.session.query") as mock_query:
+        mock_query.return_value.filter.return_value.first.return_value = None
+        mapping = tool_file_mapping()
+        with pytest.raises(ValueError, match=f"ToolFile {TEST_TOOL_FILE_ID} not found"):
+            build_from_mapping(mapping=mapping, tenant_id=TEST_TENANT_ID)
+
+
+def test_local_file_not_found():
+    """Test UploadFile not found in database."""
+    with patch("factories.file_factory.db.session.scalar", return_value=None):
+        mapping = local_file_mapping()
+        with pytest.raises(ValueError, match="Invalid upload file"):
+            build_from_mapping(mapping=mapping, tenant_id=TEST_TENANT_ID)
+
+
+def test_build_without_type_specification(mock_upload_file):
+    """Test the situation where no file type is specified"""
+    mapping = {
+        "transfer_method": "local_file",
+        "upload_file_id": TEST_UPLOAD_FILE_ID,
+        # leave out the type
+    }
+    file = build_from_mapping(mapping=mapping, tenant_id=TEST_TENANT_ID)
+    # It should automatically infer the type as "image" based on the file extension
+    assert file.type == FileType.IMAGE
+
+
+@pytest.mark.parametrize(
+    ("file_type", "should_pass", "expected_error"),
+    [
+        ("image", True, None),
+        ("video", False, "File validation failed"),
+    ],
+)
+def test_file_validation_with_config(mock_upload_file, file_type, should_pass, expected_error):
+    """Test the validation of files and configurations"""
+    mapping = local_file_mapping(file_type=file_type)
+    if should_pass:
+        file = build_from_mapping(mapping=mapping, tenant_id=TEST_TENANT_ID, config=TEST_CONFIG)
+        assert file is not None
+    else:
+        with pytest.raises(ValueError, match=expected_error):
+            build_from_mapping(mapping=mapping, tenant_id=TEST_TENANT_ID, config=TEST_CONFIG)

api/tests/unit_tests/repositories/__init__.py

@@ -0,0 +1,3 @@
+"""
+Unit tests for repositories.
+"""

api/tests/unit_tests/repositories/workflow_node_execution/__init__.py

@@ -0,0 +1,3 @@
+"""
+Unit tests for workflow_node_execution repositories.
+"""

api/tests/unit_tests/repositories/workflow_node_execution/test_sqlalchemy_repository.py

@@ -0,0 +1,178 @@
+"""
+Unit tests for the SQLAlchemy implementation of WorkflowNodeExecutionRepository.
+"""
+
+from unittest.mock import MagicMock
+
+import pytest
+from pytest_mock import MockerFixture
+from sqlalchemy.orm import Session, sessionmaker
+
+from core.repository.workflow_node_execution_repository import OrderConfig
+from models.workflow import WorkflowNodeExecution
+from repositories.workflow_node_execution.sqlalchemy_repository import SQLAlchemyWorkflowNodeExecutionRepository
+
+
+@pytest.fixture
+def session():
+    """Create a mock SQLAlchemy session."""
+    session = MagicMock(spec=Session)
+    # Configure the session to be used as a context manager
+    session.__enter__ = MagicMock(return_value=session)
+    session.__exit__ = MagicMock(return_value=None)
+
+    # Configure the session factory to return the session
+    session_factory = MagicMock(spec=sessionmaker)
+    session_factory.return_value = session
+    return session, session_factory
+
+
+@pytest.fixture
+def repository(session):
+    """Create a repository instance with test data."""
+    _, session_factory = session
+    tenant_id = "test-tenant"
+    app_id = "test-app"
+    return SQLAlchemyWorkflowNodeExecutionRepository(
+        session_factory=session_factory, tenant_id=tenant_id, app_id=app_id
+    )
+
+
+def test_save(repository, session):
+    """Test save method."""
+    session_obj, _ = session
+    # Create a mock execution
+    execution = MagicMock(spec=WorkflowNodeExecution)
+    execution.tenant_id = None
+    execution.app_id = None
+
+    # Call save method
+    repository.save(execution)
+
+    # Assert tenant_id and app_id are set
+    assert execution.tenant_id == repository._tenant_id
+    assert execution.app_id == repository._app_id
+
+    # Assert session.add was called
+    session_obj.add.assert_called_once_with(execution)
+
+
+def test_save_with_existing_tenant_id(repository, session):
+    """Test save method with existing tenant_id."""
+    session_obj, _ = session
+    # Create a mock execution with existing tenant_id
+    execution = MagicMock(spec=WorkflowNodeExecution)
+    execution.tenant_id = "existing-tenant"
+    execution.app_id = None
+
+    # Call save method
+    repository.save(execution)
+
+    # Assert tenant_id is not changed and app_id is set
+    assert execution.tenant_id == "existing-tenant"
+    assert execution.app_id == repository._app_id
+
+    # Assert session.add was called
+    session_obj.add.assert_called_once_with(execution)
+
+
+def test_get_by_node_execution_id(repository, session, mocker: MockerFixture):
+    """Test get_by_node_execution_id method."""
+    session_obj, _ = session
+    # Set up mock
+    mock_select = mocker.patch("repositories.workflow_node_execution.sqlalchemy_repository.select")
+    mock_stmt = mocker.MagicMock()
+    mock_select.return_value = mock_stmt
+    mock_stmt.where.return_value = mock_stmt
+    session_obj.scalar.return_value = mocker.MagicMock(spec=WorkflowNodeExecution)
+
+    # Call method
+    result = repository.get_by_node_execution_id("test-node-execution-id")
+
+    # Assert select was called with correct parameters
+    mock_select.assert_called_once()
+    session_obj.scalar.assert_called_once_with(mock_stmt)
+    assert result is not None
+
+
+def test_get_by_workflow_run(repository, session, mocker: MockerFixture):
+    """Test get_by_workflow_run method."""
+    session_obj, _ = session
+    # Set up mock
+    mock_select = mocker.patch("repositories.workflow_node_execution.sqlalchemy_repository.select")
+    mock_stmt = mocker.MagicMock()
+    mock_select.return_value = mock_stmt
+    mock_stmt.where.return_value = mock_stmt
+    mock_stmt.order_by.return_value = mock_stmt
+    session_obj.scalars.return_value.all.return_value = [mocker.MagicMock(spec=WorkflowNodeExecution)]
+
+    # Call method
+    order_config = OrderConfig(order_by=["index"], order_direction="desc")
+    result = repository.get_by_workflow_run(workflow_run_id="test-workflow-run-id", order_config=order_config)
+
+    # Assert select was called with correct parameters
+    mock_select.assert_called_once()
+    session_obj.scalars.assert_called_once_with(mock_stmt)
+    assert len(result) == 1
+
+
+def test_get_running_executions(repository, session, mocker: MockerFixture):
+    """Test get_running_executions method."""
+    session_obj, _ = session
+    # Set up mock
+    mock_select = mocker.patch("repositories.workflow_node_execution.sqlalchemy_repository.select")
+    mock_stmt = mocker.MagicMock()
+    mock_select.return_value = mock_stmt
+    mock_stmt.where.return_value = mock_stmt
+    session_obj.scalars.return_value.all.return_value = [mocker.MagicMock(spec=WorkflowNodeExecution)]
+
+    # Call method
+    result = repository.get_running_executions("test-workflow-run-id")
+
+    # Assert select was called with correct parameters
+    mock_select.assert_called_once()
+    session_obj.scalars.assert_called_once_with(mock_stmt)
+    assert len(result) == 1
+
+
+def test_update(repository, session):
+    """Test update method."""
+    session_obj, _ = session
+    # Create a mock execution
+    execution = MagicMock(spec=WorkflowNodeExecution)
+    execution.tenant_id = None
+    execution.app_id = None
+
+    # Call update method
+    repository.update(execution)
+
+    # Assert tenant_id and app_id are set
+    assert execution.tenant_id == repository._tenant_id
+    assert execution.app_id == repository._app_id
+
+    # Assert session.merge was called
+    session_obj.merge.assert_called_once_with(execution)
+
+
+def test_clear(repository, session, mocker: MockerFixture):
+    """Test clear method."""
+    session_obj, _ = session
+    # Set up mock
+    mock_delete = mocker.patch("repositories.workflow_node_execution.sqlalchemy_repository.delete")
+    mock_stmt = mocker.MagicMock()
+    mock_delete.return_value = mock_stmt
+    mock_stmt.where.return_value = mock_stmt
+
+    # Mock the execute result with rowcount
+    mock_result = mocker.MagicMock()
+    mock_result.rowcount = 5  # Simulate 5 records deleted
+    session_obj.execute.return_value = mock_result
+
+    # Call method
+    repository.clear()
+
+    # Assert delete was called with correct parameters
+    mock_delete.assert_called_once_with(WorkflowNodeExecution)
+    mock_stmt.where.assert_called()
+    session_obj.execute.assert_called_once_with(mock_stmt)
+    session_obj.commit.assert_called_once()

api/uv.lock

@@ -1,5 +1,4 @@
 version = 1
-revision = 1
 requires-python = ">=3.11, <3.13"
 resolution-markers = [
     "python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy'",
@@ -1012,6 +1011,11 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/b7/00/14b00a0748e9eda26e97be07a63cc911108844004687321ddcc213be956c/coverage-7.2.7-cp312-cp312-win_amd64.whl", hash = "sha256:9e31cb64d7de6b6f09702bb27c02d1904b3aebfca610c12772452c4e6c21a0d3", size = 204347 },
 ]
 
+[package.optional-dependencies]
+toml = [
+    { name = "tomli", marker = "python_full_version <= '3.11'" },
+]
+
 [[package]]
 name = "crc32c"
 version = "2.7.1"
@@ -1173,6 +1177,7 @@ dependencies = [
     { name = "gunicorn" },
     { name = "httpx", extra = ["socks"] },
     { name = "jieba" },
+    { name = "json-repair" },
     { name = "langfuse" },
     { name = "langsmith" },
     { name = "mailchimp-transactional" },
@@ -1234,6 +1239,7 @@ dev = [
     { name = "mypy" },
     { name = "pytest" },
     { name = "pytest-benchmark" },
+    { name = "pytest-cov" },
     { name = "pytest-env" },
     { name = "pytest-mock" },
     { name = "ruff" },
@@ -1340,6 +1346,7 @@ requires-dist = [
     { name = "gunicorn", specifier = "~=23.0.0" },
     { name = "httpx", extras = ["socks"], specifier = "~=0.27.0" },
     { name = "jieba", specifier = "==0.42.1" },
+    { name = "json-repair", specifier = ">=0.41.1" },
     { name = "langfuse", specifier = "~=2.51.3" },
     { name = "langsmith", specifier = "~=0.1.77" },
     { name = "mailchimp-transactional", specifier = "~=1.0.50" },
@@ -1401,6 +1408,7 @@ dev = [
     { name = "mypy", specifier = "~=1.15.0" },
     { name = "pytest", specifier = "~=8.3.2" },
     { name = "pytest-benchmark", specifier = "~=4.0.0" },
+    { name = "pytest-cov", specifier = "~=4.1.0" },
     { name = "pytest-env", specifier = "~=1.1.3" },
     { name = "pytest-mock", specifier = "~=3.14.0" },
     { name = "ruff", specifier = "~=0.11.5" },
@@ -2517,6 +2525,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/91/29/df4b9b42f2be0b623cbd5e2140cafcaa2bef0759a00b7b70104dcfe2fb51/joblib-1.4.2-py3-none-any.whl", hash = "sha256:06d478d5674cbc267e7496a410ee875abd68e4340feff4490bcb7afb88060ae6", size = 301817 },
 ]
 
+[[package]]
+name = "json-repair"
+version = "0.41.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/6d/6a/6c7a75a10da6dc807b582f2449034da1ed74415e8899746bdfff97109012/json_repair-0.41.1.tar.gz", hash = "sha256:bba404b0888c84a6b86ecc02ec43b71b673cfee463baf6da94e079c55b136565", size = 31208 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/10/5c/abd7495c934d9af5c263c2245ae30cfaa716c3c0cf027b2b8fa686ee7bd4/json_repair-0.41.1-py3-none-any.whl", hash = "sha256:0e181fd43a696887881fe19fed23422a54b3e4c558b6ff27a86a8c3ddde9ae79", size = 21578 },
+]
+
 [[package]]
 name = "jsonpath-python"
 version = "1.0.6"
@@ -4067,6 +4084,8 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/af/cd/ed6e429fb0792ce368f66e83246264dd3a7a045b0b1e63043ed22a063ce5/pycryptodome-3.19.1-cp35-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:7c9e222d0976f68d0cf6409cfea896676ddc1d98485d601e9508f90f60e2b0a2", size = 2144914 },
     { url = "https://files.pythonhosted.org/packages/f6/23/b064bd4cfbf2cc5f25afcde0e7c880df5b20798172793137ba4b62d82e72/pycryptodome-3.19.1-cp35-abi3-win32.whl", hash = "sha256:4805e053571140cb37cf153b5c72cd324bb1e3e837cbe590a19f69b6cf85fd03", size = 1713105 },
     { url = "https://files.pythonhosted.org/packages/7d/e0/ded1968a5257ab34216a0f8db7433897a2337d59e6d03be113713b346ea2/pycryptodome-3.19.1-cp35-abi3-win_amd64.whl", hash = "sha256:a470237ee71a1efd63f9becebc0ad84b88ec28e6784a2047684b693f458f41b7", size = 1749222 },
+    { url = "https://files.pythonhosted.org/packages/1d/e3/0c9679cd66cf5604b1f070bdf4525a0c01a15187be287d8348b2eafb718e/pycryptodome-3.19.1-pp27-pypy_73-manylinux2010_x86_64.whl", hash = "sha256:ed932eb6c2b1c4391e166e1a562c9d2f020bfff44a0e1b108f67af38b390ea89", size = 1629005 },
+    { url = "https://files.pythonhosted.org/packages/13/75/0d63bf0daafd0580b17202d8a9dd57f28c8487f26146b3e2799b0c5a059c/pycryptodome-3.19.1-pp27-pypy_73-win32.whl", hash = "sha256:81e9d23c0316fc1b45d984a44881b220062336bbdc340aa9218e8d0656587934", size = 1697997 },
 ]
 
 [[package]]
@@ -4333,6 +4352,19 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/4d/a1/3b70862b5b3f830f0422844f25a823d0470739d994466be9dbbbb414d85a/pytest_benchmark-4.0.0-py3-none-any.whl", hash = "sha256:fdb7db64e31c8b277dff9850d2a2556d8b60bcb0ea6524e36e28ffd7c87f71d6", size = 43951 },
 ]
 
+[[package]]
+name = "pytest-cov"
+version = "4.1.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "coverage", extra = ["toml"] },
+    { name = "pytest" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/7a/15/da3df99fd551507694a9b01f512a2f6cf1254f33601605843c3775f39460/pytest-cov-4.1.0.tar.gz", hash = "sha256:3904b13dfbfec47f003b8e77fd5b589cd11904a21ddf1ab38a64f204d6a10ef6", size = 63245 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a7/4b/8b78d126e275efa2379b1c2e09dc52cf70df16fc3b90613ef82531499d73/pytest_cov-4.1.0-py3-none-any.whl", hash = "sha256:6ba70b9e97e69fcc3fb45bfeab2d0a138fb65c4d0d6a41ef33983ad114be8c3a", size = 21949 },
+]
+
 [[package]]
 name = "pytest-env"
 version = "1.1.5"
@@ -5235,6 +5267,35 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/44/6f/7120676b6d73228c96e17f1f794d8ab046fc910d781c8d151120c3f1569e/toml-0.10.2-py2.py3-none-any.whl", hash = "sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b", size = 16588 },
 ]
 
+[[package]]
+name = "tomli"
+version = "2.2.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/18/87/302344fed471e44a87289cf4967697d07e532f2421fdaf868a303cbae4ff/tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff", size = 17175 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/43/ca/75707e6efa2b37c77dadb324ae7d9571cb424e61ea73fad7c56c2d14527f/tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249", size = 131077 },
+    { url = "https://files.pythonhosted.org/packages/c7/16/51ae563a8615d472fdbffc43a3f3d46588c264ac4f024f63f01283becfbb/tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6", size = 123429 },
+    { url = "https://files.pythonhosted.org/packages/f1/dd/4f6cd1e7b160041db83c694abc78e100473c15d54620083dbd5aae7b990e/tomli-2.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ece47d672db52ac607a3d9599a9d48dcb2f2f735c6c2d1f34130085bb12b112a", size = 226067 },
+    { url = "https://files.pythonhosted.org/packages/a9/6b/c54ede5dc70d648cc6361eaf429304b02f2871a345bbdd51e993d6cdf550/tomli-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6972ca9c9cc9f0acaa56a8ca1ff51e7af152a9f87fb64623e31d5c83700080ee", size = 236030 },
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+]
+
 [[package]]
 name = "tos"
 version = "2.7.2"

docker/.env.example

@@ -174,6 +174,12 @@ CELERY_MIN_WORKERS=
 API_TOOL_DEFAULT_CONNECT_TIMEOUT=10
 API_TOOL_DEFAULT_READ_TIMEOUT=60
 
+# -------------------------------
+# Datasource Configuration
+# --------------------------------
+ENABLE_WEBSITE_JINAREADER=true
+ENABLE_WEBSITE_FIRECRAWL=true
+ENABLE_WEBSITE_WATERCRAWL=true
 
 # ------------------------------
 # Database Configuration
@@ -404,6 +410,7 @@ MILVUS_TOKEN=
 MILVUS_USER=
 MILVUS_PASSWORD=
 MILVUS_ENABLE_HYBRID_SEARCH=False
+MILVUS_ANALYZER_PARAMS=
 
 # MyScale configuration, only available when VECTOR_STORE is `myscale`
 # For multi-language support, please set MYSCALE_FTS_PARAMS with referring to:
@@ -737,6 +744,12 @@ MAX_VARIABLE_SIZE=204800
 WORKFLOW_PARALLEL_DEPTH_LIMIT=3
 WORKFLOW_FILE_UPLOAD_LIMIT=10
 
+# Workflow storage configuration
+# Options: rdbms, hybrid
+# rdbms: Use only the relational database (default)
+# hybrid: Save new data to object storage, read from both object storage and RDBMS
+WORKFLOW_NODE_EXECUTION_STORAGE=rdbms
+
 # HTTP request node in workflow configuration
 HTTP_REQUEST_NODE_MAX_BINARY_SIZE=10485760
 HTTP_REQUEST_NODE_MAX_TEXT_SIZE=1048576

docker/docker-compose-template.yaml

@@ -17,8 +17,10 @@ services:
       PLUGIN_MAX_PACKAGE_SIZE: ${PLUGIN_MAX_PACKAGE_SIZE:-52428800}
       INNER_API_KEY_FOR_PLUGIN: ${PLUGIN_DIFY_INNER_API_KEY:-QaHbTe77CtuXmsfyhR7+vRjI/+XbV1AaFy691iy+kGDv2Jvy0/eAh8Y1}
     depends_on:
-      - db
-      - redis
+      db:
+        condition: service_healthy
+      redis:
+        condition: service_started
     volumes:
       # Mount the storage directory to the container, for storing user files.
       - ./volumes/app/storage:/app/api/storage
@@ -42,8 +44,10 @@ services:
       PLUGIN_MAX_PACKAGE_SIZE: ${PLUGIN_MAX_PACKAGE_SIZE:-52428800}
       INNER_API_KEY_FOR_PLUGIN: ${PLUGIN_DIFY_INNER_API_KEY:-QaHbTe77CtuXmsfyhR7+vRjI/+XbV1AaFy691iy+kGDv2Jvy0/eAh8Y1}
     depends_on:
-      - db
-      - redis
+      db:
+        condition: service_healthy
+      redis:
+        condition: service_started
     volumes:
       # Mount the storage directory to the container, for storing user files.
       - ./volumes/app/storage:/app/api/storage
@@ -71,7 +75,9 @@ services:
       MAX_TOOLS_NUM: ${MAX_TOOLS_NUM:-10}
       MAX_PARALLEL_LIMIT: ${MAX_PARALLEL_LIMIT:-10}
       MAX_ITERATIONS_NUM: ${MAX_ITERATIONS_NUM:-5}
-
+      ENABLE_WEBSITE_JINAREADER: ${ENABLE_WEBSITE_JINAREADER:-true}
+      ENABLE_WEBSITE_FIRECRAWL: ${ENABLE_WEBSITE_FIRECRAWL:-true}
+      ENABLE_WEBSITE_WATERCRAWL: ${ENABLE_WEBSITE_WATERCRAWL:-true}
   # The postgres database.
   db:
     image: postgres:15-alpine
@@ -124,6 +130,7 @@ services:
       HTTP_PROXY: ${SANDBOX_HTTP_PROXY:-http://ssrf_proxy:3128}
       HTTPS_PROXY: ${SANDBOX_HTTPS_PROXY:-http://ssrf_proxy:3128}
       SANDBOX_PORT: ${SANDBOX_PORT:-8194}
+      PIP_MIRROR_URL: ${PIP_MIRROR_URL:-}
     volumes:
       - ./volumes/sandbox/dependencies:/dependencies
       - ./volumes/sandbox/conf:/conf

docker/docker-compose.middleware.yaml

@@ -60,6 +60,7 @@ services:
       HTTP_PROXY: ${SANDBOX_HTTP_PROXY:-http://ssrf_proxy:3128}
       HTTPS_PROXY: ${SANDBOX_HTTPS_PROXY:-http://ssrf_proxy:3128}
       SANDBOX_PORT: ${SANDBOX_PORT:-8194}
+      PIP_MIRROR_URL: ${PIP_MIRROR_URL:-}
     volumes:
       - ./volumes/sandbox/dependencies:/dependencies
       - ./volumes/sandbox/conf:/conf

docker/docker-compose.yaml

@@ -43,6 +43,9 @@ x-shared-env: &shared-api-worker-env
   CELERY_MIN_WORKERS: ${CELERY_MIN_WORKERS:-}
   API_TOOL_DEFAULT_CONNECT_TIMEOUT: ${API_TOOL_DEFAULT_CONNECT_TIMEOUT:-10}
   API_TOOL_DEFAULT_READ_TIMEOUT: ${API_TOOL_DEFAULT_READ_TIMEOUT:-60}
+  ENABLE_WEBSITE_JINAREADER: ${ENABLE_WEBSITE_JINAREADER:-true}
+  ENABLE_WEBSITE_FIRECRAWL: ${ENABLE_WEBSITE_FIRECRAWL:-true}
+  ENABLE_WEBSITE_WATERCRAWL: ${ENABLE_WEBSITE_WATERCRAWL:-true}
   DB_USERNAME: ${DB_USERNAME:-postgres}
   DB_PASSWORD: ${DB_PASSWORD:-difyai123456}
   DB_HOST: ${DB_HOST:-db}
@@ -139,6 +142,7 @@ x-shared-env: &shared-api-worker-env
   MILVUS_USER: ${MILVUS_USER:-}
   MILVUS_PASSWORD: ${MILVUS_PASSWORD:-}
   MILVUS_ENABLE_HYBRID_SEARCH: ${MILVUS_ENABLE_HYBRID_SEARCH:-False}
+  MILVUS_ANALYZER_PARAMS: ${MILVUS_ANALYZER_PARAMS:-}
   MYSCALE_HOST: ${MYSCALE_HOST:-myscale}
   MYSCALE_PORT: ${MYSCALE_PORT:-8123}
   MYSCALE_USER: ${MYSCALE_USER:-default}
@@ -323,6 +327,7 @@ x-shared-env: &shared-api-worker-env
   MAX_VARIABLE_SIZE: ${MAX_VARIABLE_SIZE:-204800}
   WORKFLOW_PARALLEL_DEPTH_LIMIT: ${WORKFLOW_PARALLEL_DEPTH_LIMIT:-3}
   WORKFLOW_FILE_UPLOAD_LIMIT: ${WORKFLOW_FILE_UPLOAD_LIMIT:-10}
+  WORKFLOW_NODE_EXECUTION_STORAGE: ${WORKFLOW_NODE_EXECUTION_STORAGE:-rdbms}
   HTTP_REQUEST_NODE_MAX_BINARY_SIZE: ${HTTP_REQUEST_NODE_MAX_BINARY_SIZE:-10485760}
   HTTP_REQUEST_NODE_MAX_TEXT_SIZE: ${HTTP_REQUEST_NODE_MAX_TEXT_SIZE:-1048576}
   HTTP_REQUEST_NODE_SSL_VERIFY: ${HTTP_REQUEST_NODE_SSL_VERIFY:-True}
@@ -485,8 +490,10 @@ services:
       PLUGIN_MAX_PACKAGE_SIZE: ${PLUGIN_MAX_PACKAGE_SIZE:-52428800}
       INNER_API_KEY_FOR_PLUGIN: ${PLUGIN_DIFY_INNER_API_KEY:-QaHbTe77CtuXmsfyhR7+vRjI/+XbV1AaFy691iy+kGDv2Jvy0/eAh8Y1}
     depends_on:
-      - db
-      - redis
+      db:
+        condition: service_healthy
+      redis:
+        condition: service_started
     volumes:
       # Mount the storage directory to the container, for storing user files.
       - ./volumes/app/storage:/app/api/storage
@@ -510,8 +517,10 @@ services:
       PLUGIN_MAX_PACKAGE_SIZE: ${PLUGIN_MAX_PACKAGE_SIZE:-52428800}
       INNER_API_KEY_FOR_PLUGIN: ${PLUGIN_DIFY_INNER_API_KEY:-QaHbTe77CtuXmsfyhR7+vRjI/+XbV1AaFy691iy+kGDv2Jvy0/eAh8Y1}
     depends_on:
-      - db
-      - redis
+      db:
+        condition: service_healthy
+      redis:
+        condition: service_started
     volumes:
       # Mount the storage directory to the container, for storing user files.
       - ./volumes/app/storage:/app/api/storage
@@ -539,7 +548,9 @@ services:
       MAX_TOOLS_NUM: ${MAX_TOOLS_NUM:-10}
       MAX_PARALLEL_LIMIT: ${MAX_PARALLEL_LIMIT:-10}
       MAX_ITERATIONS_NUM: ${MAX_ITERATIONS_NUM:-5}
-
+      ENABLE_WEBSITE_JINAREADER: ${ENABLE_WEBSITE_JINAREADER:-true}
+      ENABLE_WEBSITE_FIRECRAWL: ${ENABLE_WEBSITE_FIRECRAWL:-true}
+      ENABLE_WEBSITE_WATERCRAWL: ${ENABLE_WEBSITE_WATERCRAWL:-true}
   # The postgres database.
   db:
     image: postgres:15-alpine
@@ -592,6 +603,7 @@ services:
       HTTP_PROXY: ${SANDBOX_HTTP_PROXY:-http://ssrf_proxy:3128}
       HTTPS_PROXY: ${SANDBOX_HTTPS_PROXY:-http://ssrf_proxy:3128}
       SANDBOX_PORT: ${SANDBOX_PORT:-8194}
+      PIP_MIRROR_URL: ${PIP_MIRROR_URL:-}
     volumes:
       - ./volumes/sandbox/dependencies:/dependencies
       - ./volumes/sandbox/conf:/conf

web/.env.example

@@ -49,3 +49,8 @@ NEXT_PUBLIC_MAX_PARALLEL_LIMIT=10
 
 # The maximum number of iterations for agent setting
 NEXT_PUBLIC_MAX_ITERATIONS_NUM=5
+
+NEXT_PUBLIC_ENABLE_WEBSITE_JINAREADER=true
+NEXT_PUBLIC_ENABLE_WEBSITE_FIRECRAWL=true
+NEXT_PUBLIC_ENABLE_WEBSITE_WATERCRAWL=true
+

web/README.md

@@ -7,7 +7,7 @@ This is a [Next.js](https://nextjs.org/) project bootstrapped with [`create-next
 ### Run by source code
 
 Before starting the web frontend service, please make sure the following environment is ready.
-- [Node.js](https://nodejs.org) >= v18.x
+- [Node.js](https://nodejs.org) >= v22.11.x
 - [pnpm](https://pnpm.io) v10.x
 
 First, install the dependencies:

web/app/(commonLayout)/app/(appDetailLayout)/[appId]/workflow/page.tsx

@@ -1,11 +1,11 @@
 'use client'
 
-import Workflow from '@/app/components/workflow'
+import WorkflowApp from '@/app/components/workflow-app'
 
 const Page = () => {
   return (
     <div className='h-full w-full overflow-x-auto'>
-      <Workflow />
+      <WorkflowApp />
     </div>
   )
 }

web/app/(commonLayout)/datasets/template/template.en.mdx

@@ -557,7 +557,7 @@ import { Row, Col, Properties, Property, Heading, SubProperty, PropertyInstructi
 
 <Heading
   url='/datasets/{dataset_id}'
-  method='POST'
+  method='PATCH'
   title='Update knowledge base'
   name='#update_dataset'
 />
@@ -585,8 +585,21 @@ import { Row, Col, Properties, Property, Heading, SubProperty, PropertyInstructi
       <Property name='embedding_model' type='string' key='embedding_model'>
         Specified embedding model, corresponding to the model field(Optional)
       </Property>
-      <Property name='retrieval_model' type='string' key='retrieval_model'>
-        Specified retrieval model, corresponding to the model field(Optional)
+      <Property name='retrieval_model' type='object' key='retrieval_model'>
+        Retrieval model (optional, if not filled, it will be recalled according to the default method)
+        - <code>search_method</code> (text) Search method: One of the following four keywords is required
+          - <code>keyword_search</code> Keyword search
+          - <code>semantic_search</code> Semantic search
+          - <code>full_text_search</code> Full-text search
+          - <code>hybrid_search</code> Hybrid search
+        - <code>reranking_enable</code> (bool) Whether to enable reranking, required if the search mode is semantic_search or hybrid_search (optional)
+        - <code>reranking_mode</code> (object) Rerank model configuration, required if reranking is enabled
+            - <code>reranking_provider_name</code> (string) Rerank model provider
+            - <code>reranking_model_name</code> (string) Rerank model name
+        - <code>weights</code> (float) Semantic search weight setting in hybrid search mode
+        - <code>top_k</code> (integer) Number of results to return (optional)
+        - <code>score_threshold_enabled</code> (bool) Whether to enable score threshold
+        - <code>score_threshold</code> (float) Score threshold
       </Property>
       <Property name='partial_member_list' type='array' key='partial_member_list'>
         Partial member list(Optional)
@@ -596,16 +609,56 @@ import { Row, Col, Properties, Property, Heading, SubProperty, PropertyInstructi
   <Col sticky>
     <CodeGroup
       title="Request"
-      tag="POST"
+      tag="PATCH"
       label="/datasets/{dataset_id}"
-      targetCode={`curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}' \\\n--header 'Authorization: Bearer {api_key}' \\\n--header 'Content-Type: application/json' \\\n--data-raw '{"name": "Test Knowledge Base", "indexing_technique": "high_quality", "permission": "only_me", "embedding_model_provider": "zhipuai", "embedding_model": "embedding-3", "retrieval_model": "", "partial_member_list": []}' `}
+      targetCode={`curl --location --request PATCH '${props.apiBaseUrl}/datasets/{dataset_id}' \\\n--header 'Authorization: Bearer {api_key}' \\\n--header 'Content-Type: application/json' \\\n--data-raw '{
+        "name": "Test Knowledge Base", 
+        "indexing_technique": "high_quality", 
+        "permission": "only_me", 
+        "embedding_model_provider": "zhipuai", 
+        "embedding_model": "embedding-3", 
+        "retrieval_model": {
+          "search_method": "keyword_search",
+          "reranking_enable": false,
+          "reranking_mode": null,
+          "reranking_model": {
+              "reranking_provider_name": "",
+              "reranking_model_name": ""
+          },
+          "weights": null,
+          "top_k": 1,
+          "score_threshold_enabled": false,
+          "score_threshold": null
+        }, 
+        "partial_member_list": []
+      }'
+    `}
     >
     ```bash {{ title: 'cURL' }}
-    curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}' \
+    curl --location --request PATCH '${props.apiBaseUrl}/datasets/{dataset_id}' \
     --header 'Authorization: Bearer {api_key}' \
     --header 'Content-Type: application/json' \
-    --data-raw '{"name": "Test Knowledge Base", "indexing_technique": "high_quality", "permission": "only_me",\
-      "embedding_model_provider": "zhipuai", "embedding_model": "embedding-3", "retrieval_model": "", "partial_member_list": []}'
+    --data-raw '{
+      "name": "Test Knowledge Base", 
+      "indexing_technique": "high_quality", 
+      "permission": "only_me", 
+      "embedding_model_provider": "zhipuai", 
+      "embedding_model": "embedding-3", 
+      "retrieval_model": {
+        "search_method": "keyword_search",
+        "reranking_enable": false,
+        "reranking_mode": null,
+        "reranking_model": {
+            "reranking_provider_name": "",
+            "reranking_model_name": ""
+        },
+        "weights": null,
+        "top_k": 1,
+        "score_threshold_enabled": false,
+        "score_threshold": null
+      }, 
+      "partial_member_list": []
+    }'
     ```
     </CodeGroup>
     <CodeGroup title="Response">

web/app/(commonLayout)/datasets/template/template.zh.mdx

@@ -94,6 +94,9 @@ import { Row, Col, Properties, Property, Heading, SubProperty, PropertyInstructi
             - <code>semantic_search</code> 语义检索
             - <code>full_text_search</code> 全文检索
           - <code>reranking_enable</code> (bool) 是否开启rerank
+          - <code>reranking_mode</code> (String) 混合检索
+            - <code>weighted_score</code> 权重设置
+            - <code>reranking_model</code> Rerank 模型
           - <code>reranking_model</code> (object) Rerank 模型配置
             - <code>reranking_provider_name</code> (string) Rerank 模型的提供商
             - <code>reranking_model_name</code> (string) Rerank 模型的名称
@@ -557,7 +560,7 @@ import { Row, Col, Properties, Property, Heading, SubProperty, PropertyInstructi
 
 <Heading
   url='/datasets/{dataset_id}'
-  method='POST'
+  method='PATCH'
   title='修改知识库详情'
   name='#update_dataset'
 />
@@ -589,8 +592,21 @@ import { Row, Col, Properties, Property, Heading, SubProperty, PropertyInstructi
       <Property name='embedding_model' type='string' key='embedding_model'>
         嵌入模型（选填）
       </Property>
-      <Property name='retrieval_model' type='string' key='retrieval_model'>
-        检索模型（选填）
+      <Property name='retrieval_model' type='object' key='retrieval_model'>
+        检索参数（选填，如不填，按照默认方式召回）
+        - <code>search_method</code> (text) 检索方法：以下四个关键字之一，必填
+          - <code>keyword_search</code> 关键字检索
+          - <code>semantic_search</code> 语义检索
+          - <code>full_text_search</code> 全文检索
+          - <code>hybrid_search</code> 混合检索
+        - <code>reranking_enable</code> (bool) 是否启用 Reranking，非必填，如果检索模式为 semantic_search 模式或者 hybrid_search 则传值
+        - <code>reranking_mode</code> (object) Rerank 模型配置，非必填，如果启用了 reranking 则传值
+            - <code>reranking_provider_name</code> (string) Rerank 模型提供商
+            - <code>reranking_model_name</code> (string) Rerank 模型名称
+        - <code>weights</code> (float) 混合检索模式下语意检索的权重设置
+        - <code>top_k</code> (integer) 返回结果数量，非必填
+        - <code>score_threshold_enabled</code> (bool) 是否开启 score 阈值
+        - <code>score_threshold</code> (float) Score 阈值
       </Property>
       <Property name='partial_member_list' type='array' key='partial_member_list'>
         部分团队成员 ID 列表（选填）
@@ -600,16 +616,56 @@ import { Row, Col, Properties, Property, Heading, SubProperty, PropertyInstructi
   <Col sticky>
     <CodeGroup
       title="Request"
-      tag="POST"
+      tag="PATCH"
       label="/datasets/{dataset_id}"
-      targetCode={`curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}' \\\n--header 'Authorization: Bearer {api_key}' \\\n--header 'Content-Type: application/json' \\\n--data-raw '{"name": "Test Knowledge Base", "indexing_technique": "high_quality", "permission": "only_me", "embedding_model_provider": "zhipuai", "embedding_model": "embedding-3", "retrieval_model": "", "partial_member_list": []}' `}
+      targetCode={`curl --location --request PATCH '${props.apiBaseUrl}/datasets/{dataset_id}' \\\n--header 'Authorization: Bearer {api_key}' \\\n--header 'Content-Type: application/json' \\\n--data-raw '{
+        "name": "Test Knowledge Base", 
+        "indexing_technique": "high_quality", 
+        "permission": "only_me", 
+        "embedding_model_provider": "zhipuai", 
+        "embedding_model": "embedding-3", 
+        "retrieval_model": {
+          "search_method": "keyword_search",
+          "reranking_enable": false,
+          "reranking_mode": null,
+          "reranking_model": {
+              "reranking_provider_name": "",
+              "reranking_model_name": ""
+          },
+          "weights": null,
+          "top_k": 1,
+          "score_threshold_enabled": false,
+          "score_threshold": null
+        }, 
+        "partial_member_list": []
+      }'
+    `}
     >
     ```bash {{ title: 'cURL' }}
-    curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}' \
+    curl --location --request PATCH '${props.apiBaseUrl}/datasets/{dataset_id}' \
     --header 'Authorization: Bearer {api_key}' \
     --header 'Content-Type: application/json' \
-    --data-raw '{"name": "Test Knowledge Base", "indexing_technique": "high_quality", "permission": "only_me",\
-      "embedding_model_provider": "zhipuai", "embedding_model": "embedding-3", "retrieval_model": "", "partial_member_list": []}'
+    --data-raw '{
+      "name": "Test Knowledge Base", 
+      "indexing_technique": "high_quality", 
+      "permission": "only_me", 
+      "embedding_model_provider": "zhipuai", 
+      "embedding_model": "embedding-3", 
+      "retrieval_model": {
+        "search_method": "keyword_search",
+        "reranking_enable": false,
+        "reranking_mode": null,
+        "reranking_model": {
+            "reranking_provider_name": "",
+            "reranking_model_name": ""
+        },
+        "weights": null,
+        "top_k": 1,
+        "score_threshold_enabled": false,
+        "score_threshold": null
+      }, 
+      "partial_member_list": []
+    }'
     ```
     </CodeGroup>
     <CodeGroup title="Response">
@@ -1764,7 +1820,7 @@ import { Row, Col, Properties, Property, Heading, SubProperty, PropertyInstructi
       </Property>
       <Property name='retrieval_model' type='object' key='retrieval_model'>
         检索参数（选填，如不填，按照默认方式召回）
-        - <code>search_method</code> (text) 检索方法：以下三个关键字之一，必填
+        - <code>search_method</code> (text) 检索方法：以下四个关键字之一，必填
           - <code>keyword_search</code> 关键字检索
           - <code>semantic_search</code> 语义检索
           - <code>full_text_search</code> 全文检索

web/app/components/app/configuration/config-var/config-select/index.spec.tsx

@@ -0,0 +1,82 @@
+import { fireEvent, render, screen } from '@testing-library/react'
+import ConfigSelect from './index'
+
+jest.mock('react-sortablejs', () => ({
+  ReactSortable: ({ children }: { children: React.ReactNode }) => <div>{children}</div>,
+}))
+
+jest.mock('react-i18next', () => ({
+  useTranslation: () => ({
+    t: (key: string) => key,
+  }),
+}))
+
+describe('ConfigSelect Component', () => {
+  const defaultProps = {
+    options: ['Option 1', 'Option 2'],
+    onChange: jest.fn(),
+  }
+
+  afterEach(() => {
+    jest.clearAllMocks()
+  })
+
+  it('renders all options', () => {
+    render(<ConfigSelect {...defaultProps} />)
+
+    defaultProps.options.forEach((option) => {
+      expect(screen.getByDisplayValue(option)).toBeInTheDocument()
+    })
+  })
+
+  it('renders add button', () => {
+    render(<ConfigSelect {...defaultProps} />)
+
+    expect(screen.getByText('appDebug.variableConfig.addOption')).toBeInTheDocument()
+  })
+
+  it('handles option deletion', () => {
+    render(<ConfigSelect {...defaultProps} />)
+    const optionContainer = screen.getByDisplayValue('Option 1').closest('div')
+    const deleteButton = optionContainer?.querySelector('div[role="button"]')
+
+    if (!deleteButton) return
+    fireEvent.click(deleteButton)
+    expect(defaultProps.onChange).toHaveBeenCalledWith(['Option 2'])
+  })
+
+  it('handles adding new option', () => {
+    render(<ConfigSelect {...defaultProps} />)
+    const addButton = screen.getByText('appDebug.variableConfig.addOption')
+
+    fireEvent.click(addButton)
+
+    expect(defaultProps.onChange).toHaveBeenCalledWith([...defaultProps.options, ''])
+  })
+
+  it('applies focus styles on input focus', () => {
+    render(<ConfigSelect {...defaultProps} />)
+    const firstInput = screen.getByDisplayValue('Option 1')
+
+    fireEvent.focus(firstInput)
+
+    expect(firstInput.closest('div')).toHaveClass('border-components-input-border-active')
+  })
+
+  it('applies delete hover styles', () => {
+    render(<ConfigSelect {...defaultProps} />)
+    const optionContainer = screen.getByDisplayValue('Option 1').closest('div')
+    const deleteButton = optionContainer?.querySelector('div[role="button"]')
+
+    if (!deleteButton) return
+    fireEvent.mouseEnter(deleteButton)
+    expect(optionContainer).toHaveClass('border-components-input-border-destructive')
+  })
+
+  it('renders empty state correctly', () => {
+    render(<ConfigSelect options={[]} onChange={defaultProps.onChange} />)
+
+    expect(screen.queryByRole('textbox')).not.toBeInTheDocument()
+    expect(screen.getByText('appDebug.variableConfig.addOption')).toBeInTheDocument()
+  })
+})