fix: code owners

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: crazywoola <100913391+crazywoola@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

.github/CODEOWNERS

@@ -0,0 +1,226 @@
+# CODEOWNERS
+# This file defines code ownership for the Dify project.
+# Each line is a file pattern followed by one or more owners.
+# Owners can be @username, @org/team-name, or email addresses.
+# For more information, see: https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-code-owners
+
+* @crazywoola @laipz8200 @Yeuoly
+
+# Backend (default owner, more specific rules below will override)
+api/ @QuantumGhost
+
+# Backend - Workflow - Engine (Core graph execution engine)
+api/core/workflow/graph_engine/ @laipz8200 @QuantumGhost
+api/core/workflow/runtime/ @laipz8200 @QuantumGhost
+api/core/workflow/graph/ @laipz8200 @QuantumGhost
+api/core/workflow/graph_events/ @laipz8200 @QuantumGhost
+api/core/workflow/node_events/ @laipz8200 @QuantumGhost
+api/core/model_runtime/ @laipz8200 @QuantumGhost
+
+# Backend - Workflow - Nodes (Agent, Iteration, Loop, LLM)
+api/core/workflow/nodes/agent/ Nov1c444
+api/core/workflow/nodes/iteration/ Nov1c444
+api/core/workflow/nodes/loop/ Nov1c444
+api/core/workflow/nodes/llm/ Nov1c444
+
+# Backend - RAG (Retrieval Augmented Generation)
+api/core/rag/ @JohnJyong
+api/services/rag_pipeline/ @JohnJyong
+api/services/dataset_service.py @JohnJyong
+api/services/knowledge_service.py @JohnJyong
+api/services/external_knowledge_service.py @JohnJyong
+api/services/hit_testing_service.py @JohnJyong
+api/services/metadata_service.py @JohnJyong
+api/services/vector_service.py @JohnJyong
+api/services/entities/knowledge_entities/ @JohnJyong
+api/services/entities/external_knowledge_entities/ @JohnJyong
+api/controllers/console/datasets/ @JohnJyong
+api/controllers/service_api/dataset/ @JohnJyong
+api/models/dataset.py @JohnJyong
+api/tasks/rag_pipeline/ @JohnJyong
+api/tasks/add_document_to_index_task.py @JohnJyong
+api/tasks/batch_clean_document_task.py @JohnJyong
+api/tasks/clean_document_task.py @JohnJyong
+api/tasks/clean_notion_document_task.py @JohnJyong
+api/tasks/document_indexing_task.py @JohnJyong
+api/tasks/document_indexing_sync_task.py @JohnJyong
+api/tasks/document_indexing_update_task.py @JohnJyong
+api/tasks/duplicate_document_indexing_task.py @JohnJyong
+api/tasks/recover_document_indexing_task.py @JohnJyong
+api/tasks/remove_document_from_index_task.py @JohnJyong
+api/tasks/retry_document_indexing_task.py @JohnJyong
+api/tasks/sync_website_document_indexing_task.py @JohnJyong
+api/tasks/batch_create_segment_to_index_task.py @JohnJyong
+api/tasks/create_segment_to_index_task.py @JohnJyong
+api/tasks/delete_segment_from_index_task.py @JohnJyong
+api/tasks/disable_segment_from_index_task.py @JohnJyong
+api/tasks/disable_segments_from_index_task.py @JohnJyong
+api/tasks/enable_segment_to_index_task.py @JohnJyong
+api/tasks/enable_segments_to_index_task.py @JohnJyong
+api/tasks/clean_dataset_task.py @JohnJyong
+api/tasks/deal_dataset_index_update_task.py @JohnJyong
+api/tasks/deal_dataset_vector_index_task.py @JohnJyong
+
+# Backend - Plugins
+api/core/plugin/ @Mairuis @Yeuoly @Stream29
+api/services/plugin/ @Mairuis @Yeuoly @Stream29
+api/controllers/console/workspace/plugin.py @Mairuis @Yeuoly @Stream29
+api/controllers/inner_api/plugin/ @Mairuis @Yeuoly @Stream29
+api/tasks/process_tenant_plugin_autoupgrade_check_task.py @Mairuis @Yeuoly @Stream29
+
+# Backend - Trigger/Schedule/Webhook
+api/controllers/trigger/ @Mairuis @Yeuoly
+api/controllers/console/app/workflow_trigger.py @Mairuis @Yeuoly
+api/controllers/console/workspace/trigger_providers.py @Mairuis @Yeuoly
+api/core/trigger/ @Mairuis @Yeuoly
+api/core/app/layers/trigger_post_layer.py @Mairuis @Yeuoly
+api/services/trigger/ @Mairuis @Yeuoly
+api/models/trigger.py @Mairuis @Yeuoly
+api/fields/workflow_trigger_fields.py @Mairuis @Yeuoly
+api/repositories/workflow_trigger_log_repository.py @Mairuis @Yeuoly
+api/repositories/sqlalchemy_workflow_trigger_log_repository.py @Mairuis @Yeuoly
+api/libs/schedule_utils.py @Mairuis @Yeuoly
+api/services/workflow/scheduler.py @Mairuis @Yeuoly
+api/schedule/trigger_provider_refresh_task.py @Mairuis @Yeuoly
+api/schedule/workflow_schedule_task.py @Mairuis @Yeuoly
+api/tasks/trigger_processing_tasks.py @Mairuis @Yeuoly
+api/tasks/trigger_subscription_refresh_tasks.py @Mairuis @Yeuoly
+api/tasks/workflow_schedule_tasks.py @Mairuis @Yeuoly
+api/tasks/workflow_cfs_scheduler/ @Mairuis @Yeuoly
+api/events/event_handlers/sync_plugin_trigger_when_app_created.py @Mairuis @Yeuoly
+api/events/event_handlers/update_app_triggers_when_app_published_workflow_updated.py @Mairuis @Yeuoly
+api/events/event_handlers/sync_workflow_schedule_when_app_published.py @Mairuis @Yeuoly
+api/events/event_handlers/sync_webhook_when_app_created.py @Mairuis @Yeuoly
+
+# Backend - Async Workflow
+api/services/async_workflow_service.py @Mairuis @Yeuoly
+api/tasks/async_workflow_tasks.py @Mairuis @Yeuoly
+
+# Backend - Billing
+api/services/billing_service.py @hj24 @zyssyz123
+api/controllers/console/billing/ @hj24 @zyssyz123
+
+# Backend - Enterprise
+api/configs/enterprise/ @GarfieldDai @GareArc
+api/services/enterprise/ @GarfieldDai @GareArc
+api/services/feature_service.py @GarfieldDai @GareArc
+api/controllers/console/feature.py @GarfieldDai @GareArc
+api/controllers/web/feature.py @GarfieldDai @GareArc
+
+# Backend - Database Migrations
+api/migrations/ @snakevash @laipz8200
+
+# Frontend
+web/ @iamjoel
+
+# Frontend - App - Orchestration
+web/app/components/workflow/ @iamjoel @zxhlyh
+web/app/components/workflow-app/ @iamjoel @zxhlyh
+web/app/components/app/configuration/ @iamjoel @zxhlyh
+web/app/components/app/app-publisher/ @iamjoel @zxhlyh
+
+# Frontend - WebApp - Chat
+web/app/components/base/chat/ @iamjoel @zxhlyh
+
+# Frontend - WebApp - Completion
+web/app/components/share/text-generation/ @iamjoel @zxhlyh
+
+# Frontend - App - List and Creation
+web/app/components/apps/ @JzoNgKVO @iamjoel
+web/app/components/app/create-app-dialog/ @JzoNgKVO @iamjoel
+web/app/components/app/create-app-modal/ @JzoNgKVO @iamjoel
+web/app/components/app/create-from-dsl-modal/ @JzoNgKVO @iamjoel
+
+# Frontend - App - API Documentation
+web/app/components/develop/ @JzoNgKVO @iamjoel
+
+# Frontend - App - Logs and Annotations
+web/app/components/app/workflow-log/ @JzoNgKVO @iamjoel
+web/app/components/app/log/ @JzoNgKVO @iamjoel
+web/app/components/app/log-annotation/ @JzoNgKVO @iamjoel
+web/app/components/app/annotation/ @JzoNgKVO @iamjoel
+
+# Frontend - App - Monitoring
+web/app/(commonLayout)/app/(appDetailLayout)/\[appId\]/overview/ @JzoNgKVO @iamjoel
+web/app/components/app/overview/ @JzoNgKVO @iamjoel
+
+# Frontend - App - Settings
+web/app/components/app-sidebar/ @JzoNgKVO @iamjoel
+
+# Frontend - RAG - Hit Testing
+web/app/components/datasets/hit-testing/ @JzoNgKVO @iamjoel
+
+# Frontend - RAG - List and Creation
+web/app/components/datasets/list/ @iamjoel @WTW0313
+web/app/components/datasets/create/ @iamjoel @WTW0313
+web/app/components/datasets/create-from-pipeline/ @iamjoel @WTW0313
+web/app/components/datasets/external-knowledge-base/ @iamjoel @WTW0313
+
+# Frontend - RAG - Orchestration (general rule first, specific rules below override)
+web/app/components/rag-pipeline/ @iamjoel @WTW0313
+web/app/components/rag-pipeline/components/rag-pipeline-main.tsx @iamjoel @zxhlyh
+web/app/components/rag-pipeline/store/ @iamjoel @zxhlyh
+
+# Frontend - RAG - Documents List
+web/app/components/datasets/documents/list.tsx @iamjoel @WTW0313
+web/app/components/datasets/documents/create-from-pipeline/ @iamjoel @WTW0313
+
+# Frontend - RAG - Segments List
+web/app/components/datasets/documents/detail/ @iamjoel @WTW0313
+
+# Frontend - RAG - Settings
+web/app/components/datasets/settings/ @iamjoel @WTW0313
+
+# Frontend - Ecosystem - Plugins
+web/app/components/plugins/ @iamjoel @zhsama
+
+# Frontend - Ecosystem - Tools
+web/app/components/tools/ @iamjoel @Yessenia-d
+
+# Frontend - Ecosystem - MarketPlace
+web/app/components/plugins/marketplace/ @iamjoel @Yessenia-d
+
+# Frontend - Login and Registration
+web/app/signin/ @douxc @iamjoel
+web/app/signup/ @douxc @iamjoel
+web/app/reset-password/ @douxc @iamjoel
+web/app/install/ @douxc @iamjoel
+web/app/init/ @douxc @iamjoel
+web/app/forgot-password/ @douxc @iamjoel
+web/app/account/ @douxc @iamjoel
+
+# Frontend - Service Authentication
+web/service/base.ts @douxc @iamjoel
+
+# Frontend - WebApp Authentication and Access Control
+web/app/(shareLayout)/components/ @douxc @iamjoel
+web/app/(shareLayout)/webapp-signin/ @douxc @iamjoel
+web/app/(shareLayout)/webapp-reset-password/ @douxc @iamjoel
+web/app/components/app/app-access-control/ @douxc @iamjoel
+
+# Frontend - Explore Page
+web/app/components/explore/ @CodingOnStar @iamjoel
+
+# Frontend - Personal Settings
+web/app/components/header/account-setting/ @CodingOnStar @iamjoel
+web/app/components/header/account-dropdown/ @CodingOnStar @iamjoel
+
+# Frontend - Analytics
+web/app/components/base/ga/ @CodingOnStar @iamjoel
+
+# Frontend - Base Components
+web/app/components/base/ @iamjoel @zxhlyh
+
+# Frontend - Utils and Hooks
+web/utils/classnames.ts @iamjoel @zxhlyh
+web/utils/time.ts @iamjoel @zxhlyh
+web/utils/format.ts @iamjoel @zxhlyh
+web/utils/clipboard.ts @iamjoel @zxhlyh
+web/hooks/use-document-title.ts @iamjoel @zxhlyh
+
+# Frontend - Billing and Education
+web/app/components/billing/ @iamjoel @zxhlyh
+web/app/education-apply/ @iamjoel @zxhlyh
+
+# Frontend - Workspace
+web/app/components/header/account-dropdown/workplace-selector/ @iamjoel @zxhlyh

.github/workflows/translate-i18n-base-on-english.yml

@@ -77,12 +77,15 @@ jobs:
         uses: peter-evans/create-pull-request@v6
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
-          commit-message: Update i18n files and type definitions based on en-US changes
-          title: 'chore: translate i18n files and update type definitions'
+          commit-message: 'chore(i18n): update translations based on en-US changes'
+          title: 'chore(i18n): translate i18n files and update type definitions'
           body: |
             This PR was automatically created to update i18n files and TypeScript type definitions based on changes in en-US locale.
-            
+
+            **Triggered by:** ${{ github.sha }}
+
             **Changes included:**
             - Updated translation files for all locales
             - Regenerated TypeScript type definitions for type safety
-          branch: chore/automated-i18n-updates
+          branch: chore/automated-i18n-updates-${{ github.sha }}
+          delete-branch: true

README.md

@@ -36,6 +36,12 @@
         <img alt="Issues closed" src="https://img.shields.io/github/issues-search?query=repo%3Alanggenius%2Fdify%20is%3Aclosed&label=issues%20closed&labelColor=%20%237d89b0&color=%20%235d6b98"></a>
     <a href="https://github.com/langgenius/dify/discussions/" target="_blank">
         <img alt="Discussion posts" src="https://img.shields.io/github/discussions/langgenius/dify?labelColor=%20%239b8afb&color=%20%237a5af8"></a>
+    <a href="https://insights.linuxfoundation.org/project/langgenius-dify" target="_blank">
+        <img alt="LFX Health Score" src="https://insights.linuxfoundation.org/api/badge/health-score?project=langgenius-dify"></a>
+    <a href="https://insights.linuxfoundation.org/project/langgenius-dify" target="_blank">
+        <img alt="LFX Contributors" src="https://insights.linuxfoundation.org/api/badge/contributors?project=langgenius-dify"></a>
+    <a href="https://insights.linuxfoundation.org/project/langgenius-dify" target="_blank">
+        <img alt="LFX Active Contributors" src="https://insights.linuxfoundation.org/api/badge/active-contributors?project=langgenius-dify"></a>
 </p>
 
 <p align="center">

api/.env.example

@@ -540,6 +540,7 @@ WORKFLOW_LOG_CLEANUP_BATCH_SIZE=100
 
 # App configuration
 APP_MAX_EXECUTION_TIME=1200
+APP_DEFAULT_ACTIVE_REQUESTS=0
 APP_MAX_ACTIVE_REQUESTS=0
 
 # Celery beat configuration

api/.importlinter

@@ -16,6 +16,7 @@ layers =
     graph
     nodes
     node_events
+    runtime
     entities
 containers =
     core.workflow

api/Dockerfile

@@ -48,6 +48,12 @@ ENV PYTHONIOENCODING=utf-8
 
 WORKDIR /app/api
 
+# Create non-root user
+ARG dify_uid=1001
+RUN groupadd -r -g ${dify_uid} dify && \
+    useradd -r -u ${dify_uid} -g ${dify_uid} -s /bin/bash dify && \
+    chown -R dify:dify /app
+
 RUN \
     apt-get update \
     # Install dependencies
@@ -69,7 +75,7 @@ RUN \
 
 # Copy Python environment and packages
 ENV VIRTUAL_ENV=/app/api/.venv
-COPY --from=packages ${VIRTUAL_ENV} ${VIRTUAL_ENV}
+COPY --from=packages --chown=dify:dify ${VIRTUAL_ENV} ${VIRTUAL_ENV}
 ENV PATH="${VIRTUAL_ENV}/bin:${PATH}"
 
 # Download nltk data
@@ -78,24 +84,20 @@ RUN mkdir -p /usr/local/share/nltk_data && NLTK_DATA=/usr/local/share/nltk_data
 
 ENV TIKTOKEN_CACHE_DIR=/app/api/.tiktoken_cache
 
-RUN python -c "import tiktoken; tiktoken.encoding_for_model('gpt2')"
+RUN python -c "import tiktoken; tiktoken.encoding_for_model('gpt2')" \
+    && chown -R dify:dify ${TIKTOKEN_CACHE_DIR}
 
 # Copy source code
-COPY . /app/api/
+COPY --chown=dify:dify . /app/api/
 
-# Copy entrypoint
-COPY docker/entrypoint.sh /entrypoint.sh
-RUN chmod +x /entrypoint.sh
+# Prepare entrypoint script
+COPY --chown=dify:dify --chmod=755 docker/entrypoint.sh /entrypoint.sh
 
-# Create non-root user and set permissions
-RUN groupadd -r -g 1001 dify && \
-    useradd -r -u 1001 -g 1001 -s /bin/bash dify && \
-    mkdir -p /home/dify && \
-    chown -R 1001:1001 /app /home/dify ${TIKTOKEN_CACHE_DIR} /entrypoint.sh
 
 ARG COMMIT_SHA
 ENV COMMIT_SHA=${COMMIT_SHA}
 ENV NLTK_DATA=/usr/local/share/nltk_data
-USER 1001
+
+USER dify
 
 ENTRYPOINT ["/bin/bash", "/entrypoint.sh"]

api/configs/feature/__init__.py

@@ -73,6 +73,10 @@ class AppExecutionConfig(BaseSettings):
         description="Maximum allowed execution time for the application in seconds",
         default=1200,
     )
+    APP_DEFAULT_ACTIVE_REQUESTS: NonNegativeInt = Field(
+        description="Default number of concurrent active requests per app (0 for unlimited)",
+        default=0,
+    )
     APP_MAX_ACTIVE_REQUESTS: NonNegativeInt = Field(
         description="Maximum number of concurrent active requests per app (0 for unlimited)",
         default=0,

api/controllers/console/app/workflow_trigger.py

@@ -1,6 +1,8 @@
 import logging
 
-from flask_restx import Resource, marshal_with, reqparse
+from flask import request
+from flask_restx import Resource, marshal_with
+from pydantic import BaseModel
 from sqlalchemy import select
 from sqlalchemy.orm import Session
 from werkzeug.exceptions import NotFound
@@ -18,16 +20,30 @@ from ..app.wraps import get_app_model
 from ..wraps import account_initialization_required, edit_permission_required, setup_required
 
 logger = logging.getLogger(__name__)
+DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
 
 
-parser = reqparse.RequestParser().add_argument("node_id", type=str, required=True, help="Node ID is required")
+class Parser(BaseModel):
+    node_id: str
+
+
+class ParserEnable(BaseModel):
+    trigger_id: str
+    enable_trigger: bool
+
+
+console_ns.schema_model(Parser.__name__, Parser.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0))
+
+console_ns.schema_model(
+    ParserEnable.__name__, ParserEnable.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
 
 
 @console_ns.route("/apps/<uuid:app_id>/workflows/triggers/webhook")
 class WebhookTriggerApi(Resource):
     """Webhook Trigger API"""
 
-    @console_ns.expect(parser)
+    @console_ns.expect(console_ns.models[Parser.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -35,9 +51,9 @@ class WebhookTriggerApi(Resource):
     @marshal_with(webhook_trigger_fields)
     def get(self, app_model: App):
         """Get webhook trigger for a node"""
-        args = parser.parse_args()
+        args = Parser.model_validate(request.args.to_dict(flat=True))  # type: ignore
 
-        node_id = str(args["node_id"])
+        node_id = args.node_id
 
         with Session(db.engine) as session:
             # Get webhook trigger for this app and node
@@ -96,16 +112,9 @@ class AppTriggersApi(Resource):
         return {"data": triggers}
 
 
-parser_enable = (
-    reqparse.RequestParser()
-    .add_argument("trigger_id", type=str, required=True, nullable=False, location="json")
-    .add_argument("enable_trigger", type=bool, required=True, nullable=False, location="json")
-)
-
-
 @console_ns.route("/apps/<uuid:app_id>/trigger-enable")
 class AppTriggerEnableApi(Resource):
-    @console_ns.expect(parser_enable)
+    @console_ns.expect(console_ns.models[ParserEnable.__name__], validate=True)
     @setup_required
     @login_required
     @account_initialization_required
@@ -114,12 +123,11 @@ class AppTriggerEnableApi(Resource):
     @marshal_with(trigger_fields)
     def post(self, app_model: App):
         """Update app trigger (enable/disable)"""
-        args = parser_enable.parse_args()
+        args = ParserEnable.model_validate(console_ns.payload)
 
         assert current_user.current_tenant_id is not None
 
-        trigger_id = args["trigger_id"]
-
+        trigger_id = args.trigger_id
         with Session(db.engine) as session:
             # Find the trigger using select
             trigger = session.execute(
@@ -134,7 +142,7 @@ class AppTriggerEnableApi(Resource):
                 raise NotFound("Trigger not found")
 
             # Update status based on enable_trigger boolean
-            trigger.status = AppTriggerStatus.ENABLED if args["enable_trigger"] else AppTriggerStatus.DISABLED
+            trigger.status = AppTriggerStatus.ENABLED if args.enable_trigger else AppTriggerStatus.DISABLED
 
             session.commit()
             session.refresh(trigger)

api/controllers/console/workspace/account.py

@@ -1,8 +1,10 @@
 from datetime import datetime
+from typing import Literal
 
 import pytz
 from flask import request
-from flask_restx import Resource, fields, marshal_with, reqparse
+from flask_restx import Resource, fields, marshal_with
+from pydantic import BaseModel, Field, field_validator, model_validator
 from sqlalchemy import select
 from sqlalchemy.orm import Session
 
@@ -42,20 +44,198 @@ from services.account_service import AccountService
 from services.billing_service import BillingService
 from services.errors.account import CurrentPasswordIncorrectError as ServiceCurrentPasswordIncorrectError
 
+DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
 
-def _init_parser():
-    parser = reqparse.RequestParser()
-    if dify_config.EDITION == "CLOUD":
-        parser.add_argument("invitation_code", type=str, location="json")
-    parser.add_argument("interface_language", type=supported_language, required=True, location="json").add_argument(
-        "timezone", type=timezone, required=True, location="json"
-    )
-    return parser
+
+class AccountInitPayload(BaseModel):
+    interface_language: str
+    timezone: str
+    invitation_code: str | None = None
+
+    @field_validator("interface_language")
+    @classmethod
+    def validate_language(cls, value: str) -> str:
+        return supported_language(value)
+
+    @field_validator("timezone")
+    @classmethod
+    def validate_timezone(cls, value: str) -> str:
+        return timezone(value)
+
+
+class AccountNamePayload(BaseModel):
+    name: str = Field(min_length=3, max_length=30)
+
+
+class AccountAvatarPayload(BaseModel):
+    avatar: str
+
+
+class AccountInterfaceLanguagePayload(BaseModel):
+    interface_language: str
+
+    @field_validator("interface_language")
+    @classmethod
+    def validate_language(cls, value: str) -> str:
+        return supported_language(value)
+
+
+class AccountInterfaceThemePayload(BaseModel):
+    interface_theme: Literal["light", "dark"]
+
+
+class AccountTimezonePayload(BaseModel):
+    timezone: str
+
+    @field_validator("timezone")
+    @classmethod
+    def validate_timezone(cls, value: str) -> str:
+        return timezone(value)
+
+
+class AccountPasswordPayload(BaseModel):
+    password: str | None = None
+    new_password: str
+    repeat_new_password: str
+
+    @model_validator(mode="after")
+    def check_passwords_match(self) -> "AccountPasswordPayload":
+        if self.new_password != self.repeat_new_password:
+            raise RepeatPasswordNotMatchError()
+        return self
+
+
+class AccountDeletePayload(BaseModel):
+    token: str
+    code: str
+
+
+class AccountDeletionFeedbackPayload(BaseModel):
+    email: str
+    feedback: str
+
+    @field_validator("email")
+    @classmethod
+    def validate_email(cls, value: str) -> str:
+        return email(value)
+
+
+class EducationActivatePayload(BaseModel):
+    token: str
+    institution: str
+    role: str
+
+
+class EducationAutocompleteQuery(BaseModel):
+    keywords: str
+    page: int = 0
+    limit: int = 20
+
+
+class ChangeEmailSendPayload(BaseModel):
+    email: str
+    language: str | None = None
+    phase: str | None = None
+    token: str | None = None
+
+    @field_validator("email")
+    @classmethod
+    def validate_email(cls, value: str) -> str:
+        return email(value)
+
+
+class ChangeEmailValidityPayload(BaseModel):
+    email: str
+    code: str
+    token: str
+
+    @field_validator("email")
+    @classmethod
+    def validate_email(cls, value: str) -> str:
+        return email(value)
+
+
+class ChangeEmailResetPayload(BaseModel):
+    new_email: str
+    token: str
+
+    @field_validator("new_email")
+    @classmethod
+    def validate_email(cls, value: str) -> str:
+        return email(value)
+
+
+class CheckEmailUniquePayload(BaseModel):
+    email: str
+
+    @field_validator("email")
+    @classmethod
+    def validate_email(cls, value: str) -> str:
+        return email(value)
+
+
+console_ns.schema_model(
+    AccountInitPayload.__name__, AccountInitPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+console_ns.schema_model(
+    AccountNamePayload.__name__, AccountNamePayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+console_ns.schema_model(
+    AccountAvatarPayload.__name__, AccountAvatarPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+console_ns.schema_model(
+    AccountInterfaceLanguagePayload.__name__,
+    AccountInterfaceLanguagePayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    AccountInterfaceThemePayload.__name__,
+    AccountInterfaceThemePayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    AccountTimezonePayload.__name__,
+    AccountTimezonePayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    AccountPasswordPayload.__name__,
+    AccountPasswordPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    AccountDeletePayload.__name__,
+    AccountDeletePayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    AccountDeletionFeedbackPayload.__name__,
+    AccountDeletionFeedbackPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    EducationActivatePayload.__name__,
+    EducationActivatePayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    EducationAutocompleteQuery.__name__,
+    EducationAutocompleteQuery.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    ChangeEmailSendPayload.__name__,
+    ChangeEmailSendPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    ChangeEmailValidityPayload.__name__,
+    ChangeEmailValidityPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    ChangeEmailResetPayload.__name__,
+    ChangeEmailResetPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    CheckEmailUniquePayload.__name__,
+    CheckEmailUniquePayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
 
 
 @console_ns.route("/account/init")
 class AccountInitApi(Resource):
-    @console_ns.expect(_init_parser())
+    @console_ns.expect(console_ns.models[AccountInitPayload.__name__])
     @setup_required
     @login_required
     def post(self):
@@ -64,17 +244,18 @@ class AccountInitApi(Resource):
         if account.status == "active":
             raise AccountAlreadyInitedError()
 
-        args = _init_parser().parse_args()
+        payload = console_ns.payload or {}
+        args = AccountInitPayload.model_validate(payload)
 
         if dify_config.EDITION == "CLOUD":
-            if not args["invitation_code"]:
+            if not args.invitation_code:
                 raise ValueError("invitation_code is required")
 
             # check invitation code
             invitation_code = (
                 db.session.query(InvitationCode)
                 .where(
-                    InvitationCode.code == args["invitation_code"],
+                    InvitationCode.code == args.invitation_code,
                     InvitationCode.status == "unused",
                 )
                 .first()
@@ -88,8 +269,8 @@ class AccountInitApi(Resource):
             invitation_code.used_by_tenant_id = account.current_tenant_id
             invitation_code.used_by_account_id = account.id
 
-        account.interface_language = args["interface_language"]
-        account.timezone = args["timezone"]
+        account.interface_language = args.interface_language
+        account.timezone = args.timezone
         account.interface_theme = "light"
         account.status = "active"
         account.initialized_at = naive_utc_now()
@@ -110,137 +291,104 @@ class AccountProfileApi(Resource):
         return current_user
 
 
-parser_name = reqparse.RequestParser().add_argument("name", type=str, required=True, location="json")
-
-
 @console_ns.route("/account/name")
 class AccountNameApi(Resource):
-    @console_ns.expect(parser_name)
+    @console_ns.expect(console_ns.models[AccountNamePayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @marshal_with(account_fields)
     def post(self):
         current_user, _ = current_account_with_tenant()
-        args = parser_name.parse_args()
-
-        # Validate account name length
-        if len(args["name"]) < 3 or len(args["name"]) > 30:
-            raise ValueError("Account name must be between 3 and 30 characters.")
-
-        updated_account = AccountService.update_account(current_user, name=args["name"])
+        payload = console_ns.payload or {}
+        args = AccountNamePayload.model_validate(payload)
+        updated_account = AccountService.update_account(current_user, name=args.name)
 
         return updated_account
 
 
-parser_avatar = reqparse.RequestParser().add_argument("avatar", type=str, required=True, location="json")
-
-
 @console_ns.route("/account/avatar")
 class AccountAvatarApi(Resource):
-    @console_ns.expect(parser_avatar)
+    @console_ns.expect(console_ns.models[AccountAvatarPayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @marshal_with(account_fields)
     def post(self):
         current_user, _ = current_account_with_tenant()
-        args = parser_avatar.parse_args()
+        payload = console_ns.payload or {}
+        args = AccountAvatarPayload.model_validate(payload)
 
-        updated_account = AccountService.update_account(current_user, avatar=args["avatar"])
+        updated_account = AccountService.update_account(current_user, avatar=args.avatar)
 
         return updated_account
 
 
-parser_interface = reqparse.RequestParser().add_argument(
-    "interface_language", type=supported_language, required=True, location="json"
-)
-
-
 @console_ns.route("/account/interface-language")
 class AccountInterfaceLanguageApi(Resource):
-    @console_ns.expect(parser_interface)
+    @console_ns.expect(console_ns.models[AccountInterfaceLanguagePayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @marshal_with(account_fields)
     def post(self):
         current_user, _ = current_account_with_tenant()
-        args = parser_interface.parse_args()
+        payload = console_ns.payload or {}
+        args = AccountInterfaceLanguagePayload.model_validate(payload)
 
-        updated_account = AccountService.update_account(current_user, interface_language=args["interface_language"])
+        updated_account = AccountService.update_account(current_user, interface_language=args.interface_language)
 
         return updated_account
 
 
-parser_theme = reqparse.RequestParser().add_argument(
-    "interface_theme", type=str, choices=["light", "dark"], required=True, location="json"
-)
-
-
 @console_ns.route("/account/interface-theme")
 class AccountInterfaceThemeApi(Resource):
-    @console_ns.expect(parser_theme)
+    @console_ns.expect(console_ns.models[AccountInterfaceThemePayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @marshal_with(account_fields)
     def post(self):
         current_user, _ = current_account_with_tenant()
-        args = parser_theme.parse_args()
+        payload = console_ns.payload or {}
+        args = AccountInterfaceThemePayload.model_validate(payload)
 
-        updated_account = AccountService.update_account(current_user, interface_theme=args["interface_theme"])
+        updated_account = AccountService.update_account(current_user, interface_theme=args.interface_theme)
 
         return updated_account
 
 
-parser_timezone = reqparse.RequestParser().add_argument("timezone", type=str, required=True, location="json")
-
-
 @console_ns.route("/account/timezone")
 class AccountTimezoneApi(Resource):
-    @console_ns.expect(parser_timezone)
+    @console_ns.expect(console_ns.models[AccountTimezonePayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @marshal_with(account_fields)
     def post(self):
         current_user, _ = current_account_with_tenant()
-        args = parser_timezone.parse_args()
+        payload = console_ns.payload or {}
+        args = AccountTimezonePayload.model_validate(payload)
 
-        # Validate timezone string, e.g. America/New_York, Asia/Shanghai
-        if args["timezone"] not in pytz.all_timezones:
-            raise ValueError("Invalid timezone string.")
-
-        updated_account = AccountService.update_account(current_user, timezone=args["timezone"])
+        updated_account = AccountService.update_account(current_user, timezone=args.timezone)
 
         return updated_account
 
 
-parser_pw = (
-    reqparse.RequestParser()
-    .add_argument("password", type=str, required=False, location="json")
-    .add_argument("new_password", type=str, required=True, location="json")
-    .add_argument("repeat_new_password", type=str, required=True, location="json")
-)
-
-
 @console_ns.route("/account/password")
 class AccountPasswordApi(Resource):
-    @console_ns.expect(parser_pw)
+    @console_ns.expect(console_ns.models[AccountPasswordPayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @marshal_with(account_fields)
     def post(self):
         current_user, _ = current_account_with_tenant()
-        args = parser_pw.parse_args()
-
-        if args["new_password"] != args["repeat_new_password"]:
-            raise RepeatPasswordNotMatchError()
+        payload = console_ns.payload or {}
+        args = AccountPasswordPayload.model_validate(payload)
 
         try:
-            AccountService.update_account_password(current_user, args["password"], args["new_password"])
+            AccountService.update_account_password(current_user, args.password, args.new_password)
         except ServiceCurrentPasswordIncorrectError:
             raise CurrentPasswordIncorrectError()
 
@@ -316,25 +464,19 @@ class AccountDeleteVerifyApi(Resource):
         return {"result": "success", "data": token}
 
 
-parser_delete = (
-    reqparse.RequestParser()
-    .add_argument("token", type=str, required=True, location="json")
-    .add_argument("code", type=str, required=True, location="json")
-)
-
-
 @console_ns.route("/account/delete")
 class AccountDeleteApi(Resource):
-    @console_ns.expect(parser_delete)
+    @console_ns.expect(console_ns.models[AccountDeletePayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def post(self):
         account, _ = current_account_with_tenant()
 
-        args = parser_delete.parse_args()
+        payload = console_ns.payload or {}
+        args = AccountDeletePayload.model_validate(payload)
 
-        if not AccountService.verify_account_deletion_code(args["token"], args["code"]):
+        if not AccountService.verify_account_deletion_code(args.token, args.code):
             raise InvalidAccountDeletionCodeError()
 
         AccountService.delete_account(account)
@@ -342,21 +484,15 @@ class AccountDeleteApi(Resource):
         return {"result": "success"}
 
 
-parser_feedback = (
-    reqparse.RequestParser()
-    .add_argument("email", type=str, required=True, location="json")
-    .add_argument("feedback", type=str, required=True, location="json")
-)
-
-
 @console_ns.route("/account/delete/feedback")
 class AccountDeleteUpdateFeedbackApi(Resource):
-    @console_ns.expect(parser_feedback)
+    @console_ns.expect(console_ns.models[AccountDeletionFeedbackPayload.__name__])
     @setup_required
     def post(self):
-        args = parser_feedback.parse_args()
+        payload = console_ns.payload or {}
+        args = AccountDeletionFeedbackPayload.model_validate(payload)
 
-        BillingService.update_account_deletion_feedback(args["email"], args["feedback"])
+        BillingService.update_account_deletion_feedback(args.email, args.feedback)
 
         return {"result": "success"}
 
@@ -379,14 +515,6 @@ class EducationVerifyApi(Resource):
         return BillingService.EducationIdentity.verify(account.id, account.email)
 
 
-parser_edu = (
-    reqparse.RequestParser()
-    .add_argument("token", type=str, required=True, location="json")
-    .add_argument("institution", type=str, required=True, location="json")
-    .add_argument("role", type=str, required=True, location="json")
-)
-
-
 @console_ns.route("/account/education")
 class EducationApi(Resource):
     status_fields = {
@@ -396,7 +524,7 @@ class EducationApi(Resource):
         "allow_refresh": fields.Boolean,
     }
 
-    @console_ns.expect(parser_edu)
+    @console_ns.expect(console_ns.models[EducationActivatePayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -405,9 +533,10 @@ class EducationApi(Resource):
     def post(self):
         account, _ = current_account_with_tenant()
 
-        args = parser_edu.parse_args()
+        payload = console_ns.payload or {}
+        args = EducationActivatePayload.model_validate(payload)
 
-        return BillingService.EducationIdentity.activate(account, args["token"], args["institution"], args["role"])
+        return BillingService.EducationIdentity.activate(account, args.token, args.institution, args.role)
 
     @setup_required
     @login_required
@@ -425,14 +554,6 @@ class EducationApi(Resource):
         return res
 
 
-parser_autocomplete = (
-    reqparse.RequestParser()
-    .add_argument("keywords", type=str, required=True, location="args")
-    .add_argument("page", type=int, required=False, location="args", default=0)
-    .add_argument("limit", type=int, required=False, location="args", default=20)
-)
-
-
 @console_ns.route("/account/education/autocomplete")
 class EducationAutoCompleteApi(Resource):
     data_fields = {
@@ -441,7 +562,7 @@ class EducationAutoCompleteApi(Resource):
         "has_next": fields.Boolean,
     }
 
-    @console_ns.expect(parser_autocomplete)
+    @console_ns.expect(console_ns.models[EducationAutocompleteQuery.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -449,46 +570,39 @@ class EducationAutoCompleteApi(Resource):
     @cloud_edition_billing_enabled
     @marshal_with(data_fields)
     def get(self):
-        args = parser_autocomplete.parse_args()
+        payload = request.args.to_dict(flat=True)  # type: ignore
+        args = EducationAutocompleteQuery.model_validate(payload)
 
-        return BillingService.EducationIdentity.autocomplete(args["keywords"], args["page"], args["limit"])
-
-
-parser_change_email = (
-    reqparse.RequestParser()
-    .add_argument("email", type=email, required=True, location="json")
-    .add_argument("language", type=str, required=False, location="json")
-    .add_argument("phase", type=str, required=False, location="json")
-    .add_argument("token", type=str, required=False, location="json")
-)
+        return BillingService.EducationIdentity.autocomplete(args.keywords, args.page, args.limit)
 
 
 @console_ns.route("/account/change-email")
 class ChangeEmailSendEmailApi(Resource):
-    @console_ns.expect(parser_change_email)
+    @console_ns.expect(console_ns.models[ChangeEmailSendPayload.__name__])
     @enable_change_email
     @setup_required
     @login_required
     @account_initialization_required
     def post(self):
         current_user, _ = current_account_with_tenant()
-        args = parser_change_email.parse_args()
+        payload = console_ns.payload or {}
+        args = ChangeEmailSendPayload.model_validate(payload)
 
         ip_address = extract_remote_ip(request)
         if AccountService.is_email_send_ip_limit(ip_address):
             raise EmailSendIpLimitError()
 
-        if args["language"] is not None and args["language"] == "zh-Hans":
+        if args.language is not None and args.language == "zh-Hans":
             language = "zh-Hans"
         else:
             language = "en-US"
         account = None
-        user_email = args["email"]
-        if args["phase"] is not None and args["phase"] == "new_email":
-            if args["token"] is None:
+        user_email = args.email
+        if args.phase is not None and args.phase == "new_email":
+            if args.token is None:
                 raise InvalidTokenError()
 
-            reset_data = AccountService.get_change_email_data(args["token"])
+            reset_data = AccountService.get_change_email_data(args.token)
             if reset_data is None:
                 raise InvalidTokenError()
             user_email = reset_data.get("email", "")
@@ -497,118 +611,103 @@ class ChangeEmailSendEmailApi(Resource):
                 raise InvalidEmailError()
         else:
             with Session(db.engine) as session:
-                account = session.execute(select(Account).filter_by(email=args["email"])).scalar_one_or_none()
+                account = session.execute(select(Account).filter_by(email=args.email)).scalar_one_or_none()
             if account is None:
                 raise AccountNotFound()
 
         token = AccountService.send_change_email_email(
-            account=account, email=args["email"], old_email=user_email, language=language, phase=args["phase"]
+            account=account, email=args.email, old_email=user_email, language=language, phase=args.phase
         )
         return {"result": "success", "data": token}
 
 
-parser_validity = (
-    reqparse.RequestParser()
-    .add_argument("email", type=email, required=True, location="json")
-    .add_argument("code", type=str, required=True, location="json")
-    .add_argument("token", type=str, required=True, nullable=False, location="json")
-)
-
-
 @console_ns.route("/account/change-email/validity")
 class ChangeEmailCheckApi(Resource):
-    @console_ns.expect(parser_validity)
+    @console_ns.expect(console_ns.models[ChangeEmailValidityPayload.__name__])
     @enable_change_email
     @setup_required
     @login_required
     @account_initialization_required
     def post(self):
-        args = parser_validity.parse_args()
+        payload = console_ns.payload or {}
+        args = ChangeEmailValidityPayload.model_validate(payload)
 
-        user_email = args["email"]
+        user_email = args.email
 
-        is_change_email_error_rate_limit = AccountService.is_change_email_error_rate_limit(args["email"])
+        is_change_email_error_rate_limit = AccountService.is_change_email_error_rate_limit(args.email)
         if is_change_email_error_rate_limit:
             raise EmailChangeLimitError()
 
-        token_data = AccountService.get_change_email_data(args["token"])
+        token_data = AccountService.get_change_email_data(args.token)
         if token_data is None:
             raise InvalidTokenError()
 
         if user_email != token_data.get("email"):
             raise InvalidEmailError()
 
-        if args["code"] != token_data.get("code"):
-            AccountService.add_change_email_error_rate_limit(args["email"])
+        if args.code != token_data.get("code"):
+            AccountService.add_change_email_error_rate_limit(args.email)
             raise EmailCodeError()
 
         # Verified, revoke the first token
-        AccountService.revoke_change_email_token(args["token"])
+        AccountService.revoke_change_email_token(args.token)
 
         # Refresh token data by generating a new token
         _, new_token = AccountService.generate_change_email_token(
-            user_email, code=args["code"], old_email=token_data.get("old_email"), additional_data={}
+            user_email, code=args.code, old_email=token_data.get("old_email"), additional_data={}
         )
 
-        AccountService.reset_change_email_error_rate_limit(args["email"])
+        AccountService.reset_change_email_error_rate_limit(args.email)
         return {"is_valid": True, "email": token_data.get("email"), "token": new_token}
 
 
-parser_reset = (
-    reqparse.RequestParser()
-    .add_argument("new_email", type=email, required=True, location="json")
-    .add_argument("token", type=str, required=True, nullable=False, location="json")
-)
-
-
 @console_ns.route("/account/change-email/reset")
 class ChangeEmailResetApi(Resource):
-    @console_ns.expect(parser_reset)
+    @console_ns.expect(console_ns.models[ChangeEmailResetPayload.__name__])
     @enable_change_email
     @setup_required
     @login_required
     @account_initialization_required
     @marshal_with(account_fields)
     def post(self):
-        args = parser_reset.parse_args()
+        payload = console_ns.payload or {}
+        args = ChangeEmailResetPayload.model_validate(payload)
 
-        if AccountService.is_account_in_freeze(args["new_email"]):
+        if AccountService.is_account_in_freeze(args.new_email):
             raise AccountInFreezeError()
 
-        if not AccountService.check_email_unique(args["new_email"]):
+        if not AccountService.check_email_unique(args.new_email):
             raise EmailAlreadyInUseError()
 
-        reset_data = AccountService.get_change_email_data(args["token"])
+        reset_data = AccountService.get_change_email_data(args.token)
         if not reset_data:
             raise InvalidTokenError()
 
-        AccountService.revoke_change_email_token(args["token"])
+        AccountService.revoke_change_email_token(args.token)
 
         old_email = reset_data.get("old_email", "")
         current_user, _ = current_account_with_tenant()
         if current_user.email != old_email:
             raise AccountNotFound()
 
-        updated_account = AccountService.update_account_email(current_user, email=args["new_email"])
+        updated_account = AccountService.update_account_email(current_user, email=args.new_email)
 
         AccountService.send_change_email_completed_notify_email(
-            email=args["new_email"],
+            email=args.new_email,
         )
 
         return updated_account
 
 
-parser_check = reqparse.RequestParser().add_argument("email", type=email, required=True, location="json")
-
-
 @console_ns.route("/account/change-email/check-email-unique")
 class CheckEmailUnique(Resource):
-    @console_ns.expect(parser_check)
+    @console_ns.expect(console_ns.models[CheckEmailUniquePayload.__name__])
     @setup_required
     def post(self):
-        args = parser_check.parse_args()
-        if AccountService.is_account_in_freeze(args["email"]):
+        payload = console_ns.payload or {}
+        args = CheckEmailUniquePayload.model_validate(payload)
+        if AccountService.is_account_in_freeze(args.email):
             raise AccountInFreezeError()
-        if not AccountService.check_email_unique(args["email"]):
+        if not AccountService.check_email_unique(args.email):
             raise EmailAlreadyInUseError()
         return {"result": "success"}

api/controllers/console/workspace/members.py

@@ -1,7 +1,8 @@
 from urllib import parse
 
 from flask import abort, request
-from flask_restx import Resource, marshal_with, reqparse
+from flask_restx import Resource, marshal_with
+from pydantic import BaseModel, Field
 
 import services
 from configs import dify_config
@@ -31,6 +32,53 @@ from services.account_service import AccountService, RegisterService, TenantServ
 from services.errors.account import AccountAlreadyInTenantError
 from services.feature_service import FeatureService
 
+DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
+
+
+class MemberInvitePayload(BaseModel):
+    emails: list[str] = Field(default_factory=list)
+    role: TenantAccountRole
+    language: str | None = None
+
+
+class MemberRoleUpdatePayload(BaseModel):
+    role: str
+
+
+class OwnerTransferEmailPayload(BaseModel):
+    language: str | None = None
+
+
+class OwnerTransferCheckPayload(BaseModel):
+    code: str
+    token: str
+
+
+class OwnerTransferPayload(BaseModel):
+    token: str
+
+
+console_ns.schema_model(
+    MemberInvitePayload.__name__,
+    MemberInvitePayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    MemberRoleUpdatePayload.__name__,
+    MemberRoleUpdatePayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    OwnerTransferEmailPayload.__name__,
+    OwnerTransferEmailPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    OwnerTransferCheckPayload.__name__,
+    OwnerTransferCheckPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+console_ns.schema_model(
+    OwnerTransferPayload.__name__,
+    OwnerTransferPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
 
 @console_ns.route("/workspaces/current/members")
 class MemberListApi(Resource):
@@ -48,29 +96,22 @@ class MemberListApi(Resource):
         return {"result": "success", "accounts": members}, 200
 
 
-parser_invite = (
-    reqparse.RequestParser()
-    .add_argument("emails", type=list, required=True, location="json")
-    .add_argument("role", type=str, required=True, default="admin", location="json")
-    .add_argument("language", type=str, required=False, location="json")
-)
-
-
 @console_ns.route("/workspaces/current/members/invite-email")
 class MemberInviteEmailApi(Resource):
     """Invite a new member by email."""
 
-    @console_ns.expect(parser_invite)
+    @console_ns.expect(console_ns.models[MemberInvitePayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @cloud_edition_billing_resource_check("members")
     def post(self):
-        args = parser_invite.parse_args()
+        payload = console_ns.payload or {}
+        args = MemberInvitePayload.model_validate(payload)
 
-        invitee_emails = args["emails"]
-        invitee_role = args["role"]
-        interface_language = args["language"]
+        invitee_emails = args.emails
+        invitee_role = args.role
+        interface_language = args.language
         if not TenantAccountRole.is_non_owner_role(invitee_role):
             return {"code": "invalid-role", "message": "Invalid role"}, 400
         current_user, _ = current_account_with_tenant()
@@ -146,20 +187,18 @@ class MemberCancelInviteApi(Resource):
         }, 200
 
 
-parser_update = reqparse.RequestParser().add_argument("role", type=str, required=True, location="json")
-
-
 @console_ns.route("/workspaces/current/members/<uuid:member_id>/update-role")
 class MemberUpdateRoleApi(Resource):
     """Update member role."""
 
-    @console_ns.expect(parser_update)
+    @console_ns.expect(console_ns.models[MemberRoleUpdatePayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def put(self, member_id):
-        args = parser_update.parse_args()
-        new_role = args["role"]
+        payload = console_ns.payload or {}
+        args = MemberRoleUpdatePayload.model_validate(payload)
+        new_role = args.role
 
         if not TenantAccountRole.is_valid_role(new_role):
             return {"code": "invalid-role", "message": "Invalid role"}, 400
@@ -197,20 +236,18 @@ class DatasetOperatorMemberListApi(Resource):
         return {"result": "success", "accounts": members}, 200
 
 
-parser_send = reqparse.RequestParser().add_argument("language", type=str, required=False, location="json")
-
-
 @console_ns.route("/workspaces/current/members/send-owner-transfer-confirm-email")
 class SendOwnerTransferEmailApi(Resource):
     """Send owner transfer email."""
 
-    @console_ns.expect(parser_send)
+    @console_ns.expect(console_ns.models[OwnerTransferEmailPayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @is_allow_transfer_owner
     def post(self):
-        args = parser_send.parse_args()
+        payload = console_ns.payload or {}
+        args = OwnerTransferEmailPayload.model_validate(payload)
         ip_address = extract_remote_ip(request)
         if AccountService.is_email_send_ip_limit(ip_address):
             raise EmailSendIpLimitError()
@@ -221,7 +258,7 @@ class SendOwnerTransferEmailApi(Resource):
         if not TenantService.is_owner(current_user, current_user.current_tenant):
             raise NotOwnerError()
 
-        if args["language"] is not None and args["language"] == "zh-Hans":
+        if args.language is not None and args.language == "zh-Hans":
             language = "zh-Hans"
         else:
             language = "en-US"
@@ -238,22 +275,16 @@ class SendOwnerTransferEmailApi(Resource):
         return {"result": "success", "data": token}
 
 
-parser_owner = (
-    reqparse.RequestParser()
-    .add_argument("code", type=str, required=True, location="json")
-    .add_argument("token", type=str, required=True, nullable=False, location="json")
-)
-
-
 @console_ns.route("/workspaces/current/members/owner-transfer-check")
 class OwnerTransferCheckApi(Resource):
-    @console_ns.expect(parser_owner)
+    @console_ns.expect(console_ns.models[OwnerTransferCheckPayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @is_allow_transfer_owner
     def post(self):
-        args = parser_owner.parse_args()
+        payload = console_ns.payload or {}
+        args = OwnerTransferCheckPayload.model_validate(payload)
         # check if the current user is the owner of the workspace
         current_user, _ = current_account_with_tenant()
         if not current_user.current_tenant:
@@ -267,41 +298,37 @@ class OwnerTransferCheckApi(Resource):
         if is_owner_transfer_error_rate_limit:
             raise OwnerTransferLimitError()
 
-        token_data = AccountService.get_owner_transfer_data(args["token"])
+        token_data = AccountService.get_owner_transfer_data(args.token)
         if token_data is None:
             raise InvalidTokenError()
 
         if user_email != token_data.get("email"):
             raise InvalidEmailError()
 
-        if args["code"] != token_data.get("code"):
+        if args.code != token_data.get("code"):
             AccountService.add_owner_transfer_error_rate_limit(user_email)
             raise EmailCodeError()
 
         # Verified, revoke the first token
-        AccountService.revoke_owner_transfer_token(args["token"])
+        AccountService.revoke_owner_transfer_token(args.token)
 
         # Refresh token data by generating a new token
-        _, new_token = AccountService.generate_owner_transfer_token(user_email, code=args["code"], additional_data={})
+        _, new_token = AccountService.generate_owner_transfer_token(user_email, code=args.code, additional_data={})
 
         AccountService.reset_owner_transfer_error_rate_limit(user_email)
         return {"is_valid": True, "email": token_data.get("email"), "token": new_token}
 
 
-parser_owner_transfer = reqparse.RequestParser().add_argument(
-    "token", type=str, required=True, nullable=False, location="json"
-)
-
-
 @console_ns.route("/workspaces/current/members/<uuid:member_id>/owner-transfer")
 class OwnerTransfer(Resource):
-    @console_ns.expect(parser_owner_transfer)
+    @console_ns.expect(console_ns.models[OwnerTransferPayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @is_allow_transfer_owner
     def post(self, member_id):
-        args = parser_owner_transfer.parse_args()
+        payload = console_ns.payload or {}
+        args = OwnerTransferPayload.model_validate(payload)
 
         # check if the current user is the owner of the workspace
         current_user, _ = current_account_with_tenant()
@@ -313,14 +340,14 @@ class OwnerTransfer(Resource):
         if current_user.id == str(member_id):
             raise CannotTransferOwnerToSelfError()
 
-        transfer_token_data = AccountService.get_owner_transfer_data(args["token"])
+        transfer_token_data = AccountService.get_owner_transfer_data(args.token)
         if not transfer_token_data:
             raise InvalidTokenError()
 
         if transfer_token_data.get("email") != current_user.email:
             raise InvalidEmailError()
 
-        AccountService.revoke_owner_transfer_token(args["token"])
+        AccountService.revoke_owner_transfer_token(args.token)
 
         member = db.session.get(Account, str(member_id))
         if not member:

api/controllers/console/workspace/model_providers.py

@@ -1,31 +1,123 @@
 import io
+from typing import Any, Literal
 
-from flask import send_file
-from flask_restx import Resource, reqparse
+from flask import request, send_file
+from flask_restx import Resource
+from pydantic import BaseModel, Field, field_validator
 
 from controllers.console import console_ns
 from controllers.console.wraps import account_initialization_required, is_admin_or_owner_required, setup_required
 from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.utils.encoders import jsonable_encoder
-from libs.helper import StrLen, uuid_value
+from libs.helper import uuid_value
 from libs.login import current_account_with_tenant, login_required
 from services.billing_service import BillingService
 from services.model_provider_service import ModelProviderService
 
-parser_model = reqparse.RequestParser().add_argument(
-    "model_type",
-    type=str,
-    required=False,
-    nullable=True,
-    choices=[mt.value for mt in ModelType],
-    location="args",
+DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
+
+
+class ParserModelList(BaseModel):
+    model_type: ModelType | None = None
+
+
+class ParserCredentialId(BaseModel):
+    credential_id: str | None = None
+
+    @field_validator("credential_id")
+    @classmethod
+    def validate_optional_credential_id(cls, value: str | None) -> str | None:
+        if value is None:
+            return value
+        return uuid_value(value)
+
+
+class ParserCredentialCreate(BaseModel):
+    credentials: dict[str, Any]
+    name: str | None = Field(default=None, max_length=30)
+
+
+class ParserCredentialUpdate(BaseModel):
+    credential_id: str
+    credentials: dict[str, Any]
+    name: str | None = Field(default=None, max_length=30)
+
+    @field_validator("credential_id")
+    @classmethod
+    def validate_update_credential_id(cls, value: str) -> str:
+        return uuid_value(value)
+
+
+class ParserCredentialDelete(BaseModel):
+    credential_id: str
+
+    @field_validator("credential_id")
+    @classmethod
+    def validate_delete_credential_id(cls, value: str) -> str:
+        return uuid_value(value)
+
+
+class ParserCredentialSwitch(BaseModel):
+    credential_id: str
+
+    @field_validator("credential_id")
+    @classmethod
+    def validate_switch_credential_id(cls, value: str) -> str:
+        return uuid_value(value)
+
+
+class ParserCredentialValidate(BaseModel):
+    credentials: dict[str, Any]
+
+
+class ParserPreferredProviderType(BaseModel):
+    preferred_provider_type: Literal["system", "custom"]
+
+
+console_ns.schema_model(
+    ParserModelList.__name__, ParserModelList.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+console_ns.schema_model(
+    ParserCredentialId.__name__,
+    ParserCredentialId.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserCredentialCreate.__name__,
+    ParserCredentialCreate.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserCredentialUpdate.__name__,
+    ParserCredentialUpdate.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserCredentialDelete.__name__,
+    ParserCredentialDelete.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserCredentialSwitch.__name__,
+    ParserCredentialSwitch.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserCredentialValidate.__name__,
+    ParserCredentialValidate.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserPreferredProviderType.__name__,
+    ParserPreferredProviderType.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
 )
 
 
 @console_ns.route("/workspaces/current/model-providers")
 class ModelProviderListApi(Resource):
-    @console_ns.expect(parser_model)
+    @console_ns.expect(console_ns.models[ParserModelList.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -33,38 +125,18 @@ class ModelProviderListApi(Resource):
         _, current_tenant_id = current_account_with_tenant()
         tenant_id = current_tenant_id
 
-        args = parser_model.parse_args()
+        payload = request.args.to_dict(flat=True)  # type: ignore
+        args = ParserModelList.model_validate(payload)
 
         model_provider_service = ModelProviderService()
-        provider_list = model_provider_service.get_provider_list(tenant_id=tenant_id, model_type=args.get("model_type"))
+        provider_list = model_provider_service.get_provider_list(tenant_id=tenant_id, model_type=args.model_type)
 
         return jsonable_encoder({"data": provider_list})
 
 
-parser_cred = reqparse.RequestParser().add_argument(
-    "credential_id", type=uuid_value, required=False, nullable=True, location="args"
-)
-parser_post_cred = (
-    reqparse.RequestParser()
-    .add_argument("credentials", type=dict, required=True, nullable=False, location="json")
-    .add_argument("name", type=StrLen(30), required=False, nullable=True, location="json")
-)
-
-parser_put_cred = (
-    reqparse.RequestParser()
-    .add_argument("credential_id", type=uuid_value, required=True, nullable=False, location="json")
-    .add_argument("credentials", type=dict, required=True, nullable=False, location="json")
-    .add_argument("name", type=StrLen(30), required=False, nullable=True, location="json")
-)
-
-parser_delete_cred = reqparse.RequestParser().add_argument(
-    "credential_id", type=uuid_value, required=True, nullable=False, location="json"
-)
-
-
 @console_ns.route("/workspaces/current/model-providers/<path:provider>/credentials")
 class ModelProviderCredentialApi(Resource):
-    @console_ns.expect(parser_cred)
+    @console_ns.expect(console_ns.models[ParserCredentialId.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -72,23 +144,25 @@ class ModelProviderCredentialApi(Resource):
         _, current_tenant_id = current_account_with_tenant()
         tenant_id = current_tenant_id
         # if credential_id is not provided, return current used credential
-        args = parser_cred.parse_args()
+        payload = request.args.to_dict(flat=True)  # type: ignore
+        args = ParserCredentialId.model_validate(payload)
 
         model_provider_service = ModelProviderService()
         credentials = model_provider_service.get_provider_credential(
-            tenant_id=tenant_id, provider=provider, credential_id=args.get("credential_id")
+            tenant_id=tenant_id, provider=provider, credential_id=args.credential_id
         )
 
         return {"credentials": credentials}
 
-    @console_ns.expect(parser_post_cred)
+    @console_ns.expect(console_ns.models[ParserCredentialCreate.__name__])
     @setup_required
     @login_required
     @is_admin_or_owner_required
     @account_initialization_required
     def post(self, provider: str):
         _, current_tenant_id = current_account_with_tenant()
-        args = parser_post_cred.parse_args()
+        payload = console_ns.payload or {}
+        args = ParserCredentialCreate.model_validate(payload)
 
         model_provider_service = ModelProviderService()
 
@@ -96,15 +170,15 @@ class ModelProviderCredentialApi(Resource):
             model_provider_service.create_provider_credential(
                 tenant_id=current_tenant_id,
                 provider=provider,
-                credentials=args["credentials"],
-                credential_name=args["name"],
+                credentials=args.credentials,
+                credential_name=args.name,
             )
         except CredentialsValidateFailedError as ex:
             raise ValueError(str(ex))
 
         return {"result": "success"}, 201
 
-    @console_ns.expect(parser_put_cred)
+    @console_ns.expect(console_ns.models[ParserCredentialUpdate.__name__])
     @setup_required
     @login_required
     @is_admin_or_owner_required
@@ -112,7 +186,8 @@ class ModelProviderCredentialApi(Resource):
     def put(self, provider: str):
         _, current_tenant_id = current_account_with_tenant()
 
-        args = parser_put_cred.parse_args()
+        payload = console_ns.payload or {}
+        args = ParserCredentialUpdate.model_validate(payload)
 
         model_provider_service = ModelProviderService()
 
@@ -120,71 +195,64 @@ class ModelProviderCredentialApi(Resource):
             model_provider_service.update_provider_credential(
                 tenant_id=current_tenant_id,
                 provider=provider,
-                credentials=args["credentials"],
-                credential_id=args["credential_id"],
-                credential_name=args["name"],
+                credentials=args.credentials,
+                credential_id=args.credential_id,
+                credential_name=args.name,
             )
         except CredentialsValidateFailedError as ex:
             raise ValueError(str(ex))
 
         return {"result": "success"}
 
-    @console_ns.expect(parser_delete_cred)
+    @console_ns.expect(console_ns.models[ParserCredentialDelete.__name__])
     @setup_required
     @login_required
     @is_admin_or_owner_required
     @account_initialization_required
     def delete(self, provider: str):
         _, current_tenant_id = current_account_with_tenant()
-        args = parser_delete_cred.parse_args()
+        payload = console_ns.payload or {}
+        args = ParserCredentialDelete.model_validate(payload)
 
         model_provider_service = ModelProviderService()
         model_provider_service.remove_provider_credential(
-            tenant_id=current_tenant_id, provider=provider, credential_id=args["credential_id"]
+            tenant_id=current_tenant_id, provider=provider, credential_id=args.credential_id
         )
 
         return {"result": "success"}, 204
 
 
-parser_switch = reqparse.RequestParser().add_argument(
-    "credential_id", type=str, required=True, nullable=False, location="json"
-)
-
-
 @console_ns.route("/workspaces/current/model-providers/<path:provider>/credentials/switch")
 class ModelProviderCredentialSwitchApi(Resource):
-    @console_ns.expect(parser_switch)
+    @console_ns.expect(console_ns.models[ParserCredentialSwitch.__name__])
     @setup_required
     @login_required
     @is_admin_or_owner_required
     @account_initialization_required
     def post(self, provider: str):
         _, current_tenant_id = current_account_with_tenant()
-        args = parser_switch.parse_args()
+        payload = console_ns.payload or {}
+        args = ParserCredentialSwitch.model_validate(payload)
 
         service = ModelProviderService()
         service.switch_active_provider_credential(
             tenant_id=current_tenant_id,
             provider=provider,
-            credential_id=args["credential_id"],
+            credential_id=args.credential_id,
         )
         return {"result": "success"}
 
 
-parser_validate = reqparse.RequestParser().add_argument(
-    "credentials", type=dict, required=True, nullable=False, location="json"
-)
-
-
 @console_ns.route("/workspaces/current/model-providers/<path:provider>/credentials/validate")
 class ModelProviderValidateApi(Resource):
-    @console_ns.expect(parser_validate)
+    @console_ns.expect(console_ns.models[ParserCredentialValidate.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def post(self, provider: str):
         _, current_tenant_id = current_account_with_tenant()
-        args = parser_validate.parse_args()
+        payload = console_ns.payload or {}
+        args = ParserCredentialValidate.model_validate(payload)
 
         tenant_id = current_tenant_id
 
@@ -195,7 +263,7 @@ class ModelProviderValidateApi(Resource):
 
         try:
             model_provider_service.validate_provider_credentials(
-                tenant_id=tenant_id, provider=provider, credentials=args["credentials"]
+                tenant_id=tenant_id, provider=provider, credentials=args.credentials
             )
         except CredentialsValidateFailedError as ex:
             result = False
@@ -228,19 +296,9 @@ class ModelProviderIconApi(Resource):
         return send_file(io.BytesIO(icon), mimetype=mimetype)
 
 
-parser_preferred = reqparse.RequestParser().add_argument(
-    "preferred_provider_type",
-    type=str,
-    required=True,
-    nullable=False,
-    choices=["system", "custom"],
-    location="json",
-)
-
-
 @console_ns.route("/workspaces/current/model-providers/<path:provider>/preferred-provider-type")
 class PreferredProviderTypeUpdateApi(Resource):
-    @console_ns.expect(parser_preferred)
+    @console_ns.expect(console_ns.models[ParserPreferredProviderType.__name__])
     @setup_required
     @login_required
     @is_admin_or_owner_required
@@ -250,11 +308,12 @@ class PreferredProviderTypeUpdateApi(Resource):
 
         tenant_id = current_tenant_id
 
-        args = parser_preferred.parse_args()
+        payload = console_ns.payload or {}
+        args = ParserPreferredProviderType.model_validate(payload)
 
         model_provider_service = ModelProviderService()
         model_provider_service.switch_preferred_provider(
-            tenant_id=tenant_id, provider=provider, preferred_provider_type=args["preferred_provider_type"]
+            tenant_id=tenant_id, provider=provider, preferred_provider_type=args.preferred_provider_type
         )
 
         return {"result": "success"}

api/controllers/console/workspace/models.py

@@ -1,52 +1,172 @@
 import logging
+from typing import Any, cast
 
-from flask_restx import Resource, reqparse
+from flask import request
+from flask_restx import Resource
+from pydantic import BaseModel, Field, field_validator
 
 from controllers.console import console_ns
 from controllers.console.wraps import account_initialization_required, is_admin_or_owner_required, setup_required
 from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.utils.encoders import jsonable_encoder
-from libs.helper import StrLen, uuid_value
+from libs.helper import uuid_value
 from libs.login import current_account_with_tenant, login_required
 from services.model_load_balancing_service import ModelLoadBalancingService
 from services.model_provider_service import ModelProviderService
 
 logger = logging.getLogger(__name__)
+DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
 
 
-parser_get_default = reqparse.RequestParser().add_argument(
-    "model_type",
-    type=str,
-    required=True,
-    nullable=False,
-    choices=[mt.value for mt in ModelType],
-    location="args",
+class ParserGetDefault(BaseModel):
+    model_type: ModelType
+
+
+class ParserPostDefault(BaseModel):
+    class Inner(BaseModel):
+        model_type: ModelType
+        model: str | None = None
+        provider: str | None = None
+
+    model_settings: list[Inner]
+
+
+console_ns.schema_model(
+    ParserGetDefault.__name__, ParserGetDefault.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
 )
-parser_post_default = reqparse.RequestParser().add_argument(
-    "model_settings", type=list, required=True, nullable=False, location="json"
+
+console_ns.schema_model(
+    ParserPostDefault.__name__, ParserPostDefault.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+
+class ParserDeleteModels(BaseModel):
+    model: str
+    model_type: ModelType
+
+
+console_ns.schema_model(
+    ParserDeleteModels.__name__, ParserDeleteModels.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+
+class LoadBalancingPayload(BaseModel):
+    configs: list[dict[str, Any]] | None = None
+    enabled: bool | None = None
+
+
+class ParserPostModels(BaseModel):
+    model: str
+    model_type: ModelType
+    load_balancing: LoadBalancingPayload | None = None
+    config_from: str | None = None
+    credential_id: str | None = None
+
+    @field_validator("credential_id")
+    @classmethod
+    def validate_credential_id(cls, value: str | None) -> str | None:
+        if value is None:
+            return value
+        return uuid_value(value)
+
+
+class ParserGetCredentials(BaseModel):
+    model: str
+    model_type: ModelType
+    config_from: str | None = None
+    credential_id: str | None = None
+
+    @field_validator("credential_id")
+    @classmethod
+    def validate_get_credential_id(cls, value: str | None) -> str | None:
+        if value is None:
+            return value
+        return uuid_value(value)
+
+
+class ParserCredentialBase(BaseModel):
+    model: str
+    model_type: ModelType
+
+
+class ParserCreateCredential(ParserCredentialBase):
+    name: str | None = Field(default=None, max_length=30)
+    credentials: dict[str, Any]
+
+
+class ParserUpdateCredential(ParserCredentialBase):
+    credential_id: str
+    credentials: dict[str, Any]
+    name: str | None = Field(default=None, max_length=30)
+
+    @field_validator("credential_id")
+    @classmethod
+    def validate_update_credential_id(cls, value: str) -> str:
+        return uuid_value(value)
+
+
+class ParserDeleteCredential(ParserCredentialBase):
+    credential_id: str
+
+    @field_validator("credential_id")
+    @classmethod
+    def validate_delete_credential_id(cls, value: str) -> str:
+        return uuid_value(value)
+
+
+class ParserParameter(BaseModel):
+    model: str
+
+
+console_ns.schema_model(
+    ParserPostModels.__name__, ParserPostModels.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+console_ns.schema_model(
+    ParserGetCredentials.__name__,
+    ParserGetCredentials.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserCreateCredential.__name__,
+    ParserCreateCredential.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserUpdateCredential.__name__,
+    ParserUpdateCredential.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserDeleteCredential.__name__,
+    ParserDeleteCredential.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserParameter.__name__, ParserParameter.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
 )
 
 
 @console_ns.route("/workspaces/current/default-model")
 class DefaultModelApi(Resource):
-    @console_ns.expect(parser_get_default)
+    @console_ns.expect(console_ns.models[ParserGetDefault.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def get(self):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_get_default.parse_args()
+        args = ParserGetDefault.model_validate(request.args.to_dict(flat=True))  # type: ignore
 
         model_provider_service = ModelProviderService()
         default_model_entity = model_provider_service.get_default_model_of_model_type(
-            tenant_id=tenant_id, model_type=args["model_type"]
+            tenant_id=tenant_id, model_type=args.model_type
         )
 
         return jsonable_encoder({"data": default_model_entity})
 
-    @console_ns.expect(parser_post_default)
+    @console_ns.expect(console_ns.models[ParserPostDefault.__name__])
     @setup_required
     @login_required
     @is_admin_or_owner_required
@@ -54,66 +174,31 @@ class DefaultModelApi(Resource):
     def post(self):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_post_default.parse_args()
+        args = ParserPostDefault.model_validate(console_ns.payload)
         model_provider_service = ModelProviderService()
-        model_settings = args["model_settings"]
+        model_settings = args.model_settings
         for model_setting in model_settings:
-            if "model_type" not in model_setting or model_setting["model_type"] not in [mt.value for mt in ModelType]:
-                raise ValueError("invalid model type")
-
-            if "provider" not in model_setting:
+            if model_setting.provider is None:
                 continue
 
-            if "model" not in model_setting:
-                raise ValueError("invalid model")
-
             try:
                 model_provider_service.update_default_model_of_model_type(
                     tenant_id=tenant_id,
-                    model_type=model_setting["model_type"],
-                    provider=model_setting["provider"],
-                    model=model_setting["model"],
+                    model_type=model_setting.model_type,
+                    provider=model_setting.provider,
+                    model=cast(str, model_setting.model),
                 )
             except Exception as ex:
                 logger.exception(
                     "Failed to update default model, model type: %s, model: %s",
-                    model_setting["model_type"],
-                    model_setting.get("model"),
+                    model_setting.model_type,
+                    model_setting.model,
                 )
                 raise ex
 
         return {"result": "success"}
 
 
-parser_post_models = (
-    reqparse.RequestParser()
-    .add_argument("model", type=str, required=True, nullable=False, location="json")
-    .add_argument(
-        "model_type",
-        type=str,
-        required=True,
-        nullable=False,
-        choices=[mt.value for mt in ModelType],
-        location="json",
-    )
-    .add_argument("load_balancing", type=dict, required=False, nullable=True, location="json")
-    .add_argument("config_from", type=str, required=False, nullable=True, location="json")
-    .add_argument("credential_id", type=uuid_value, required=False, nullable=True, location="json")
-)
-parser_delete_models = (
-    reqparse.RequestParser()
-    .add_argument("model", type=str, required=True, nullable=False, location="json")
-    .add_argument(
-        "model_type",
-        type=str,
-        required=True,
-        nullable=False,
-        choices=[mt.value for mt in ModelType],
-        location="json",
-    )
-)
-
-
 @console_ns.route("/workspaces/current/model-providers/<path:provider>/models")
 class ModelProviderModelApi(Resource):
     @setup_required
@@ -127,7 +212,7 @@ class ModelProviderModelApi(Resource):
 
         return jsonable_encoder({"data": models})
 
-    @console_ns.expect(parser_post_models)
+    @console_ns.expect(console_ns.models[ParserPostModels.__name__])
     @setup_required
     @login_required
     @is_admin_or_owner_required
@@ -135,45 +220,45 @@ class ModelProviderModelApi(Resource):
     def post(self, provider: str):
         # To save the model's load balance configs
         _, tenant_id = current_account_with_tenant()
-        args = parser_post_models.parse_args()
+        args = ParserPostModels.model_validate(console_ns.payload)
 
-        if args.get("config_from", "") == "custom-model":
-            if not args.get("credential_id"):
+        if args.config_from == "custom-model":
+            if not args.credential_id:
                 raise ValueError("credential_id is required when configuring a custom-model")
             service = ModelProviderService()
             service.switch_active_custom_model_credential(
                 tenant_id=tenant_id,
                 provider=provider,
-                model_type=args["model_type"],
-                model=args["model"],
-                credential_id=args["credential_id"],
+                model_type=args.model_type,
+                model=args.model,
+                credential_id=args.credential_id,
             )
 
         model_load_balancing_service = ModelLoadBalancingService()
 
-        if "load_balancing" in args and args["load_balancing"] and "configs" in args["load_balancing"]:
+        if args.load_balancing and args.load_balancing.configs:
             # save load balancing configs
             model_load_balancing_service.update_load_balancing_configs(
                 tenant_id=tenant_id,
                 provider=provider,
-                model=args["model"],
-                model_type=args["model_type"],
-                configs=args["load_balancing"]["configs"],
-                config_from=args.get("config_from", ""),
+                model=args.model,
+                model_type=args.model_type,
+                configs=args.load_balancing.configs,
+                config_from=args.config_from or "",
             )
 
-            if args.get("load_balancing", {}).get("enabled"):
+            if args.load_balancing.enabled:
                 model_load_balancing_service.enable_model_load_balancing(
-                    tenant_id=tenant_id, provider=provider, model=args["model"], model_type=args["model_type"]
+                    tenant_id=tenant_id, provider=provider, model=args.model, model_type=args.model_type
                 )
             else:
                 model_load_balancing_service.disable_model_load_balancing(
-                    tenant_id=tenant_id, provider=provider, model=args["model"], model_type=args["model_type"]
+                    tenant_id=tenant_id, provider=provider, model=args.model, model_type=args.model_type
                 )
 
         return {"result": "success"}, 200
 
-    @console_ns.expect(parser_delete_models)
+    @console_ns.expect(console_ns.models[ParserDeleteModels.__name__], validate=True)
     @setup_required
     @login_required
     @is_admin_or_owner_required
@@ -181,113 +266,53 @@ class ModelProviderModelApi(Resource):
     def delete(self, provider: str):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_delete_models.parse_args()
+        args = ParserDeleteModels.model_validate(console_ns.payload)
 
         model_provider_service = ModelProviderService()
         model_provider_service.remove_model(
-            tenant_id=tenant_id, provider=provider, model=args["model"], model_type=args["model_type"]
+            tenant_id=tenant_id, provider=provider, model=args.model, model_type=args.model_type
         )
 
         return {"result": "success"}, 204
 
 
-parser_get_credentials = (
-    reqparse.RequestParser()
-    .add_argument("model", type=str, required=True, nullable=False, location="args")
-    .add_argument(
-        "model_type",
-        type=str,
-        required=True,
-        nullable=False,
-        choices=[mt.value for mt in ModelType],
-        location="args",
-    )
-    .add_argument("config_from", type=str, required=False, nullable=True, location="args")
-    .add_argument("credential_id", type=uuid_value, required=False, nullable=True, location="args")
-)
-
-
-parser_post_cred = (
-    reqparse.RequestParser()
-    .add_argument("model", type=str, required=True, nullable=False, location="json")
-    .add_argument(
-        "model_type",
-        type=str,
-        required=True,
-        nullable=False,
-        choices=[mt.value for mt in ModelType],
-        location="json",
-    )
-    .add_argument("name", type=StrLen(30), required=False, nullable=True, location="json")
-    .add_argument("credentials", type=dict, required=True, nullable=False, location="json")
-)
-parser_put_cred = (
-    reqparse.RequestParser()
-    .add_argument("model", type=str, required=True, nullable=False, location="json")
-    .add_argument(
-        "model_type",
-        type=str,
-        required=True,
-        nullable=False,
-        choices=[mt.value for mt in ModelType],
-        location="json",
-    )
-    .add_argument("credential_id", type=uuid_value, required=True, nullable=False, location="json")
-    .add_argument("credentials", type=dict, required=True, nullable=False, location="json")
-    .add_argument("name", type=StrLen(30), required=False, nullable=True, location="json")
-)
-parser_delete_cred = (
-    reqparse.RequestParser()
-    .add_argument("model", type=str, required=True, nullable=False, location="json")
-    .add_argument(
-        "model_type",
-        type=str,
-        required=True,
-        nullable=False,
-        choices=[mt.value for mt in ModelType],
-        location="json",
-    )
-    .add_argument("credential_id", type=uuid_value, required=True, nullable=False, location="json")
-)
-
-
 @console_ns.route("/workspaces/current/model-providers/<path:provider>/models/credentials")
 class ModelProviderModelCredentialApi(Resource):
-    @console_ns.expect(parser_get_credentials)
+    @console_ns.expect(console_ns.models[ParserGetCredentials.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def get(self, provider: str):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_get_credentials.parse_args()
+        args = ParserGetCredentials.model_validate(request.args.to_dict(flat=True))  # type: ignore
 
         model_provider_service = ModelProviderService()
         current_credential = model_provider_service.get_model_credential(
             tenant_id=tenant_id,
             provider=provider,
-            model_type=args["model_type"],
-            model=args["model"],
-            credential_id=args.get("credential_id"),
+            model_type=args.model_type,
+            model=args.model,
+            credential_id=args.credential_id,
         )
 
         model_load_balancing_service = ModelLoadBalancingService()
         is_load_balancing_enabled, load_balancing_configs = model_load_balancing_service.get_load_balancing_configs(
             tenant_id=tenant_id,
             provider=provider,
-            model=args["model"],
-            model_type=args["model_type"],
-            config_from=args.get("config_from", ""),
+            model=args.model,
+            model_type=args.model_type,
+            config_from=args.config_from or "",
         )
 
-        if args.get("config_from", "") == "predefined-model":
+        if args.config_from == "predefined-model":
             available_credentials = model_provider_service.provider_manager.get_provider_available_credentials(
                 tenant_id=tenant_id, provider_name=provider
             )
         else:
-            model_type = ModelType.value_of(args["model_type"]).to_origin_model_type()
+            model_type = args.model_type
             available_credentials = model_provider_service.provider_manager.get_provider_model_available_credentials(
-                tenant_id=tenant_id, provider_name=provider, model_type=model_type, model_name=args["model"]
+                tenant_id=tenant_id, provider_name=provider, model_type=model_type, model_name=args.model
             )
 
         return jsonable_encoder(
@@ -304,7 +329,7 @@ class ModelProviderModelCredentialApi(Resource):
             }
         )
 
-    @console_ns.expect(parser_post_cred)
+    @console_ns.expect(console_ns.models[ParserCreateCredential.__name__])
     @setup_required
     @login_required
     @is_admin_or_owner_required
@@ -312,7 +337,7 @@ class ModelProviderModelCredentialApi(Resource):
     def post(self, provider: str):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_post_cred.parse_args()
+        args = ParserCreateCredential.model_validate(console_ns.payload)
 
         model_provider_service = ModelProviderService()
 
@@ -320,30 +345,30 @@ class ModelProviderModelCredentialApi(Resource):
             model_provider_service.create_model_credential(
                 tenant_id=tenant_id,
                 provider=provider,
-                model=args["model"],
-                model_type=args["model_type"],
-                credentials=args["credentials"],
-                credential_name=args["name"],
+                model=args.model,
+                model_type=args.model_type,
+                credentials=args.credentials,
+                credential_name=args.name,
             )
         except CredentialsValidateFailedError as ex:
             logger.exception(
                 "Failed to save model credentials, tenant_id: %s, model: %s, model_type: %s",
                 tenant_id,
-                args.get("model"),
-                args.get("model_type"),
+                args.model,
+                args.model_type,
             )
             raise ValueError(str(ex))
 
         return {"result": "success"}, 201
 
-    @console_ns.expect(parser_put_cred)
+    @console_ns.expect(console_ns.models[ParserUpdateCredential.__name__])
     @setup_required
     @login_required
     @is_admin_or_owner_required
     @account_initialization_required
     def put(self, provider: str):
         _, current_tenant_id = current_account_with_tenant()
-        args = parser_put_cred.parse_args()
+        args = ParserUpdateCredential.model_validate(console_ns.payload)
 
         model_provider_service = ModelProviderService()
 
@@ -351,106 +376,87 @@ class ModelProviderModelCredentialApi(Resource):
             model_provider_service.update_model_credential(
                 tenant_id=current_tenant_id,
                 provider=provider,
-                model_type=args["model_type"],
-                model=args["model"],
-                credentials=args["credentials"],
-                credential_id=args["credential_id"],
-                credential_name=args["name"],
+                model_type=args.model_type,
+                model=args.model,
+                credentials=args.credentials,
+                credential_id=args.credential_id,
+                credential_name=args.name,
             )
         except CredentialsValidateFailedError as ex:
             raise ValueError(str(ex))
 
         return {"result": "success"}
 
-    @console_ns.expect(parser_delete_cred)
+    @console_ns.expect(console_ns.models[ParserDeleteCredential.__name__])
     @setup_required
     @login_required
     @is_admin_or_owner_required
     @account_initialization_required
     def delete(self, provider: str):
         _, current_tenant_id = current_account_with_tenant()
-        args = parser_delete_cred.parse_args()
+        args = ParserDeleteCredential.model_validate(console_ns.payload)
 
         model_provider_service = ModelProviderService()
         model_provider_service.remove_model_credential(
             tenant_id=current_tenant_id,
             provider=provider,
-            model_type=args["model_type"],
-            model=args["model"],
-            credential_id=args["credential_id"],
+            model_type=args.model_type,
+            model=args.model,
+            credential_id=args.credential_id,
         )
 
         return {"result": "success"}, 204
 
 
-parser_switch = (
-    reqparse.RequestParser()
-    .add_argument("model", type=str, required=True, nullable=False, location="json")
-    .add_argument(
-        "model_type",
-        type=str,
-        required=True,
-        nullable=False,
-        choices=[mt.value for mt in ModelType],
-        location="json",
-    )
-    .add_argument("credential_id", type=str, required=True, nullable=False, location="json")
+class ParserSwitch(BaseModel):
+    model: str
+    model_type: ModelType
+    credential_id: str
+
+
+console_ns.schema_model(
+    ParserSwitch.__name__, ParserSwitch.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
 )
 
 
 @console_ns.route("/workspaces/current/model-providers/<path:provider>/models/credentials/switch")
 class ModelProviderModelCredentialSwitchApi(Resource):
-    @console_ns.expect(parser_switch)
+    @console_ns.expect(console_ns.models[ParserSwitch.__name__])
     @setup_required
     @login_required
     @is_admin_or_owner_required
     @account_initialization_required
     def post(self, provider: str):
         _, current_tenant_id = current_account_with_tenant()
-
-        args = parser_switch.parse_args()
+        args = ParserSwitch.model_validate(console_ns.payload)
 
         service = ModelProviderService()
         service.add_model_credential_to_model_list(
             tenant_id=current_tenant_id,
             provider=provider,
-            model_type=args["model_type"],
-            model=args["model"],
-            credential_id=args["credential_id"],
+            model_type=args.model_type,
+            model=args.model,
+            credential_id=args.credential_id,
         )
         return {"result": "success"}
 
 
-parser_model_enable_disable = (
-    reqparse.RequestParser()
-    .add_argument("model", type=str, required=True, nullable=False, location="json")
-    .add_argument(
-        "model_type",
-        type=str,
-        required=True,
-        nullable=False,
-        choices=[mt.value for mt in ModelType],
-        location="json",
-    )
-)
-
-
 @console_ns.route(
     "/workspaces/current/model-providers/<path:provider>/models/enable", endpoint="model-provider-model-enable"
 )
 class ModelProviderModelEnableApi(Resource):
-    @console_ns.expect(parser_model_enable_disable)
+    @console_ns.expect(console_ns.models[ParserDeleteModels.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def patch(self, provider: str):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_model_enable_disable.parse_args()
+        args = ParserDeleteModels.model_validate(console_ns.payload)
 
         model_provider_service = ModelProviderService()
         model_provider_service.enable_model(
-            tenant_id=tenant_id, provider=provider, model=args["model"], model_type=args["model_type"]
+            tenant_id=tenant_id, provider=provider, model=args.model, model_type=args.model_type
         )
 
         return {"result": "success"}
@@ -460,48 +466,43 @@ class ModelProviderModelEnableApi(Resource):
     "/workspaces/current/model-providers/<path:provider>/models/disable", endpoint="model-provider-model-disable"
 )
 class ModelProviderModelDisableApi(Resource):
-    @console_ns.expect(parser_model_enable_disable)
+    @console_ns.expect(console_ns.models[ParserDeleteModels.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def patch(self, provider: str):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_model_enable_disable.parse_args()
+        args = ParserDeleteModels.model_validate(console_ns.payload)
 
         model_provider_service = ModelProviderService()
         model_provider_service.disable_model(
-            tenant_id=tenant_id, provider=provider, model=args["model"], model_type=args["model_type"]
+            tenant_id=tenant_id, provider=provider, model=args.model, model_type=args.model_type
         )
 
         return {"result": "success"}
 
 
-parser_validate = (
-    reqparse.RequestParser()
-    .add_argument("model", type=str, required=True, nullable=False, location="json")
-    .add_argument(
-        "model_type",
-        type=str,
-        required=True,
-        nullable=False,
-        choices=[mt.value for mt in ModelType],
-        location="json",
-    )
-    .add_argument("credentials", type=dict, required=True, nullable=False, location="json")
+class ParserValidate(BaseModel):
+    model: str
+    model_type: ModelType
+    credentials: dict
+
+
+console_ns.schema_model(
+    ParserValidate.__name__, ParserValidate.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
 )
 
 
 @console_ns.route("/workspaces/current/model-providers/<path:provider>/models/credentials/validate")
 class ModelProviderModelValidateApi(Resource):
-    @console_ns.expect(parser_validate)
+    @console_ns.expect(console_ns.models[ParserValidate.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def post(self, provider: str):
         _, tenant_id = current_account_with_tenant()
-
-        args = parser_validate.parse_args()
+        args = ParserValidate.model_validate(console_ns.payload)
 
         model_provider_service = ModelProviderService()
 
@@ -512,9 +513,9 @@ class ModelProviderModelValidateApi(Resource):
             model_provider_service.validate_model_credentials(
                 tenant_id=tenant_id,
                 provider=provider,
-                model=args["model"],
-                model_type=args["model_type"],
-                credentials=args["credentials"],
+                model=args.model,
+                model_type=args.model_type,
+                credentials=args.credentials,
             )
         except CredentialsValidateFailedError as ex:
             result = False
@@ -528,24 +529,19 @@ class ModelProviderModelValidateApi(Resource):
         return response
 
 
-parser_parameter = reqparse.RequestParser().add_argument(
-    "model", type=str, required=True, nullable=False, location="args"
-)
-
-
 @console_ns.route("/workspaces/current/model-providers/<path:provider>/models/parameter-rules")
 class ModelProviderModelParameterRuleApi(Resource):
-    @console_ns.expect(parser_parameter)
+    @console_ns.expect(console_ns.models[ParserParameter.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def get(self, provider: str):
-        args = parser_parameter.parse_args()
+        args = ParserParameter.model_validate(request.args.to_dict(flat=True))  # type: ignore
         _, tenant_id = current_account_with_tenant()
 
         model_provider_service = ModelProviderService()
         parameter_rules = model_provider_service.get_model_parameter_rules(
-            tenant_id=tenant_id, provider=provider, model=args["model"]
+            tenant_id=tenant_id, provider=provider, model=args.model
         )
 
         return jsonable_encoder({"data": parameter_rules})

api/controllers/console/workspace/plugin.py

@@ -1,7 +1,9 @@
 import io
+from typing import Literal
 
 from flask import request, send_file
-from flask_restx import Resource, reqparse
+from flask_restx import Resource
+from pydantic import BaseModel, Field
 from werkzeug.exceptions import Forbidden
 
 from configs import dify_config
@@ -17,6 +19,8 @@ from services.plugin.plugin_parameter_service import PluginParameterService
 from services.plugin.plugin_permission_service import PluginPermissionService
 from services.plugin.plugin_service import PluginService
 
+DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
+
 
 @console_ns.route("/workspaces/current/plugin/debugging-key")
 class PluginDebuggingKeyApi(Resource):
@@ -37,88 +41,251 @@ class PluginDebuggingKeyApi(Resource):
             raise ValueError(e)
 
 
-parser_list = (
-    reqparse.RequestParser()
-    .add_argument("page", type=int, required=False, location="args", default=1)
-    .add_argument("page_size", type=int, required=False, location="args", default=256)
+class ParserList(BaseModel):
+    page: int = Field(default=1)
+    page_size: int = Field(default=256)
+
+
+console_ns.schema_model(
+    ParserList.__name__, ParserList.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
 )
 
 
 @console_ns.route("/workspaces/current/plugin/list")
 class PluginListApi(Resource):
-    @console_ns.expect(parser_list)
+    @console_ns.expect(console_ns.models[ParserList.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def get(self):
         _, tenant_id = current_account_with_tenant()
-        args = parser_list.parse_args()
+        args = ParserList.model_validate(request.args.to_dict(flat=True))  # type: ignore
         try:
-            plugins_with_total = PluginService.list_with_total(tenant_id, args["page"], args["page_size"])
+            plugins_with_total = PluginService.list_with_total(tenant_id, args.page, args.page_size)
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
         return jsonable_encoder({"plugins": plugins_with_total.list, "total": plugins_with_total.total})
 
 
-parser_latest = reqparse.RequestParser().add_argument("plugin_ids", type=list, required=True, location="json")
+class ParserLatest(BaseModel):
+    plugin_ids: list[str]
+
+
+console_ns.schema_model(
+    ParserLatest.__name__, ParserLatest.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+
+class ParserIcon(BaseModel):
+    tenant_id: str
+    filename: str
+
+
+class ParserAsset(BaseModel):
+    plugin_unique_identifier: str
+    file_name: str
+
+
+class ParserGithubUpload(BaseModel):
+    repo: str
+    version: str
+    package: str
+
+
+class ParserPluginIdentifiers(BaseModel):
+    plugin_unique_identifiers: list[str]
+
+
+class ParserGithubInstall(BaseModel):
+    plugin_unique_identifier: str
+    repo: str
+    version: str
+    package: str
+
+
+class ParserPluginIdentifierQuery(BaseModel):
+    plugin_unique_identifier: str
+
+
+class ParserTasks(BaseModel):
+    page: int
+    page_size: int
+
+
+class ParserMarketplaceUpgrade(BaseModel):
+    original_plugin_unique_identifier: str
+    new_plugin_unique_identifier: str
+
+
+class ParserGithubUpgrade(BaseModel):
+    original_plugin_unique_identifier: str
+    new_plugin_unique_identifier: str
+    repo: str
+    version: str
+    package: str
+
+
+class ParserUninstall(BaseModel):
+    plugin_installation_id: str
+
+
+class ParserPermissionChange(BaseModel):
+    install_permission: TenantPluginPermission.InstallPermission
+    debug_permission: TenantPluginPermission.DebugPermission
+
+
+class ParserDynamicOptions(BaseModel):
+    plugin_id: str
+    provider: str
+    action: str
+    parameter: str
+    credential_id: str | None = None
+    provider_type: Literal["tool", "trigger"]
+
+
+class PluginPermissionSettingsPayload(BaseModel):
+    install_permission: TenantPluginPermission.InstallPermission = TenantPluginPermission.InstallPermission.EVERYONE
+    debug_permission: TenantPluginPermission.DebugPermission = TenantPluginPermission.DebugPermission.EVERYONE
+
+
+class PluginAutoUpgradeSettingsPayload(BaseModel):
+    strategy_setting: TenantPluginAutoUpgradeStrategy.StrategySetting = (
+        TenantPluginAutoUpgradeStrategy.StrategySetting.FIX_ONLY
+    )
+    upgrade_time_of_day: int = 0
+    upgrade_mode: TenantPluginAutoUpgradeStrategy.UpgradeMode = TenantPluginAutoUpgradeStrategy.UpgradeMode.EXCLUDE
+    exclude_plugins: list[str] = Field(default_factory=list)
+    include_plugins: list[str] = Field(default_factory=list)
+
+
+class ParserPreferencesChange(BaseModel):
+    permission: PluginPermissionSettingsPayload
+    auto_upgrade: PluginAutoUpgradeSettingsPayload
+
+
+class ParserExcludePlugin(BaseModel):
+    plugin_id: str
+
+
+class ParserReadme(BaseModel):
+    plugin_unique_identifier: str
+    language: str = Field(default="en-US")
+
+
+console_ns.schema_model(
+    ParserIcon.__name__, ParserIcon.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+console_ns.schema_model(
+    ParserAsset.__name__, ParserAsset.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+console_ns.schema_model(
+    ParserGithubUpload.__name__, ParserGithubUpload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+console_ns.schema_model(
+    ParserPluginIdentifiers.__name__,
+    ParserPluginIdentifiers.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserGithubInstall.__name__, ParserGithubInstall.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+console_ns.schema_model(
+    ParserPluginIdentifierQuery.__name__,
+    ParserPluginIdentifierQuery.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserTasks.__name__, ParserTasks.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+console_ns.schema_model(
+    ParserMarketplaceUpgrade.__name__,
+    ParserMarketplaceUpgrade.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserGithubUpgrade.__name__, ParserGithubUpgrade.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+console_ns.schema_model(
+    ParserUninstall.__name__, ParserUninstall.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+console_ns.schema_model(
+    ParserPermissionChange.__name__,
+    ParserPermissionChange.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserDynamicOptions.__name__,
+    ParserDynamicOptions.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserPreferencesChange.__name__,
+    ParserPreferencesChange.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserExcludePlugin.__name__,
+    ParserExcludePlugin.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    ParserReadme.__name__, ParserReadme.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
 
 
 @console_ns.route("/workspaces/current/plugin/list/latest-versions")
 class PluginListLatestVersionsApi(Resource):
-    @console_ns.expect(parser_latest)
+    @console_ns.expect(console_ns.models[ParserLatest.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def post(self):
-        args = parser_latest.parse_args()
+        args = ParserLatest.model_validate(console_ns.payload)
 
         try:
-            versions = PluginService.list_latest_versions(args["plugin_ids"])
+            versions = PluginService.list_latest_versions(args.plugin_ids)
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
         return jsonable_encoder({"versions": versions})
 
 
-parser_ids = reqparse.RequestParser().add_argument("plugin_ids", type=list, required=True, location="json")
-
-
 @console_ns.route("/workspaces/current/plugin/list/installations/ids")
 class PluginListInstallationsFromIdsApi(Resource):
-    @console_ns.expect(parser_ids)
+    @console_ns.expect(console_ns.models[ParserLatest.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def post(self):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_ids.parse_args()
+        args = ParserLatest.model_validate(console_ns.payload)
 
         try:
-            plugins = PluginService.list_installations_from_ids(tenant_id, args["plugin_ids"])
+            plugins = PluginService.list_installations_from_ids(tenant_id, args.plugin_ids)
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
         return jsonable_encoder({"plugins": plugins})
 
 
-parser_icon = (
-    reqparse.RequestParser()
-    .add_argument("tenant_id", type=str, required=True, location="args")
-    .add_argument("filename", type=str, required=True, location="args")
-)
-
-
 @console_ns.route("/workspaces/current/plugin/icon")
 class PluginIconApi(Resource):
-    @console_ns.expect(parser_icon)
+    @console_ns.expect(console_ns.models[ParserIcon.__name__])
     @setup_required
     def get(self):
-        args = parser_icon.parse_args()
+        args = ParserIcon.model_validate(request.args.to_dict(flat=True))  # type: ignore
 
         try:
-            icon_bytes, mimetype = PluginService.get_asset(args["tenant_id"], args["filename"])
+            icon_bytes, mimetype = PluginService.get_asset(args.tenant_id, args.filename)
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
@@ -128,20 +295,16 @@ class PluginIconApi(Resource):
 
 @console_ns.route("/workspaces/current/plugin/asset")
 class PluginAssetApi(Resource):
+    @console_ns.expect(console_ns.models[ParserAsset.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def get(self):
-        req = (
-            reqparse.RequestParser()
-            .add_argument("plugin_unique_identifier", type=str, required=True, location="args")
-            .add_argument("file_name", type=str, required=True, location="args")
-        )
-        args = req.parse_args()
+        args = ParserAsset.model_validate(request.args.to_dict(flat=True))  # type: ignore
 
         _, tenant_id = current_account_with_tenant()
         try:
-            binary = PluginService.extract_asset(tenant_id, args["plugin_unique_identifier"], args["file_name"])
+            binary = PluginService.extract_asset(tenant_id, args.plugin_unique_identifier, args.file_name)
             return send_file(io.BytesIO(binary), mimetype="application/octet-stream")
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
@@ -171,17 +334,9 @@ class PluginUploadFromPkgApi(Resource):
         return jsonable_encoder(response)
 
 
-parser_github = (
-    reqparse.RequestParser()
-    .add_argument("repo", type=str, required=True, location="json")
-    .add_argument("version", type=str, required=True, location="json")
-    .add_argument("package", type=str, required=True, location="json")
-)
-
-
 @console_ns.route("/workspaces/current/plugin/upload/github")
 class PluginUploadFromGithubApi(Resource):
-    @console_ns.expect(parser_github)
+    @console_ns.expect(console_ns.models[ParserGithubUpload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -189,10 +344,10 @@ class PluginUploadFromGithubApi(Resource):
     def post(self):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_github.parse_args()
+        args = ParserGithubUpload.model_validate(console_ns.payload)
 
         try:
-            response = PluginService.upload_pkg_from_github(tenant_id, args["repo"], args["version"], args["package"])
+            response = PluginService.upload_pkg_from_github(tenant_id, args.repo, args.version, args.package)
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
@@ -223,47 +378,28 @@ class PluginUploadFromBundleApi(Resource):
         return jsonable_encoder(response)
 
 
-parser_pkg = reqparse.RequestParser().add_argument(
-    "plugin_unique_identifiers", type=list, required=True, location="json"
-)
-
-
 @console_ns.route("/workspaces/current/plugin/install/pkg")
 class PluginInstallFromPkgApi(Resource):
-    @console_ns.expect(parser_pkg)
+    @console_ns.expect(console_ns.models[ParserPluginIdentifiers.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @plugin_permission_required(install_required=True)
     def post(self):
         _, tenant_id = current_account_with_tenant()
-        args = parser_pkg.parse_args()
-
-        # check if all plugin_unique_identifiers are valid string
-        for plugin_unique_identifier in args["plugin_unique_identifiers"]:
-            if not isinstance(plugin_unique_identifier, str):
-                raise ValueError("Invalid plugin unique identifier")
+        args = ParserPluginIdentifiers.model_validate(console_ns.payload)
 
         try:
-            response = PluginService.install_from_local_pkg(tenant_id, args["plugin_unique_identifiers"])
+            response = PluginService.install_from_local_pkg(tenant_id, args.plugin_unique_identifiers)
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
         return jsonable_encoder(response)
 
 
-parser_githubapi = (
-    reqparse.RequestParser()
-    .add_argument("repo", type=str, required=True, location="json")
-    .add_argument("version", type=str, required=True, location="json")
-    .add_argument("package", type=str, required=True, location="json")
-    .add_argument("plugin_unique_identifier", type=str, required=True, location="json")
-)
-
-
 @console_ns.route("/workspaces/current/plugin/install/github")
 class PluginInstallFromGithubApi(Resource):
-    @console_ns.expect(parser_githubapi)
+    @console_ns.expect(console_ns.models[ParserGithubInstall.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -271,15 +407,15 @@ class PluginInstallFromGithubApi(Resource):
     def post(self):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_githubapi.parse_args()
+        args = ParserGithubInstall.model_validate(console_ns.payload)
 
         try:
             response = PluginService.install_from_github(
                 tenant_id,
-                args["plugin_unique_identifier"],
-                args["repo"],
-                args["version"],
-                args["package"],
+                args.plugin_unique_identifier,
+                args.repo,
+                args.version,
+                args.package,
             )
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
@@ -287,14 +423,9 @@ class PluginInstallFromGithubApi(Resource):
         return jsonable_encoder(response)
 
 
-parser_marketplace = reqparse.RequestParser().add_argument(
-    "plugin_unique_identifiers", type=list, required=True, location="json"
-)
-
-
 @console_ns.route("/workspaces/current/plugin/install/marketplace")
 class PluginInstallFromMarketplaceApi(Resource):
-    @console_ns.expect(parser_marketplace)
+    @console_ns.expect(console_ns.models[ParserPluginIdentifiers.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -302,43 +433,33 @@ class PluginInstallFromMarketplaceApi(Resource):
     def post(self):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_marketplace.parse_args()
-
-        # check if all plugin_unique_identifiers are valid string
-        for plugin_unique_identifier in args["plugin_unique_identifiers"]:
-            if not isinstance(plugin_unique_identifier, str):
-                raise ValueError("Invalid plugin unique identifier")
+        args = ParserPluginIdentifiers.model_validate(console_ns.payload)
 
         try:
-            response = PluginService.install_from_marketplace_pkg(tenant_id, args["plugin_unique_identifiers"])
+            response = PluginService.install_from_marketplace_pkg(tenant_id, args.plugin_unique_identifiers)
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
         return jsonable_encoder(response)
 
 
-parser_pkgapi = reqparse.RequestParser().add_argument(
-    "plugin_unique_identifier", type=str, required=True, location="args"
-)
-
-
 @console_ns.route("/workspaces/current/plugin/marketplace/pkg")
 class PluginFetchMarketplacePkgApi(Resource):
-    @console_ns.expect(parser_pkgapi)
+    @console_ns.expect(console_ns.models[ParserPluginIdentifierQuery.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @plugin_permission_required(install_required=True)
     def get(self):
         _, tenant_id = current_account_with_tenant()
-        args = parser_pkgapi.parse_args()
+        args = ParserPluginIdentifierQuery.model_validate(request.args.to_dict(flat=True))  # type: ignore
 
         try:
             return jsonable_encoder(
                 {
                     "manifest": PluginService.fetch_marketplace_pkg(
                         tenant_id,
-                        args["plugin_unique_identifier"],
+                        args.plugin_unique_identifier,
                     )
                 }
             )
@@ -346,14 +467,9 @@ class PluginFetchMarketplacePkgApi(Resource):
             raise ValueError(e)
 
 
-parser_fetch = reqparse.RequestParser().add_argument(
-    "plugin_unique_identifier", type=str, required=True, location="args"
-)
-
-
 @console_ns.route("/workspaces/current/plugin/fetch-manifest")
 class PluginFetchManifestApi(Resource):
-    @console_ns.expect(parser_fetch)
+    @console_ns.expect(console_ns.models[ParserPluginIdentifierQuery.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -361,30 +477,19 @@ class PluginFetchManifestApi(Resource):
     def get(self):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_fetch.parse_args()
+        args = ParserPluginIdentifierQuery.model_validate(request.args.to_dict(flat=True))  # type: ignore
 
         try:
             return jsonable_encoder(
-                {
-                    "manifest": PluginService.fetch_plugin_manifest(
-                        tenant_id, args["plugin_unique_identifier"]
-                    ).model_dump()
-                }
+                {"manifest": PluginService.fetch_plugin_manifest(tenant_id, args.plugin_unique_identifier).model_dump()}
             )
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
 
-parser_tasks = (
-    reqparse.RequestParser()
-    .add_argument("page", type=int, required=True, location="args")
-    .add_argument("page_size", type=int, required=True, location="args")
-)
-
-
 @console_ns.route("/workspaces/current/plugin/tasks")
 class PluginFetchInstallTasksApi(Resource):
-    @console_ns.expect(parser_tasks)
+    @console_ns.expect(console_ns.models[ParserTasks.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -392,12 +497,10 @@ class PluginFetchInstallTasksApi(Resource):
     def get(self):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_tasks.parse_args()
+        args = ParserTasks.model_validate(request.args.to_dict(flat=True))  # type: ignore
 
         try:
-            return jsonable_encoder(
-                {"tasks": PluginService.fetch_install_tasks(tenant_id, args["page"], args["page_size"])}
-            )
+            return jsonable_encoder({"tasks": PluginService.fetch_install_tasks(tenant_id, args.page, args.page_size)})
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
@@ -462,16 +565,9 @@ class PluginDeleteInstallTaskItemApi(Resource):
             raise ValueError(e)
 
 
-parser_marketplace_api = (
-    reqparse.RequestParser()
-    .add_argument("original_plugin_unique_identifier", type=str, required=True, location="json")
-    .add_argument("new_plugin_unique_identifier", type=str, required=True, location="json")
-)
-
-
 @console_ns.route("/workspaces/current/plugin/upgrade/marketplace")
 class PluginUpgradeFromMarketplaceApi(Resource):
-    @console_ns.expect(parser_marketplace_api)
+    @console_ns.expect(console_ns.models[ParserMarketplaceUpgrade.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -479,31 +575,21 @@ class PluginUpgradeFromMarketplaceApi(Resource):
     def post(self):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_marketplace_api.parse_args()
+        args = ParserMarketplaceUpgrade.model_validate(console_ns.payload)
 
         try:
             return jsonable_encoder(
                 PluginService.upgrade_plugin_with_marketplace(
-                    tenant_id, args["original_plugin_unique_identifier"], args["new_plugin_unique_identifier"]
+                    tenant_id, args.original_plugin_unique_identifier, args.new_plugin_unique_identifier
                 )
             )
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
 
-parser_github_post = (
-    reqparse.RequestParser()
-    .add_argument("original_plugin_unique_identifier", type=str, required=True, location="json")
-    .add_argument("new_plugin_unique_identifier", type=str, required=True, location="json")
-    .add_argument("repo", type=str, required=True, location="json")
-    .add_argument("version", type=str, required=True, location="json")
-    .add_argument("package", type=str, required=True, location="json")
-)
-
-
 @console_ns.route("/workspaces/current/plugin/upgrade/github")
 class PluginUpgradeFromGithubApi(Resource):
-    @console_ns.expect(parser_github_post)
+    @console_ns.expect(console_ns.models[ParserGithubUpgrade.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -511,56 +597,44 @@ class PluginUpgradeFromGithubApi(Resource):
     def post(self):
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_github_post.parse_args()
+        args = ParserGithubUpgrade.model_validate(console_ns.payload)
 
         try:
             return jsonable_encoder(
                 PluginService.upgrade_plugin_with_github(
                     tenant_id,
-                    args["original_plugin_unique_identifier"],
-                    args["new_plugin_unique_identifier"],
-                    args["repo"],
-                    args["version"],
-                    args["package"],
+                    args.original_plugin_unique_identifier,
+                    args.new_plugin_unique_identifier,
+                    args.repo,
+                    args.version,
+                    args.package,
                 )
             )
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
 
-parser_uninstall = reqparse.RequestParser().add_argument(
-    "plugin_installation_id", type=str, required=True, location="json"
-)
-
-
 @console_ns.route("/workspaces/current/plugin/uninstall")
 class PluginUninstallApi(Resource):
-    @console_ns.expect(parser_uninstall)
+    @console_ns.expect(console_ns.models[ParserUninstall.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @plugin_permission_required(install_required=True)
     def post(self):
-        args = parser_uninstall.parse_args()
+        args = ParserUninstall.model_validate(console_ns.payload)
 
         _, tenant_id = current_account_with_tenant()
 
         try:
-            return {"success": PluginService.uninstall(tenant_id, args["plugin_installation_id"])}
+            return {"success": PluginService.uninstall(tenant_id, args.plugin_installation_id)}
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
 
 
-parser_change_post = (
-    reqparse.RequestParser()
-    .add_argument("install_permission", type=str, required=True, location="json")
-    .add_argument("debug_permission", type=str, required=True, location="json")
-)
-
-
 @console_ns.route("/workspaces/current/plugin/permission/change")
 class PluginChangePermissionApi(Resource):
-    @console_ns.expect(parser_change_post)
+    @console_ns.expect(console_ns.models[ParserPermissionChange.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -570,14 +644,15 @@ class PluginChangePermissionApi(Resource):
         if not user.is_admin_or_owner:
             raise Forbidden()
 
-        args = parser_change_post.parse_args()
-
-        install_permission = TenantPluginPermission.InstallPermission(args["install_permission"])
-        debug_permission = TenantPluginPermission.DebugPermission(args["debug_permission"])
+        args = ParserPermissionChange.model_validate(console_ns.payload)
 
         tenant_id = current_tenant_id
 
-        return {"success": PluginPermissionService.change_permission(tenant_id, install_permission, debug_permission)}
+        return {
+            "success": PluginPermissionService.change_permission(
+                tenant_id, args.install_permission, args.debug_permission
+            )
+        }
 
 
 @console_ns.route("/workspaces/current/plugin/permission/fetch")
@@ -605,20 +680,9 @@ class PluginFetchPermissionApi(Resource):
         )
 
 
-parser_dynamic = (
-    reqparse.RequestParser()
-    .add_argument("plugin_id", type=str, required=True, location="args")
-    .add_argument("provider", type=str, required=True, location="args")
-    .add_argument("action", type=str, required=True, location="args")
-    .add_argument("parameter", type=str, required=True, location="args")
-    .add_argument("credential_id", type=str, required=False, location="args")
-    .add_argument("provider_type", type=str, required=True, location="args")
-)
-
-
 @console_ns.route("/workspaces/current/plugin/parameters/dynamic-options")
 class PluginFetchDynamicSelectOptionsApi(Resource):
-    @console_ns.expect(parser_dynamic)
+    @console_ns.expect(console_ns.models[ParserDynamicOptions.__name__])
     @setup_required
     @login_required
     @is_admin_or_owner_required
@@ -627,18 +691,18 @@ class PluginFetchDynamicSelectOptionsApi(Resource):
         current_user, tenant_id = current_account_with_tenant()
         user_id = current_user.id
 
-        args = parser_dynamic.parse_args()
+        args = ParserDynamicOptions.model_validate(request.args.to_dict(flat=True))  # type: ignore
 
         try:
             options = PluginParameterService.get_dynamic_select_options(
                 tenant_id=tenant_id,
                 user_id=user_id,
-                plugin_id=args["plugin_id"],
-                provider=args["provider"],
-                action=args["action"],
-                parameter=args["parameter"],
-                credential_id=args["credential_id"],
-                provider_type=args["provider_type"],
+                plugin_id=args.plugin_id,
+                provider=args.provider,
+                action=args.action,
+                parameter=args.parameter,
+                credential_id=args.credential_id,
+                provider_type=args.provider_type,
             )
         except PluginDaemonClientSideError as e:
             raise ValueError(e)
@@ -646,16 +710,9 @@ class PluginFetchDynamicSelectOptionsApi(Resource):
         return jsonable_encoder({"options": options})
 
 
-parser_change = (
-    reqparse.RequestParser()
-    .add_argument("permission", type=dict, required=True, location="json")
-    .add_argument("auto_upgrade", type=dict, required=True, location="json")
-)
-
-
 @console_ns.route("/workspaces/current/plugin/preferences/change")
 class PluginChangePreferencesApi(Resource):
-    @console_ns.expect(parser_change)
+    @console_ns.expect(console_ns.models[ParserPreferencesChange.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -664,22 +721,20 @@ class PluginChangePreferencesApi(Resource):
         if not user.is_admin_or_owner:
             raise Forbidden()
 
-        args = parser_change.parse_args()
+        args = ParserPreferencesChange.model_validate(console_ns.payload)
 
-        permission = args["permission"]
+        permission = args.permission
 
-        install_permission = TenantPluginPermission.InstallPermission(permission.get("install_permission", "everyone"))
-        debug_permission = TenantPluginPermission.DebugPermission(permission.get("debug_permission", "everyone"))
+        install_permission = permission.install_permission
+        debug_permission = permission.debug_permission
 
-        auto_upgrade = args["auto_upgrade"]
+        auto_upgrade = args.auto_upgrade
 
-        strategy_setting = TenantPluginAutoUpgradeStrategy.StrategySetting(
-            auto_upgrade.get("strategy_setting", "fix_only")
-        )
-        upgrade_time_of_day = auto_upgrade.get("upgrade_time_of_day", 0)
-        upgrade_mode = TenantPluginAutoUpgradeStrategy.UpgradeMode(auto_upgrade.get("upgrade_mode", "exclude"))
-        exclude_plugins = auto_upgrade.get("exclude_plugins", [])
-        include_plugins = auto_upgrade.get("include_plugins", [])
+        strategy_setting = auto_upgrade.strategy_setting
+        upgrade_time_of_day = auto_upgrade.upgrade_time_of_day
+        upgrade_mode = auto_upgrade.upgrade_mode
+        exclude_plugins = auto_upgrade.exclude_plugins
+        include_plugins = auto_upgrade.include_plugins
 
         # set permission
         set_permission_result = PluginPermissionService.change_permission(
@@ -744,12 +799,9 @@ class PluginFetchPreferencesApi(Resource):
         return jsonable_encoder({"permission": permission_dict, "auto_upgrade": auto_upgrade_dict})
 
 
-parser_exclude = reqparse.RequestParser().add_argument("plugin_id", type=str, required=True, location="json")
-
-
 @console_ns.route("/workspaces/current/plugin/preferences/autoupgrade/exclude")
 class PluginAutoUpgradeExcludePluginApi(Resource):
-    @console_ns.expect(parser_exclude)
+    @console_ns.expect(console_ns.models[ParserExcludePlugin.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -757,28 +809,20 @@ class PluginAutoUpgradeExcludePluginApi(Resource):
         # exclude one single plugin
         _, tenant_id = current_account_with_tenant()
 
-        args = parser_exclude.parse_args()
+        args = ParserExcludePlugin.model_validate(console_ns.payload)
 
-        return jsonable_encoder({"success": PluginAutoUpgradeService.exclude_plugin(tenant_id, args["plugin_id"])})
+        return jsonable_encoder({"success": PluginAutoUpgradeService.exclude_plugin(tenant_id, args.plugin_id)})
 
 
 @console_ns.route("/workspaces/current/plugin/readme")
 class PluginReadmeApi(Resource):
+    @console_ns.expect(console_ns.models[ParserReadme.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def get(self):
         _, tenant_id = current_account_with_tenant()
-        parser = (
-            reqparse.RequestParser()
-            .add_argument("plugin_unique_identifier", type=str, required=True, location="args")
-            .add_argument("language", type=str, required=False, location="args")
-        )
-        args = parser.parse_args()
+        args = ParserReadme.model_validate(request.args.to_dict(flat=True))  # type: ignore
         return jsonable_encoder(
-            {
-                "readme": PluginService.fetch_plugin_readme(
-                    tenant_id, args["plugin_unique_identifier"], args.get("language", "en-US")
-                )
-            }
+            {"readme": PluginService.fetch_plugin_readme(tenant_id, args.plugin_unique_identifier, args.language)}
         )

api/controllers/console/workspace/workspace.py

@@ -1,7 +1,8 @@
 import logging
 
 from flask import request
-from flask_restx import Resource, fields, inputs, marshal, marshal_with, reqparse
+from flask_restx import Resource, fields, marshal, marshal_with
+from pydantic import BaseModel, Field
 from sqlalchemy import select
 from werkzeug.exceptions import Unauthorized
 
@@ -32,6 +33,45 @@ from services.file_service import FileService
 from services.workspace_service import WorkspaceService
 
 logger = logging.getLogger(__name__)
+DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
+
+
+class WorkspaceListQuery(BaseModel):
+    page: int = Field(default=1, ge=1, le=99999)
+    limit: int = Field(default=20, ge=1, le=100)
+
+
+class SwitchWorkspacePayload(BaseModel):
+    tenant_id: str
+
+
+class WorkspaceCustomConfigPayload(BaseModel):
+    remove_webapp_brand: bool | None = None
+    replace_webapp_logo: str | None = None
+
+
+class WorkspaceInfoPayload(BaseModel):
+    name: str
+
+
+console_ns.schema_model(
+    WorkspaceListQuery.__name__, WorkspaceListQuery.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
+
+console_ns.schema_model(
+    SwitchWorkspacePayload.__name__,
+    SwitchWorkspacePayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    WorkspaceCustomConfigPayload.__name__,
+    WorkspaceCustomConfigPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
+
+console_ns.schema_model(
+    WorkspaceInfoPayload.__name__,
+    WorkspaceInfoPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
 
 
 provider_fields = {
@@ -95,18 +135,15 @@ class TenantListApi(Resource):
 
 @console_ns.route("/all-workspaces")
 class WorkspaceListApi(Resource):
+    @console_ns.expect(console_ns.models[WorkspaceListQuery.__name__])
     @setup_required
     @admin_required
     def get(self):
-        parser = (
-            reqparse.RequestParser()
-            .add_argument("page", type=inputs.int_range(1, 99999), required=False, default=1, location="args")
-            .add_argument("limit", type=inputs.int_range(1, 100), required=False, default=20, location="args")
-        )
-        args = parser.parse_args()
+        payload = request.args.to_dict(flat=True)  # type: ignore
+        args = WorkspaceListQuery.model_validate(payload)
 
         stmt = select(Tenant).order_by(Tenant.created_at.desc())
-        tenants = db.paginate(select=stmt, page=args["page"], per_page=args["limit"], error_out=False)
+        tenants = db.paginate(select=stmt, page=args.page, per_page=args.limit, error_out=False)
         has_more = False
 
         if tenants.has_next:
@@ -115,8 +152,8 @@ class WorkspaceListApi(Resource):
         return {
             "data": marshal(tenants.items, workspace_fields),
             "has_more": has_more,
-            "limit": args["limit"],
-            "page": args["page"],
+            "limit": args.limit,
+            "page": args.page,
             "total": tenants.total,
         }, 200
 
@@ -150,26 +187,24 @@ class TenantApi(Resource):
         return WorkspaceService.get_tenant_info(tenant), 200
 
 
-parser_switch = reqparse.RequestParser().add_argument("tenant_id", type=str, required=True, location="json")
-
-
 @console_ns.route("/workspaces/switch")
 class SwitchWorkspaceApi(Resource):
-    @console_ns.expect(parser_switch)
+    @console_ns.expect(console_ns.models[SwitchWorkspacePayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     def post(self):
         current_user, _ = current_account_with_tenant()
-        args = parser_switch.parse_args()
+        payload = console_ns.payload or {}
+        args = SwitchWorkspacePayload.model_validate(payload)
 
         # check if tenant_id is valid, 403 if not
         try:
-            TenantService.switch_tenant(current_user, args["tenant_id"])
+            TenantService.switch_tenant(current_user, args.tenant_id)
         except Exception:
             raise AccountNotLinkTenantError("Account not link tenant")
 
-        new_tenant = db.session.query(Tenant).get(args["tenant_id"])  # Get new tenant
+        new_tenant = db.session.query(Tenant).get(args.tenant_id)  # Get new tenant
         if new_tenant is None:
             raise ValueError("Tenant not found")
 
@@ -178,24 +213,21 @@ class SwitchWorkspaceApi(Resource):
 
 @console_ns.route("/workspaces/custom-config")
 class CustomConfigWorkspaceApi(Resource):
+    @console_ns.expect(console_ns.models[WorkspaceCustomConfigPayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     @cloud_edition_billing_resource_check("workspace_custom")
     def post(self):
         _, current_tenant_id = current_account_with_tenant()
-        parser = (
-            reqparse.RequestParser()
-            .add_argument("remove_webapp_brand", type=bool, location="json")
-            .add_argument("replace_webapp_logo", type=str, location="json")
-        )
-        args = parser.parse_args()
+        payload = console_ns.payload or {}
+        args = WorkspaceCustomConfigPayload.model_validate(payload)
         tenant = db.get_or_404(Tenant, current_tenant_id)
 
         custom_config_dict = {
-            "remove_webapp_brand": args["remove_webapp_brand"],
-            "replace_webapp_logo": args["replace_webapp_logo"]
-            if args["replace_webapp_logo"] is not None
+            "remove_webapp_brand": args.remove_webapp_brand,
+            "replace_webapp_logo": args.replace_webapp_logo
+            if args.replace_webapp_logo is not None
             else tenant.custom_config_dict.get("replace_webapp_logo"),
         }
 
@@ -245,24 +277,22 @@ class WebappLogoWorkspaceApi(Resource):
         return {"id": upload_file.id}, 201
 
 
-parser_info = reqparse.RequestParser().add_argument("name", type=str, required=True, location="json")
-
-
 @console_ns.route("/workspaces/info")
 class WorkspaceInfoApi(Resource):
-    @console_ns.expect(parser_info)
+    @console_ns.expect(console_ns.models[WorkspaceInfoPayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
     # Change workspace name
     def post(self):
         _, current_tenant_id = current_account_with_tenant()
-        args = parser_info.parse_args()
+        payload = console_ns.payload or {}
+        args = WorkspaceInfoPayload.model_validate(payload)
 
         if not current_tenant_id:
             raise ValueError("No current tenant")
         tenant = db.get_or_404(Tenant, current_tenant_id)
-        tenant.name = args["name"]
+        tenant.name = args.name
         db.session.commit()
 
         return {"result": "success", "tenant": marshal(WorkspaceService.get_tenant_info(tenant), tenant_fields)}

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

@@ -62,7 +62,8 @@ from core.app.task_pipeline.message_cycle_manager import MessageCycleManager
 from core.base.tts import AppGeneratorTTSPublisher, AudioTrunk
 from core.model_runtime.entities.llm_entities import LLMUsage
 from core.model_runtime.utils.encoders import jsonable_encoder
-from core.ops.ops_trace_manager import TraceQueueManager
+from core.ops.entities.trace_entity import TraceTaskName
+from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
 from core.workflow.enums import WorkflowExecutionStatus
 from core.workflow.nodes import NodeType
 from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory
@@ -72,7 +73,7 @@ from extensions.ext_database import db
 from libs.datetime_utils import naive_utc_now
 from models import Account, Conversation, EndUser, Message, MessageFile
 from models.enums import CreatorUserRole
-from models.workflow import Workflow
+from models.workflow import Workflow, WorkflowNodeExecutionModel
 
 logger = logging.getLogger(__name__)
 
@@ -580,7 +581,7 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
 
             with self._database_session() as session:
                 # Save message
-                self._save_message(session=session, graph_runtime_state=resolved_state)
+                self._save_message(session=session, graph_runtime_state=resolved_state, trace_manager=trace_manager)
 
             yield workflow_finish_resp
         elif event.stopped_by in (
@@ -590,7 +591,7 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
             # When hitting input-moderation or annotation-reply, the workflow will not start
             with self._database_session() as session:
                 # Save message
-                self._save_message(session=session)
+                self._save_message(session=session, trace_manager=trace_manager)
 
         yield self._message_end_to_stream_response()
 
@@ -599,6 +600,7 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
         event: QueueAdvancedChatMessageEndEvent,
         *,
         graph_runtime_state: GraphRuntimeState | None = None,
+        trace_manager: TraceQueueManager | None = None,
         **kwargs,
     ) -> Generator[StreamResponse, None, None]:
         """Handle advanced chat message end events."""
@@ -616,7 +618,7 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
 
         # Save message
         with self._database_session() as session:
-            self._save_message(session=session, graph_runtime_state=resolved_state)
+            self._save_message(session=session, graph_runtime_state=resolved_state, trace_manager=trace_manager)
 
         yield self._message_end_to_stream_response()
 
@@ -770,7 +772,13 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
         if self._conversation_name_generate_thread:
             self._conversation_name_generate_thread.join()
 
-    def _save_message(self, *, session: Session, graph_runtime_state: GraphRuntimeState | None = None):
+    def _save_message(
+        self,
+        *,
+        session: Session,
+        graph_runtime_state: GraphRuntimeState | None = None,
+        trace_manager: TraceQueueManager | None = None,
+    ):
         message = self._get_message(session=session)
 
         # If there are assistant files, remove markdown image links from answer
@@ -809,6 +817,14 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
 
         metadata = self._task_state.metadata.model_dump()
         message.message_metadata = json.dumps(jsonable_encoder(metadata))
+
+        # Extract model provider and model_id from workflow node executions for tracing
+        if message.workflow_run_id:
+            model_info = self._extract_model_info_from_workflow(session, message.workflow_run_id)
+            if model_info:
+                message.model_provider = model_info.get("provider")
+                message.model_id = model_info.get("model")
+
         message_files = [
             MessageFile(
                 message_id=message.id,
@@ -826,6 +842,68 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
         ]
         session.add_all(message_files)
 
+        # Trigger MESSAGE_TRACE for tracing integrations
+        if trace_manager:
+            trace_manager.add_trace_task(
+                TraceTask(
+                    TraceTaskName.MESSAGE_TRACE, conversation_id=self._conversation_id, message_id=self._message_id
+                )
+            )
+
+    def _extract_model_info_from_workflow(self, session: Session, workflow_run_id: str) -> dict[str, str] | None:
+        """
+        Extract model provider and model_id from workflow node executions.
+        Returns dict with 'provider' and 'model' keys, or None if not found.
+        """
+        try:
+            # Query workflow node executions for LLM or Agent nodes
+            stmt = (
+                select(WorkflowNodeExecutionModel)
+                .where(WorkflowNodeExecutionModel.workflow_run_id == workflow_run_id)
+                .where(WorkflowNodeExecutionModel.node_type.in_(["llm", "agent"]))
+                .order_by(WorkflowNodeExecutionModel.created_at.desc())
+                .limit(1)
+            )
+            node_execution = session.scalar(stmt)
+
+            if not node_execution:
+                return None
+
+            # Try to extract from execution_metadata for agent nodes
+            if node_execution.execution_metadata:
+                try:
+                    metadata = json.loads(node_execution.execution_metadata)
+                    agent_log = metadata.get("agent_log", [])
+                    # Look for the first agent thought with provider info
+                    for log_entry in agent_log:
+                        entry_metadata = log_entry.get("metadata", {})
+                        provider_str = entry_metadata.get("provider")
+                        if provider_str:
+                            # Parse format like "langgenius/deepseek/deepseek"
+                            parts = provider_str.split("/")
+                            if len(parts) >= 3:
+                                return {"provider": parts[1], "model": parts[2]}
+                            elif len(parts) == 2:
+                                return {"provider": parts[0], "model": parts[1]}
+                except (json.JSONDecodeError, KeyError, AttributeError) as e:
+                    logger.debug("Failed to parse execution_metadata: %s", e)
+
+            # Try to extract from process_data for llm nodes
+            if node_execution.process_data:
+                try:
+                    process_data = json.loads(node_execution.process_data)
+                    provider = process_data.get("model_provider")
+                    model = process_data.get("model_name")
+                    if provider and model:
+                        return {"provider": provider, "model": model}
+                except (json.JSONDecodeError, KeyError) as e:
+                    logger.debug("Failed to parse process_data: %s", e)
+
+            return None
+        except Exception as e:
+            logger.warning("Failed to extract model info from workflow: %s", e)
+            return None
+
     def _seed_graph_runtime_state_from_queue_manager(self) -> None:
         """Bootstrap the cached runtime state from the queue manager when present."""
         candidate = self._base_task_pipeline.queue_manager.graph_runtime_state

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

@@ -258,6 +258,10 @@ class WorkflowAppGenerateTaskPipeline(GraphRuntimeStateSupport):
 
         run_id = self._extract_workflow_run_id(runtime_state)
         self._workflow_execution_id = run_id
+
+        with self._database_session() as session:
+            self._save_workflow_app_log(session=session, workflow_run_id=self._workflow_execution_id)
+
         start_resp = self._workflow_response_converter.workflow_start_to_stream_response(
             task_id=self._application_generate_entity.task_id,
             workflow_run_id=run_id,
@@ -414,9 +418,6 @@ class WorkflowAppGenerateTaskPipeline(GraphRuntimeStateSupport):
             graph_runtime_state=validated_state,
         )
 
-        with self._database_session() as session:
-            self._save_workflow_app_log(session=session, workflow_run_id=self._workflow_execution_id)
-
         yield workflow_finish_resp
 
     def _handle_workflow_partial_success_event(
@@ -437,10 +438,6 @@ class WorkflowAppGenerateTaskPipeline(GraphRuntimeStateSupport):
             graph_runtime_state=validated_state,
             exceptions_count=event.exceptions_count,
         )
-
-        with self._database_session() as session:
-            self._save_workflow_app_log(session=session, workflow_run_id=self._workflow_execution_id)
-
         yield workflow_finish_resp
 
     def _handle_workflow_failed_and_stop_events(
@@ -471,10 +468,6 @@ class WorkflowAppGenerateTaskPipeline(GraphRuntimeStateSupport):
             error=error,
             exceptions_count=exceptions_count,
         )
-
-        with self._database_session() as session:
-            self._save_workflow_app_log(session=session, workflow_run_id=self._workflow_execution_id)
-
         yield workflow_finish_resp
 
     def _handle_text_chunk_event(
@@ -655,7 +648,6 @@ class WorkflowAppGenerateTaskPipeline(GraphRuntimeStateSupport):
         )
 
         session.add(workflow_app_log)
-        session.commit()
 
     def _text_chunk_to_stream_response(
         self, text: str, from_variable_selector: list[str] | None = None

api/core/app/entities/task_entities.py

@@ -40,6 +40,9 @@ class EasyUITaskState(TaskState):
     """
 
     llm_result: LLMResult
+    first_token_time: float | None = None
+    last_token_time: float | None = None
+    is_streaming_response: bool = False
 
 
 class WorkflowTaskState(TaskState):

api/core/app/layers/pause_state_persist_layer.py

@@ -118,6 +118,7 @@ class PauseStatePersistenceLayer(GraphEngineLayer):
             workflow_run_id=workflow_run_id,
             state_owner_user_id=self._state_owner_user_id,
             state=state.dumps(),
+            pause_reasons=event.reasons,
         )
 
     def on_graph_end(self, error: Exception | None) -> None:

api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py

@@ -332,6 +332,12 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
                 if not self._task_state.llm_result.prompt_messages:
                     self._task_state.llm_result.prompt_messages = chunk.prompt_messages
 
+                # Track streaming response times
+                if self._task_state.first_token_time is None:
+                    self._task_state.first_token_time = time.perf_counter()
+                    self._task_state.is_streaming_response = True
+                self._task_state.last_token_time = time.perf_counter()
+
                 # handle output moderation chunk
                 should_direct_answer = self._handle_output_moderation_chunk(cast(str, delta_text))
                 if should_direct_answer:
@@ -398,6 +404,18 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
         message.total_price = usage.total_price
         message.currency = usage.currency
         self._task_state.llm_result.usage.latency = message.provider_response_latency
+
+        # Add streaming metrics to usage if available
+        if self._task_state.is_streaming_response and self._task_state.first_token_time:
+            start_time = self.start_at
+            first_token_time = self._task_state.first_token_time
+            last_token_time = self._task_state.last_token_time or first_token_time
+            usage.time_to_first_token = round(first_token_time - start_time, 3)
+            usage.time_to_generate = round(last_token_time - first_token_time, 3)
+
+        # Update metadata with the complete usage info
+        self._task_state.metadata.usage = usage
+
         message.message_metadata = self._task_state.metadata.model_dump_json()
 
         if trace_manager:

api/core/helper/code_executor/code_executor.py

@@ -152,10 +152,5 @@ class CodeExecutor:
             raise CodeExecutionError(f"Unsupported language {language}")
 
         runner, preload = template_transformer.transform_caller(code, inputs)
-
-        try:
-            response = cls.execute_code(language, preload, runner)
-        except CodeExecutionError as e:
-            raise e
-
+        response = cls.execute_code(language, preload, runner)
         return template_transformer.transform_response(response)

api/core/model_runtime/docs/en_US/customizable_model_scale_out.md

@@ -1,308 +0,0 @@
-## Custom Integration of Pre-defined Models
-
-### Introduction
-
-After completing the vendors integration, the next step is to connect the vendor's models. To illustrate the entire connection process, we will use Xinference as an example to demonstrate a complete vendor integration.
-
-It is important to note that for custom models, each model connection requires a complete vendor credential.
-
-Unlike pre-defined models, a custom vendor integration always includes the following two parameters, which do not need to be defined in the vendor YAML file.
-
-![](images/index/image-3.png)
-
-As mentioned earlier, vendors do not need to implement validate_provider_credential. The runtime will automatically call the corresponding model layer's validate_credentials to validate the credentials based on the model type and name selected by the user.
-
-### Writing the Vendor YAML
-
-First, we need to identify the types of models supported by the vendor we are integrating.
-
-Currently supported model types are as follows:
-
-- `llm` Text Generation Models
-
-- `text_embedding` Text Embedding Models
-
-- `rerank` Rerank Models
-
-- `speech2text` Speech-to-Text
-
-- `tts` Text-to-Speech
-
-- `moderation` Moderation
-
-Xinference supports LLM, Text Embedding, and Rerank. So we will start by writing xinference.yaml.
-
-```yaml
-provider: xinference #Define the vendor identifier
-label: # Vendor display name, supports both en_US (English) and zh_Hans (Simplified Chinese). If zh_Hans is not set, it will use en_US by default.
-  en_US: Xorbits Inference
-icon_small: # Small icon, refer to other vendors' icons stored in the _assets directory within the vendor implementation directory; follows the same language policy as the label
-  en_US: icon_s_en.svg
-icon_large: # Large icon
-  en_US: icon_l_en.svg
-help: # Help information
-  title:
-    en_US: How to deploy Xinference
-    zh_Hans: 如何部署 Xinference
-  url:
-    en_US: https://github.com/xorbitsai/inference
-supported_model_types: # Supported model types. Xinference supports LLM, Text Embedding, and Rerank
-- llm
-- text-embedding
-- rerank
-configurate_methods: # Since Xinference is a locally deployed vendor with no predefined models, users need to deploy whatever models they need according to Xinference documentation. Thus, it only supports custom models.
-- customizable-model
-provider_credential_schema:
-  credential_form_schemas:
-```
-
-Then, we need to determine what credentials are required to define a model in Xinference.
-
-- Since it supports three different types of models, we need to specify the model_type to denote the model type. Here is how we can define it:
-
-```yaml
-provider_credential_schema:
-  credential_form_schemas:
-  - variable: model_type
-    type: select
-    label:
-      en_US: Model type
-      zh_Hans: 模型类型
-    required: true
-    options:
-    - value: text-generation
-      label:
-        en_US: Language Model
-        zh_Hans: 语言模型
-    - value: embeddings
-      label:
-        en_US: Text Embedding
-    - value: reranking
-      label:
-        en_US: Rerank
-```
-
-- Next, each model has its own model_name, so we need to define that here:
-
-```yaml
-  - variable: model_name
-    type: text-input
-    label:
-      en_US: Model name
-      zh_Hans: 模型名称
-    required: true
-    placeholder:
-      zh_Hans: 填写模型名称
-      en_US: Input model name
-```
-
-- Specify the Xinference local deployment address:
-
-```yaml
-  - variable: server_url
-    label:
-      zh_Hans: 服务器 URL
-      en_US: Server url
-    type: text-input
-    required: true
-    placeholder:
-      zh_Hans: 在此输入 Xinference 的服务器地址，如 https://example.com/xxx
-      en_US: Enter the url of your Xinference, for example https://example.com/xxx
-```
-
-- Each model has a unique model_uid, so we also need to define that here:
-
-```yaml
-  - variable: model_uid
-    label:
-      zh_Hans: 模型 UID
-      en_US: Model uid
-    type: text-input
-    required: true
-    placeholder:
-      zh_Hans: 在此输入您的 Model UID
-      en_US: Enter the model uid
-```
-
-Now, we have completed the basic definition of the vendor.
-
-### Writing the Model Code
-
-Next, let's take the `llm` type as an example and write `xinference.llm.llm.py`.
-
-In `llm.py`, create a Xinference LLM class, we name it `XinferenceAILargeLanguageModel` (this can be arbitrary), inheriting from the `__base.large_language_model.LargeLanguageModel` base class, and implement the following methods:
-
-- LLM Invocation
-
-Implement the core method for LLM invocation, supporting both stream and synchronous responses.
-
-```python
-def _invoke(self, model: str, credentials: dict,
-            prompt_messages: list[PromptMessage], model_parameters: dict,
-            tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
-            stream: bool = True, user: Optional[str] = None) \
-        -> Union[LLMResult, Generator]:
-    """
-    Invoke large language model
-    
-    :param model: model name
-	:param credentials: model credentials
-	:param prompt_messages: prompt messages
-	:param model_parameters: model parameters
-	:param tools: tools for tool usage
-	:param stop: stop words
-	:param stream: is the response a stream
-	:param user: unique user id
-	:return: full response or stream response chunk generator result
-	"""
-```
-
-When implementing, ensure to use two functions to return data separately for synchronous and stream responses. This is important because Python treats functions containing the `yield` keyword as generator functions, mandating them to return `Generator` types. Here’s an example (note that the example uses simplified parameters; in real implementation, use the parameter list as defined above):
-
-```python
-def _invoke(self, stream: bool, **kwargs) \
-        -> Union[LLMResult, Generator]:
-    if stream:
-          return self._handle_stream_response(**kwargs)
-    return self._handle_sync_response(**kwargs)
-
-def _handle_stream_response(self, **kwargs) -> Generator:
-    for chunk in response:
-          yield chunk
-def _handle_sync_response(self, **kwargs) -> LLMResult:
-    return LLMResult(**response)
-```
-
-- Pre-compute Input Tokens
-
-If the model does not provide an interface for pre-computing tokens, you can return 0 directly.
-
-```python
-def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],tools: Optional[list[PromptMessageTool]] = None) -> int:
-  """
-  Get number of tokens for given prompt messages
-
-  :param model: model name
-  :param credentials: model credentials
-  :param prompt_messages: prompt messages
-  :param tools: tools for tool usage
-  :return: token count
-  """
-```
-
-Sometimes, you might not want to return 0 directly. In such cases, you can use `self._get_num_tokens_by_gpt2(text: str)` to get pre-computed tokens and ensure environment variable `PLUGIN_BASED_TOKEN_COUNTING_ENABLED` is set to `true`, This method is provided by the `AIModel` base class, and it uses GPT2's Tokenizer for calculation. However, it should be noted that this is only a substitute and may not be fully accurate.
-
-- Model Credentials Validation
-
-Similar to vendor credentials validation, this method validates individual model credentials.
-
-```python
-def validate_credentials(self, model: str, credentials: dict) -> None:
-    """
-    Validate model credentials
-    
-    :param model: model name
-	:param credentials: model credentials
-	:return: None
-	"""
-```
-
-- Model Parameter Schema
-
-Unlike custom types, since the YAML file does not define which parameters a model supports, we need to dynamically generate the model parameter schema.
-
-For instance, Xinference supports `max_tokens`, `temperature`, and `top_p` parameters.
-
-However, some vendors may support different parameters for different models. For example, the `OpenLLM` vendor supports `top_k`, but not all models provided by this vendor support `top_k`. Let's say model A supports `top_k` but model B does not. In such cases, we need to dynamically generate the model parameter schema, as illustrated below:
-
-```python
-    def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]:
-        """
-            used to define customizable model schema
-        """
-        rules = [
-            ParameterRule(
-                name='temperature', type=ParameterType.FLOAT,
-                use_template='temperature',
-                label=I18nObject(
-                    zh_Hans='温度', en_US='Temperature'
-                )
-            ),
-            ParameterRule(
-                name='top_p', type=ParameterType.FLOAT,
-                use_template='top_p',
-                label=I18nObject(
-                    zh_Hans='Top P', en_US='Top P'
-                )
-            ),
-            ParameterRule(
-                name='max_tokens', type=ParameterType.INT,
-                use_template='max_tokens',
-                min=1,
-                default=512,
-                label=I18nObject(
-                    zh_Hans='最大生成长度', en_US='Max Tokens'
-                )
-            )
-        ]
-
-        # if model is A, add top_k to rules
-        if model == 'A':
-            rules.append(
-                ParameterRule(
-                    name='top_k', type=ParameterType.INT,
-                    use_template='top_k',
-                    min=1,
-                    default=50,
-                    label=I18nObject(
-                        zh_Hans='Top K', en_US='Top K'
-                    )
-                )
-            )
-
-        """
-            some NOT IMPORTANT code here
-        """
-
-        entity = AIModelEntity(
-            model=model,
-            label=I18nObject(
-                en_US=model
-            ),
-            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
-            model_type=model_type,
-            model_properties={ 
-                ModelPropertyKey.MODE:  ModelType.LLM,
-            },
-            parameter_rules=rules
-        )
-
-        return entity
-```
-
-- Exception Error Mapping
-
-When a model invocation error occurs, it should be mapped to the runtime's specified `InvokeError` type, enabling Dify to handle different errors appropriately.
-
-Runtime Errors:
-
-- `InvokeConnectionError` Connection error during invocation
-- `InvokeServerUnavailableError` Service provider unavailable
-- `InvokeRateLimitError` Rate limit reached
-- `InvokeAuthorizationError` Authorization failure
-- `InvokeBadRequestError` Invalid request parameters
-
-```python
-  @property
-  def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
-      """
-      Map model invoke error to unified error
-      The key is the error type thrown to the caller
-      The value is the error type thrown by the model,
-      which needs to be converted into a unified error type for the caller.
-  
-      :return: Invoke error mapping
-      """
-```
-
-For interface method details, see: [Interfaces](./interfaces.md). For specific implementations, refer to: [llm.py](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/llm/llm.py).

api/core/model_runtime/docs/en_US/interfaces.md

@@ -1,701 +0,0 @@
-# Interface Methods
-
-This section describes the interface methods and parameter explanations that need to be implemented by providers and various model types.
-
-## Provider
-
-Inherit the `__base.model_provider.ModelProvider` base class and implement the following interfaces:
-
-```python
-def validate_provider_credentials(self, credentials: dict) -> None:
-    """
-    Validate provider credentials
-    You can choose any validate_credentials method of model type or implement validate method by yourself,
-    such as: get model list api
-
-    if validate failed, raise exception
-
-    :param credentials: provider credentials, credentials form defined in `provider_credential_schema`.
-    """
-```
-
-- `credentials` (object) Credential information
-
-  The parameters of credential information are defined by the `provider_credential_schema` in the provider's YAML configuration file. Inputs such as `api_key` are included.
-
-If verification fails, throw the `errors.validate.CredentialsValidateFailedError` error.
-
-## Model
-
-Models are divided into 5 different types, each inheriting from different base classes and requiring the implementation of different methods.
-
-All models need to uniformly implement the following 2 methods:
-
-- Model Credential Verification
-
-  Similar to provider credential verification, this step involves verification for an individual model.
-
-  ```python
-  def validate_credentials(self, model: str, credentials: dict) -> None:
-      """
-      Validate model credentials
-
-      :param model: model name
-      :param credentials: model credentials
-      :return:
-      """
-  ```
-
-  Parameters:
-
-  - `model` (string) Model name
-
-  - `credentials` (object) Credential information
-
-    The parameters of credential information are defined by either the `provider_credential_schema` or `model_credential_schema` in the provider's YAML configuration file. Inputs such as `api_key` are included.
-
-  If verification fails, throw the `errors.validate.CredentialsValidateFailedError` error.
-
-- Invocation Error Mapping Table
-
-  When there is an exception in model invocation, it needs to be mapped to the `InvokeError` type specified by Runtime. This facilitates Dify's ability to handle different errors with appropriate follow-up actions.
-
-  Runtime Errors:
-
-  - `InvokeConnectionError` Invocation connection error
-  - `InvokeServerUnavailableError` Invocation service provider unavailable
-  - `InvokeRateLimitError` Invocation reached rate limit
-  - `InvokeAuthorizationError` Invocation authorization failure
-  - `InvokeBadRequestError` Invocation parameter error
-
-  ```python
-  @property
-  def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
-      """
-      Map model invoke error to unified error
-      The key is the error type thrown to the caller
-      The value is the error type thrown by the model,
-      which needs to be converted into a unified error type for the caller.
-
-      :return: Invoke error mapping
-      """
-  ```
-
-​ You can refer to OpenAI's `_invoke_error_mapping` for an example.
-
-### LLM
-
-Inherit the `__base.large_language_model.LargeLanguageModel` base class and implement the following interfaces:
-
-- LLM Invocation
-
-  Implement the core method for LLM invocation, which can support both streaming and synchronous returns.
-
-  ```python
-  def _invoke(self, model: str, credentials: dict,
-              prompt_messages: list[PromptMessage], model_parameters: dict,
-              tools: Optional[list[PromptMessageTool]] = None, stop: Optional[List[str]] = None,
-              stream: bool = True, user: Optional[str] = None) \
-          -> Union[LLMResult, Generator]:
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param prompt_messages: prompt messages
-      :param model_parameters: model parameters
-      :param tools: tools for tool calling
-      :param stop: stop words
-      :param stream: is stream response
-      :param user: unique user id
-      :return: full response or stream response chunk generator result
-      """
-  ```
-
-  - Parameters:
-
-    - `model` (string) Model name
-
-    - `credentials` (object) Credential information
-
-      The parameters of credential information are defined by either the `provider_credential_schema` or `model_credential_schema` in the provider's YAML configuration file. Inputs such as `api_key` are included.
-
-    - `prompt_messages` (array\[[PromptMessage](#PromptMessage)\]) List of prompts
-
-      If the model is of the `Completion` type, the list only needs to include one [UserPromptMessage](#UserPromptMessage) element;
-
-      If the model is of the `Chat` type, it requires a list of elements such as [SystemPromptMessage](#SystemPromptMessage), [UserPromptMessage](#UserPromptMessage), [AssistantPromptMessage](#AssistantPromptMessage), [ToolPromptMessage](#ToolPromptMessage) depending on the message.
-
-    - `model_parameters` (object) Model parameters
-
-      The model parameters are defined by the `parameter_rules` in the model's YAML configuration.
-
-    - `tools` (array\[[PromptMessageTool](#PromptMessageTool)\]) [optional] List of tools, equivalent to the `function` in `function calling`.
-
-      That is, the tool list for tool calling.
-
-    - `stop` (array[string]) [optional] Stop sequences
-
-      The model output will stop before the string defined by the stop sequence.
-
-    - `stream` (bool) Whether to output in a streaming manner, default is True
-
-      Streaming output returns Generator\[[LLMResultChunk](#LLMResultChunk)\], non-streaming output returns [LLMResult](#LLMResult).
-
-    - `user` (string) [optional] Unique identifier of the user
-
-      This can help the provider monitor and detect abusive behavior.
-
-  - Returns
-
-    Streaming output returns Generator\[[LLMResultChunk](#LLMResultChunk)\], non-streaming output returns [LLMResult](#LLMResult).
-
-- Pre-calculating Input Tokens
-
-  If the model does not provide a pre-calculated tokens interface, you can directly return 0.
-
-  ```python
-  def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],
-                     tools: Optional[list[PromptMessageTool]] = None) -> int:
-      """
-      Get number of tokens for given prompt messages
-
-      :param model: model name
-      :param credentials: model credentials
-      :param prompt_messages: prompt messages
-      :param tools: tools for tool calling
-      :return:
-      """
-  ```
-
-  For parameter explanations, refer to the above section on `LLM Invocation`.
-
-- Fetch Custom Model Schema [Optional]
-
-  ```python
-  def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]:
-      """
-      Get customizable model schema
-
-      :param model: model name
-      :param credentials: model credentials
-      :return: model schema
-      """
-  ```
-
-  When the provider supports adding custom LLMs, this method can be implemented to allow custom models to fetch model schema. The default return null.
-
-### TextEmbedding
-
-Inherit the `__base.text_embedding_model.TextEmbeddingModel` base class and implement the following interfaces:
-
-- Embedding Invocation
-
-  ```python
-  def _invoke(self, model: str, credentials: dict,
-              texts: list[str], user: Optional[str] = None) \
-          -> TextEmbeddingResult:
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param texts: texts to embed
-      :param user: unique user id
-      :return: embeddings result
-      """
-  ```
-
-  - Parameters:
-
-    - `model` (string) Model name
-
-    - `credentials` (object) Credential information
-
-      The parameters of credential information are defined by either the `provider_credential_schema` or `model_credential_schema` in the provider's YAML configuration file. Inputs such as `api_key` are included.
-
-    - `texts` (array[string]) List of texts, capable of batch processing
-
-    - `user` (string) [optional] Unique identifier of the user
-
-      This can help the provider monitor and detect abusive behavior.
-
-  - Returns:
-
-    [TextEmbeddingResult](#TextEmbeddingResult) entity.
-
-- Pre-calculating Tokens
-
-  ```python
-  def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int:
-      """
-      Get number of tokens for given prompt messages
-
-      :param model: model name
-      :param credentials: model credentials
-      :param texts: texts to embed
-      :return:
-      """
-  ```
-
-  For parameter explanations, refer to the above section on `Embedding Invocation`.
-
-### Rerank
-
-Inherit the `__base.rerank_model.RerankModel` base class and implement the following interfaces:
-
-- Rerank Invocation
-
-  ```python
-  def _invoke(self, model: str, credentials: dict,
-              query: str, docs: list[str], score_threshold: Optional[float] = None, top_n: Optional[int] = None,
-              user: Optional[str] = None) \
-          -> RerankResult:
-      """
-      Invoke rerank model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param query: search query
-      :param docs: docs for reranking
-      :param score_threshold: score threshold
-      :param top_n: top n
-      :param user: unique user id
-      :return: rerank result
-      """
-  ```
-
-  - Parameters:
-
-    - `model` (string) Model name
-
-    - `credentials` (object) Credential information
-
-      The parameters of credential information are defined by either the `provider_credential_schema` or `model_credential_schema` in the provider's YAML configuration file. Inputs such as `api_key` are included.
-
-    - `query` (string) Query request content
-
-    - `docs` (array[string]) List of segments to be reranked
-
-    - `score_threshold` (float) [optional] Score threshold
-
-    - `top_n` (int) [optional] Select the top n segments
-
-    - `user` (string) [optional] Unique identifier of the user
-
-      This can help the provider monitor and detect abusive behavior.
-
-  - Returns:
-
-    [RerankResult](#RerankResult) entity.
-
-### Speech2text
-
-Inherit the `__base.speech2text_model.Speech2TextModel` base class and implement the following interfaces:
-
-- Invoke Invocation
-
-  ```python
-  def _invoke(self, model: str, credentials: dict, file: IO[bytes], user: Optional[str] = None) -> str:
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param file: audio file
-      :param user: unique user id
-      :return: text for given audio file
-      """	
-  ```
-
-  - Parameters:
-
-    - `model` (string) Model name
-
-    - `credentials` (object) Credential information
-
-      The parameters of credential information are defined by either the `provider_credential_schema` or `model_credential_schema` in the provider's YAML configuration file. Inputs such as `api_key` are included.
-
-    - `file` (File) File stream
-
-    - `user` (string) [optional] Unique identifier of the user
-
-      This can help the provider monitor and detect abusive behavior.
-
-  - Returns:
-
-    The string after speech-to-text conversion.
-
-### Text2speech
-
-Inherit the `__base.text2speech_model.Text2SpeechModel` base class and implement the following interfaces:
-
-- Invoke Invocation
-
-  ```python
-  def _invoke(self, model: str, credentials: dict, content_text: str, streaming: bool, user: Optional[str] = None):
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param content_text: text content to be translated
-      :param streaming: output is streaming
-      :param user: unique user id
-      :return: translated audio file
-      """	
-  ```
-
-  - Parameters：
-
-    - `model` (string) Model name
-
-    - `credentials` (object) Credential information
-
-      The parameters of credential information are defined by either the `provider_credential_schema` or `model_credential_schema` in the provider's YAML configuration file. Inputs such as `api_key` are included.
-
-    - `content_text` (string) The text content that needs to be converted
-
-    - `streaming` (bool) Whether to stream output
-
-    - `user` (string) [optional] Unique identifier of the user
-
-      This can help the provider monitor and detect abusive behavior.
-
-  - Returns：
-
-    Text converted speech stream.
-
-### Moderation
-
-Inherit the `__base.moderation_model.ModerationModel` base class and implement the following interfaces:
-
-- Invoke Invocation
-
-  ```python
-  def _invoke(self, model: str, credentials: dict,
-              text: str, user: Optional[str] = None) \
-          -> bool:
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param text: text to moderate
-      :param user: unique user id
-      :return: false if text is safe, true otherwise
-      """
-  ```
-
-  - Parameters:
-
-    - `model` (string) Model name
-
-    - `credentials` (object) Credential information
-
-      The parameters of credential information are defined by either the `provider_credential_schema` or `model_credential_schema` in the provider's YAML configuration file. Inputs such as `api_key` are included.
-
-    - `text` (string) Text content
-
-    - `user` (string) [optional] Unique identifier of the user
-
-      This can help the provider monitor and detect abusive behavior.
-
-  - Returns:
-
-    False indicates that the input text is safe, True indicates otherwise.
-
-## Entities
-
-### PromptMessageRole
-
-Message role
-
-```python
-class PromptMessageRole(Enum):
-    """
-    Enum class for prompt message.
-    """
-    SYSTEM = "system"
-    USER = "user"
-    ASSISTANT = "assistant"
-    TOOL = "tool"
-```
-
-### PromptMessageContentType
-
-Message content types, divided into text and image.
-
-```python
-class PromptMessageContentType(Enum):
-    """
-    Enum class for prompt message content type.
-    """
-    TEXT = 'text'
-    IMAGE = 'image'
-```
-
-### PromptMessageContent
-
-Message content base class, used only for parameter declaration and cannot be initialized.
-
-```python
-class PromptMessageContent(BaseModel):
-    """
-    Model class for prompt message content.
-    """
-    type: PromptMessageContentType
-    data: str
-```
-
-Currently, two types are supported: text and image. It's possible to simultaneously input text and multiple images.
-
-You need to initialize `TextPromptMessageContent` and `ImagePromptMessageContent` separately for input.
-
-### TextPromptMessageContent
-
-```python
-class TextPromptMessageContent(PromptMessageContent):
-    """
-    Model class for text prompt message content.
-    """
-    type: PromptMessageContentType = PromptMessageContentType.TEXT
-```
-
-If inputting a combination of text and images, the text needs to be constructed into this entity as part of the `content` list.
-
-### ImagePromptMessageContent
-
-```python
-class ImagePromptMessageContent(PromptMessageContent):
-    """
-    Model class for image prompt message content.
-    """
-    class DETAIL(Enum):
-        LOW = 'low'
-        HIGH = 'high'
-
-    type: PromptMessageContentType = PromptMessageContentType.IMAGE
-    detail: DETAIL = DETAIL.LOW  # Resolution
-```
-
-If inputting a combination of text and images, the images need to be constructed into this entity as part of the `content` list.
-
-`data` can be either a `url` or a `base64` encoded string of the image.
-
-### PromptMessage
-
-The base class for all Role message bodies, used only for parameter declaration and cannot be initialized.
-
-```python
-class PromptMessage(BaseModel):
-    """
-    Model class for prompt message.
-    """
-    role: PromptMessageRole
-    content: Optional[str | list[PromptMessageContent]] = None  # Supports two types: string and content list. The content list is designed to meet the needs of multimodal inputs. For more details, see the PromptMessageContent explanation.
-    name: Optional[str] = None
-```
-
-### UserPromptMessage
-
-UserMessage message body, representing a user's message.
-
-```python
-class UserPromptMessage(PromptMessage):
-    """
-    Model class for user prompt message.
-    """
-    role: PromptMessageRole = PromptMessageRole.USER
-```
-
-### AssistantPromptMessage
-
-Represents a message returned by the model, typically used for `few-shots` or inputting chat history.
-
-```python
-class AssistantPromptMessage(PromptMessage):
-    """
-    Model class for assistant prompt message.
-    """
-    class ToolCall(BaseModel):
-        """
-        Model class for assistant prompt message tool call.
-        """
-        class ToolCallFunction(BaseModel):
-            """
-            Model class for assistant prompt message tool call function.
-            """
-            name: str  # tool name
-            arguments: str  # tool arguments
-
-        id: str  # Tool ID, effective only in OpenAI tool calls. It's the unique ID for tool invocation and the same tool can be called multiple times.
-        type: str  # default: function
-        function: ToolCallFunction  # tool call information
-
-    role: PromptMessageRole = PromptMessageRole.ASSISTANT
-    tool_calls: list[ToolCall] = []  # The result of tool invocation in response from the model (returned only when tools are input and the model deems it necessary to invoke a tool).
-```
-
-Where `tool_calls` are the list of `tool calls` returned by the model after invoking the model with the `tools` input.
-
-### SystemPromptMessage
-
-Represents system messages, usually used for setting system commands given to the model.
-
-```python
-class SystemPromptMessage(PromptMessage):
-    """
-    Model class for system prompt message.
-    """
-    role: PromptMessageRole = PromptMessageRole.SYSTEM
-```
-
-### ToolPromptMessage
-
-Represents tool messages, used for conveying the results of a tool execution to the model for the next step of processing.
-
-```python
-class ToolPromptMessage(PromptMessage):
-    """
-    Model class for tool prompt message.
-    """
-    role: PromptMessageRole = PromptMessageRole.TOOL
-    tool_call_id: str  # Tool invocation ID. If OpenAI tool call is not supported, the name of the tool can also be inputted.
-```
-
-The base class's `content` takes in the results of tool execution.
-
-### PromptMessageTool
-
-```python
-class PromptMessageTool(BaseModel):
-    """
-    Model class for prompt message tool.
-    """
-    name: str
-    description: str
-    parameters: dict
-```
-
-______________________________________________________________________
-
-### LLMResult
-
-```python
-class LLMResult(BaseModel):
-    """
-    Model class for llm result.
-    """
-    model: str  # Actual used modele
-    prompt_messages: list[PromptMessage]  # prompt messages
-    message: AssistantPromptMessage  # response message
-    usage: LLMUsage  # usage info
-    system_fingerprint: Optional[str] = None  # request fingerprint, refer to OpenAI definition
-```
-
-### LLMResultChunkDelta
-
-In streaming returns, each iteration contains the `delta` entity.
-
-```python
-class LLMResultChunkDelta(BaseModel):
-    """
-    Model class for llm result chunk delta.
-    """
-    index: int
-    message: AssistantPromptMessage  # response message
-    usage: Optional[LLMUsage] = None  # usage info
-    finish_reason: Optional[str] = None  # finish reason, only the last one returns
-```
-
-### LLMResultChunk
-
-Each iteration entity in streaming returns.
-
-```python
-class LLMResultChunk(BaseModel):
-    """
-    Model class for llm result chunk.
-    """
-    model: str  # Actual used modele
-    prompt_messages: list[PromptMessage]  # prompt messages
-    system_fingerprint: Optional[str] = None  # request fingerprint, refer to OpenAI definition
-    delta: LLMResultChunkDelta
-```
-
-### LLMUsage
-
-```python
-class LLMUsage(ModelUsage):
-    """
-    Model class for LLM usage.
-    """
-    prompt_tokens: int  # Tokens used for prompt
-    prompt_unit_price: Decimal  # Unit price for prompt
-    prompt_price_unit: Decimal  # Price unit for prompt, i.e., the unit price based on how many tokens
-    prompt_price: Decimal  # Cost for prompt
-    completion_tokens: int  # Tokens used for response
-    completion_unit_price: Decimal  # Unit price for response
-    completion_price_unit: Decimal  # Price unit for response, i.e., the unit price based on how many tokens
-    completion_price: Decimal  # Cost for response
-    total_tokens: int  # Total number of tokens used
-    total_price: Decimal  # Total cost
-    currency: str  # Currency unit
-    latency: float  # Request latency (s)
-```
-
-______________________________________________________________________
-
-### TextEmbeddingResult
-
-```python
-class TextEmbeddingResult(BaseModel):
-    """
-    Model class for text embedding result.
-    """
-    model: str  # Actual model used
-    embeddings: list[list[float]]  # List of embedding vectors, corresponding to the input texts list
-    usage: EmbeddingUsage  # Usage information
-```
-
-### EmbeddingUsage
-
-```python
-class EmbeddingUsage(ModelUsage):
-    """
-    Model class for embedding usage.
-    """
-    tokens: int  # Number of tokens used
-    total_tokens: int  # Total number of tokens used
-    unit_price: Decimal  # Unit price
-    price_unit: Decimal  # Price unit, i.e., the unit price based on how many tokens
-    total_price: Decimal  # Total cost
-    currency: str  # Currency unit
-    latency: float  # Request latency (s)
-```
-
-______________________________________________________________________
-
-### RerankResult
-
-```python
-class RerankResult(BaseModel):
-    """
-    Model class for rerank result.
-    """
-    model: str  # Actual model used
-    docs: list[RerankDocument]  # Reranked document list	
-```
-
-### RerankDocument
-
-```python
-class RerankDocument(BaseModel):
-    """
-    Model class for rerank document.
-    """
-    index: int  # original index
-    text: str
-    score: float
-```

api/core/model_runtime/docs/en_US/predefined_model_scale_out.md

@@ -1,176 +0,0 @@
-## Predefined Model Integration
-
-After completing the vendor integration, the next step is to integrate the models from the vendor.
-
-First, we need to determine the type of model to be integrated and create the corresponding model type `module` under the respective vendor's directory.
-
-Currently supported model types are:
-
-- `llm` Text Generation Model
-- `text_embedding` Text Embedding Model
-- `rerank` Rerank Model
-- `speech2text` Speech-to-Text
-- `tts` Text-to-Speech
-- `moderation` Moderation
-
-Continuing with `Anthropic` as an example, `Anthropic` only supports LLM, so create a `module` named `llm` under `model_providers.anthropic`.
-
-For predefined models, we first need to create a YAML file named after the model under the `llm` `module`, such as `claude-2.1.yaml`.
-
-### Prepare Model YAML
-
-```yaml
-model: claude-2.1  # Model identifier
-# Display name of the model, which can be set to en_US English or zh_Hans Chinese. If zh_Hans is not set, it will default to en_US.
-# This can also be omitted, in which case the model identifier will be used as the label
-label:
-  en_US: claude-2.1
-model_type: llm  # Model type, claude-2.1 is an LLM
-features:  # Supported features, agent-thought supports Agent reasoning, vision supports image understanding
-- agent-thought
-model_properties:  # Model properties
-  mode: chat  # LLM mode, complete for text completion models, chat for conversation models
-  context_size: 200000  # Maximum context size
-parameter_rules:  # Parameter rules for the model call; only LLM requires this
-- name: temperature  # Parameter variable name
-  # Five default configuration templates are provided: temperature/top_p/max_tokens/presence_penalty/frequency_penalty
-  # The template variable name can be set directly in use_template, which will use the default configuration in entities.defaults.PARAMETER_RULE_TEMPLATE
-  # Additional configuration parameters will override the default configuration if set
-  use_template: temperature
-- name: top_p
-  use_template: top_p
-- name: top_k
-  label:  # Display name of the parameter
-    zh_Hans: 取样数量
-    en_US: Top k
-  type: int  # Parameter type, supports float/int/string/boolean
-  help:  # Help information, describing the parameter's function
-    zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
-    en_US: Only sample from the top K options for each subsequent token.
-  required: false  # Whether the parameter is mandatory; can be omitted
-- name: max_tokens_to_sample
-  use_template: max_tokens
-  default: 4096  # Default value of the parameter
-  min: 1  # Minimum value of the parameter, applicable to float/int only
-  max: 4096  # Maximum value of the parameter, applicable to float/int only
-pricing:  # Pricing information
-  input: '8.00'  # Input unit price, i.e., prompt price
-  output: '24.00'  # Output unit price, i.e., response content price
-  unit: '0.000001'  # Price unit, meaning the above prices are per 100K
-  currency: USD  # Price currency
-```
-
-It is recommended to prepare all model configurations before starting the implementation of the model code.
-
-You can also refer to the YAML configuration information under the corresponding model type directories of other vendors in the `model_providers` directory. For the complete YAML rules, refer to: [Schema](schema.md#aimodelentity).
-
-### Implement the Model Call Code
-
-Next, create a Python file named `llm.py` under the `llm` `module` to write the implementation code.
-
-Create an Anthropic LLM class named `AnthropicLargeLanguageModel` (or any other name), inheriting from the `__base.large_language_model.LargeLanguageModel` base class, and implement the following methods:
-
-- LLM Call
-
-Implement the core method for calling the LLM, supporting both streaming and synchronous responses.
-
-```python
-  def _invoke(self, model: str, credentials: dict,
-              prompt_messages: list[PromptMessage], model_parameters: dict,
-              tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
-              stream: bool = True, user: Optional[str] = None) \
-          -> Union[LLMResult, Generator]:
-      """
-      Invoke large language model
-  
-      :param model: model name
-      :param credentials: model credentials
-      :param prompt_messages: prompt messages
-      :param model_parameters: model parameters
-      :param tools: tools for tool calling
-      :param stop: stop words
-      :param stream: is stream response
-      :param user: unique user id
-      :return: full response or stream response chunk generator result
-      """
-```
-
-Ensure to use two functions for returning data, one for synchronous returns and the other for streaming returns, because Python identifies functions containing the `yield` keyword as generator functions, fixing the return type to `Generator`. Thus, synchronous and streaming returns need to be implemented separately, as shown below (note that the example uses simplified parameters, for actual implementation follow the above parameter list):
-
-```python
-  def _invoke(self, stream: bool, **kwargs) \
-          -> Union[LLMResult, Generator]:
-      if stream:
-            return self._handle_stream_response(**kwargs)
-      return self._handle_sync_response(**kwargs)
-
-  def _handle_stream_response(self, **kwargs) -> Generator:
-      for chunk in response:
-            yield chunk
-  def _handle_sync_response(self, **kwargs) -> LLMResult:
-      return LLMResult(**response)
-```
-
-- Pre-compute Input Tokens
-
-If the model does not provide an interface to precompute tokens, return 0 directly.
-
-```python
-  def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],
-                     tools: Optional[list[PromptMessageTool]] = None) -> int:
-      """
-      Get number of tokens for given prompt messages
-
-      :param model: model name
-      :param credentials: model credentials
-      :param prompt_messages: prompt messages
-      :param tools: tools for tool calling
-      :return:
-      """
-```
-
-- Validate Model Credentials
-
-Similar to vendor credential validation, but specific to a single model.
-
-```python
-  def validate_credentials(self, model: str, credentials: dict) -> None:
-      """
-      Validate model credentials
-  
-      :param model: model name
-      :param credentials: model credentials
-      :return:
-      """
-```
-
-- Map Invoke Errors
-
-When a model call fails, map it to a specific `InvokeError` type as required by Runtime, allowing Dify to handle different errors accordingly.
-
-Runtime Errors:
-
-- `InvokeConnectionError` Connection error
-
-- `InvokeServerUnavailableError` Service provider unavailable
-
-- `InvokeRateLimitError` Rate limit reached
-
-- `InvokeAuthorizationError` Authorization failed
-
-- `InvokeBadRequestError` Parameter error
-
-```python
-  @property
-  def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
-      """
-      Map model invoke error to unified error
-      The key is the error type thrown to the caller
-      The value is the error type thrown by the model,
-      which needs to be converted into a unified error type for the caller.
-  
-      :return: Invoke error mapping
-      """
-```
-
-For interface method explanations, see: [Interfaces](./interfaces.md). For detailed implementation, refer to: [llm.py](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/llm/llm.py).

api/core/model_runtime/docs/en_US/provider_scale_out.md

@@ -1,266 +0,0 @@
-## Adding a New Provider
-
-Providers support three types of model configuration methods:
-
-- `predefined-model` Predefined model
-
-  This indicates that users only need to configure the unified provider credentials to use the predefined models under the provider.
-
-- `customizable-model` Customizable model
-
-  Users need to add credential configurations for each model.
-
-- `fetch-from-remote` Fetch from remote
-
-  This is consistent with the `predefined-model` configuration method. Only unified provider credentials need to be configured, and models are obtained from the provider through credential information.
-
-These three configuration methods **can coexist**, meaning a provider can support `predefined-model` + `customizable-model` or `predefined-model` + `fetch-from-remote`, etc. In other words, configuring the unified provider credentials allows the use of predefined and remotely fetched models, and if new models are added, they can be used in addition to the custom models.
-
-## Getting Started
-
-Adding a new provider starts with determining the English identifier of the provider, such as `anthropic`, and using this identifier to create a `module` in `model_providers`.
-
-Under this `module`, we first need to prepare the provider's YAML configuration.
-
-### Preparing Provider YAML
-
-Here, using `Anthropic` as an example, we preset the provider's basic information, supported model types, configuration methods, and credential rules.
-
-```YAML
-provider: anthropic  # Provider identifier
-label:  # Provider display name, can be set in en_US English and zh_Hans Chinese, zh_Hans will default to en_US if not set.
-  en_US: Anthropic
-icon_small:  # Small provider icon, stored in the _assets directory under the corresponding provider implementation directory, same language strategy as label
-  en_US: icon_s_en.png
-icon_large:  # Large provider icon, stored in the _assets directory under the corresponding provider implementation directory, same language strategy as label
-  en_US: icon_l_en.png
-supported_model_types:  # Supported model types, Anthropic only supports LLM
-- llm
-configurate_methods:  # Supported configuration methods, Anthropic only supports predefined models
-- predefined-model
-provider_credential_schema:  # Provider credential rules, as Anthropic only supports predefined models, unified provider credential rules need to be defined
-  credential_form_schemas:  # List of credential form items
-  - variable: anthropic_api_key  # Credential parameter variable name
-    label:  # Display name
-      en_US: API Key
-    type: secret-input  # Form type, here secret-input represents an encrypted information input box, showing masked information when editing.
-    required: true  # Whether required
-    placeholder:  # Placeholder information
-      zh_Hans: Enter your API Key here
-      en_US: Enter your API Key
-  - variable: anthropic_api_url
-    label:
-      en_US: API URL
-    type: text-input  # Form type, here text-input represents a text input box
-    required: false
-    placeholder:
-      zh_Hans: Enter your API URL here
-      en_US: Enter your API URL
-```
-
-You can also refer to the YAML configuration information under other provider directories in `model_providers`. The complete YAML rules are available at: [Schema](schema.md#provider).
-
-### Implementing Provider Code
-
-Providers need to inherit the `__base.model_provider.ModelProvider` base class and implement the `validate_provider_credentials` method for unified provider credential verification. For reference, see [AnthropicProvider](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/anthropic.py).
-
-> If the provider is the type of `customizable-model`, there is no need to implement the `validate_provider_credentials` method.
-
-```python
-def validate_provider_credentials(self, credentials: dict) -> None:
-    """
-    Validate provider credentials
-    You can choose any validate_credentials method of model type or implement validate method by yourself,
-    such as: get model list api
-
-    if validate failed, raise exception
-
-    :param credentials: provider credentials, credentials form defined in `provider_credential_schema`.
-    """
-```
-
-Of course, you can also preliminarily reserve the implementation of `validate_provider_credentials` and directly reuse it after the model credential verification method is implemented.
-
-______________________________________________________________________
-
-### Adding Models
-
-After the provider integration is complete, the next step is to integrate models under the provider.
-
-First, we need to determine the type of the model to be integrated and create a `module` for the corresponding model type in the provider's directory.
-
-The currently supported model types are as follows:
-
-- `llm` Text generation model
-- `text_embedding` Text Embedding model
-- `rerank` Rerank model
-- `speech2text` Speech to text
-- `tts` Text to speech
-- `moderation` Moderation
-
-Continuing with `Anthropic` as an example, since `Anthropic` only supports LLM, we create a `module` named `llm` in `model_providers.anthropic`.
-
-For predefined models, we first need to create a YAML file named after the model, such as `claude-2.1.yaml`, under the `llm` `module`.
-
-#### Preparing Model YAML
-
-```yaml
-model: claude-2.1  # Model identifier
-# Model display name, can be set in en_US English and zh_Hans Chinese, zh_Hans will default to en_US if not set.
-# Alternatively, if the label is not set, use the model identifier content.
-label:
-  en_US: claude-2.1
-model_type: llm  # Model type, claude-2.1 is an LLM
-features:  # Supported features, agent-thought for Agent reasoning, vision for image understanding
-- agent-thought
-model_properties:  # Model properties
-  mode: chat  # LLM mode, complete for text completion model, chat for dialogue model
-  context_size: 200000  # Maximum supported context size
-parameter_rules:  # Model invocation parameter rules, only required for LLM
-- name: temperature  # Invocation parameter variable name
-  # Default preset with 5 variable content configuration templates: temperature/top_p/max_tokens/presence_penalty/frequency_penalty
-  # Directly set the template variable name in use_template, which will use the default configuration in entities.defaults.PARAMETER_RULE_TEMPLATE
-  # If additional configuration parameters are set, they will override the default configuration
-  use_template: temperature
-- name: top_p
-  use_template: top_p
-- name: top_k
-  label:  # Invocation parameter display name
-    zh_Hans: Sampling quantity
-    en_US: Top k
-  type: int  # Parameter type, supports float/int/string/boolean
-  help:  # Help information, describing the role of the parameter
-    zh_Hans: Only sample from the top K options for each subsequent token.
-    en_US: Only sample from the top K options for each subsequent token.
-  required: false  # Whether required, can be left unset
-- name: max_tokens_to_sample
-  use_template: max_tokens
-  default: 4096  # Default parameter value
-  min: 1  # Minimum parameter value, only applicable for float/int
-  max: 4096  # Maximum parameter value, only applicable for float/int
-pricing:  # Pricing information
-  input: '8.00'  # Input price, i.e., Prompt price
-  output: '24.00'  # Output price, i.e., returned content price
-  unit: '0.000001'  # Pricing unit, i.e., the above prices are per 100K
-  currency: USD  # Currency
-```
-
-It is recommended to prepare all model configurations before starting the implementation of the model code.
-
-Similarly, you can also refer to the YAML configuration information for corresponding model types of other providers in the `model_providers` directory. The complete YAML rules can be found at: [Schema](schema.md#AIModel).
-
-#### Implementing Model Invocation Code
-
-Next, you need to create a python file named `llm.py` under the `llm` `module` to write the implementation code.
-
-In `llm.py`, create an Anthropic LLM class, which we name `AnthropicLargeLanguageModel` (arbitrarily), inheriting the `__base.large_language_model.LargeLanguageModel` base class, and implement the following methods:
-
-- LLM Invocation
-
-  Implement the core method for LLM invocation, which can support both streaming and synchronous returns.
-
-  ```python
-  def _invoke(self, model: str, credentials: dict,
-              prompt_messages: list[PromptMessage], model_parameters: dict,
-              tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
-              stream: bool = True, user: Optional[str] = None) \
-          -> Union[LLMResult, Generator]:
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param prompt_messages: prompt messages
-      :param model_parameters: model parameters
-      :param tools: tools for tool calling
-      :param stop: stop words
-      :param stream: is stream response
-      :param user: unique user id
-      :return: full response or stream response chunk generator result
-      """
-  ```
-
-- Pre-calculating Input Tokens
-
-  If the model does not provide a pre-calculated tokens interface, you can directly return 0.
-
-  ```python
-  def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],
-                   tools: Optional[list[PromptMessageTool]] = None) -> int:
-    """
-    Get number of tokens for given prompt messages
-
-    :param model: model name
-    :param credentials: model credentials
-    :param prompt_messages: prompt messages
-    :param tools: tools for tool calling
-    :return:
-    """
-  ```
-
-- Model Credential Verification
-
-  Similar to provider credential verification, this step involves verification for an individual model.
-
-  ```python
-  def validate_credentials(self, model: str, credentials: dict) -> None:
-      """
-      Validate model credentials
-
-      :param model: model name
-      :param credentials: model credentials
-      :return:
-      """
-  ```
-
-- Invocation Error Mapping Table
-
-  When there is an exception in model invocation, it needs to be mapped to the `InvokeError` type specified by Runtime. This facilitates Dify's ability to handle different errors with appropriate follow-up actions.
-
-  Runtime Errors:
-
-  - `InvokeConnectionError` Invocation connection error
-  - `InvokeServerUnavailableError` Invocation service provider unavailable
-  - `InvokeRateLimitError` Invocation reached rate limit
-  - `InvokeAuthorizationError` Invocation authorization failure
-  - `InvokeBadRequestError` Invocation parameter error
-
-  ```python
-  @property
-  def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
-      """
-      Map model invoke error to unified error
-      The key is the error type thrown to the caller
-      The value is the error type thrown by the model,
-      which needs to be converted into a unified error type for the caller.
-
-      :return: Invoke error mapping
-      """
-  ```
-
-For details on the interface methods, see: [Interfaces](interfaces.md). For specific implementations, refer to: [llm.py](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/llm/llm.py).
-
-### Testing
-
-To ensure the availability of integrated providers/models, each method written needs corresponding integration test code in the `tests` directory.
-
-Continuing with `Anthropic` as an example:
-
-Before writing test code, you need to first add the necessary credential environment variables for the test provider in `.env.example`, such as: `ANTHROPIC_API_KEY`.
-
-Before execution, copy `.env.example` to `.env` and then execute.
-
-#### Writing Test Code
-
-Create a `module` with the same name as the provider in the `tests` directory: `anthropic`, and continue to create `test_provider.py` and test py files for the corresponding model types within this module, as shown below:
-
-```shell
-.
-├── __init__.py
-├── anthropic
-│   ├── __init__.py
-│   ├── test_llm.py       # LLM Testing
-│   └── test_provider.py  # Provider Testing
-```
-
-Write test code for all the various cases implemented above and submit the code after passing the tests.

api/core/model_runtime/docs/en_US/schema.md

@@ -1,208 +0,0 @@
-# Configuration Rules
-
-- Provider rules are based on the [Provider](#Provider) entity.
-- Model rules are based on the [AIModelEntity](#AIModelEntity) entity.
-
-> All entities mentioned below are based on `Pydantic BaseModel` and can be found in the `entities` module.
-
-### Provider
-
-- `provider` (string) Provider identifier, e.g., `openai`
-- `label` (object) Provider display name, i18n, with `en_US` English and `zh_Hans` Chinese language settings
-  - `zh_Hans` (string) [optional] Chinese label name, if `zh_Hans` is not set, `en_US` will be used by default.
-  - `en_US` (string) English label name
-- `description` (object) Provider description, i18n
-  - `zh_Hans` (string) [optional] Chinese description
-  - `en_US` (string) English description
-- `icon_small` (string) [optional] Small provider ICON, stored in the `_assets` directory under the corresponding provider implementation directory, with the same language strategy as `label`
-  - `zh_Hans` (string) Chinese ICON
-  - `en_US` (string) English ICON
-- `icon_large` (string) [optional] Large provider ICON, stored in the `_assets` directory under the corresponding provider implementation directory, with the same language strategy as `label`
-  - `zh_Hans` (string) Chinese ICON
-  - `en_US` (string) English ICON
-- `background` (string) [optional] Background color value, e.g., #FFFFFF, if empty, the default frontend color value will be displayed.
-- `help` (object) [optional] help information
-  - `title` (object) help title, i18n
-    - `zh_Hans` (string) [optional] Chinese title
-    - `en_US` (string) English title
-  - `url` (object) help link, i18n
-    - `zh_Hans` (string) [optional] Chinese link
-    - `en_US` (string) English link
-- `supported_model_types` (array\[[ModelType](#ModelType)\]) Supported model types
-- `configurate_methods` (array\[[ConfigurateMethod](#ConfigurateMethod)\]) Configuration methods
-- `provider_credential_schema` ([ProviderCredentialSchema](#ProviderCredentialSchema)) Provider credential specification
-- `model_credential_schema` ([ModelCredentialSchema](#ModelCredentialSchema)) Model credential specification
-
-### AIModelEntity
-
-- `model` (string) Model identifier, e.g., `gpt-3.5-turbo`
-- `label` (object) [optional] Model display name, i18n, with `en_US` English and `zh_Hans` Chinese language settings
-  - `zh_Hans` (string) [optional] Chinese label name
-  - `en_US` (string) English label name
-- `model_type` ([ModelType](#ModelType)) Model type
-- `features` (array\[[ModelFeature](#ModelFeature)\]) [optional] Supported feature list
-- `model_properties` (object) Model properties
-  - `mode` ([LLMMode](#LLMMode)) Mode (available for model type `llm`)
-  - `context_size` (int) Context size (available for model types `llm`, `text-embedding`)
-  - `max_chunks` (int) Maximum number of chunks (available for model types `text-embedding`, `moderation`)
-  - `file_upload_limit` (int) Maximum file upload limit, in MB (available for model type `speech2text`)
-  - `supported_file_extensions` (string) Supported file extension formats, e.g., mp3, mp4 (available for model type `speech2text`)
-  - `default_voice` (string) default voice, e.g.：alloy,echo,fable,onyx,nova,shimmer（available for model type `tts`）
-  - `voices` (list) List of available voice.（available for model type `tts`）
-    - `mode` (string) voice model.（available for model type `tts`）
-    - `name` (string) voice model display name.（available for model type `tts`）
-    - `language` (string) the voice model supports languages.（available for model type `tts`）
-  - `word_limit` (int) Single conversion word limit, paragraph-wise by default（available for model type `tts`）
-  - `audio_type` (string) Support audio file extension format, e.g.：mp3,wav（available for model type `tts`）
-  - `max_workers` (int) Number of concurrent workers supporting text and audio conversion（available for model type`tts`）
-  - `max_characters_per_chunk` (int) Maximum characters per chunk (available for model type `moderation`)
-- `parameter_rules` (array\[[ParameterRule](#ParameterRule)\]) [optional] Model invocation parameter rules
-- `pricing` ([PriceConfig](#PriceConfig)) [optional] Pricing information
-- `deprecated` (bool) Whether deprecated. If deprecated, the model will no longer be displayed in the list, but those already configured can continue to be used. Default False.
-
-### ModelType
-
-- `llm` Text generation model
-- `text-embedding` Text Embedding model
-- `rerank` Rerank model
-- `speech2text` Speech to text
-- `tts` Text to speech
-- `moderation` Moderation
-
-### ConfigurateMethod
-
-- `predefined-model` Predefined model
-
-  Indicates that users can use the predefined models under the provider by configuring the unified provider credentials.
-
-- `customizable-model` Customizable model
-
-  Users need to add credential configuration for each model.
-
-- `fetch-from-remote` Fetch from remote
-
-  Consistent with the `predefined-model` configuration method, only unified provider credentials need to be configured, and models are obtained from the provider through credential information.
-
-### ModelFeature
-
-- `agent-thought` Agent reasoning, generally over 70B with thought chain capability.
-- `vision` Vision, i.e., image understanding.
-- `tool-call`
-- `multi-tool-call`
-- `stream-tool-call`
-
-### FetchFrom
-
-- `predefined-model` Predefined model
-- `fetch-from-remote` Remote model
-
-### LLMMode
-
-- `complete` Text completion
-- `chat` Dialogue
-
-### ParameterRule
-
-- `name` (string) Actual model invocation parameter name
-
-- `use_template` (string) [optional] Using template
-
-  By default, 5 variable content configuration templates are preset:
-
-  - `temperature`
-  - `top_p`
-  - `frequency_penalty`
-  - `presence_penalty`
-  - `max_tokens`
-
-  In use_template, you can directly set the template variable name, which will use the default configuration in entities.defaults.PARAMETER_RULE_TEMPLATE
-  No need to set any parameters other than `name` and `use_template`. If additional configuration parameters are set, they will override the default configuration.
-  Refer to `openai/llm/gpt-3.5-turbo.yaml`.
-
-- `label` (object) [optional] Label, i18n
-
-  - `zh_Hans`(string) [optional] Chinese label name
-  - `en_US` (string) English label name
-
-- `type`(string) [optional] Parameter type
-
-  - `int` Integer
-  - `float` Float
-  - `string` String
-  - `boolean` Boolean
-
-- `help` (string) [optional] Help information
-
-  - `zh_Hans` (string) [optional] Chinese help information
-  - `en_US` (string) English help information
-
-- `required` (bool) Required, default False.
-
-- `default`(int/float/string/bool) [optional] Default value
-
-- `min`(int/float) [optional] Minimum value, applicable only to numeric types
-
-- `max`(int/float) [optional] Maximum value, applicable only to numeric types
-
-- `precision`(int) [optional] Precision, number of decimal places to keep, applicable only to numeric types
-
-- `options` (array[string]) [optional] Dropdown option values, applicable only when `type` is `string`, if not set or null, option values are not restricted
-
-### PriceConfig
-
-- `input` (float) Input price, i.e., Prompt price
-- `output` (float) Output price, i.e., returned content price
-- `unit` (float) Pricing unit, e.g., if the price is measured in 1M tokens, the corresponding token amount for the unit price is `0.000001`.
-- `currency` (string) Currency unit
-
-### ProviderCredentialSchema
-
-- `credential_form_schemas` (array\[[CredentialFormSchema](#CredentialFormSchema)\]) Credential form standard
-
-### ModelCredentialSchema
-
-- `model` (object) Model identifier, variable name defaults to `model`
-  - `label` (object) Model form item display name
-    - `en_US` (string) English
-    - `zh_Hans`(string) [optional] Chinese
-  - `placeholder` (object) Model prompt content
-    - `en_US`(string) English
-    - `zh_Hans`(string) [optional] Chinese
-- `credential_form_schemas` (array\[[CredentialFormSchema](#CredentialFormSchema)\]) Credential form standard
-
-### CredentialFormSchema
-
-- `variable` (string) Form item variable name
-- `label` (object) Form item label name
-  - `en_US`(string) English
-  - `zh_Hans` (string) [optional] Chinese
-- `type` ([FormType](#FormType)) Form item type
-- `required` (bool) Whether required
-- `default`(string) Default value
-- `options` (array\[[FormOption](#FormOption)\]) Specific property of form items of type `select` or `radio`, defining dropdown content
-- `placeholder`(object) Specific property of form items of type `text-input`, placeholder content
-  - `en_US`(string) English
-  - `zh_Hans` (string) [optional] Chinese
-- `max_length` (int) Specific property of form items of type `text-input`, defining maximum input length, 0 for no limit.
-- `show_on` (array\[[FormShowOnObject](#FormShowOnObject)\]) Displayed when other form item values meet certain conditions, displayed always if empty.
-
-### FormType
-
-- `text-input` Text input component
-- `secret-input` Password input component
-- `select` Single-choice dropdown
-- `radio` Radio component
-- `switch` Switch component, only supports `true` and `false` values
-
-### FormOption
-
-- `label` (object) Label
-  - `en_US`(string) English
-  - `zh_Hans`(string) [optional] Chinese
-- `value` (string) Dropdown option value
-- `show_on` (array\[[FormShowOnObject](#FormShowOnObject)\]) Displayed when other form item values meet certain conditions, displayed always if empty.
-
-### FormShowOnObject
-
-- `variable` (string) Variable name of other form items
-- `value` (string) Variable value of other form items

api/core/model_runtime/docs/zh_Hans/customizable_model_scale_out.md

@@ -1,304 +0,0 @@
-## 自定义预定义模型接入
-
-### 介绍
-
-供应商集成完成后，接下来为供应商下模型的接入，为了帮助理解整个接入过程，我们以`Xinference`为例，逐步完成一个完整的供应商接入。
-
-需要注意的是，对于自定义模型，每一个模型的接入都需要填写一个完整的供应商凭据。
-
-而不同于预定义模型，自定义供应商接入时永远会拥有如下两个参数，不需要在供应商 yaml 中定义。
-
-![Alt text](images/index/image-3.png)
-
-在前文中，我们已经知道了供应商无需实现`validate_provider_credential`，Runtime 会自行根据用户在此选择的模型类型和模型名称调用对应的模型层的`validate_credentials`来进行验证。
-
-### 编写供应商 yaml
-
-我们首先要确定，接入的这个供应商支持哪些类型的模型。
-
-当前支持模型类型如下：
-
-- `llm` 文本生成模型
-- `text_embedding` 文本 Embedding 模型
-- `rerank` Rerank 模型
-- `speech2text` 语音转文字
-- `tts` 文字转语音
-- `moderation` 审查
-
-`Xinference`支持`LLM`和`Text Embedding`和 Rerank，那么我们开始编写`xinference.yaml`。
-
-```yaml
-provider: xinference #确定供应商标识
-label: # 供应商展示名称，可设置 en_US 英文、zh_Hans 中文两种语言，zh_Hans 不设置将默认使用 en_US。
-  en_US: Xorbits Inference
-icon_small: # 小图标，可以参考其他供应商的图标，存储在对应供应商实现目录下的 _assets 目录，中英文策略同 label
-  en_US: icon_s_en.svg
-icon_large: # 大图标
-  en_US: icon_l_en.svg
-help: # 帮助
-  title:
-    en_US: How to deploy Xinference
-    zh_Hans: 如何部署 Xinference
-  url:
-    en_US: https://github.com/xorbitsai/inference
-supported_model_types: # 支持的模型类型，Xinference 同时支持 LLM/Text Embedding/Rerank
-- llm
-- text-embedding
-- rerank
-configurate_methods: # 因为 Xinference 为本地部署的供应商，并且没有预定义模型，需要用什么模型需要根据 Xinference 的文档自己部署，所以这里只支持自定义模型
-- customizable-model
-provider_credential_schema:
-  credential_form_schemas:
-```
-
-随后，我们需要思考在 Xinference 中定义一个模型需要哪些凭据
-
-- 它支持三种不同的模型，因此，我们需要有`model_type`来指定这个模型的类型，它有三种类型，所以我们这么编写
-
-```yaml
-provider_credential_schema:
-  credential_form_schemas:
-  - variable: model_type
-    type: select
-    label:
-      en_US: Model type
-      zh_Hans: 模型类型
-    required: true
-    options:
-    - value: text-generation
-      label:
-        en_US: Language Model
-        zh_Hans: 语言模型
-    - value: embeddings
-      label:
-        en_US: Text Embedding
-    - value: reranking
-      label:
-        en_US: Rerank
-```
-
-- 每一个模型都有自己的名称`model_name`，因此需要在这里定义
-
-```yaml
-  - variable: model_name
-    type: text-input
-    label:
-      en_US: Model name
-      zh_Hans: 模型名称
-    required: true
-    placeholder:
-      zh_Hans: 填写模型名称
-      en_US: Input model name
-```
-
-- 填写 Xinference 本地部署的地址
-
-```yaml
-  - variable: server_url
-    label:
-      zh_Hans: 服务器 URL
-      en_US: Server url
-    type: text-input
-    required: true
-    placeholder:
-      zh_Hans: 在此输入 Xinference 的服务器地址，如 https://example.com/xxx
-      en_US: Enter the url of your Xinference, for example https://example.com/xxx
-```
-
-- 每个模型都有唯一的 model_uid，因此需要在这里定义
-
-```yaml
-  - variable: model_uid
-    label:
-      zh_Hans: 模型 UID
-      en_US: Model uid
-    type: text-input
-    required: true
-    placeholder:
-      zh_Hans: 在此输入您的 Model UID
-      en_US: Enter the model uid
-```
-
-现在，我们就完成了供应商的基础定义。
-
-### 编写模型代码
-
-然后我们以`llm`类型为例，编写`xinference.llm.llm.py`
-
-在 `llm.py` 中创建一个 Xinference LLM 类，我们取名为 `XinferenceAILargeLanguageModel`（随意），继承 `__base.large_language_model.LargeLanguageModel` 基类，实现以下几个方法：
-
-- LLM 调用
-
-  实现 LLM 调用的核心方法，可同时支持流式和同步返回。
-
-  ```python
-  def _invoke(self, model: str, credentials: dict,
-              prompt_messages: list[PromptMessage], model_parameters: dict,
-              tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
-              stream: bool = True, user: Optional[str] = None) \
-          -> Union[LLMResult, Generator]:
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param prompt_messages: prompt messages
-      :param model_parameters: model parameters
-      :param tools: tools for tool calling
-      :param stop: stop words
-      :param stream: is stream response
-      :param user: unique user id
-      :return: full response or stream response chunk generator result
-      """
-  ```
-
-  在实现时，需要注意使用两个函数来返回数据，分别用于处理同步返回和流式返回，因为 Python 会将函数中包含 `yield` 关键字的函数识别为生成器函数，返回的数据类型固定为 `Generator`，因此同步和流式返回需要分别实现，就像下面这样（注意下面例子使用了简化参数，实际实现时需要按照上面的参数列表进行实现）：
-
-  ```python
-  def _invoke(self, stream: bool, **kwargs) \
-          -> Union[LLMResult, Generator]:
-      if stream:
-            return self._handle_stream_response(**kwargs)
-      return self._handle_sync_response(**kwargs)
-
-  def _handle_stream_response(self, **kwargs) -> Generator:
-      for chunk in response:
-            yield chunk
-  def _handle_sync_response(self, **kwargs) -> LLMResult:
-      return LLMResult(**response)
-  ```
-
-- 预计算输入 tokens
-
-  若模型未提供预计算 tokens 接口，可直接返回 0。
-
-  ```python
-  def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],
-                   tools: Optional[list[PromptMessageTool]] = None) -> int:
-    """
-    Get number of tokens for given prompt messages
-
-    :param model: model name
-    :param credentials: model credentials
-    :param prompt_messages: prompt messages
-    :param tools: tools for tool calling
-    :return:
-    """
-  ```
-
-  有时候，也许你不需要直接返回 0，所以你可以使用`self._get_num_tokens_by_gpt2(text: str)`来获取预计算的 tokens，并确保环境变量`PLUGIN_BASED_TOKEN_COUNTING_ENABLED`设置为`true`，这个方法位于`AIModel`基类中，它会使用 GPT2 的 Tokenizer 进行计算，但是只能作为替代方法，并不完全准确。
-
-- 模型凭据校验
-
-  与供应商凭据校验类似，这里针对单个模型进行校验。
-
-  ```python
-  def validate_credentials(self, model: str, credentials: dict) -> None:
-      """
-      Validate model credentials
-
-      :param model: model name
-      :param credentials: model credentials
-      :return:
-      """
-  ```
-
-- 模型参数 Schema
-
-  与自定义类型不同，由于没有在 yaml 文件中定义一个模型支持哪些参数，因此，我们需要动态时间模型参数的 Schema。
-
-  如 Xinference 支持`max_tokens` `temperature` `top_p` 这三个模型参数。
-
-  但是有的供应商根据不同的模型支持不同的参数，如供应商`OpenLLM`支持`top_k`，但是并不是这个供应商提供的所有模型都支持`top_k`，我们这里举例 A 模型支持`top_k`，B 模型不支持`top_k`，那么我们需要在这里动态生成模型参数的 Schema，如下所示：
-
-  ```python
-  def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]:
-      """
-          used to define customizable model schema
-      """
-      rules = [
-          ParameterRule(
-              name='temperature', type=ParameterType.FLOAT,
-              use_template='temperature',
-              label=I18nObject(
-                  zh_Hans='温度', en_US='Temperature'
-              )
-          ),
-          ParameterRule(
-              name='top_p', type=ParameterType.FLOAT,
-              use_template='top_p',
-              label=I18nObject(
-                  zh_Hans='Top P', en_US='Top P'
-              )
-          ),
-          ParameterRule(
-              name='max_tokens', type=ParameterType.INT,
-              use_template='max_tokens',
-              min=1,
-              default=512,
-              label=I18nObject(
-                  zh_Hans='最大生成长度', en_US='Max Tokens'
-              )
-          )
-      ]
-
-      # if model is A, add top_k to rules
-      if model == 'A':
-          rules.append(
-              ParameterRule(
-                  name='top_k', type=ParameterType.INT,
-                  use_template='top_k',
-                  min=1,
-                  default=50,
-                  label=I18nObject(
-                      zh_Hans='Top K', en_US='Top K'
-                  )
-              )
-          )
-
-      """
-          some NOT IMPORTANT code here
-      """
-
-      entity = AIModelEntity(
-          model=model,
-          label=I18nObject(
-              en_US=model
-          ),
-          fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
-          model_type=model_type,
-          model_properties={ 
-              ModelPropertyKey.MODE:  ModelType.LLM,
-          },
-          parameter_rules=rules
-      )
-
-      return entity
-  ```
-
-- 调用异常错误映射表
-
-  当模型调用异常时需要映射到 Runtime 指定的 `InvokeError` 类型，方便 Dify 针对不同错误做不同后续处理。
-
-  Runtime Errors:
-
-  - `InvokeConnectionError` 调用连接错误
-  - `InvokeServerUnavailableError ` 调用服务方不可用
-  - `InvokeRateLimitError ` 调用达到限额
-  - `InvokeAuthorizationError` 调用鉴权失败
-  - `InvokeBadRequestError ` 调用传参有误
-
-  ```python
-  @property
-  def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
-      """
-      Map model invoke error to unified error
-      The key is the error type thrown to the caller
-      The value is the error type thrown by the model,
-      which needs to be converted into a unified error type for the caller.
-
-      :return: Invoke error mapping
-      """
-  ```
-
-接口方法说明见：[Interfaces](./interfaces.md)，具体实现可参考：[llm.py](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/llm/llm.py)。

api/core/model_runtime/docs/zh_Hans/interfaces.md

@@ -1,744 +0,0 @@
-# 接口方法
-
-这里介绍供应商和各模型类型需要实现的接口方法和参数说明。
-
-## 供应商
-
-继承 `__base.model_provider.ModelProvider` 基类，实现以下接口：
-
-```python
-def validate_provider_credentials(self, credentials: dict) -> None:
-    """
-    Validate provider credentials
-    You can choose any validate_credentials method of model type or implement validate method by yourself,
-    such as: get model list api
-
-    if validate failed, raise exception
-
-    :param credentials: provider credentials, credentials form defined in `provider_credential_schema`.
-    """
-```
-
-- `credentials` (object) 凭据信息
-
-  凭据信息的参数由供应商 YAML 配置文件的 `provider_credential_schema` 定义，传入如：`api_key` 等。
-
-验证失败请抛出 `errors.validate.CredentialsValidateFailedError` 错误。
-
-**注：预定义模型需完整实现该接口，自定义模型供应商只需要如下简单实现即可**
-
-```python
-class XinferenceProvider(Provider):
-    def validate_provider_credentials(self, credentials: dict) -> None:
-        pass
-```
-
-## 模型
-
-模型分为 5 种不同的模型类型，不同模型类型继承的基类不同，需要实现的方法也不同。
-
-### 通用接口
-
-所有模型均需要统一实现下面 2 个方法：
-
-- 模型凭据校验
-
-  与供应商凭据校验类似，这里针对单个模型进行校验。
-
-  ```python
-  def validate_credentials(self, model: str, credentials: dict) -> None:
-      """
-      Validate model credentials
-
-      :param model: model name
-      :param credentials: model credentials
-      :return:
-      """
-  ```
-
-  参数：
-
-  - `model` (string) 模型名称
-
-  - `credentials` (object) 凭据信息
-
-    凭据信息的参数由供应商 YAML 配置文件的 `provider_credential_schema` 或 `model_credential_schema` 定义，传入如：`api_key` 等。
-
-  验证失败请抛出 `errors.validate.CredentialsValidateFailedError` 错误。
-
-- 调用异常错误映射表
-
-  当模型调用异常时需要映射到 Runtime 指定的 `InvokeError` 类型，方便 Dify 针对不同错误做不同后续处理。
-
-  Runtime Errors:
-
-  - `InvokeConnectionError` 调用连接错误
-  - `InvokeServerUnavailableError ` 调用服务方不可用
-  - `InvokeRateLimitError ` 调用达到限额
-  - `InvokeAuthorizationError` 调用鉴权失败
-  - `InvokeBadRequestError ` 调用传参有误
-
-  ```python
-  @property
-  def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
-      """
-      Map model invoke error to unified error
-      The key is the error type thrown to the caller
-      The value is the error type thrown by the model,
-      which needs to be converted into a unified error type for the caller.
-
-      :return: Invoke error mapping
-      """
-  ```
-
-  也可以直接抛出对应 Errors，并做如下定义，这样在之后的调用中可以直接抛出`InvokeConnectionError`等异常。
-
-  ```python
-  @property
-  def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
-      return {
-          InvokeConnectionError: [
-            InvokeConnectionError
-          ],
-          InvokeServerUnavailableError: [
-            InvokeServerUnavailableError
-          ],
-          InvokeRateLimitError: [
-            InvokeRateLimitError
-          ],
-          InvokeAuthorizationError: [
-            InvokeAuthorizationError
-          ],
-          InvokeBadRequestError: [
-            InvokeBadRequestError
-          ],
-      }
-  ```
-
-​ 可参考 OpenAI `_invoke_error_mapping`。
-
-### LLM
-
-继承 `__base.large_language_model.LargeLanguageModel` 基类，实现以下接口：
-
-- LLM 调用
-
-  实现 LLM 调用的核心方法，可同时支持流式和同步返回。
-
-  ```python
-  def _invoke(self, model: str, credentials: dict,
-              prompt_messages: list[PromptMessage], model_parameters: dict,
-              tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
-              stream: bool = True, user: Optional[str] = None) \
-          -> Union[LLMResult, Generator]:
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param prompt_messages: prompt messages
-      :param model_parameters: model parameters
-      :param tools: tools for tool calling
-      :param stop: stop words
-      :param stream: is stream response
-      :param user: unique user id
-      :return: full response or stream response chunk generator result
-      """
-  ```
-
-  - 参数：
-
-    - `model` (string) 模型名称
-
-    - `credentials` (object) 凭据信息
-
-      凭据信息的参数由供应商 YAML 配置文件的 `provider_credential_schema` 或 `model_credential_schema` 定义，传入如：`api_key` 等。
-
-    - `prompt_messages` (array\[[PromptMessage](#PromptMessage)\]) Prompt 列表
-
-      若模型为 `Completion` 类型，则列表只需要传入一个 [UserPromptMessage](#UserPromptMessage) 元素即可；
-
-      若模型为 `Chat` 类型，需要根据消息不同传入 [SystemPromptMessage](#SystemPromptMessage), [UserPromptMessage](#UserPromptMessage), [AssistantPromptMessage](#AssistantPromptMessage), [ToolPromptMessage](#ToolPromptMessage) 元素列表
-
-    - `model_parameters` (object) 模型参数
-
-      模型参数由模型 YAML 配置的 `parameter_rules` 定义。
-
-    - `tools` (array\[[PromptMessageTool](#PromptMessageTool)\]) [optional] 工具列表，等同于 `function calling` 中的 `function`。
-
-      即传入 tool calling 的工具列表。
-
-    - `stop` (array[string]) [optional] 停止序列
-
-      模型返回将在停止序列定义的字符串之前停止输出。
-
-    - `stream` (bool) 是否流式输出，默认 True
-
-      流式输出返回 Generator\[[LLMResultChunk](#LLMResultChunk)\]，非流式输出返回 [LLMResult](#LLMResult)。
-
-    - `user` (string) [optional] 用户的唯一标识符
-
-      可以帮助供应商监控和检测滥用行为。
-
-  - 返回
-
-    流式输出返回 Generator\[[LLMResultChunk](#LLMResultChunk)\]，非流式输出返回 [LLMResult](#LLMResult)。
-
-- 预计算输入 tokens
-
-  若模型未提供预计算 tokens 接口，可直接返回 0。
-
-  ```python
-  def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],
-                     tools: Optional[list[PromptMessageTool]] = None) -> int:
-      """
-      Get number of tokens for given prompt messages
-
-      :param model: model name
-      :param credentials: model credentials
-      :param prompt_messages: prompt messages
-      :param tools: tools for tool calling
-      :return:
-      """
-  ```
-
-  参数说明见上述 `LLM 调用`。
-
-  该接口需要根据对应`model`选择合适的`tokenizer`进行计算，如果对应模型没有提供`tokenizer`，可以使用`AIModel`基类中的`_get_num_tokens_by_gpt2(text: str)`方法进行计算。
-
-- 获取自定义模型规则 [可选]
-
-  ```python
-  def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]:
-      """
-      Get customizable model schema
-
-      :param model: model name
-      :param credentials: model credentials
-      :return: model schema
-      """
-  ```
-
-​当供应商支持增加自定义 LLM 时，可实现此方法让自定义模型可获取模型规则，默认返回 None。
-
-对于`OpenAI`供应商下的大部分微调模型，可以通过其微调模型名称获取到其基类模型，如`gpt-3.5-turbo-1106`，然后返回基类模型的预定义参数规则，参考[openai](https://github.com/langgenius/dify/blob/feat/model-runtime/api/core/model_runtime/model_providers/openai/llm/llm.py#L801)
-的具体实现
-
-### TextEmbedding
-
-继承 `__base.text_embedding_model.TextEmbeddingModel` 基类，实现以下接口：
-
-- Embedding 调用
-
-  ```python
-  def _invoke(self, model: str, credentials: dict,
-              texts: list[str], user: Optional[str] = None) \
-          -> TextEmbeddingResult:
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param texts: texts to embed
-      :param user: unique user id
-      :return: embeddings result
-      """
-  ```
-
-  - 参数：
-
-    - `model` (string) 模型名称
-
-    - `credentials` (object) 凭据信息
-
-      凭据信息的参数由供应商 YAML 配置文件的 `provider_credential_schema` 或 `model_credential_schema` 定义，传入如：`api_key` 等。
-
-    - `texts` (array[string]) 文本列表，可批量处理
-
-    - `user` (string) [optional] 用户的唯一标识符
-
-      可以帮助供应商监控和检测滥用行为。
-
-  - 返回：
-
-    [TextEmbeddingResult](#TextEmbeddingResult) 实体。
-
-- 预计算 tokens
-
-  ```python
-  def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int:
-      """
-      Get number of tokens for given prompt messages
-
-      :param model: model name
-      :param credentials: model credentials
-      :param texts: texts to embed
-      :return:
-      """
-  ```
-
-  参数说明见上述 `Embedding 调用`。
-
-  同上述`LargeLanguageModel`，该接口需要根据对应`model`选择合适的`tokenizer`进行计算，如果对应模型没有提供`tokenizer`，可以使用`AIModel`基类中的`_get_num_tokens_by_gpt2(text: str)`方法进行计算。
-
-### Rerank
-
-继承 `__base.rerank_model.RerankModel` 基类，实现以下接口：
-
-- rerank 调用
-
-  ```python
-  def _invoke(self, model: str, credentials: dict,
-              query: str, docs: list[str], score_threshold: Optional[float] = None, top_n: Optional[int] = None,
-              user: Optional[str] = None) \
-          -> RerankResult:
-      """
-      Invoke rerank model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param query: search query
-      :param docs: docs for reranking
-      :param score_threshold: score threshold
-      :param top_n: top n
-      :param user: unique user id
-      :return: rerank result
-      """
-  ```
-
-  - 参数：
-
-    - `model` (string) 模型名称
-
-    - `credentials` (object) 凭据信息
-
-      凭据信息的参数由供应商 YAML 配置文件的 `provider_credential_schema` 或 `model_credential_schema` 定义，传入如：`api_key` 等。
-
-    - `query` (string) 查询请求内容
-
-    - `docs` (array[string]) 需要重排的分段列表
-
-    - `score_threshold` (float) [optional] Score 阈值
-
-    - `top_n` (int) [optional] 取前 n 个分段
-
-    - `user` (string) [optional] 用户的唯一标识符
-
-      可以帮助供应商监控和检测滥用行为。
-
-  - 返回：
-
-    [RerankResult](#RerankResult) 实体。
-
-### Speech2text
-
-继承 `__base.speech2text_model.Speech2TextModel` 基类，实现以下接口：
-
-- Invoke 调用
-
-  ```python
-  def _invoke(self, model: str, credentials: dict,
-              file: IO[bytes], user: Optional[str] = None) \
-          -> str:
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param file: audio file
-      :param user: unique user id
-      :return: text for given audio file
-      """	
-  ```
-
-  - 参数：
-
-    - `model` (string) 模型名称
-
-    - `credentials` (object) 凭据信息
-
-      凭据信息的参数由供应商 YAML 配置文件的 `provider_credential_schema` 或 `model_credential_schema` 定义，传入如：`api_key` 等。
-
-    - `file` (File) 文件流
-
-    - `user` (string) [optional] 用户的唯一标识符
-
-      可以帮助供应商监控和检测滥用行为。
-
-  - 返回：
-
-    语音转换后的字符串。
-
-### Text2speech
-
-继承 `__base.text2speech_model.Text2SpeechModel` 基类，实现以下接口：
-
-- Invoke 调用
-
-  ```python
-  def _invoke(self, model: str, credentials: dict, content_text: str, streaming: bool, user: Optional[str] = None):
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param content_text: text content to be translated
-      :param streaming: output is streaming
-      :param user: unique user id
-      :return: translated audio file
-      """	
-  ```
-
-  - 参数：
-
-    - `model` (string) 模型名称
-
-    - `credentials` (object) 凭据信息
-
-      凭据信息的参数由供应商 YAML 配置文件的 `provider_credential_schema` 或 `model_credential_schema` 定义，传入如：`api_key` 等。
-
-    - `content_text` (string) 需要转换的文本内容
-
-    - `streaming` (bool) 是否进行流式输出
-
-    - `user` (string) [optional] 用户的唯一标识符
-
-      可以帮助供应商监控和检测滥用行为。
-
-  - 返回：
-
-    文本转换后的语音流。
-
-### Moderation
-
-继承 `__base.moderation_model.ModerationModel` 基类，实现以下接口：
-
-- Invoke 调用
-
-  ```python
-  def _invoke(self, model: str, credentials: dict,
-              text: str, user: Optional[str] = None) \
-          -> bool:
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param text: text to moderate
-      :param user: unique user id
-      :return: false if text is safe, true otherwise
-      """
-  ```
-
-  - 参数：
-
-    - `model` (string) 模型名称
-
-    - `credentials` (object) 凭据信息
-
-      凭据信息的参数由供应商 YAML 配置文件的 `provider_credential_schema` 或 `model_credential_schema` 定义，传入如：`api_key` 等。
-
-    - `text` (string) 文本内容
-
-    - `user` (string) [optional] 用户的唯一标识符
-
-      可以帮助供应商监控和检测滥用行为。
-
-  - 返回：
-
-    False 代表传入的文本安全，True 则反之。
-
-## 实体
-
-### PromptMessageRole
-
-消息角色
-
-```python
-class PromptMessageRole(Enum):
-    """
-    Enum class for prompt message.
-    """
-    SYSTEM = "system"
-    USER = "user"
-    ASSISTANT = "assistant"
-    TOOL = "tool"
-```
-
-### PromptMessageContentType
-
-消息内容类型，分为纯文本和图片。
-
-```python
-class PromptMessageContentType(Enum):
-    """
-    Enum class for prompt message content type.
-    """
-    TEXT = 'text'
-    IMAGE = 'image'
-```
-
-### PromptMessageContent
-
-消息内容基类，仅作为参数声明用，不可初始化。
-
-```python
-class PromptMessageContent(BaseModel):
-    """
-    Model class for prompt message content.
-    """
-    type: PromptMessageContentType
-    data: str  # 内容数据
-```
-
-当前支持文本和图片两种类型，可支持同时传入文本和多图。
-
-需要分别初始化 `TextPromptMessageContent` 和 `ImagePromptMessageContent` 传入。
-
-### TextPromptMessageContent
-
-```python
-class TextPromptMessageContent(PromptMessageContent):
-    """
-    Model class for text prompt message content.
-    """
-    type: PromptMessageContentType = PromptMessageContentType.TEXT
-```
-
-若传入图文，其中文字需要构造此实体作为 `content` 列表中的一部分。
-
-### ImagePromptMessageContent
-
-```python
-class ImagePromptMessageContent(PromptMessageContent):
-    """
-    Model class for image prompt message content.
-    """
-    class DETAIL(Enum):
-        LOW = 'low'
-        HIGH = 'high'
-
-    type: PromptMessageContentType = PromptMessageContentType.IMAGE
-    detail: DETAIL = DETAIL.LOW  # 分辨率
-```
-
-若传入图文，其中图片需要构造此实体作为 `content` 列表中的一部分
-
-`data` 可以为 `url` 或者图片 `base64` 加密后的字符串。
-
-### PromptMessage
-
-所有 Role 消息体的基类，仅作为参数声明用，不可初始化。
-
-```python
-class PromptMessage(BaseModel):
-    """
-    Model class for prompt message.
-    """
-    role: PromptMessageRole  # 消息角色
-    content: Optional[str | list[PromptMessageContent]] = None  # 支持两种类型，字符串和内容列表，内容列表是为了满足多模态的需要，可详见 PromptMessageContent 说明。
-    name: Optional[str] = None  # 名称，可选。
-```
-
-### UserPromptMessage
-
-UserMessage 消息体，代表用户消息。
-
-```python
-class UserPromptMessage(PromptMessage):
-    """
-    Model class for user prompt message.
-    """
-    role: PromptMessageRole = PromptMessageRole.USER
-```
-
-### AssistantPromptMessage
-
-代表模型返回消息，通常用于 `few-shots` 或聊天历史传入。
-
-```python
-class AssistantPromptMessage(PromptMessage):
-    """
-    Model class for assistant prompt message.
-    """
-    class ToolCall(BaseModel):
-        """
-        Model class for assistant prompt message tool call.
-        """
-        class ToolCallFunction(BaseModel):
-            """
-            Model class for assistant prompt message tool call function.
-            """
-            name: str  # 工具名称
-            arguments: str  # 工具参数
-
-        id: str  # 工具 ID，仅在 OpenAI tool call 生效，为工具调用的唯一 ID，同一个工具可以调用多次
-        type: str  # 默认 function
-        function: ToolCallFunction  # 工具调用信息
-
-    role: PromptMessageRole = PromptMessageRole.ASSISTANT
-    tool_calls: list[ToolCall] = []  # 模型回复的工具调用结果（仅当传入 tools，并且模型认为需要调用工具时返回）
-```
-
-其中 `tool_calls` 为调用模型传入 `tools` 后，由模型返回的 `tool call` 列表。
-
-### SystemPromptMessage
-
-代表系统消息，通常用于设定给模型的系统指令。
-
-```python
-class SystemPromptMessage(PromptMessage):
-    """
-    Model class for system prompt message.
-    """
-    role: PromptMessageRole = PromptMessageRole.SYSTEM
-```
-
-### ToolPromptMessage
-
-代表工具消息，用于工具执行后将结果交给模型进行下一步计划。
-
-```python
-class ToolPromptMessage(PromptMessage):
-    """
-    Model class for tool prompt message.
-    """
-    role: PromptMessageRole = PromptMessageRole.TOOL
-    tool_call_id: str  # 工具调用 ID，若不支持 OpenAI tool call，也可传入工具名称
-```
-
-基类的 `content` 传入工具执行结果。
-
-### PromptMessageTool
-
-```python
-class PromptMessageTool(BaseModel):
-    """
-    Model class for prompt message tool.
-    """
-    name: str  # 工具名称
-    description: str  # 工具描述
-    parameters: dict  # 工具参数 dict
-```
-
-______________________________________________________________________
-
-### LLMResult
-
-```python
-class LLMResult(BaseModel):
-    """
-    Model class for llm result.
-    """
-    model: str  # 实际使用模型
-    prompt_messages: list[PromptMessage]  # prompt 消息列表
-    message: AssistantPromptMessage  # 回复消息
-    usage: LLMUsage  # 使用的 tokens 及费用信息
-    system_fingerprint: Optional[str] = None  # 请求指纹，可参考 OpenAI 该参数定义
-```
-
-### LLMResultChunkDelta
-
-流式返回中每个迭代内部 `delta` 实体
-
-```python
-class LLMResultChunkDelta(BaseModel):
-    """
-    Model class for llm result chunk delta.
-    """
-    index: int  # 序号
-    message: AssistantPromptMessage  # 回复消息
-    usage: Optional[LLMUsage] = None  # 使用的 tokens 及费用信息，仅最后一条返回
-    finish_reason: Optional[str] = None  # 结束原因，仅最后一条返回
-```
-
-### LLMResultChunk
-
-流式返回中每个迭代实体
-
-```python
-class LLMResultChunk(BaseModel):
-    """
-    Model class for llm result chunk.
-    """
-    model: str  # 实际使用模型
-    prompt_messages: list[PromptMessage]  # prompt 消息列表
-    system_fingerprint: Optional[str] = None  # 请求指纹，可参考 OpenAI 该参数定义
-    delta: LLMResultChunkDelta  # 每个迭代存在变化的内容
-```
-
-### LLMUsage
-
-```python
-class LLMUsage(ModelUsage):
-    """
-    Model class for llm usage.
-    """
-    prompt_tokens: int  # prompt 使用 tokens
-    prompt_unit_price: Decimal  # prompt 单价
-    prompt_price_unit: Decimal  # prompt 价格单位，即单价基于多少 tokens 
-    prompt_price: Decimal  # prompt 费用
-    completion_tokens: int  # 回复使用 tokens
-    completion_unit_price: Decimal  # 回复单价
-    completion_price_unit: Decimal  # 回复价格单位，即单价基于多少 tokens 
-    completion_price: Decimal  # 回复费用
-    total_tokens: int  # 总使用 token 数
-    total_price: Decimal  # 总费用
-    currency: str  # 货币单位
-    latency: float  # 请求耗时 (s)
-```
-
-______________________________________________________________________
-
-### TextEmbeddingResult
-
-```python
-class TextEmbeddingResult(BaseModel):
-    """
-    Model class for text embedding result.
-    """
-    model: str  # 实际使用模型
-    embeddings: list[list[float]]  # embedding 向量列表，对应传入的 texts 列表
-    usage: EmbeddingUsage  # 使用信息
-```
-
-### EmbeddingUsage
-
-```python
-class EmbeddingUsage(ModelUsage):
-    """
-    Model class for embedding usage.
-    """
-    tokens: int  # 使用 token 数
-    total_tokens: int  # 总使用 token 数
-    unit_price: Decimal  # 单价
-    price_unit: Decimal  # 价格单位，即单价基于多少 tokens
-    total_price: Decimal  # 总费用
-    currency: str  # 货币单位
-    latency: float  # 请求耗时 (s)
-```
-
-______________________________________________________________________
-
-### RerankResult
-
-```python
-class RerankResult(BaseModel):
-    """
-    Model class for rerank result.
-    """
-    model: str  # 实际使用模型
-    docs: list[RerankDocument]  # 重排后的分段列表	
-```
-
-### RerankDocument
-
-```python
-class RerankDocument(BaseModel):
-    """
-    Model class for rerank document.
-    """
-    index: int  # 原序号
-    text: str  # 分段文本内容
-    score: float  # 分数
-```

api/core/model_runtime/docs/zh_Hans/predefined_model_scale_out.md

@@ -1,172 +0,0 @@
-## 预定义模型接入
-
-供应商集成完成后，接下来为供应商下模型的接入。
-
-我们首先需要确定接入模型的类型，并在对应供应商的目录下创建对应模型类型的 `module`。
-
-当前支持模型类型如下：
-
-- `llm` 文本生成模型
-- `text_embedding` 文本 Embedding 模型
-- `rerank` Rerank 模型
-- `speech2text` 语音转文字
-- `tts` 文字转语音
-- `moderation` 审查
-
-依旧以 `Anthropic` 为例，`Anthropic` 仅支持 LLM，因此在 `model_providers.anthropic` 创建一个 `llm` 为名称的 `module`。
-
-对于预定义的模型，我们首先需要在 `llm` `module` 下创建以模型名为文件名称的 YAML 文件，如：`claude-2.1.yaml`。
-
-### 准备模型 YAML
-
-```yaml
-model: claude-2.1  # 模型标识
-# 模型展示名称，可设置 en_US 英文、zh_Hans 中文两种语言，zh_Hans 不设置将默认使用 en_US。
-# 也可不设置 label，则使用 model 标识内容。
-label:
-  en_US: claude-2.1
-model_type: llm  # 模型类型，claude-2.1 为 LLM
-features:  # 支持功能，agent-thought 为支持 Agent 推理，vision 为支持图片理解
-- agent-thought
-model_properties:  # 模型属性
-  mode: chat  # LLM 模式，complete 文本补全模型，chat 对话模型
-  context_size: 200000  # 支持最大上下文大小
-parameter_rules:  # 模型调用参数规则，仅 LLM 需要提供
-- name: temperature  # 调用参数变量名
-  # 默认预置了 5 种变量内容配置模板，temperature/top_p/max_tokens/presence_penalty/frequency_penalty
-  # 可在 use_template 中直接设置模板变量名，将会使用 entities.defaults.PARAMETER_RULE_TEMPLATE 中的默认配置
-  # 若设置了额外的配置参数，将覆盖默认配置
-  use_template: temperature
-- name: top_p
-  use_template: top_p
-- name: top_k
-  label:  # 调用参数展示名称
-    zh_Hans: 取样数量
-    en_US: Top k
-  type: int  # 参数类型，支持 float/int/string/boolean
-  help:  # 帮助信息，描述参数作用
-    zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
-    en_US: Only sample from the top K options for each subsequent token.
-  required: false  # 是否必填，可不设置
-- name: max_tokens_to_sample
-  use_template: max_tokens
-  default: 4096  # 参数默认值
-  min: 1  # 参数最小值，仅 float/int 可用
-  max: 4096  # 参数最大值，仅 float/int 可用
-pricing:  # 价格信息
-  input: '8.00'  # 输入单价，即 Prompt 单价
-  output: '24.00'  # 输出单价，即返回内容单价
-  unit: '0.000001'  # 价格单位，即上述价格为每 100K 的单价
-  currency: USD  # 价格货币
-```
-
-建议将所有模型配置都准备完毕后再开始模型代码的实现。
-
-同样，也可以参考 `model_providers` 目录下其他供应商对应模型类型目录下的 YAML 配置信息，完整的 YAML 规则见：[Schema](schema.md#aimodelentity)。
-
-### 实现模型调用代码
-
-接下来需要在 `llm` `module` 下创建一个同名的 python 文件 `llm.py` 来编写代码实现。
-
-在 `llm.py` 中创建一个 Anthropic LLM 类，我们取名为 `AnthropicLargeLanguageModel`（随意），继承 `__base.large_language_model.LargeLanguageModel` 基类，实现以下几个方法：
-
-- LLM 调用
-
-  实现 LLM 调用的核心方法，可同时支持流式和同步返回。
-
-  ```python
-  def _invoke(self, model: str, credentials: dict,
-              prompt_messages: list[PromptMessage], model_parameters: dict,
-              tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
-              stream: bool = True, user: Optional[str] = None) \
-          -> Union[LLMResult, Generator]:
-      """
-      Invoke large language model
-
-      :param model: model name
-      :param credentials: model credentials
-      :param prompt_messages: prompt messages
-      :param model_parameters: model parameters
-      :param tools: tools for tool calling
-      :param stop: stop words
-      :param stream: is stream response
-      :param user: unique user id
-      :return: full response or stream response chunk generator result
-      """
-  ```
-
-  在实现时，需要注意使用两个函数来返回数据，分别用于处理同步返回和流式返回，因为 Python 会将函数中包含 `yield` 关键字的函数识别为生成器函数，返回的数据类型固定为 `Generator`，因此同步和流式返回需要分别实现，就像下面这样（注意下面例子使用了简化参数，实际实现时需要按照上面的参数列表进行实现）：
-
-  ```python
-  def _invoke(self, stream: bool, **kwargs) \
-          -> Union[LLMResult, Generator]:
-      if stream:
-            return self._handle_stream_response(**kwargs)
-      return self._handle_sync_response(**kwargs)
-
-  def _handle_stream_response(self, **kwargs) -> Generator:
-      for chunk in response:
-            yield chunk
-  def _handle_sync_response(self, **kwargs) -> LLMResult:
-      return LLMResult(**response)
-  ```
-
-- 预计算输入 tokens
-
-  若模型未提供预计算 tokens 接口，可直接返回 0。
-
-  ```python
-  def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],
-                     tools: Optional[list[PromptMessageTool]] = None) -> int:
-      """
-      Get number of tokens for given prompt messages
-
-      :param model: model name
-      :param credentials: model credentials
-      :param prompt_messages: prompt messages
-      :param tools: tools for tool calling
-      :return:
-      """
-  ```
-
-- 模型凭据校验
-
-  与供应商凭据校验类似，这里针对单个模型进行校验。
-
-  ```python
-  def validate_credentials(self, model: str, credentials: dict) -> None:
-      """
-      Validate model credentials
-
-      :param model: model name
-      :param credentials: model credentials
-      :return:
-      """
-  ```
-
-- 调用异常错误映射表
-
-  当模型调用异常时需要映射到 Runtime 指定的 `InvokeError` 类型，方便 Dify 针对不同错误做不同后续处理。
-
-  Runtime Errors:
-
-  - `InvokeConnectionError` 调用连接错误
-  - `InvokeServerUnavailableError ` 调用服务方不可用
-  - `InvokeRateLimitError ` 调用达到限额
-  - `InvokeAuthorizationError` 调用鉴权失败
-  - `InvokeBadRequestError ` 调用传参有误
-
-  ```python
-  @property
-  def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
-      """
-      Map model invoke error to unified error
-      The key is the error type thrown to the caller
-      The value is the error type thrown by the model,
-      which needs to be converted into a unified error type for the caller.
-
-      :return: Invoke error mapping
-      """
-  ```
-
-接口方法说明见：[Interfaces](./interfaces.md)，具体实现可参考：[llm.py](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/llm/llm.py)。

api/core/model_runtime/docs/zh_Hans/provider_scale_out.md

@@ -1,192 +0,0 @@
-## 增加新供应商
-
-供应商支持三种模型配置方式：
-
-- `predefined-model  ` 预定义模型
-
-  表示用户只需要配置统一的供应商凭据即可使用供应商下的预定义模型。
-
-- `customizable-model` 自定义模型
-
-  用户需要新增每个模型的凭据配置，如 Xinference，它同时支持 LLM 和 Text Embedding，但是每个模型都有唯一的**model_uid**，如果想要将两者同时接入，就需要为每个模型配置一个**model_uid**。
-
-- `fetch-from-remote` 从远程获取
-
-  与 `predefined-model` 配置方式一致，只需要配置统一的供应商凭据即可，模型通过凭据信息从供应商获取。
-
-  如 OpenAI，我们可以基于 gpt-turbo-3.5 来 Fine Tune 多个模型，而他们都位于同一个**api_key**下，当配置为 `fetch-from-remote` 时，开发者只需要配置统一的**api_key**即可让 DifyRuntime 获取到开发者所有的微调模型并接入 Dify。
-
-这三种配置方式**支持共存**，即存在供应商支持 `predefined-model` + `customizable-model` 或 `predefined-model` + `fetch-from-remote` 等，也就是配置了供应商统一凭据可以使用预定义模型和从远程获取的模型，若新增了模型，则可以在此基础上额外使用自定义的模型。
-
-## 开始
-
-### 介绍
-
-#### 名词解释
-
-- `module`: 一个`module`即为一个 Python Package，或者通俗一点，称为一个文件夹，里面包含了一个`__init__.py`文件，以及其他的`.py`文件。
-
-#### 步骤
-
-新增一个供应商主要分为几步，这里简单列出，帮助大家有一个大概的认识，具体的步骤会在下面详细介绍。
-
-- 创建供应商 yaml 文件，根据[ProviderSchema](./schema.md#provider)编写
-- 创建供应商代码，实现一个`class`。
-- 根据模型类型，在供应商`module`下创建对应的模型类型 `module`，如`llm`或`text_embedding`。
-- 根据模型类型，在对应的模型`module`下创建同名的代码文件，如`llm.py`，并实现一个`class`。
-- 如果有预定义模型，根据模型名称创建同名的 yaml 文件在模型`module`下，如`claude-2.1.yaml`，根据[AIModelEntity](./schema.md#aimodelentity)编写。
-- 编写测试代码，确保功能可用。
-
-### 开始吧
-
-增加一个新的供应商需要先确定供应商的英文标识，如 `anthropic`，使用该标识在 `model_providers` 创建以此为名称的 `module`。
-
-在此 `module` 下，我们需要先准备供应商的 YAML 配置。
-
-#### 准备供应商 YAML
-
-此处以 `Anthropic` 为例，预设了供应商基础信息、支持的模型类型、配置方式、凭据规则。
-
-```YAML
-provider: anthropic  # 供应商标识
-label:  # 供应商展示名称，可设置 en_US 英文、zh_Hans 中文两种语言，zh_Hans 不设置将默认使用 en_US。
-  en_US: Anthropic
-icon_small:  # 供应商小图标，存储在对应供应商实现目录下的 _assets 目录，中英文策略同 label
-  en_US: icon_s_en.png
-icon_large:  # 供应商大图标，存储在对应供应商实现目录下的 _assets 目录，中英文策略同 label
-  en_US: icon_l_en.png
-supported_model_types:  # 支持的模型类型，Anthropic 仅支持 LLM
-- llm
-configurate_methods:  # 支持的配置方式，Anthropic 仅支持预定义模型
-- predefined-model
-provider_credential_schema:  # 供应商凭据规则，由于 Anthropic 仅支持预定义模型，则需要定义统一供应商凭据规则
-  credential_form_schemas:  # 凭据表单项列表
-  - variable: anthropic_api_key  # 凭据参数变量名
-    label:  # 展示名称
-      en_US: API Key
-    type: secret-input  # 表单类型，此处 secret-input 代表加密信息输入框，编辑时只展示屏蔽后的信息。
-    required: true  # 是否必填
-    placeholder:  # PlaceHolder 信息
-      zh_Hans: 在此输入您的 API Key
-      en_US: Enter your API Key
-  - variable: anthropic_api_url
-    label:
-      en_US: API URL
-    type: text-input  # 表单类型，此处 text-input 代表文本输入框
-    required: false
-    placeholder:
-      zh_Hans: 在此输入您的 API URL
-      en_US: Enter your API URL
-```
-
-如果接入的供应商提供自定义模型，比如`OpenAI`提供微调模型，那么我们就需要添加[`model_credential_schema`](./schema.md#modelcredentialschema)，以`OpenAI`为例：
-
-```yaml
-model_credential_schema:
-  model: # 微调模型名称
-    label:
-      en_US: Model Name
-      zh_Hans: 模型名称
-    placeholder:
-      en_US: Enter your model name
-      zh_Hans: 输入模型名称
-  credential_form_schemas:
-  - variable: openai_api_key
-    label:
-      en_US: API Key
-    type: secret-input
-    required: true
-    placeholder:
-      zh_Hans: 在此输入您的 API Key
-      en_US: Enter your API Key
-  - variable: openai_organization
-    label:
-        zh_Hans: 组织 ID
-        en_US: Organization
-    type: text-input
-    required: false
-    placeholder:
-      zh_Hans: 在此输入您的组织 ID
-      en_US: Enter your Organization ID
-  - variable: openai_api_base
-    label:
-      zh_Hans: API Base
-      en_US: API Base
-    type: text-input
-    required: false
-    placeholder:
-      zh_Hans: 在此输入您的 API Base
-      en_US: Enter your API Base
-```
-
-也可以参考 `model_providers` 目录下其他供应商目录下的 YAML 配置信息，完整的 YAML 规则见：[Schema](schema.md#provider)。
-
-#### 实现供应商代码
-
-我们需要在`model_providers`下创建一个同名的 python 文件，如`anthropic.py`，并实现一个`class`，继承`__base.provider.Provider`基类，如`AnthropicProvider`。
-
-##### 自定义模型供应商
-
-当供应商为 Xinference 等自定义模型供应商时，可跳过该步骤，仅创建一个空的`XinferenceProvider`类即可，并实现一个空的`validate_provider_credentials`方法，该方法并不会被实际使用，仅用作避免抽象类无法实例化。
-
-```python
-class XinferenceProvider(Provider):
-    def validate_provider_credentials(self, credentials: dict) -> None:
-        pass
-```
-
-##### 预定义模型供应商
-
-供应商需要继承 `__base.model_provider.ModelProvider` 基类，实现 `validate_provider_credentials` 供应商统一凭据校验方法即可，可参考 [AnthropicProvider](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/anthropic.py)。
-
-```python
-def validate_provider_credentials(self, credentials: dict) -> None:
-    """
-    Validate provider credentials
-    You can choose any validate_credentials method of model type or implement validate method by yourself,
-    such as: get model list api
-
-    if validate failed, raise exception
-
-    :param credentials: provider credentials, credentials form defined in `provider_credential_schema`.
-    """
-```
-
-当然也可以先预留 `validate_provider_credentials` 实现，在模型凭据校验方法实现后直接复用。
-
-#### 增加模型
-
-#### [增加预定义模型 👈🏻](./predefined_model_scale_out.md)
-
-对于预定义模型，我们可以通过简单定义一个 yaml，并通过实现调用代码来接入。
-
-#### [增加自定义模型 👈🏻](./customizable_model_scale_out.md)
-
-对于自定义模型，我们只需要实现调用代码即可接入，但是它需要处理的参数可能会更加复杂。
-
-______________________________________________________________________
-
-### 测试
-
-为了保证接入供应商/模型的可用性，编写后的每个方法均需要在 `tests` 目录中编写对应的集成测试代码。
-
-依旧以 `Anthropic` 为例。
-
-在编写测试代码前，需要先在 `.env.example` 新增测试供应商所需要的凭据环境变量，如：`ANTHROPIC_API_KEY`。
-
-在执行前需要将 `.env.example` 复制为 `.env` 再执行。
-
-#### 编写测试代码
-
-在 `tests` 目录下创建供应商同名的 `module`: `anthropic`，继续在此模块中创建 `test_provider.py` 以及对应模型类型的 test py 文件，如下所示：
-
-```shell
-.
-├── __init__.py
-├── anthropic
-│   ├── __init__.py
-│   ├── test_llm.py       # LLM 测试
-│   └── test_provider.py  # 供应商测试
-```
-
-针对上面实现的代码的各种情况进行测试代码编写，并测试通过后提交代码。

api/core/model_runtime/docs/zh_Hans/schema.md

@@ -1,209 +0,0 @@
-# 配置规则
-
-- 供应商规则基于 [Provider](#Provider) 实体。
-
-- 模型规则基于 [AIModelEntity](#AIModelEntity) 实体。
-
-> 以下所有实体均基于 `Pydantic BaseModel`，可在 `entities` 模块中找到对应实体。
-
-### Provider
-
-- `provider` (string) 供应商标识，如：`openai`
-- `label` (object) 供应商展示名称，i18n，可设置 `en_US` 英文、`zh_Hans` 中文两种语言
-  - `zh_Hans ` (string) [optional] 中文标签名，`zh_Hans` 不设置将默认使用 `en_US`。
-  - `en_US` (string) 英文标签名
-- `description` (object) [optional] 供应商描述，i18n
-  - `zh_Hans` (string) [optional] 中文描述
-  - `en_US` (string) 英文描述
-- `icon_small` (string) [optional] 供应商小 ICON，存储在对应供应商实现目录下的 `_assets` 目录，中英文策略同 `label`
-  - `zh_Hans` (string) [optional] 中文 ICON
-  - `en_US` (string) 英文 ICON
-- `icon_large` (string) [optional] 供应商大 ICON，存储在对应供应商实现目录下的 \_assets 目录，中英文策略同 label
-  - `zh_Hans `(string) [optional] 中文 ICON
-  - `en_US` (string) 英文 ICON
-- `background` (string) [optional] 背景颜色色值，例：#FFFFFF，为空则展示前端默认色值。
-- `help` (object) [optional] 帮助信息
-  - `title` (object) 帮助标题，i18n
-    - `zh_Hans` (string) [optional] 中文标题
-    - `en_US` (string) 英文标题
-  - `url` (object) 帮助链接，i18n
-    - `zh_Hans` (string) [optional] 中文链接
-    - `en_US` (string) 英文链接
-- `supported_model_types` (array\[[ModelType](#ModelType)\]) 支持的模型类型
-- `configurate_methods` (array\[[ConfigurateMethod](#ConfigurateMethod)\]) 配置方式
-- `provider_credential_schema` ([ProviderCredentialSchema](#ProviderCredentialSchema)) 供应商凭据规格
-- `model_credential_schema` ([ModelCredentialSchema](#ModelCredentialSchema)) 模型凭据规格
-
-### AIModelEntity
-
-- `model` (string) 模型标识，如：`gpt-3.5-turbo`
-- `label` (object) [optional] 模型展示名称，i18n，可设置 `en_US` 英文、`zh_Hans` 中文两种语言
-  - `zh_Hans `(string) [optional] 中文标签名
-  - `en_US` (string) 英文标签名
-- `model_type` ([ModelType](#ModelType)) 模型类型
-- `features` (array\[[ModelFeature](#ModelFeature)\]) [optional] 支持功能列表
-- `model_properties` (object) 模型属性
-  - `mode` ([LLMMode](#LLMMode)) 模式 (模型类型 `llm` 可用)
-  - `context_size` (int) 上下文大小 (模型类型 `llm` `text-embedding` 可用)
-  - `max_chunks` (int) 最大分块数量 (模型类型 `text-embedding ` `moderation` 可用)
-  - `file_upload_limit` (int) 文件最大上传限制，单位：MB。（模型类型 `speech2text` 可用）
-  - `supported_file_extensions` (string) 支持文件扩展格式，如：mp3,mp4（模型类型 `speech2text` 可用）
-  - `default_voice` (string) 缺省音色，必选：alloy,echo,fable,onyx,nova,shimmer（模型类型 `tts` 可用）
-  - `voices` (list) 可选音色列表。
-    - `mode` (string) 音色模型。（模型类型 `tts` 可用）
-    - `name` (string) 音色模型显示名称。（模型类型 `tts` 可用）
-    - `language` (string) 音色模型支持语言。（模型类型 `tts` 可用）
-  - `word_limit` (int) 单次转换字数限制，默认按段落分段（模型类型 `tts` 可用）
-  - `audio_type` (string) 支持音频文件扩展格式，如：mp3,wav（模型类型 `tts` 可用）
-  - `max_workers` (int) 支持文字音频转换并发任务数（模型类型 `tts` 可用）
-  - `max_characters_per_chunk` (int) 每块最大字符数 (模型类型 `moderation` 可用)
-- `parameter_rules` (array\[[ParameterRule](#ParameterRule)\]) [optional] 模型调用参数规则
-- `pricing` ([PriceConfig](#PriceConfig)) [optional] 价格信息
-- `deprecated` (bool) 是否废弃。若废弃，模型列表将不再展示，但已经配置的可以继续使用，默认 False。
-
-### ModelType
-
-- `llm` 文本生成模型
-- `text-embedding` 文本 Embedding 模型
-- `rerank` Rerank 模型
-- `speech2text` 语音转文字
-- `tts` 文字转语音
-- `moderation` 审查
-
-### ConfigurateMethod
-
-- `predefined-model  ` 预定义模型
-
-  表示用户只需要配置统一的供应商凭据即可使用供应商下的预定义模型。
-
-- `customizable-model` 自定义模型
-
-  用户需要新增每个模型的凭据配置。
-
-- `fetch-from-remote` 从远程获取
-
-  与 `predefined-model` 配置方式一致，只需要配置统一的供应商凭据即可，模型通过凭据信息从供应商获取。
-
-### ModelFeature
-
-- `agent-thought` Agent 推理，一般超过 70B 有思维链能力。
-- `vision` 视觉，即：图像理解。
-- `tool-call` 工具调用
-- `multi-tool-call` 多工具调用
-- `stream-tool-call` 流式工具调用
-
-### FetchFrom
-
-- `predefined-model` 预定义模型
-- `fetch-from-remote` 远程模型
-
-### LLMMode
-
-- `completion` 文本补全
-- `chat` 对话
-
-### ParameterRule
-
-- `name` (string) 调用模型实际参数名
-
-- `use_template` (string) [optional] 使用模板
-
-  默认预置了 5 种变量内容配置模板：
-
-  - `temperature`
-  - `top_p`
-  - `frequency_penalty`
-  - `presence_penalty`
-  - `max_tokens`
-
-  可在 use_template 中直接设置模板变量名，将会使用 entities.defaults.PARAMETER_RULE_TEMPLATE 中的默认配置
-  不用设置除 `name` 和 `use_template` 之外的所有参数，若设置了额外的配置参数，将覆盖默认配置。
-  可参考 `openai/llm/gpt-3.5-turbo.yaml`。
-
-- `label` (object) [optional] 标签，i18n
-
-  - `zh_Hans`(string) [optional] 中文标签名
-  - `en_US` (string) 英文标签名
-
-- `type`(string) [optional] 参数类型
-
-  - `int` 整数
-  - `float` 浮点数
-  - `string` 字符串
-  - `boolean` 布尔型
-
-- `help` (string) [optional] 帮助信息
-
-  - `zh_Hans` (string) [optional] 中文帮助信息
-  - `en_US` (string) 英文帮助信息
-
-- `required` (bool) 是否必填，默认 False。
-
-- `default`(int/float/string/bool) [optional] 默认值
-
-- `min`(int/float) [optional] 最小值，仅数字类型适用
-
-- `max`(int/float) [optional] 最大值，仅数字类型适用
-
-- `precision`(int) [optional] 精度，保留小数位数，仅数字类型适用
-
-- `options` (array[string]) [optional] 下拉选项值，仅当 `type` 为 `string` 时适用，若不设置或为 null 则不限制选项值
-
-### PriceConfig
-
-- `input` (float) 输入单价，即 Prompt 单价
-- `output` (float) 输出单价，即返回内容单价
-- `unit` (float) 价格单位，如以 1M tokens 计价，则单价对应的单位 token 数为 `0.000001`
-- `currency` (string) 货币单位
-
-### ProviderCredentialSchema
-
-- `credential_form_schemas` (array\[[CredentialFormSchema](#CredentialFormSchema)\]) 凭据表单规范
-
-### ModelCredentialSchema
-
-- `model` (object) 模型标识，变量名默认 `model`
-  - `label` (object) 模型表单项展示名称
-    - `en_US` (string) 英文
-    - `zh_Hans`(string) [optional] 中文
-  - `placeholder` (object) 模型提示内容
-    - `en_US`(string) 英文
-    - `zh_Hans`(string) [optional] 中文
-- `credential_form_schemas` (array\[[CredentialFormSchema](#CredentialFormSchema)\]) 凭据表单规范
-
-### CredentialFormSchema
-
-- `variable` (string) 表单项变量名
-- `label` (object) 表单项标签名
-  - `en_US`(string) 英文
-  - `zh_Hans` (string) [optional] 中文
-- `type` ([FormType](#FormType)) 表单项类型
-- `required` (bool) 是否必填
-- `default`(string) 默认值
-- `options` (array\[[FormOption](#FormOption)\]) 表单项为 `select` 或 `radio` 专有属性，定义下拉内容
-- `placeholder`(object) 表单项为 `text-input `专有属性，表单项 PlaceHolder
-  - `en_US`(string) 英文
-  - `zh_Hans` (string) [optional] 中文
-- `max_length` (int) 表单项为`text-input`专有属性，定义输入最大长度，0 为不限制。
-- `show_on` (array\[[FormShowOnObject](#FormShowOnObject)\]) 当其他表单项值符合条件时显示，为空则始终显示。
-
-### FormType
-
-- `text-input` 文本输入组件
-- `secret-input` 密码输入组件
-- `select` 单选下拉
-- `radio` Radio 组件
-- `switch` 开关组件，仅支持 `true` 和 `false`
-
-### FormOption
-
-- `label` (object) 标签
-  - `en_US`(string) 英文
-  - `zh_Hans`(string) [optional] 中文
-- `value` (string) 下拉选项值
-- `show_on` (array\[[FormShowOnObject](#FormShowOnObject)\]) 当其他表单项值符合条件时显示，为空则始终显示。
-
-### FormShowOnObject
-
-- `variable` (string) 其他表单项变量名
-- `value` (string) 其他表单项变量值

api/core/ops/tencent_trace/span_builder.py

@@ -222,6 +222,59 @@ class TencentSpanBuilder:
             links=links,
         )
 
+    @staticmethod
+    def build_message_llm_span(
+        trace_info: MessageTraceInfo, trace_id: int, parent_span_id: int, user_id: str
+    ) -> SpanData:
+        """Build LLM span for message traces with detailed LLM attributes."""
+        status = Status(StatusCode.OK)
+        if trace_info.error:
+            status = Status(StatusCode.ERROR, trace_info.error)
+
+        # Extract model information from `metadata`` or `message_data`
+        trace_metadata = trace_info.metadata or {}
+        message_data = trace_info.message_data or {}
+
+        model_provider = trace_metadata.get("ls_provider") or (
+            message_data.get("model_provider", "") if isinstance(message_data, dict) else ""
+        )
+        model_name = trace_metadata.get("ls_model_name") or (
+            message_data.get("model_id", "") if isinstance(message_data, dict) else ""
+        )
+
+        inputs_str = str(trace_info.inputs or "")
+        outputs_str = str(trace_info.outputs or "")
+
+        attributes = {
+            GEN_AI_SESSION_ID: trace_metadata.get("conversation_id", ""),
+            GEN_AI_USER_ID: str(user_id),
+            GEN_AI_SPAN_KIND: GenAISpanKind.GENERATION.value,
+            GEN_AI_FRAMEWORK: "dify",
+            GEN_AI_MODEL_NAME: str(model_name),
+            GEN_AI_PROVIDER: str(model_provider),
+            GEN_AI_USAGE_INPUT_TOKENS: str(trace_info.message_tokens or 0),
+            GEN_AI_USAGE_OUTPUT_TOKENS: str(trace_info.answer_tokens or 0),
+            GEN_AI_USAGE_TOTAL_TOKENS: str(trace_info.total_tokens or 0),
+            GEN_AI_PROMPT: inputs_str,
+            GEN_AI_COMPLETION: outputs_str,
+            INPUT_VALUE: inputs_str,
+            OUTPUT_VALUE: outputs_str,
+        }
+
+        if trace_info.is_streaming_request:
+            attributes[GEN_AI_IS_STREAMING_REQUEST] = "true"
+
+        return SpanData(
+            trace_id=trace_id,
+            parent_span_id=parent_span_id,
+            span_id=TencentTraceUtils.convert_to_span_id(trace_info.message_id, "llm"),
+            name="GENERATION",
+            start_time=TencentSpanBuilder._get_time_nanoseconds(trace_info.start_time),
+            end_time=TencentSpanBuilder._get_time_nanoseconds(trace_info.end_time),
+            attributes=attributes,
+            status=status,
+        )
+
     @staticmethod
     def build_tool_span(trace_info: ToolTraceInfo, trace_id: int, parent_span_id: int) -> SpanData:
         """Build tool span."""

api/core/ops/tencent_trace/tencent_trace.py

@@ -107,9 +107,13 @@ class TencentDataTrace(BaseTraceInstance):
                 links.append(TencentTraceUtils.create_link(trace_info.trace_id))
 
             message_span = TencentSpanBuilder.build_message_span(trace_info, trace_id, str(user_id), links)
-
             self.trace_client.add_span(message_span)
 
+            # Add LLM child span with detailed attributes
+            parent_span_id = TencentTraceUtils.convert_to_span_id(trace_info.message_id, "message")
+            llm_span = TencentSpanBuilder.build_message_llm_span(trace_info, trace_id, parent_span_id, str(user_id))
+            self.trace_client.add_span(llm_span)
+
             self._record_message_llm_metrics(trace_info)
 
             # Record trace duration for entry span

api/core/tools/entities/tool_bundle.py

@@ -1,4 +1,6 @@
-from pydantic import BaseModel
+from collections.abc import Mapping
+
+from pydantic import BaseModel, Field
 
 from core.tools.entities.tool_entities import ToolParameter
 
@@ -25,3 +27,5 @@ class ApiToolBundle(BaseModel):
     icon: str | None = None
     # openapi operation
     openapi: dict
+    # output schema
+    output_schema: Mapping[str, object] = Field(default_factory=dict)

api/core/tools/utils/workflow_configuration_sync.py

@@ -3,6 +3,7 @@ from typing import Any
 
 from core.app.app_config.entities import VariableEntity
 from core.tools.entities.tool_entities import WorkflowToolParameterConfiguration
+from core.workflow.nodes.base.entities import OutputVariableEntity
 
 
 class WorkflowToolConfigurationUtils:
@@ -24,6 +25,31 @@ class WorkflowToolConfigurationUtils:
 
         return [VariableEntity.model_validate(variable) for variable in start_node.get("data", {}).get("variables", [])]
 
+    @classmethod
+    def get_workflow_graph_output(cls, graph: Mapping[str, Any]) -> Sequence[OutputVariableEntity]:
+        """
+        get workflow graph output
+        """
+        nodes = graph.get("nodes", [])
+        outputs_by_variable: dict[str, OutputVariableEntity] = {}
+        variable_order: list[str] = []
+
+        for node in nodes:
+            if node.get("data", {}).get("type") != "end":
+                continue
+
+            for output in node.get("data", {}).get("outputs", []):
+                entity = OutputVariableEntity.model_validate(output)
+                variable = entity.variable
+
+                if variable not in variable_order:
+                    variable_order.append(variable)
+
+                # Later end nodes override duplicated variable definitions.
+                outputs_by_variable[variable] = entity
+
+        return [outputs_by_variable[variable] for variable in variable_order]
+
     @classmethod
     def check_is_synced(
         cls, variables: list[VariableEntity], tool_configurations: list[WorkflowToolParameterConfiguration]

api/core/tools/workflow_as_tool/provider.py

@@ -162,6 +162,20 @@ class WorkflowToolProviderController(ToolProviderController):
             else:
                 raise ValueError("variable not found")
 
+        # get output schema from workflow
+        outputs = WorkflowToolConfigurationUtils.get_workflow_graph_output(graph)
+
+        reserved_keys = {"json", "text", "files"}
+
+        properties = {}
+        for output in outputs:
+            if output.variable not in reserved_keys:
+                properties[output.variable] = {
+                    "type": output.value_type,
+                    "description": "",
+                }
+        output_schema = {"type": "object", "properties": properties}
+
         return WorkflowTool(
             workflow_as_tool_id=db_provider.id,
             entity=ToolEntity(
@@ -177,6 +191,7 @@ class WorkflowToolProviderController(ToolProviderController):
                     llm=db_provider.description,
                 ),
                 parameters=workflow_tool_parameters,
+                output_schema=output_schema,
             ),
             runtime=ToolRuntime(
                 tenant_id=db_provider.tenant_id,

api/core/tools/workflow_as_tool/tool.py

@@ -114,6 +114,11 @@ class WorkflowTool(Tool):
             for file in files:
                 yield self.create_file_message(file)  # type: ignore
 
+        # traverse `outputs` field and create variable messages
+        for key, value in outputs.items():
+            if key not in {"text", "json", "files"}:
+                yield self.create_variable_message(variable_name=key, variable_value=value)
+
         self._latest_usage = self._derive_usage_from_result(data)
 
         yield self.create_text_message(json.dumps(outputs, ensure_ascii=False))

api/core/workflow/entities/__init__.py

@@ -1,17 +1,11 @@
-from ..runtime.graph_runtime_state import GraphRuntimeState
-from ..runtime.variable_pool import VariablePool
 from .agent import AgentNodeStrategyInit
 from .graph_init_params import GraphInitParams
 from .workflow_execution import WorkflowExecution
 from .workflow_node_execution import WorkflowNodeExecution
-from .workflow_pause import WorkflowPauseEntity
 
 __all__ = [
     "AgentNodeStrategyInit",
     "GraphInitParams",
-    "GraphRuntimeState",
-    "VariablePool",
     "WorkflowExecution",
     "WorkflowNodeExecution",
-    "WorkflowPauseEntity",
 ]

api/core/workflow/entities/pause_reason.py

@@ -1,49 +1,26 @@
 from enum import StrEnum, auto
-from typing import Annotated, Any, ClassVar, TypeAlias
+from typing import Annotated, Literal, TypeAlias
 
-from pydantic import BaseModel, Discriminator, Tag
+from pydantic import BaseModel, Field
 
 
-class _PauseReasonType(StrEnum):
+class PauseReasonType(StrEnum):
     HUMAN_INPUT_REQUIRED = auto()
     SCHEDULED_PAUSE = auto()
 
 
-class _PauseReasonBase(BaseModel):
-    TYPE: ClassVar[_PauseReasonType]
+class HumanInputRequired(BaseModel):
+    TYPE: Literal[PauseReasonType.HUMAN_INPUT_REQUIRED] = PauseReasonType.HUMAN_INPUT_REQUIRED
+
+    form_id: str
+    # The identifier of the human input node causing the pause.
+    node_id: str
 
 
-class HumanInputRequired(_PauseReasonBase):
-    TYPE = _PauseReasonType.HUMAN_INPUT_REQUIRED
-
-
-class SchedulingPause(_PauseReasonBase):
-    TYPE = _PauseReasonType.SCHEDULED_PAUSE
+class SchedulingPause(BaseModel):
+    TYPE: Literal[PauseReasonType.SCHEDULED_PAUSE] = PauseReasonType.SCHEDULED_PAUSE
 
     message: str
 
 
-def _get_pause_reason_discriminator(v: Any) -> _PauseReasonType | None:
-    if isinstance(v, _PauseReasonBase):
-        return v.TYPE
-    elif isinstance(v, dict):
-        reason_type_str = v.get("TYPE")
-        if reason_type_str is None:
-            return None
-        try:
-            reason_type = _PauseReasonType(reason_type_str)
-        except ValueError:
-            return None
-        return reason_type
-    else:
-        # return None if the discriminator value isn't found
-        return None
-
-
-PauseReason: TypeAlias = Annotated[
-    (
-        Annotated[HumanInputRequired, Tag(_PauseReasonType.HUMAN_INPUT_REQUIRED)]
-        | Annotated[SchedulingPause, Tag(_PauseReasonType.SCHEDULED_PAUSE)]
-    ),
-    Discriminator(_get_pause_reason_discriminator),
-]
+PauseReason: TypeAlias = Annotated[HumanInputRequired | SchedulingPause, Field(discriminator="TYPE")]

api/core/workflow/graph_engine/domain/graph_execution.py

@@ -42,7 +42,7 @@ class GraphExecutionState(BaseModel):
     completed: bool = Field(default=False)
     aborted: bool = Field(default=False)
     paused: bool = Field(default=False)
-    pause_reason: PauseReason | None = Field(default=None)
+    pause_reasons: list[PauseReason] = Field(default_factory=list)
     error: GraphExecutionErrorState | None = Field(default=None)
     exceptions_count: int = Field(default=0)
     node_executions: list[NodeExecutionState] = Field(default_factory=list[NodeExecutionState])
@@ -107,7 +107,7 @@ class GraphExecution:
     completed: bool = False
     aborted: bool = False
     paused: bool = False
-    pause_reason: PauseReason | None = None
+    pause_reasons: list[PauseReason] = field(default_factory=list)
     error: Exception | None = None
     node_executions: dict[str, NodeExecution] = field(default_factory=dict[str, NodeExecution])
     exceptions_count: int = 0
@@ -137,10 +137,8 @@ class GraphExecution:
             raise RuntimeError("Cannot pause execution that has completed")
         if self.aborted:
             raise RuntimeError("Cannot pause execution that has been aborted")
-        if self.paused:
-            return
         self.paused = True
-        self.pause_reason = reason
+        self.pause_reasons.append(reason)
 
     def fail(self, error: Exception) -> None:
         """Mark the graph execution as failed."""
@@ -195,7 +193,7 @@ class GraphExecution:
             completed=self.completed,
             aborted=self.aborted,
             paused=self.paused,
-            pause_reason=self.pause_reason,
+            pause_reasons=self.pause_reasons,
             error=_serialize_error(self.error),
             exceptions_count=self.exceptions_count,
             node_executions=node_states,
@@ -221,7 +219,7 @@ class GraphExecution:
         self.completed = state.completed
         self.aborted = state.aborted
         self.paused = state.paused
-        self.pause_reason = state.pause_reason
+        self.pause_reasons = state.pause_reasons
         self.error = _deserialize_error(state.error)
         self.exceptions_count = state.exceptions_count
         self.node_executions = {

api/core/workflow/graph_engine/event_management/event_manager.py

@@ -110,7 +110,13 @@ class EventManager:
         """
         with self._lock.write_lock():
             self._events.append(event)
-            self._notify_layers(event)
+
+        # NOTE: `_notify_layers` is intentionally called outside the critical section
+        # to minimize lock contention and avoid blocking other readers or writers.
+        #
+        # The public `notify_layers` method also does not use a write lock,
+        # so protecting `_notify_layers` with a lock here is unnecessary.
+        self._notify_layers(event)
 
     def _get_new_events(self, start_index: int) -> list[GraphEngineEvent]:
         """

api/core/workflow/graph_engine/graph_engine.py

@@ -232,7 +232,7 @@ class GraphEngine:
                 self._graph_execution.start()
             else:
                 self._graph_execution.paused = False
-                self._graph_execution.pause_reason = None
+                self._graph_execution.pause_reasons = []
 
             start_event = GraphRunStartedEvent()
             self._event_manager.notify_layers(start_event)
@@ -246,11 +246,11 @@ class GraphEngine:
 
             # Handle completion
             if self._graph_execution.is_paused:
-                pause_reason = self._graph_execution.pause_reason
-                assert pause_reason is not None, "pause_reason should not be None when execution is paused."
+                pause_reasons = self._graph_execution.pause_reasons
+                assert pause_reasons, "pause_reasons should not be empty when execution is paused."
                 # Ensure we have a valid PauseReason for the event
                 paused_event = GraphRunPausedEvent(
-                    reason=pause_reason,
+                    reasons=pause_reasons,
                     outputs=self._graph_runtime_state.outputs,
                 )
                 self._event_manager.notify_layers(paused_event)

api/core/workflow/graph_events/graph.py

@@ -45,8 +45,7 @@ class GraphRunAbortedEvent(BaseGraphEvent):
 class GraphRunPausedEvent(BaseGraphEvent):
     """Event emitted when a graph run is paused by user command."""
 
-    # reason: str | None = Field(default=None, description="reason for pause")
-    reason: PauseReason = Field(..., description="reason for pause")
+    reasons: list[PauseReason] = Field(description="reason for pause", default_factory=list)
     outputs: dict[str, object] = Field(
         default_factory=dict,
         description="Outputs available to the client while the run is paused.",

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

@@ -26,7 +26,6 @@ from core.tools.tool_manager import ToolManager
 from core.tools.utils.message_transformer import ToolFileMessageTransformer
 from core.variables.segments import ArrayFileSegment, StringSegment
 from core.workflow.enums import (
-    ErrorStrategy,
     NodeType,
     SystemVariableKey,
     WorkflowNodeExecutionMetadataKey,
@@ -40,7 +39,6 @@ from core.workflow.node_events import (
     StreamCompletedEvent,
 )
 from core.workflow.nodes.agent.entities import AgentNodeData, AgentOldVersionModelFeatures, ParamsAutoGenerated
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.base.variable_template_parser import VariableTemplateParser
 from core.workflow.runtime import VariablePool
@@ -66,34 +64,12 @@ if TYPE_CHECKING:
     from core.plugin.entities.request import InvokeCredentials
 
 
-class AgentNode(Node):
+class AgentNode(Node[AgentNodeData]):
     """
     Agent Node
     """
 
     node_type = NodeType.AGENT
-    _node_data: AgentNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = AgentNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
 
     @classmethod
     def version(cls) -> str:
@@ -105,8 +81,8 @@ class AgentNode(Node):
         try:
             strategy = get_plugin_agent_strategy(
                 tenant_id=self.tenant_id,
-                agent_strategy_provider_name=self._node_data.agent_strategy_provider_name,
-                agent_strategy_name=self._node_data.agent_strategy_name,
+                agent_strategy_provider_name=self.node_data.agent_strategy_provider_name,
+                agent_strategy_name=self.node_data.agent_strategy_name,
             )
         except Exception as e:
             yield StreamCompletedEvent(
@@ -124,13 +100,13 @@ class AgentNode(Node):
         parameters = self._generate_agent_parameters(
             agent_parameters=agent_parameters,
             variable_pool=self.graph_runtime_state.variable_pool,
-            node_data=self._node_data,
+            node_data=self.node_data,
             strategy=strategy,
         )
         parameters_for_log = self._generate_agent_parameters(
             agent_parameters=agent_parameters,
             variable_pool=self.graph_runtime_state.variable_pool,
-            node_data=self._node_data,
+            node_data=self.node_data,
             for_log=True,
             strategy=strategy,
         )
@@ -163,7 +139,7 @@ class AgentNode(Node):
                 messages=message_stream,
                 tool_info={
                     "icon": self.agent_strategy_icon,
-                    "agent_strategy": self._node_data.agent_strategy_name,
+                    "agent_strategy": self.node_data.agent_strategy_name,
                 },
                 parameters_for_log=parameters_for_log,
                 user_id=self.user_id,
@@ -410,7 +386,7 @@ class AgentNode(Node):
             current_plugin = next(
                 plugin
                 for plugin in plugins
-                if f"{plugin.plugin_id}/{plugin.name}" == self._node_data.agent_strategy_provider_name
+                if f"{plugin.plugin_id}/{plugin.name}" == self.node_data.agent_strategy_provider_name
             )
             icon = current_plugin.declaration.icon
         except StopIteration:

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

@@ -2,48 +2,24 @@ from collections.abc import Mapping, Sequence
 from typing import Any
 
 from core.variables import ArrayFileSegment, FileSegment, Segment
-from core.workflow.enums import ErrorStrategy, NodeExecutionType, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeExecutionType, NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
 from core.workflow.nodes.answer.entities import AnswerNodeData
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.base.template import Template
 from core.workflow.nodes.base.variable_template_parser import VariableTemplateParser
 
 
-class AnswerNode(Node):
+class AnswerNode(Node[AnswerNodeData]):
     node_type = NodeType.ANSWER
     execution_type = NodeExecutionType.RESPONSE
 
-    _node_data: AnswerNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = AnswerNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"
 
     def _run(self) -> NodeRunResult:
-        segments = self.graph_runtime_state.variable_pool.convert_template(self._node_data.answer)
+        segments = self.graph_runtime_state.variable_pool.convert_template(self.node_data.answer)
         files = self._extract_files_from_segments(segments.value)
         return NodeRunResult(
             status=WorkflowNodeExecutionStatus.SUCCEEDED,
@@ -93,4 +69,4 @@ class AnswerNode(Node):
         Returns:
             Template instance for this Answer node
         """
-        return Template.from_answer_template(self._node_data.answer)
+        return Template.from_answer_template(self.node_data.answer)

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

@@ -5,7 +5,7 @@ from collections.abc import Sequence
 from enum import StrEnum
 from typing import Any, Union
 
-from pydantic import BaseModel, model_validator
+from pydantic import BaseModel, field_validator, model_validator
 
 from core.workflow.enums import ErrorStrategy
 
@@ -35,6 +35,45 @@ class VariableSelector(BaseModel):
     value_selector: Sequence[str]
 
 
+class OutputVariableType(StrEnum):
+    STRING = "string"
+    NUMBER = "number"
+    INTEGER = "integer"
+    SECRET = "secret"
+    BOOLEAN = "boolean"
+    OBJECT = "object"
+    FILE = "file"
+    ARRAY = "array"
+    ARRAY_STRING = "array[string]"
+    ARRAY_NUMBER = "array[number]"
+    ARRAY_OBJECT = "array[object]"
+    ARRAY_BOOLEAN = "array[boolean]"
+    ARRAY_FILE = "array[file]"
+    ANY = "any"
+    ARRAY_ANY = "array[any]"
+
+
+class OutputVariableEntity(BaseModel):
+    """
+    Output Variable Entity.
+    """
+
+    variable: str
+    value_type: OutputVariableType
+    value_selector: Sequence[str]
+
+    @field_validator("value_type", mode="before")
+    @classmethod
+    def normalize_value_type(cls, v: Any) -> Any:
+        """
+        Normalize value_type to handle case-insensitive array types.
+        Converts 'Array[...]' to 'array[...]' for backward compatibility.
+        """
+        if isinstance(v, str) and v.startswith("Array["):
+            return v.lower()
+        return v
+
+
 class DefaultValueType(StrEnum):
     STRING = "string"
     NUMBER = "number"

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

@@ -2,7 +2,7 @@ import logging
 from abc import abstractmethod
 from collections.abc import Generator, Mapping, Sequence
 from functools import singledispatchmethod
-from typing import Any, ClassVar
+from typing import Any, ClassVar, Generic, TypeVar, cast, get_args, get_origin
 from uuid import uuid4
 
 from core.app.entities.app_invoke_entities import InvokeFrom
@@ -49,12 +49,121 @@ from models.enums import UserFrom
 
 from .entities import BaseNodeData, RetryConfig
 
+NodeDataT = TypeVar("NodeDataT", bound=BaseNodeData)
+
 logger = logging.getLogger(__name__)
 
 
-class Node:
+class Node(Generic[NodeDataT]):
     node_type: ClassVar["NodeType"]
     execution_type: NodeExecutionType = NodeExecutionType.EXECUTABLE
+    _node_data_type: ClassVar[type[BaseNodeData]] = BaseNodeData
+
+    def __init_subclass__(cls, **kwargs: Any) -> None:
+        """
+        Automatically extract and validate the node data type from the generic parameter.
+
+        When a subclass is defined as `class MyNode(Node[MyNodeData])`, this method:
+        1. Inspects `__orig_bases__` to find the `Node[T]` parameterization
+        2. Extracts `T` (e.g., `MyNodeData`) from the generic argument
+        3. Validates that `T` is a proper `BaseNodeData` subclass
+        4. Stores it in `_node_data_type` for automatic hydration in `__init__`
+
+        This eliminates the need for subclasses to manually implement boilerplate
+        accessor methods like `_get_title()`, `_get_error_strategy()`, etc.
+
+        How it works:
+        ::
+
+            class CodeNode(Node[CodeNodeData]):
+                          │         │
+                          │         └─────────────────────────────────┐
+                          │                                           │
+                          ▼                                           ▼
+            ┌─────────────────────────────┐     ┌─────────────────────────────────┐
+            │  __orig_bases__ = (         │     │  CodeNodeData(BaseNodeData)     │
+            │    Node[CodeNodeData],      │     │    title: str                   │
+            │  )                          │     │    desc: str | None             │
+            └──────────────┬──────────────┘     │    ...                          │
+                           │                    └─────────────────────────────────┘
+                           ▼                                      ▲
+            ┌─────────────────────────────┐                       │
+            │  get_origin(base) -> Node   │                       │
+            │  get_args(base) -> (        │                       │
+            │    CodeNodeData,            │ ──────────────────────┘
+            │  )                          │
+            └──────────────┬──────────────┘
+                           │
+                           ▼
+            ┌─────────────────────────────┐
+            │  Validate:                  │
+            │  - Is it a type?            │
+            │  - Is it a BaseNodeData     │
+            │    subclass?                │
+            └──────────────┬──────────────┘
+                           │
+                           ▼
+            ┌─────────────────────────────┐
+            │  cls._node_data_type =      │
+            │    CodeNodeData             │
+            └─────────────────────────────┘
+
+        Later, in __init__:
+        ::
+
+            config["data"] ──► _hydrate_node_data() ──► _node_data_type.model_validate()
+                                                                │
+                                                                ▼
+                                                        CodeNodeData instance
+                                                        (stored in self._node_data)
+
+        Example:
+            class CodeNode(Node[CodeNodeData]):  # CodeNodeData is auto-extracted
+                node_type = NodeType.CODE
+                # No need to implement _get_title, _get_error_strategy, etc.
+        """
+        super().__init_subclass__(**kwargs)
+
+        if cls is Node:
+            return
+
+        node_data_type = cls._extract_node_data_type_from_generic()
+
+        if node_data_type is None:
+            raise TypeError(f"{cls.__name__} must inherit from Node[T] with a BaseNodeData subtype")
+
+        cls._node_data_type = node_data_type
+
+    @classmethod
+    def _extract_node_data_type_from_generic(cls) -> type[BaseNodeData] | None:
+        """
+        Extract the node data type from the generic parameter `Node[T]`.
+
+        Inspects `__orig_bases__` to find the `Node[T]` parameterization and extracts `T`.
+
+        Returns:
+            The extracted BaseNodeData subtype, or None if not found.
+
+        Raises:
+            TypeError: If the generic argument is invalid (not exactly one argument,
+                      or not a BaseNodeData subtype).
+        """
+        # __orig_bases__ contains the original generic bases before type erasure.
+        # For `class CodeNode(Node[CodeNodeData])`, this would be `(Node[CodeNodeData],)`.
+        for base in getattr(cls, "__orig_bases__", ()):  # type: ignore[attr-defined]
+            origin = get_origin(base)  # Returns `Node` for `Node[CodeNodeData]`
+            if origin is Node:
+                args = get_args(base)  # Returns `(CodeNodeData,)` for `Node[CodeNodeData]`
+                if len(args) != 1:
+                    raise TypeError(f"{cls.__name__} must specify exactly one node data generic argument")
+
+                candidate = args[0]
+                if not isinstance(candidate, type) or not issubclass(candidate, BaseNodeData):
+                    raise TypeError(f"{cls.__name__} must parameterize Node with a BaseNodeData subtype")
+
+                return candidate
+
+        return None
 
     def __init__(
         self,
@@ -63,6 +172,7 @@ class Node:
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
     ) -> None:
+        self._graph_init_params = graph_init_params
         self.id = id
         self.tenant_id = graph_init_params.tenant_id
         self.app_id = graph_init_params.app_id
@@ -83,8 +193,24 @@ class Node:
         self._node_execution_id: str = ""
         self._start_at = naive_utc_now()
 
-    @abstractmethod
-    def init_node_data(self, data: Mapping[str, Any]) -> None: ...
+        raw_node_data = config.get("data") or {}
+        if not isinstance(raw_node_data, Mapping):
+            raise ValueError("Node config data must be a mapping.")
+
+        self._node_data: NodeDataT = self._hydrate_node_data(raw_node_data)
+
+        self.post_init()
+
+    def post_init(self) -> None:
+        """Optional hook for subclasses requiring extra initialization."""
+        return
+
+    @property
+    def graph_init_params(self) -> "GraphInitParams":
+        return self._graph_init_params
+
+    def _hydrate_node_data(self, data: Mapping[str, Any]) -> NodeDataT:
+        return cast(NodeDataT, self._node_data_type.model_validate(data))
 
     @abstractmethod
     def _run(self) -> NodeRunResult | Generator[NodeEventBase, None, None]:
@@ -273,38 +399,29 @@ class Node:
     def retry(self) -> bool:
         return False
 
-    # Abstract methods that subclasses must implement to provide access
-    # to BaseNodeData properties in a type-safe way
-
-    @abstractmethod
     def _get_error_strategy(self) -> ErrorStrategy | None:
         """Get the error strategy for this node."""
-        ...
+        return self._node_data.error_strategy
 
-    @abstractmethod
     def _get_retry_config(self) -> RetryConfig:
         """Get the retry configuration for this node."""
-        ...
+        return self._node_data.retry_config
 
-    @abstractmethod
     def _get_title(self) -> str:
         """Get the node title."""
-        ...
+        return self._node_data.title
 
-    @abstractmethod
     def _get_description(self) -> str | None:
         """Get the node description."""
-        ...
+        return self._node_data.desc
 
-    @abstractmethod
     def _get_default_value_dict(self) -> dict[str, Any]:
         """Get the default values dictionary for this node."""
-        ...
+        return self._node_data.default_value_dict
 
-    @abstractmethod
     def get_base_node_data(self) -> BaseNodeData:
         """Get the BaseNodeData object for this node."""
-        ...
+        return self._node_data
 
     # Public interface properties that delegate to abstract methods
     @property
@@ -332,6 +449,11 @@ class Node:
         """Get the default values dictionary for this node."""
         return self._get_default_value_dict()
 
+    @property
+    def node_data(self) -> NodeDataT:
+        """Typed access to this node's configuration data."""
+        return self._node_data
+
     def _convert_node_run_result_to_graph_node_event(self, result: NodeRunResult) -> GraphNodeEventBase:
         match result.status:
             case WorkflowNodeExecutionStatus.FAILED:

api/core/workflow/nodes/code/code_node.py

@@ -9,9 +9,8 @@ from core.helper.code_executor.javascript.javascript_code_provider import Javasc
 from core.helper.code_executor.python3.python3_code_provider import Python3CodeProvider
 from core.variables.segments import ArrayFileSegment
 from core.variables.types import SegmentType
-from core.workflow.enums import ErrorStrategy, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.code.entities import CodeNodeData
 
@@ -22,32 +21,9 @@ from .exc import (
 )
 
 
-class CodeNode(Node):
+class CodeNode(Node[CodeNodeData]):
     node_type = NodeType.CODE
 
-    _node_data: CodeNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = CodeNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]:
         """
@@ -70,12 +46,12 @@ class CodeNode(Node):
 
     def _run(self) -> NodeRunResult:
         # Get code language
-        code_language = self._node_data.code_language
-        code = self._node_data.code
+        code_language = self.node_data.code_language
+        code = self.node_data.code
 
         # Get variables
         variables = {}
-        for variable_selector in self._node_data.variables:
+        for variable_selector in self.node_data.variables:
             variable_name = variable_selector.variable
             variable = self.graph_runtime_state.variable_pool.get(variable_selector.value_selector)
             if isinstance(variable, ArrayFileSegment):
@@ -91,7 +67,7 @@ class CodeNode(Node):
             )
 
             # Transform result
-            result = self._transform_result(result=result, output_schema=self._node_data.outputs)
+            result = self._transform_result(result=result, output_schema=self.node_data.outputs)
         except (CodeExecutionError, CodeNodeError) as e:
             return NodeRunResult(
                 status=WorkflowNodeExecutionStatus.FAILED, inputs=variables, error=str(e), error_type=type(e).__name__
@@ -428,7 +404,7 @@ class CodeNode(Node):
 
     @property
     def retry(self) -> bool:
-        return self._node_data.retry_config.retry_enabled
+        return self.node_data.retry_config.retry_enabled
 
     @staticmethod
     def _convert_boolean_to_int(value: bool | int | float | None) -> int | float | None:

api/core/workflow/nodes/datasource/datasource_node.py

@@ -20,9 +20,8 @@ from core.plugin.impl.exc import PluginDaemonClientSideError
 from core.variables.segments import ArrayAnySegment
 from core.variables.variables import ArrayAnyVariable
 from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus
-from core.workflow.enums import ErrorStrategy, NodeExecutionType, NodeType, SystemVariableKey
+from core.workflow.enums import NodeExecutionType, NodeType, SystemVariableKey
 from core.workflow.node_events import NodeRunResult, StreamChunkEvent, StreamCompletedEvent
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.base.variable_template_parser import VariableTemplateParser
 from core.workflow.nodes.tool.exc import ToolFileError
@@ -38,42 +37,20 @@ from .entities import DatasourceNodeData
 from .exc import DatasourceNodeError, DatasourceParameterError
 
 
-class DatasourceNode(Node):
+class DatasourceNode(Node[DatasourceNodeData]):
     """
     Datasource Node
     """
 
-    _node_data: DatasourceNodeData
     node_type = NodeType.DATASOURCE
     execution_type = NodeExecutionType.ROOT
 
-    def init_node_data(self, data: Mapping[str, Any]) -> None:
-        self._node_data = DatasourceNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     def _run(self) -> Generator:
         """
         Run the datasource node
         """
 
-        node_data = self._node_data
+        node_data = self.node_data
         variable_pool = self.graph_runtime_state.variable_pool
         datasource_type_segement = variable_pool.get(["sys", SystemVariableKey.DATASOURCE_TYPE])
         if not datasource_type_segement:

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

@@ -25,9 +25,8 @@ from core.file import File, FileTransferMethod, file_manager
 from core.helper import ssrf_proxy
 from core.variables import ArrayFileSegment
 from core.variables.segments import ArrayStringSegment, FileSegment
-from core.workflow.enums import ErrorStrategy, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 
 from .entities import DocumentExtractorNodeData
@@ -36,7 +35,7 @@ from .exc import DocumentExtractorError, FileDownloadError, TextExtractionError,
 logger = logging.getLogger(__name__)
 
 
-class DocumentExtractorNode(Node):
+class DocumentExtractorNode(Node[DocumentExtractorNodeData]):
     """
     Extracts text content from various file types.
     Supports plain text, PDF, and DOC/DOCX files.
@@ -44,35 +43,12 @@ class DocumentExtractorNode(Node):
 
     node_type = NodeType.DOCUMENT_EXTRACTOR
 
-    _node_data: DocumentExtractorNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = DocumentExtractorNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"
 
     def _run(self):
-        variable_selector = self._node_data.variable_selector
+        variable_selector = self.node_data.variable_selector
         variable = self.graph_runtime_state.variable_pool.get(variable_selector)
 
         if variable is None:

api/core/workflow/nodes/end/end_node.py

@@ -1,41 +1,14 @@
-from collections.abc import Mapping
-from typing import Any
-
-from core.workflow.enums import ErrorStrategy, NodeExecutionType, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeExecutionType, NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.base.template import Template
 from core.workflow.nodes.end.entities import EndNodeData
 
 
-class EndNode(Node):
+class EndNode(Node[EndNodeData]):
     node_type = NodeType.END
     execution_type = NodeExecutionType.RESPONSE
 
-    _node_data: EndNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = EndNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"
@@ -47,7 +20,7 @@ class EndNode(Node):
         This method runs after streaming is complete (if streaming was enabled).
         It collects all output variables and returns them.
         """
-        output_variables = self._node_data.outputs
+        output_variables = self.node_data.outputs
 
         outputs = {}
         for variable_selector in output_variables:
@@ -69,6 +42,6 @@ class EndNode(Node):
             Template instance for this End node
         """
         outputs_config = [
-            {"variable": output.variable, "value_selector": output.value_selector} for output in self._node_data.outputs
+            {"variable": output.variable, "value_selector": output.value_selector} for output in self.node_data.outputs
         ]
         return Template.from_end_outputs(outputs_config)

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

@@ -1,7 +1,6 @@
 from pydantic import BaseModel, Field
 
-from core.workflow.nodes.base import BaseNodeData
-from core.workflow.nodes.base.entities import VariableSelector
+from core.workflow.nodes.base.entities import BaseNodeData, OutputVariableEntity
 
 
 class EndNodeData(BaseNodeData):
@@ -9,7 +8,7 @@ class EndNodeData(BaseNodeData):
     END Node Data.
     """
 
-    outputs: list[VariableSelector]
+    outputs: list[OutputVariableEntity]
 
 
 class EndStreamParam(BaseModel):

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

@@ -7,10 +7,10 @@ from configs import dify_config
 from core.file import File, FileTransferMethod
 from core.tools.tool_file_manager import ToolFileManager
 from core.variables.segments import ArrayFileSegment
-from core.workflow.enums import ErrorStrategy, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
 from core.workflow.nodes.base import variable_template_parser
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig, VariableSelector
+from core.workflow.nodes.base.entities import VariableSelector
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.http_request.executor import Executor
 from factories import file_factory
@@ -31,32 +31,9 @@ HTTP_REQUEST_DEFAULT_TIMEOUT = HttpRequestNodeTimeout(
 logger = logging.getLogger(__name__)
 
 
-class HttpRequestNode(Node):
+class HttpRequestNode(Node[HttpRequestNodeData]):
     node_type = NodeType.HTTP_REQUEST
 
-    _node_data: HttpRequestNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = HttpRequestNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]:
         return {
@@ -90,8 +67,8 @@ class HttpRequestNode(Node):
         process_data = {}
         try:
             http_executor = Executor(
-                node_data=self._node_data,
-                timeout=self._get_request_timeout(self._node_data),
+                node_data=self.node_data,
+                timeout=self._get_request_timeout(self.node_data),
                 variable_pool=self.graph_runtime_state.variable_pool,
                 max_retries=0,
             )
@@ -246,4 +223,4 @@ class HttpRequestNode(Node):
 
     @property
     def retry(self) -> bool:
-        return self._node_data.retry_config.retry_enabled
+        return self.node_data.retry_config.retry_enabled

api/core/workflow/nodes/human_input/human_input_node.py

@@ -2,15 +2,14 @@ from collections.abc import Mapping
 from typing import Any
 
 from core.workflow.entities.pause_reason import HumanInputRequired
-from core.workflow.enums import ErrorStrategy, NodeExecutionType, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeExecutionType, NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult, PauseRequestedEvent
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 
 from .entities import HumanInputNodeData
 
 
-class HumanInputNode(Node):
+class HumanInputNode(Node[HumanInputNodeData]):
     node_type = NodeType.HUMAN_INPUT
     execution_type = NodeExecutionType.BRANCH
 
@@ -26,33 +25,10 @@ class HumanInputNode(Node):
         "handle",
     )
 
-    _node_data: HumanInputNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]) -> None:
-        self._node_data = HumanInputNodeData(**data)
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"
 
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
     def _run(self):  # type: ignore[override]
         if self._is_completion_ready():
             branch_handle = self._resolve_branch_selection()
@@ -65,17 +41,18 @@ class HumanInputNode(Node):
         return self._pause_generator()
 
     def _pause_generator(self):
-        yield PauseRequestedEvent(reason=HumanInputRequired())
+        # TODO(QuantumGhost): yield a real form id.
+        yield PauseRequestedEvent(reason=HumanInputRequired(form_id="test_form_id", node_id=self.id))
 
     def _is_completion_ready(self) -> bool:
         """Determine whether all required inputs are satisfied."""
 
-        if not self._node_data.required_variables:
+        if not self.node_data.required_variables:
             return False
 
         variable_pool = self.graph_runtime_state.variable_pool
 
-        for selector_str in self._node_data.required_variables:
+        for selector_str in self.node_data.required_variables:
             parts = selector_str.split(".")
             if len(parts) != 2:
                 return False
@@ -95,7 +72,7 @@ class HumanInputNode(Node):
             if handle:
                 return handle
 
-        default_values = self._node_data.default_value_dict
+        default_values = self.node_data.default_value_dict
         for key in self._BRANCH_SELECTION_KEYS:
             handle = self._normalize_branch_value(default_values.get(key))
             if handle:

api/core/workflow/nodes/if_else/if_else_node.py

@@ -3,9 +3,8 @@ from typing import Any, Literal
 
 from typing_extensions import deprecated
 
-from core.workflow.enums import ErrorStrategy, NodeExecutionType, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeExecutionType, NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.if_else.entities import IfElseNodeData
 from core.workflow.runtime import VariablePool
@@ -13,33 +12,10 @@ from core.workflow.utils.condition.entities import Condition
 from core.workflow.utils.condition.processor import ConditionProcessor
 
 
-class IfElseNode(Node):
+class IfElseNode(Node[IfElseNodeData]):
     node_type = NodeType.IF_ELSE
     execution_type = NodeExecutionType.BRANCH
 
-    _node_data: IfElseNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = IfElseNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"
@@ -59,8 +35,8 @@ class IfElseNode(Node):
         condition_processor = ConditionProcessor()
         try:
             # Check if the new cases structure is used
-            if self._node_data.cases:
-                for case in self._node_data.cases:
+            if self.node_data.cases:
+                for case in self.node_data.cases:
                     input_conditions, group_result, final_result = condition_processor.process_conditions(
                         variable_pool=self.graph_runtime_state.variable_pool,
                         conditions=case.conditions,
@@ -86,8 +62,8 @@ class IfElseNode(Node):
                 input_conditions, group_result, final_result = _should_not_use_old_function(  # pyright: ignore [reportDeprecated]
                     condition_processor=condition_processor,
                     variable_pool=self.graph_runtime_state.variable_pool,
-                    conditions=self._node_data.conditions or [],
-                    operator=self._node_data.logical_operator or "and",
+                    conditions=self.node_data.conditions or [],
+                    operator=self.node_data.logical_operator or "and",
                 )
 
                 selected_case_id = "true" if final_result else "false"

api/core/workflow/nodes/iteration/iteration_node.py

@@ -14,7 +14,6 @@ from core.variables.segments import ArrayAnySegment, ArraySegment
 from core.variables.variables import VariableUnion
 from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID
 from core.workflow.enums import (
-    ErrorStrategy,
     NodeExecutionType,
     NodeType,
     WorkflowNodeExecutionMetadataKey,
@@ -36,7 +35,6 @@ from core.workflow.node_events import (
     StreamCompletedEvent,
 )
 from core.workflow.nodes.base import LLMUsageTrackingMixin
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.iteration.entities import ErrorHandleMode, IterationNodeData
 from core.workflow.runtime import VariablePool
@@ -60,35 +58,13 @@ logger = logging.getLogger(__name__)
 EmptyArraySegment = NewType("EmptyArraySegment", ArraySegment)
 
 
-class IterationNode(LLMUsageTrackingMixin, Node):
+class IterationNode(LLMUsageTrackingMixin, Node[IterationNodeData]):
     """
     Iteration Node.
     """
 
     node_type = NodeType.ITERATION
     execution_type = NodeExecutionType.CONTAINER
-    _node_data: IterationNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = IterationNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
 
     @classmethod
     def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]:
@@ -159,10 +135,10 @@ class IterationNode(LLMUsageTrackingMixin, Node):
             )
 
     def _get_iterator_variable(self) -> ArraySegment | NoneSegment:
-        variable = self.graph_runtime_state.variable_pool.get(self._node_data.iterator_selector)
+        variable = self.graph_runtime_state.variable_pool.get(self.node_data.iterator_selector)
 
         if not variable:
-            raise IteratorVariableNotFoundError(f"iterator variable {self._node_data.iterator_selector} not found")
+            raise IteratorVariableNotFoundError(f"iterator variable {self.node_data.iterator_selector} not found")
 
         if not isinstance(variable, ArraySegment) and not isinstance(variable, NoneSegment):
             raise InvalidIteratorValueError(f"invalid iterator value: {variable}, please provide a list.")
@@ -197,7 +173,7 @@ class IterationNode(LLMUsageTrackingMixin, Node):
         return cast(list[object], iterator_list_value)
 
     def _validate_start_node(self) -> None:
-        if not self._node_data.start_node_id:
+        if not self.node_data.start_node_id:
             raise StartNodeIdNotFoundError(f"field start_node_id in iteration {self._node_id} not found")
 
     def _execute_iterations(
@@ -207,7 +183,7 @@ class IterationNode(LLMUsageTrackingMixin, Node):
         iter_run_map: dict[str, float],
         usage_accumulator: list[LLMUsage],
     ) -> Generator[GraphNodeEventBase | NodeEventBase, None, None]:
-        if self._node_data.is_parallel:
+        if self.node_data.is_parallel:
             # Parallel mode execution
             yield from self._execute_parallel_iterations(
                 iterator_list_value=iterator_list_value,
@@ -254,7 +230,7 @@ class IterationNode(LLMUsageTrackingMixin, Node):
         outputs.extend([None] * len(iterator_list_value))
 
         # Determine the number of parallel workers
-        max_workers = min(self._node_data.parallel_nums, len(iterator_list_value))
+        max_workers = min(self.node_data.parallel_nums, len(iterator_list_value))
 
         with ThreadPoolExecutor(max_workers=max_workers) as executor:
             # Submit all iteration tasks
@@ -310,7 +286,7 @@ class IterationNode(LLMUsageTrackingMixin, Node):
 
                 except Exception as e:
                     # Handle errors based on error_handle_mode
-                    match self._node_data.error_handle_mode:
+                    match self.node_data.error_handle_mode:
                         case ErrorHandleMode.TERMINATED:
                             # Cancel remaining futures and re-raise
                             for f in future_to_index:
@@ -323,7 +299,7 @@ class IterationNode(LLMUsageTrackingMixin, Node):
                             outputs[index] = None  # Will be filtered later
 
         # Remove None values if in REMOVE_ABNORMAL_OUTPUT mode
-        if self._node_data.error_handle_mode == ErrorHandleMode.REMOVE_ABNORMAL_OUTPUT:
+        if self.node_data.error_handle_mode == ErrorHandleMode.REMOVE_ABNORMAL_OUTPUT:
             outputs[:] = [output for output in outputs if output is not None]
 
     def _execute_single_iteration_parallel(
@@ -412,7 +388,7 @@ class IterationNode(LLMUsageTrackingMixin, Node):
         If flatten_output is True (default), flattens the list if all elements are lists.
         """
         # If flatten_output is disabled, return outputs as-is
-        if not self._node_data.flatten_output:
+        if not self.node_data.flatten_output:
             return outputs
 
         if not outputs:
@@ -592,14 +568,14 @@ class IterationNode(LLMUsageTrackingMixin, Node):
                 self._append_iteration_info_to_event(event=event, iter_run_index=current_index)
                 yield event
             elif isinstance(event, (GraphRunSucceededEvent, GraphRunPartialSucceededEvent)):
-                result = variable_pool.get(self._node_data.output_selector)
+                result = variable_pool.get(self.node_data.output_selector)
                 if result is None:
                     outputs.append(None)
                 else:
                     outputs.append(result.to_object())
                 return
             elif isinstance(event, GraphRunFailedEvent):
-                match self._node_data.error_handle_mode:
+                match self.node_data.error_handle_mode:
                     case ErrorHandleMode.TERMINATED:
                         raise IterationNodeError(event.error)
                     case ErrorHandleMode.CONTINUE_ON_ERROR:
@@ -650,7 +626,7 @@ class IterationNode(LLMUsageTrackingMixin, Node):
 
         # Initialize the iteration graph with the new node factory
         iteration_graph = Graph.init(
-            graph_config=self.graph_config, node_factory=node_factory, root_node_id=self._node_data.start_node_id
+            graph_config=self.graph_config, node_factory=node_factory, root_node_id=self.node_data.start_node_id
         )
 
         if not iteration_graph:

api/core/workflow/nodes/iteration/iteration_start_node.py

@@ -1,43 +1,16 @@
-from collections.abc import Mapping
-from typing import Any
-
-from core.workflow.enums import ErrorStrategy, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.iteration.entities import IterationStartNodeData
 
 
-class IterationStartNode(Node):
+class IterationStartNode(Node[IterationStartNodeData]):
     """
     Iteration Start Node.
     """
 
     node_type = NodeType.ITERATION_START
 
-    _node_data: IterationStartNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = IterationStartNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"

api/core/workflow/nodes/knowledge_index/knowledge_index_node.py

@@ -10,9 +10,8 @@ from core.app.entities.app_invoke_entities import InvokeFrom
 from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
 from core.rag.retrieval.retrieval_methods import RetrievalMethod
 from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus
-from core.workflow.enums import ErrorStrategy, NodeExecutionType, NodeType, SystemVariableKey
+from core.workflow.enums import NodeExecutionType, NodeType, SystemVariableKey
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.base.template import Template
 from core.workflow.runtime import VariablePool
@@ -35,34 +34,12 @@ default_retrieval_model = {
 }
 
 
-class KnowledgeIndexNode(Node):
-    _node_data: KnowledgeIndexNodeData
+class KnowledgeIndexNode(Node[KnowledgeIndexNodeData]):
     node_type = NodeType.KNOWLEDGE_INDEX
     execution_type = NodeExecutionType.RESPONSE
 
-    def init_node_data(self, data: Mapping[str, Any]) -> None:
-        self._node_data = KnowledgeIndexNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     def _run(self) -> NodeRunResult:  # type: ignore
-        node_data = self._node_data
+        node_data = self.node_data
         variable_pool = self.graph_runtime_state.variable_pool
         dataset_id = variable_pool.get(["sys", SystemVariableKey.DATASET_ID])
         if not dataset_id:

api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py

@@ -30,14 +30,12 @@ from core.variables import (
 from core.variables.segments import ArrayObjectSegment
 from core.workflow.entities import GraphInitParams
 from core.workflow.enums import (
-    ErrorStrategy,
     NodeType,
     WorkflowNodeExecutionMetadataKey,
     WorkflowNodeExecutionStatus,
 )
 from core.workflow.node_events import ModelInvokeCompletedEvent, NodeRunResult
 from core.workflow.nodes.base import LLMUsageTrackingMixin
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.knowledge_retrieval.template_prompts import (
     METADATA_FILTER_ASSISTANT_PROMPT_1,
@@ -82,11 +80,9 @@ default_retrieval_model = {
 }
 
 
-class KnowledgeRetrievalNode(LLMUsageTrackingMixin, Node):
+class KnowledgeRetrievalNode(LLMUsageTrackingMixin, Node[KnowledgeRetrievalNodeData]):
     node_type = NodeType.KNOWLEDGE_RETRIEVAL
 
-    _node_data: KnowledgeRetrievalNodeData
-
     # Instance attributes specific to LLMNode.
     # Output variable for file
     _file_outputs: list["File"]
@@ -118,34 +114,13 @@ class KnowledgeRetrievalNode(LLMUsageTrackingMixin, Node):
             )
         self._llm_file_saver = llm_file_saver
 
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = KnowledgeRetrievalNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls):
         return "1"
 
     def _run(self) -> NodeRunResult:
         # extract variables
-        variable = self.graph_runtime_state.variable_pool.get(self._node_data.query_variable_selector)
+        variable = self.graph_runtime_state.variable_pool.get(self.node_data.query_variable_selector)
         if not isinstance(variable, StringSegment):
             return NodeRunResult(
                 status=WorkflowNodeExecutionStatus.FAILED,
@@ -186,7 +161,7 @@ class KnowledgeRetrievalNode(LLMUsageTrackingMixin, Node):
         # retrieve knowledge
         usage = LLMUsage.empty_usage()
         try:
-            results, usage = self._fetch_dataset_retriever(node_data=self._node_data, query=query)
+            results, usage = self._fetch_dataset_retriever(node_data=self.node_data, query=query)
             outputs = {"result": ArrayObjectSegment(value=results)}
             return NodeRunResult(
                 status=WorkflowNodeExecutionStatus.SUCCEEDED,
@@ -559,7 +534,7 @@ class KnowledgeRetrievalNode(LLMUsageTrackingMixin, Node):
                 prompt_messages=prompt_messages,
                 stop=stop,
                 user_id=self.user_id,
-                structured_output_enabled=self._node_data.structured_output_enabled,
+                structured_output_enabled=self.node_data.structured_output_enabled,
                 structured_output=None,
                 file_saver=self._llm_file_saver,
                 file_outputs=self._file_outputs,

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

@@ -1,12 +1,11 @@
-from collections.abc import Callable, Mapping, Sequence
+from collections.abc import Callable, Sequence
 from typing import Any, TypeAlias, TypeVar
 
 from core.file import File
 from core.variables import ArrayFileSegment, ArrayNumberSegment, ArrayStringSegment
 from core.variables.segments import ArrayAnySegment, ArrayBooleanSegment, ArraySegment
-from core.workflow.enums import ErrorStrategy, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 
 from .entities import FilterOperator, ListOperatorNodeData, Order
@@ -35,32 +34,9 @@ def _negation(filter_: Callable[[_T], bool]) -> Callable[[_T], bool]:
     return wrapper
 
 
-class ListOperatorNode(Node):
+class ListOperatorNode(Node[ListOperatorNodeData]):
     node_type = NodeType.LIST_OPERATOR
 
-    _node_data: ListOperatorNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = ListOperatorNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"
@@ -70,9 +46,9 @@ class ListOperatorNode(Node):
         process_data: dict[str, Sequence[object]] = {}
         outputs: dict[str, Any] = {}
 
-        variable = self.graph_runtime_state.variable_pool.get(self._node_data.variable)
+        variable = self.graph_runtime_state.variable_pool.get(self.node_data.variable)
         if variable is None:
-            error_message = f"Variable not found for selector: {self._node_data.variable}"
+            error_message = f"Variable not found for selector: {self.node_data.variable}"
             return NodeRunResult(
                 status=WorkflowNodeExecutionStatus.FAILED, error=error_message, inputs=inputs, outputs=outputs
             )
@@ -91,7 +67,7 @@ class ListOperatorNode(Node):
                 outputs=outputs,
             )
         if not isinstance(variable, _SUPPORTED_TYPES_TUPLE):
-            error_message = f"Variable {self._node_data.variable} is not an array type, actual type: {type(variable)}"
+            error_message = f"Variable {self.node_data.variable} is not an array type, actual type: {type(variable)}"
             return NodeRunResult(
                 status=WorkflowNodeExecutionStatus.FAILED, error=error_message, inputs=inputs, outputs=outputs
             )
@@ -105,19 +81,19 @@ class ListOperatorNode(Node):
 
         try:
             # Filter
-            if self._node_data.filter_by.enabled:
+            if self.node_data.filter_by.enabled:
                 variable = self._apply_filter(variable)
 
             # Extract
-            if self._node_data.extract_by.enabled:
+            if self.node_data.extract_by.enabled:
                 variable = self._extract_slice(variable)
 
             # Order
-            if self._node_data.order_by.enabled:
+            if self.node_data.order_by.enabled:
                 variable = self._apply_order(variable)
 
             # Slice
-            if self._node_data.limit.enabled:
+            if self.node_data.limit.enabled:
                 variable = self._apply_slice(variable)
 
             outputs = {
@@ -143,7 +119,7 @@ class ListOperatorNode(Node):
     def _apply_filter(self, variable: _SUPPORTED_TYPES_ALIAS) -> _SUPPORTED_TYPES_ALIAS:
         filter_func: Callable[[Any], bool]
         result: list[Any] = []
-        for condition in self._node_data.filter_by.conditions:
+        for condition in self.node_data.filter_by.conditions:
             if isinstance(variable, ArrayStringSegment):
                 if not isinstance(condition.value, str):
                     raise InvalidFilterValueError(f"Invalid filter value: {condition.value}")
@@ -182,22 +158,22 @@ class ListOperatorNode(Node):
 
     def _apply_order(self, variable: _SUPPORTED_TYPES_ALIAS) -> _SUPPORTED_TYPES_ALIAS:
         if isinstance(variable, (ArrayStringSegment, ArrayNumberSegment, ArrayBooleanSegment)):
-            result = sorted(variable.value, reverse=self._node_data.order_by.value == Order.DESC)
+            result = sorted(variable.value, reverse=self.node_data.order_by.value == Order.DESC)
             variable = variable.model_copy(update={"value": result})
         else:
             result = _order_file(
-                order=self._node_data.order_by.value, order_by=self._node_data.order_by.key, array=variable.value
+                order=self.node_data.order_by.value, order_by=self.node_data.order_by.key, array=variable.value
             )
             variable = variable.model_copy(update={"value": result})
 
         return variable
 
     def _apply_slice(self, variable: _SUPPORTED_TYPES_ALIAS) -> _SUPPORTED_TYPES_ALIAS:
-        result = variable.value[: self._node_data.limit.size]
+        result = variable.value[: self.node_data.limit.size]
         return variable.model_copy(update={"value": result})
 
     def _extract_slice(self, variable: _SUPPORTED_TYPES_ALIAS) -> _SUPPORTED_TYPES_ALIAS:
-        value = int(self.graph_runtime_state.variable_pool.convert_template(self._node_data.extract_by.serial).text)
+        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}")
         if value > len(variable.value):

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

@@ -55,7 +55,6 @@ from core.variables import (
 from core.workflow.constants import SYSTEM_VARIABLE_NODE_ID
 from core.workflow.entities import GraphInitParams
 from core.workflow.enums import (
-    ErrorStrategy,
     NodeType,
     SystemVariableKey,
     WorkflowNodeExecutionMetadataKey,
@@ -69,7 +68,7 @@ from core.workflow.node_events import (
     StreamChunkEvent,
     StreamCompletedEvent,
 )
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig, VariableSelector
+from core.workflow.nodes.base.entities import VariableSelector
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.base.variable_template_parser import VariableTemplateParser
 from core.workflow.runtime import VariablePool
@@ -100,11 +99,9 @@ if TYPE_CHECKING:
 logger = logging.getLogger(__name__)
 
 
-class LLMNode(Node):
+class LLMNode(Node[LLMNodeData]):
     node_type = NodeType.LLM
 
-    _node_data: LLMNodeData
-
     # Compiled regex for extracting <think> blocks (with compatibility for attributes)
     _THINK_PATTERN = re.compile(r"<think[^>]*>(.*?)</think>", re.IGNORECASE | re.DOTALL)
 
@@ -139,27 +136,6 @@ class LLMNode(Node):
             )
         self._llm_file_saver = llm_file_saver
 
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = LLMNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"
@@ -176,13 +152,13 @@ class LLMNode(Node):
 
         try:
             # init messages template
-            self._node_data.prompt_template = self._transform_chat_messages(self._node_data.prompt_template)
+            self.node_data.prompt_template = self._transform_chat_messages(self.node_data.prompt_template)
 
             # fetch variables and fetch values from variable pool
-            inputs = self._fetch_inputs(node_data=self._node_data)
+            inputs = self._fetch_inputs(node_data=self.node_data)
 
             # fetch jinja2 inputs
-            jinja_inputs = self._fetch_jinja_inputs(node_data=self._node_data)
+            jinja_inputs = self._fetch_jinja_inputs(node_data=self.node_data)
 
             # merge inputs
             inputs.update(jinja_inputs)
@@ -191,9 +167,9 @@ class LLMNode(Node):
             files = (
                 llm_utils.fetch_files(
                     variable_pool=variable_pool,
-                    selector=self._node_data.vision.configs.variable_selector,
+                    selector=self.node_data.vision.configs.variable_selector,
                 )
-                if self._node_data.vision.enabled
+                if self.node_data.vision.enabled
                 else []
             )
 
@@ -201,7 +177,7 @@ class LLMNode(Node):
                 node_inputs["#files#"] = [file.to_dict() for file in files]
 
             # fetch context value
-            generator = self._fetch_context(node_data=self._node_data)
+            generator = self._fetch_context(node_data=self.node_data)
             context = None
             for event in generator:
                 context = event.context
@@ -211,7 +187,7 @@ class LLMNode(Node):
 
             # fetch model config
             model_instance, model_config = LLMNode._fetch_model_config(
-                node_data_model=self._node_data.model,
+                node_data_model=self.node_data.model,
                 tenant_id=self.tenant_id,
             )
 
@@ -219,13 +195,13 @@ class LLMNode(Node):
             memory = llm_utils.fetch_memory(
                 variable_pool=variable_pool,
                 app_id=self.app_id,
-                node_data_memory=self._node_data.memory,
+                node_data_memory=self.node_data.memory,
                 model_instance=model_instance,
             )
 
             query: str | None = None
-            if self._node_data.memory:
-                query = self._node_data.memory.query_prompt_template
+            if self.node_data.memory:
+                query = self.node_data.memory.query_prompt_template
                 if not query and (
                     query_variable := variable_pool.get((SYSTEM_VARIABLE_NODE_ID, SystemVariableKey.QUERY))
                 ):
@@ -237,29 +213,29 @@ class LLMNode(Node):
                 context=context,
                 memory=memory,
                 model_config=model_config,
-                prompt_template=self._node_data.prompt_template,
-                memory_config=self._node_data.memory,
-                vision_enabled=self._node_data.vision.enabled,
-                vision_detail=self._node_data.vision.configs.detail,
+                prompt_template=self.node_data.prompt_template,
+                memory_config=self.node_data.memory,
+                vision_enabled=self.node_data.vision.enabled,
+                vision_detail=self.node_data.vision.configs.detail,
                 variable_pool=variable_pool,
-                jinja2_variables=self._node_data.prompt_config.jinja2_variables,
+                jinja2_variables=self.node_data.prompt_config.jinja2_variables,
                 tenant_id=self.tenant_id,
             )
 
             # handle invoke result
             generator = LLMNode.invoke_llm(
-                node_data_model=self._node_data.model,
+                node_data_model=self.node_data.model,
                 model_instance=model_instance,
                 prompt_messages=prompt_messages,
                 stop=stop,
                 user_id=self.user_id,
-                structured_output_enabled=self._node_data.structured_output_enabled,
-                structured_output=self._node_data.structured_output,
+                structured_output_enabled=self.node_data.structured_output_enabled,
+                structured_output=self.node_data.structured_output,
                 file_saver=self._llm_file_saver,
                 file_outputs=self._file_outputs,
                 node_id=self._node_id,
                 node_type=self.node_type,
-                reasoning_format=self._node_data.reasoning_format,
+                reasoning_format=self.node_data.reasoning_format,
             )
 
             structured_output: LLMStructuredOutput | None = None
@@ -275,12 +251,12 @@ class LLMNode(Node):
                     reasoning_content = event.reasoning_content or ""
 
                     # For downstream nodes, determine clean text based on reasoning_format
-                    if self._node_data.reasoning_format == "tagged":
+                    if self.node_data.reasoning_format == "tagged":
                         # Keep <think> tags for backward compatibility
                         clean_text = result_text
                     else:
                         # Extract clean text from <think> tags
-                        clean_text, _ = LLMNode._split_reasoning(result_text, self._node_data.reasoning_format)
+                        clean_text, _ = LLMNode._split_reasoning(result_text, self.node_data.reasoning_format)
 
                     # Process structured output if available from the event.
                     structured_output = (
@@ -1226,7 +1202,7 @@ class LLMNode(Node):
 
     @property
     def retry(self) -> bool:
-        return self._node_data.retry_config.retry_enabled
+        return self.node_data.retry_config.retry_enabled
 
 
 def _combine_message_content_with_role(

api/core/workflow/nodes/loop/loop_end_node.py

@@ -1,43 +1,16 @@
-from collections.abc import Mapping
-from typing import Any
-
-from core.workflow.enums import ErrorStrategy, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.loop.entities import LoopEndNodeData
 
 
-class LoopEndNode(Node):
+class LoopEndNode(Node[LoopEndNodeData]):
     """
     Loop End Node.
     """
 
     node_type = NodeType.LOOP_END
 
-    _node_data: LoopEndNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = LoopEndNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"

api/core/workflow/nodes/loop/loop_node.py

@@ -8,7 +8,6 @@ from typing import TYPE_CHECKING, Any, Literal, cast
 from core.model_runtime.entities.llm_entities import LLMUsage
 from core.variables import Segment, SegmentType
 from core.workflow.enums import (
-    ErrorStrategy,
     NodeExecutionType,
     NodeType,
     WorkflowNodeExecutionMetadataKey,
@@ -29,7 +28,6 @@ from core.workflow.node_events import (
     StreamCompletedEvent,
 )
 from core.workflow.nodes.base import LLMUsageTrackingMixin
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.loop.entities import LoopNodeData, LoopVariableData
 from core.workflow.utils.condition.processor import ConditionProcessor
@@ -42,36 +40,14 @@ if TYPE_CHECKING:
 logger = logging.getLogger(__name__)
 
 
-class LoopNode(LLMUsageTrackingMixin, Node):
+class LoopNode(LLMUsageTrackingMixin, Node[LoopNodeData]):
     """
     Loop Node.
     """
 
     node_type = NodeType.LOOP
-    _node_data: LoopNodeData
     execution_type = NodeExecutionType.CONTAINER
 
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = LoopNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"
@@ -79,27 +55,27 @@ class LoopNode(LLMUsageTrackingMixin, Node):
     def _run(self) -> Generator:
         """Run the node."""
         # Get inputs
-        loop_count = self._node_data.loop_count
-        break_conditions = self._node_data.break_conditions
-        logical_operator = self._node_data.logical_operator
+        loop_count = self.node_data.loop_count
+        break_conditions = self.node_data.break_conditions
+        logical_operator = self.node_data.logical_operator
 
         inputs = {"loop_count": loop_count}
 
-        if not self._node_data.start_node_id:
+        if not self.node_data.start_node_id:
             raise ValueError(f"field start_node_id in loop {self._node_id} not found")
 
-        root_node_id = self._node_data.start_node_id
+        root_node_id = self.node_data.start_node_id
 
         # Initialize loop variables in the original variable pool
         loop_variable_selectors = {}
-        if self._node_data.loop_variables:
+        if self.node_data.loop_variables:
             value_processor: dict[Literal["constant", "variable"], Callable[[LoopVariableData], Segment | None]] = {
                 "constant": lambda var: self._get_segment_for_constant(var.var_type, var.value),
                 "variable": lambda var: self.graph_runtime_state.variable_pool.get(var.value)
                 if isinstance(var.value, list)
                 else None,
             }
-            for loop_variable in self._node_data.loop_variables:
+            for loop_variable in self.node_data.loop_variables:
                 if loop_variable.value_type not in value_processor:
                     raise ValueError(
                         f"Invalid value type '{loop_variable.value_type}' for loop variable {loop_variable.label}"
@@ -187,7 +163,7 @@ class LoopNode(LLMUsageTrackingMixin, Node):
 
                 yield LoopNextEvent(
                     index=i + 1,
-                    pre_loop_output=self._node_data.outputs,
+                    pre_loop_output=self.node_data.outputs,
                 )
 
             self._accumulate_usage(loop_usage)
@@ -195,7 +171,7 @@ class LoopNode(LLMUsageTrackingMixin, Node):
             yield LoopSucceededEvent(
                 start_at=start_at,
                 inputs=inputs,
-                outputs=self._node_data.outputs,
+                outputs=self.node_data.outputs,
                 steps=loop_count,
                 metadata={
                     WorkflowNodeExecutionMetadataKey.TOTAL_TOKENS: loop_usage.total_tokens,
@@ -217,7 +193,7 @@ class LoopNode(LLMUsageTrackingMixin, Node):
                         WorkflowNodeExecutionMetadataKey.LOOP_DURATION_MAP: loop_duration_map,
                         WorkflowNodeExecutionMetadataKey.LOOP_VARIABLE_MAP: single_loop_variable_map,
                     },
-                    outputs=self._node_data.outputs,
+                    outputs=self.node_data.outputs,
                     inputs=inputs,
                     llm_usage=loop_usage,
                 )
@@ -275,11 +251,11 @@ class LoopNode(LLMUsageTrackingMixin, Node):
             if isinstance(event, GraphRunFailedEvent):
                 raise Exception(event.error)
 
-        for loop_var in self._node_data.loop_variables or []:
+        for loop_var in self.node_data.loop_variables or []:
             key, sel = loop_var.label, [self._node_id, loop_var.label]
             segment = self.graph_runtime_state.variable_pool.get(sel)
-            self._node_data.outputs[key] = segment.value if segment else None
-        self._node_data.outputs["loop_round"] = current_index + 1
+            self.node_data.outputs[key] = segment.value if segment else None
+        self.node_data.outputs["loop_round"] = current_index + 1
 
         return reach_break_node
 

api/core/workflow/nodes/loop/loop_start_node.py

@@ -1,43 +1,16 @@
-from collections.abc import Mapping
-from typing import Any
-
-from core.workflow.enums import ErrorStrategy, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.loop.entities import LoopStartNodeData
 
 
-class LoopStartNode(Node):
+class LoopStartNode(Node[LoopStartNodeData]):
     """
     Loop Start Node.
     """
 
     node_type = NodeType.LOOP_START
 
-    _node_data: LoopStartNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = LoopStartNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"

api/core/workflow/nodes/node_factory.py

@@ -69,17 +69,9 @@ class DifyNodeFactory(NodeFactory):
             raise ValueError(f"No latest version class found for node type: {node_type}")
 
         # Create node instance
-        node_instance = node_class(
+        return node_class(
             id=node_id,
             config=node_config,
             graph_init_params=self.graph_init_params,
             graph_runtime_state=self.graph_runtime_state,
         )
-
-        # Initialize node with provided data
-        node_data = node_config.get("data", {})
-        if not is_str_dict(node_data):
-            raise ValueError(f"Node {node_id} missing data information")
-        node_instance.init_node_data(node_data)
-
-        return node_instance

api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py

@@ -27,10 +27,9 @@ from core.prompt.entities.advanced_prompt_entities import ChatModelMessage, Comp
 from core.prompt.simple_prompt_transform import ModelMode
 from core.prompt.utils.prompt_message_util import PromptMessageUtil
 from core.variables.types import ArrayValidation, SegmentType
-from core.workflow.enums import ErrorStrategy, NodeType, WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeType, WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
 from core.workflow.nodes.base import variable_template_parser
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.llm import ModelConfig, llm_utils
 from core.workflow.runtime import VariablePool
@@ -84,36 +83,13 @@ def extract_json(text):
     return None
 
 
-class ParameterExtractorNode(Node):
+class ParameterExtractorNode(Node[ParameterExtractorNodeData]):
     """
     Parameter Extractor Node.
     """
 
     node_type = NodeType.PARAMETER_EXTRACTOR
 
-    _node_data: ParameterExtractorNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = ParameterExtractorNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     _model_instance: ModelInstance | None = None
     _model_config: ModelConfigWithCredentialsEntity | None = None
 
@@ -138,7 +114,7 @@ class ParameterExtractorNode(Node):
         """
         Run the node.
         """
-        node_data = self._node_data
+        node_data = self.node_data
         variable = self.graph_runtime_state.variable_pool.get(node_data.query)
         query = variable.text if variable else ""
 

api/core/workflow/nodes/question_classifier/question_classifier_node.py

@@ -13,14 +13,13 @@ from core.prompt.simple_prompt_transform import ModelMode
 from core.prompt.utils.prompt_message_util import PromptMessageUtil
 from core.workflow.entities import GraphInitParams
 from core.workflow.enums import (
-    ErrorStrategy,
     NodeExecutionType,
     NodeType,
     WorkflowNodeExecutionMetadataKey,
     WorkflowNodeExecutionStatus,
 )
 from core.workflow.node_events import ModelInvokeCompletedEvent, NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig, VariableSelector
+from core.workflow.nodes.base.entities import VariableSelector
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.base.variable_template_parser import VariableTemplateParser
 from core.workflow.nodes.llm import LLMNode, LLMNodeChatModelMessage, LLMNodeCompletionModelPromptTemplate, llm_utils
@@ -44,12 +43,10 @@ if TYPE_CHECKING:
     from core.workflow.runtime import GraphRuntimeState
 
 
-class QuestionClassifierNode(Node):
+class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
     node_type = NodeType.QUESTION_CLASSIFIER
     execution_type = NodeExecutionType.BRANCH
 
-    _node_data: QuestionClassifierNodeData
-
     _file_outputs: list["File"]
     _llm_file_saver: LLMFileSaver
 
@@ -78,33 +75,12 @@ class QuestionClassifierNode(Node):
             )
         self._llm_file_saver = llm_file_saver
 
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = QuestionClassifierNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls):
         return "1"
 
     def _run(self):
-        node_data = self._node_data
+        node_data = self.node_data
         variable_pool = self.graph_runtime_state.variable_pool
 
         # extract variables

api/core/workflow/nodes/start/start_node.py

@@ -1,41 +1,14 @@
-from collections.abc import Mapping
-from typing import Any
-
 from core.workflow.constants import SYSTEM_VARIABLE_NODE_ID
-from core.workflow.enums import ErrorStrategy, NodeExecutionType, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeExecutionType, NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.start.entities import StartNodeData
 
 
-class StartNode(Node):
+class StartNode(Node[StartNodeData]):
     node_type = NodeType.START
     execution_type = NodeExecutionType.ROOT
 
-    _node_data: StartNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = StartNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"

api/core/workflow/nodes/template_transform/template_transform_node.py

@@ -3,41 +3,17 @@ from typing import Any
 
 from configs import dify_config
 from core.helper.code_executor.code_executor import CodeExecutionError, CodeExecutor, CodeLanguage
-from core.workflow.enums import ErrorStrategy, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.template_transform.entities import TemplateTransformNodeData
 
 MAX_TEMPLATE_TRANSFORM_OUTPUT_LENGTH = dify_config.TEMPLATE_TRANSFORM_MAX_LENGTH
 
 
-class TemplateTransformNode(Node):
+class TemplateTransformNode(Node[TemplateTransformNodeData]):
     node_type = NodeType.TEMPLATE_TRANSFORM
 
-    _node_data: TemplateTransformNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = TemplateTransformNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]:
         """
@@ -57,14 +33,14 @@ class TemplateTransformNode(Node):
     def _run(self) -> NodeRunResult:
         # Get variables
         variables: dict[str, Any] = {}
-        for variable_selector in self._node_data.variables:
+        for variable_selector in self.node_data.variables:
             variable_name = variable_selector.variable
             value = self.graph_runtime_state.variable_pool.get(variable_selector.value_selector)
             variables[variable_name] = value.to_object() if value else None
         # Run code
         try:
             result = CodeExecutor.execute_workflow_code_template(
-                language=CodeLanguage.JINJA2, code=self._node_data.template, inputs=variables
+                language=CodeLanguage.JINJA2, code=self.node_data.template, inputs=variables
             )
         except CodeExecutionError as e:
             return NodeRunResult(inputs=variables, status=WorkflowNodeExecutionStatus.FAILED, error=str(e))

api/core/workflow/nodes/tool/tool_node.py

@@ -16,14 +16,12 @@ from core.tools.workflow_as_tool.tool import WorkflowTool
 from core.variables.segments import ArrayAnySegment, ArrayFileSegment
 from core.variables.variables import ArrayAnyVariable
 from core.workflow.enums import (
-    ErrorStrategy,
     NodeType,
     SystemVariableKey,
     WorkflowNodeExecutionMetadataKey,
     WorkflowNodeExecutionStatus,
 )
 from core.workflow.node_events import NodeEventBase, NodeRunResult, StreamChunkEvent, StreamCompletedEvent
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.base.variable_template_parser import VariableTemplateParser
 from extensions.ext_database import db
@@ -42,18 +40,13 @@ if TYPE_CHECKING:
     from core.workflow.runtime import VariablePool
 
 
-class ToolNode(Node):
+class ToolNode(Node[ToolNodeData]):
     """
     Tool Node
     """
 
     node_type = NodeType.TOOL
 
-    _node_data: ToolNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = ToolNodeData.model_validate(data)
-
     @classmethod
     def version(cls) -> str:
         return "1"
@@ -64,13 +57,11 @@ class ToolNode(Node):
         """
         from core.plugin.impl.exc import PluginDaemonClientSideError, PluginInvokeError
 
-        node_data = self._node_data
-
         # fetch tool icon
         tool_info = {
-            "provider_type": node_data.provider_type.value,
-            "provider_id": node_data.provider_id,
-            "plugin_unique_identifier": node_data.plugin_unique_identifier,
+            "provider_type": self.node_data.provider_type.value,
+            "provider_id": self.node_data.provider_id,
+            "plugin_unique_identifier": self.node_data.plugin_unique_identifier,
         }
 
         # get tool runtime
@@ -82,10 +73,10 @@ class ToolNode(Node):
             # But for backward compatibility with historical data
             # this version field judgment is still preserved here.
             variable_pool: VariablePool | None = None
-            if node_data.version != "1" or node_data.tool_node_version is not None:
+            if self.node_data.version != "1" or self.node_data.tool_node_version is not None:
                 variable_pool = self.graph_runtime_state.variable_pool
             tool_runtime = ToolManager.get_workflow_tool_runtime(
-                self.tenant_id, self.app_id, self._node_id, self._node_data, self.invoke_from, variable_pool
+                self.tenant_id, self.app_id, self._node_id, self.node_data, self.invoke_from, variable_pool
             )
         except ToolNodeError as e:
             yield StreamCompletedEvent(
@@ -104,12 +95,12 @@ class ToolNode(Node):
         parameters = self._generate_parameters(
             tool_parameters=tool_parameters,
             variable_pool=self.graph_runtime_state.variable_pool,
-            node_data=self._node_data,
+            node_data=self.node_data,
         )
         parameters_for_log = self._generate_parameters(
             tool_parameters=tool_parameters,
             variable_pool=self.graph_runtime_state.variable_pool,
-            node_data=self._node_data,
+            node_data=self.node_data,
             for_log=True,
         )
         # get conversation id
@@ -154,7 +145,7 @@ class ToolNode(Node):
                     status=WorkflowNodeExecutionStatus.FAILED,
                     inputs=parameters_for_log,
                     metadata={WorkflowNodeExecutionMetadataKey.TOOL_INFO: tool_info},
-                    error=f"Failed to invoke tool {node_data.provider_name}: {str(e)}",
+                    error=f"Failed to invoke tool {self.node_data.provider_name}: {str(e)}",
                     error_type=type(e).__name__,
                 )
             )
@@ -164,7 +155,7 @@ class ToolNode(Node):
                     status=WorkflowNodeExecutionStatus.FAILED,
                     inputs=parameters_for_log,
                     metadata={WorkflowNodeExecutionMetadataKey.TOOL_INFO: tool_info},
-                    error=e.to_user_friendly_error(plugin_name=node_data.provider_name),
+                    error=e.to_user_friendly_error(plugin_name=self.node_data.provider_name),
                     error_type=type(e).__name__,
                 )
             )
@@ -498,24 +489,6 @@ class ToolNode(Node):
 
         return result
 
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @property
     def retry(self) -> bool:
-        return self._node_data.retry_config.retry_enabled
+        return self.node_data.retry_config.retry_enabled

api/core/workflow/nodes/trigger_plugin/trigger_event_node.py

@@ -1,43 +1,18 @@
 from collections.abc import Mapping
-from typing import Any
 
 from core.workflow.constants import SYSTEM_VARIABLE_NODE_ID
 from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus
-from core.workflow.enums import ErrorStrategy, NodeExecutionType, NodeType
+from core.workflow.enums import NodeExecutionType, NodeType
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 
 from .entities import TriggerEventNodeData
 
 
-class TriggerEventNode(Node):
+class TriggerEventNode(Node[TriggerEventNodeData]):
     node_type = NodeType.TRIGGER_PLUGIN
     execution_type = NodeExecutionType.ROOT
 
-    _node_data: TriggerEventNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]) -> None:
-        self._node_data = TriggerEventNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]:
         return {
@@ -68,9 +43,9 @@ class TriggerEventNode(Node):
         # Get trigger data passed when workflow was triggered
         metadata = {
             WorkflowNodeExecutionMetadataKey.TRIGGER_INFO: {
-                "provider_id": self._node_data.provider_id,
-                "event_name": self._node_data.event_name,
-                "plugin_unique_identifier": self._node_data.plugin_unique_identifier,
+                "provider_id": self.node_data.provider_id,
+                "event_name": self.node_data.event_name,
+                "plugin_unique_identifier": self.node_data.plugin_unique_identifier,
             },
         }
         node_inputs = dict(self.graph_runtime_state.variable_pool.user_inputs)

api/core/workflow/nodes/trigger_schedule/trigger_schedule_node.py

@@ -1,42 +1,17 @@
 from collections.abc import Mapping
-from typing import Any
 
 from core.workflow.constants import SYSTEM_VARIABLE_NODE_ID
 from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus
-from core.workflow.enums import ErrorStrategy, NodeExecutionType, NodeType
+from core.workflow.enums import NodeExecutionType, NodeType
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.trigger_schedule.entities import TriggerScheduleNodeData
 
 
-class TriggerScheduleNode(Node):
+class TriggerScheduleNode(Node[TriggerScheduleNodeData]):
     node_type = NodeType.TRIGGER_SCHEDULE
     execution_type = NodeExecutionType.ROOT
 
-    _node_data: TriggerScheduleNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]) -> None:
-        self._node_data = TriggerScheduleNodeData(**data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"

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

@@ -3,41 +3,17 @@ from typing import Any
 
 from core.workflow.constants import SYSTEM_VARIABLE_NODE_ID
 from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus
-from core.workflow.enums import ErrorStrategy, NodeExecutionType, NodeType
+from core.workflow.enums import NodeExecutionType, NodeType
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 
 from .entities import ContentType, WebhookData
 
 
-class TriggerWebhookNode(Node):
+class TriggerWebhookNode(Node[WebhookData]):
     node_type = NodeType.TRIGGER_WEBHOOK
     execution_type = NodeExecutionType.ROOT
 
-    _node_data: WebhookData
-
-    def init_node_data(self, data: Mapping[str, Any]) -> None:
-        self._node_data = WebhookData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def get_default_config(cls, filters: Mapping[str, object] | None = None) -> Mapping[str, object]:
         return {
@@ -108,7 +84,7 @@ class TriggerWebhookNode(Node):
         webhook_headers = webhook_data.get("headers", {})
         webhook_headers_lower = {k.lower(): v for k, v in webhook_headers.items()}
 
-        for header in self._node_data.headers:
+        for header in self.node_data.headers:
             header_name = header.name
             value = _get_normalized(webhook_headers, header_name)
             if value is None:
@@ -117,20 +93,20 @@ class TriggerWebhookNode(Node):
             outputs[sanitized_name] = value
 
         # Extract configured query parameters
-        for param in self._node_data.params:
+        for param in self.node_data.params:
             param_name = param.name
             outputs[param_name] = webhook_data.get("query_params", {}).get(param_name)
 
         # Extract configured body parameters
-        for body_param in self._node_data.body:
+        for body_param in self.node_data.body:
             param_name = body_param.name
             param_type = body_param.type
 
-            if self._node_data.content_type == ContentType.TEXT:
+            if self.node_data.content_type == ContentType.TEXT:
                 # For text/plain, the entire body is a single string parameter
                 outputs[param_name] = str(webhook_data.get("body", {}).get("raw", ""))
                 continue
-            elif self._node_data.content_type == ContentType.BINARY:
+            elif self.node_data.content_type == ContentType.BINARY:
                 outputs[param_name] = webhook_data.get("body", {}).get("raw", b"")
                 continue
 

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

@@ -23,12 +23,11 @@ class AdvancedSettings(BaseModel):
     groups: list[Group]
 
 
-class VariableAssignerNodeData(BaseNodeData):
+class VariableAggregatorNodeData(BaseNodeData):
     """
-    Variable Assigner Node Data.
+    Variable Aggregator Node Data.
     """
 
-    type: str = "variable-assigner"
     output_type: str
     variables: list[list[str]]
     advanced_settings: AdvancedSettings | None = None

api/core/workflow/nodes/variable_aggregator/variable_aggregator_node.py

@@ -1,40 +1,15 @@
 from collections.abc import Mapping
-from typing import Any
 
 from core.variables.segments import Segment
-from core.workflow.enums import ErrorStrategy, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
-from core.workflow.nodes.variable_aggregator.entities import VariableAssignerNodeData
+from core.workflow.nodes.variable_aggregator.entities import VariableAggregatorNodeData
 
 
-class VariableAggregatorNode(Node):
+class VariableAggregatorNode(Node[VariableAggregatorNodeData]):
     node_type = NodeType.VARIABLE_AGGREGATOR
 
-    _node_data: VariableAssignerNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = VariableAssignerNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     @classmethod
     def version(cls) -> str:
         return "1"
@@ -44,8 +19,8 @@ class VariableAggregatorNode(Node):
         outputs: dict[str, Segment | Mapping[str, Segment]] = {}
         inputs = {}
 
-        if not self._node_data.advanced_settings or not self._node_data.advanced_settings.group_enabled:
-            for selector in self._node_data.variables:
+        if not self.node_data.advanced_settings or not self.node_data.advanced_settings.group_enabled:
+            for selector in self.node_data.variables:
                 variable = self.graph_runtime_state.variable_pool.get(selector)
                 if variable is not None:
                     outputs = {"output": variable}
@@ -53,7 +28,7 @@ class VariableAggregatorNode(Node):
                     inputs = {".".join(selector[1:]): variable.to_object()}
                     break
         else:
-            for group in self._node_data.advanced_settings.groups:
+            for group in self.node_data.advanced_settings.groups:
                 for selector in group.variables:
                     variable = self.graph_runtime_state.variable_pool.get(selector)
 

api/core/workflow/nodes/variable_assigner/v1/node.py

@@ -5,9 +5,8 @@ from core.variables import SegmentType, Variable
 from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID
 from core.workflow.conversation_variable_updater import ConversationVariableUpdater
 from core.workflow.entities import GraphInitParams
-from core.workflow.enums import ErrorStrategy, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.variable_assigner.common import helpers as common_helpers
 from core.workflow.nodes.variable_assigner.common.exc import VariableOperatorNodeError
@@ -22,33 +21,10 @@ if TYPE_CHECKING:
 _CONV_VAR_UPDATER_FACTORY: TypeAlias = Callable[[], ConversationVariableUpdater]
 
 
-class VariableAssignerNode(Node):
+class VariableAssignerNode(Node[VariableAssignerData]):
     node_type = NodeType.VARIABLE_ASSIGNER
     _conv_var_updater_factory: _CONV_VAR_UPDATER_FACTORY
 
-    _node_data: VariableAssignerData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = VariableAssignerData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     def __init__(
         self,
         id: str,
@@ -93,21 +69,21 @@ class VariableAssignerNode(Node):
         return mapping
 
     def _run(self) -> NodeRunResult:
-        assigned_variable_selector = self._node_data.assigned_variable_selector
+        assigned_variable_selector = self.node_data.assigned_variable_selector
         # Should be String, Number, Object, ArrayString, ArrayNumber, ArrayObject
         original_variable = self.graph_runtime_state.variable_pool.get(assigned_variable_selector)
         if not isinstance(original_variable, Variable):
             raise VariableOperatorNodeError("assigned variable not found")
 
-        match self._node_data.write_mode:
+        match self.node_data.write_mode:
             case WriteMode.OVER_WRITE:
-                income_value = self.graph_runtime_state.variable_pool.get(self._node_data.input_variable_selector)
+                income_value = self.graph_runtime_state.variable_pool.get(self.node_data.input_variable_selector)
                 if not income_value:
                     raise VariableOperatorNodeError("input value not found")
                 updated_variable = original_variable.model_copy(update={"value": income_value.value})
 
             case WriteMode.APPEND:
-                income_value = self.graph_runtime_state.variable_pool.get(self._node_data.input_variable_selector)
+                income_value = self.graph_runtime_state.variable_pool.get(self.node_data.input_variable_selector)
                 if not income_value:
                     raise VariableOperatorNodeError("input value not found")
                 updated_value = original_variable.value + [income_value.value]

api/core/workflow/nodes/variable_assigner/v2/node.py

@@ -7,9 +7,8 @@ from core.variables import SegmentType, Variable
 from core.variables.consts import SELECTORS_LENGTH
 from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID
 from core.workflow.conversation_variable_updater import ConversationVariableUpdater
-from core.workflow.enums import ErrorStrategy, NodeType, WorkflowNodeExecutionStatus
+from core.workflow.enums import NodeType, WorkflowNodeExecutionStatus
 from core.workflow.node_events import NodeRunResult
-from core.workflow.nodes.base.entities import BaseNodeData, RetryConfig
 from core.workflow.nodes.base.node import Node
 from core.workflow.nodes.variable_assigner.common import helpers as common_helpers
 from core.workflow.nodes.variable_assigner.common.exc import VariableOperatorNodeError
@@ -51,32 +50,9 @@ def _source_mapping_from_item(mapping: MutableMapping[str, Sequence[str]], node_
     mapping[key] = selector
 
 
-class VariableAssignerNode(Node):
+class VariableAssignerNode(Node[VariableAssignerNodeData]):
     node_type = NodeType.VARIABLE_ASSIGNER
 
-    _node_data: VariableAssignerNodeData
-
-    def init_node_data(self, data: Mapping[str, Any]):
-        self._node_data = VariableAssignerNodeData.model_validate(data)
-
-    def _get_error_strategy(self) -> ErrorStrategy | None:
-        return self._node_data.error_strategy
-
-    def _get_retry_config(self) -> RetryConfig:
-        return self._node_data.retry_config
-
-    def _get_title(self) -> str:
-        return self._node_data.title
-
-    def _get_description(self) -> str | None:
-        return self._node_data.desc
-
-    def _get_default_value_dict(self) -> dict[str, Any]:
-        return self._node_data.default_value_dict
-
-    def get_base_node_data(self) -> BaseNodeData:
-        return self._node_data
-
     def blocks_variable_output(self, variable_selectors: set[tuple[str, ...]]) -> bool:
         """
         Check if this Variable Assigner node blocks the output of specific variables.
@@ -84,7 +60,7 @@ class VariableAssignerNode(Node):
         Returns True if this node updates any of the requested conversation variables.
         """
         # Check each item in this Variable Assigner node
-        for item in self._node_data.items:
+        for item in self.node_data.items:
             # Convert the item's variable_selector to tuple for comparison
             item_selector_tuple = tuple(item.variable_selector)
 
@@ -119,13 +95,13 @@ class VariableAssignerNode(Node):
         return var_mapping
 
     def _run(self) -> NodeRunResult:
-        inputs = self._node_data.model_dump()
+        inputs = self.node_data.model_dump()
         process_data: dict[str, Any] = {}
         # NOTE: This node has no outputs
         updated_variable_selectors: list[Sequence[str]] = []
 
         try:
-            for item in self._node_data.items:
+            for item in self.node_data.items:
                 variable = self.graph_runtime_state.variable_pool.get(item.variable_selector)
 
                 # ==================== Validation Part

api/core/workflow/runtime/graph_runtime_state.py

@@ -10,6 +10,7 @@ from typing import Any, Protocol
 from pydantic.json import pydantic_encoder
 
 from core.model_runtime.entities.llm_entities import LLMUsage
+from core.workflow.entities.pause_reason import PauseReason
 from core.workflow.runtime.variable_pool import VariablePool
 
 
@@ -46,7 +47,11 @@ class ReadyQueueProtocol(Protocol):
 
 
 class GraphExecutionProtocol(Protocol):
-    """Structural interface for graph execution aggregate."""
+    """Structural interface for graph execution aggregate.
+
+    Defines the minimal set of attributes and methods required from a GraphExecution entity
+    for runtime orchestration and state management.
+    """
 
     workflow_id: str
     started: bool
@@ -54,6 +59,7 @@ class GraphExecutionProtocol(Protocol):
     aborted: bool
     error: Exception | None
     exceptions_count: int
+    pause_reasons: list[PauseReason]
 
     def start(self) -> None:
         """Transition execution into the running state."""

api/core/workflow/workflow_entry.py

@@ -159,7 +159,6 @@ class WorkflowEntry:
             graph_init_params=graph_init_params,
             graph_runtime_state=graph_runtime_state,
         )
-        node.init_node_data(node_config_data)
 
         try:
             # variable selector to variable mapping
@@ -303,7 +302,6 @@ class WorkflowEntry:
             graph_init_params=graph_init_params,
             graph_runtime_state=graph_runtime_state,
         )
-        node.init_node_data(node_data)
 
         try:
             # variable selector to variable mapping

api/factories/file_factory.py

@@ -1,5 +1,6 @@
 import mimetypes
 import os
+import re
 import urllib.parse
 import uuid
 from collections.abc import Callable, Mapping, Sequence
@@ -268,15 +269,47 @@ def _build_from_remote_url(
 
 
 def _extract_filename(url_path: str, content_disposition: str | None) -> str | None:
-    filename = None
+    filename: str | None = None
     # Try to extract from Content-Disposition header first
     if content_disposition:
-        _, params = parse_options_header(content_disposition)
-        # RFC 5987 https://datatracker.ietf.org/doc/html/rfc5987: filename* takes precedence over filename
-        filename = params.get("filename*") or params.get("filename")
+        # Manually extract filename* parameter since parse_options_header doesn't support it
+        filename_star_match = re.search(r"filename\*=([^;]+)", content_disposition)
+        if filename_star_match:
+            raw_star = filename_star_match.group(1).strip()
+            # Remove trailing quotes if present
+            raw_star = raw_star.removesuffix('"')
+            # format: charset'lang'value
+            try:
+                parts = raw_star.split("'", 2)
+                charset = (parts[0] or "utf-8").lower() if len(parts) >= 1 else "utf-8"
+                value = parts[2] if len(parts) == 3 else parts[-1]
+                filename = urllib.parse.unquote(value, encoding=charset, errors="replace")
+            except Exception:
+                # Fallback: try to extract value after the last single quote
+                if "''" in raw_star:
+                    filename = urllib.parse.unquote(raw_star.split("''")[-1])
+                else:
+                    filename = urllib.parse.unquote(raw_star)
+
+        if not filename:
+            # Fallback to regular filename parameter
+            _, params = parse_options_header(content_disposition)
+            raw = params.get("filename")
+            if raw:
+                # Strip surrounding quotes and percent-decode if present
+                if len(raw) >= 2 and raw[0] == raw[-1] == '"':
+                    raw = raw[1:-1]
+                filename = urllib.parse.unquote(raw)
     # Fallback to URL path if no filename from header
     if not filename:
-        filename = os.path.basename(url_path)
+        candidate = os.path.basename(url_path)
+        filename = urllib.parse.unquote(candidate) if candidate else None
+    # Defense-in-depth: ensure basename only
+    if filename:
+        filename = os.path.basename(filename)
+        # Return None if filename is empty or only whitespace
+        if not filename or not filename.strip():
+            filename = None
     return filename or None
 
 

api/migrations/versions/2025_11_18_1859-7bb281b7a422_add_workflow_pause_reasons_table.py

@@ -0,0 +1,41 @@
+"""Add workflow_pauses_reasons table
+
+Revision ID: 7bb281b7a422
+Revises: 09cfdda155d1
+Create Date: 2025-11-18 18:59:26.999572
+
+"""
+
+from alembic import op
+import models as models
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = "7bb281b7a422"
+down_revision = "09cfdda155d1"
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+    op.create_table(
+        "workflow_pause_reasons",
+        sa.Column("id", models.types.StringUUID(), nullable=False),
+        sa.Column("created_at", sa.DateTime(), server_default=sa.text("CURRENT_TIMESTAMP"), nullable=False),
+        sa.Column("updated_at", sa.DateTime(), server_default=sa.text("CURRENT_TIMESTAMP"), nullable=False),
+
+        sa.Column("pause_id", models.types.StringUUID(), nullable=False),
+        sa.Column("type_", sa.String(20), nullable=False),
+        sa.Column("form_id", sa.String(length=36), nullable=False),
+        sa.Column("node_id", sa.String(length=255), nullable=False),
+        sa.Column("message", sa.String(length=255), nullable=False),
+
+        sa.PrimaryKeyConstraint("id", name=op.f("workflow_pause_reasons_pkey")),
+    )
+    with op.batch_alter_table("workflow_pause_reasons", schema=None) as batch_op:
+        batch_op.create_index(batch_op.f("workflow_pause_reasons_pause_id_idx"), ["pause_id"], unique=False)
+
+
+def downgrade():
+    op.drop_table("workflow_pause_reasons")