fix: dataset editor

2025-03-07 15:59:36 +08:00
62 changed files with 912 additions and 887 deletions
@@ -5,8 +5,9 @@ on:
    branches:
      - "main"
      - "deploy/dev"
-    tags:
-      - "*"
+      - "fix/dataset-admin"
+  release:
+    types: [published]

 concurrency:
  group: build-push-${{ github.head_ref || github.run_id }}
@@ -1,3 +0,0 @@
-{
-    "MD024": false
-}
@@ -1,32 +0,0 @@
-# Changelog
-
-All notable changes to Dify will be documented in this file.
-
-The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [0.15.7] - 2025-04-27
-
-### Added
-
- Added support for GPT-4.1 in model providers (#18912)
- Added support for Amazon Bedrock DeepSeek-R1 model (#18908)
- Added support for Amazon Bedrock Claude Sonnet 3.7 model (#18788)
- Refined version compatibility logic in app DSL service
-
-### Fixed
-
- Fixed issue with creating apps from template categories (#18807, #18868)
- Fixed DSL version check when creating apps from explore templates (#18872, #18878)
-
-## [0.15.6] - 2025-04-22
-
-### Security
-
- Fixed clickjacking vulnerability (#18552)
- Fixed reset password security issue (#18366)
- Updated reset password token when email code verification succeeds (#18362)
-
-### Fixed
-
- Fixed Vertex AI Gemini 2.0 Flash 001 schema (#18405)
@@ -430,7 +430,4 @@ CREATE_TIDB_SERVICE_JOB_ENABLED=false
 # Maximum number of submitted thread count in a ThreadPool for parallel node execution
 MAX_SUBMIT_COUNT=100
 # Lockout duration in seconds
-LOGIN_LOCKOUT_DURATION=86400
-
-# Prevent Clickjacking
-ALLOW_EMBED=false
+LOGIN_LOCKOUT_DURATION=86400
@@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):

    CURRENT_VERSION: str = Field(
        description="Dify version",
-        default="0.15.7",
+        default="0.15.3",
    )

    COMMIT_SHA: str = Field(
@@ -8,7 +8,7 @@ from constants.languages import languages
 from controllers.console import api
 from controllers.console.auth.error import EmailCodeError, InvalidEmailError, InvalidTokenError, PasswordMismatchError
 from controllers.console.error import AccountInFreezeError, AccountNotFound, EmailSendIpLimitError
-from controllers.console.wraps import email_password_login_enabled, setup_required
+from controllers.console.wraps import setup_required
 from events.tenant_event import tenant_was_created
 from extensions.ext_database import db
 from libs.helper import email, extract_remote_ip
@@ -22,7 +22,6 @@ from services.feature_service import FeatureService

 class ForgotPasswordSendEmailApi(Resource):
    @setup_required
-    @email_password_login_enabled
    def post(self):
        parser = reqparse.RequestParser()
        parser.add_argument("email", type=email, required=True, location="json")
@@ -54,7 +53,6 @@ class ForgotPasswordSendEmailApi(Resource):

 class ForgotPasswordCheckApi(Resource):
    @setup_required
-    @email_password_login_enabled
    def post(self):
        parser = reqparse.RequestParser()
        parser.add_argument("email", type=str, required=True, location="json")
@@ -74,20 +72,11 @@ class ForgotPasswordCheckApi(Resource):
        if args["code"] != token_data.get("code"):
            raise EmailCodeError()

-        # Verified, revoke the first token
-        AccountService.revoke_reset_password_token(args["token"])
-
-        # Refresh token data by generating a new token
-        _, new_token = AccountService.generate_reset_password_token(
-            user_email, code=args["code"], additional_data={"phase": "reset"}
-        )
-
-        return {"is_valid": True, "email": token_data.get("email"), "token": new_token}
+        return {"is_valid": True, "email": token_data.get("email")}


 class ForgotPasswordResetApi(Resource):
    @setup_required
-    @email_password_login_enabled
    def post(self):
        parser = reqparse.RequestParser()
        parser.add_argument("token", type=str, required=True, nullable=False, location="json")
@@ -106,9 +95,6 @@ class ForgotPasswordResetApi(Resource):

        if reset_data is None:
            raise InvalidTokenError()
-        # Must use token in reset phase
-        if reset_data.get("phase", "") != "reset":
-            raise InvalidTokenError()

        AccountService.revoke_reset_password_token(token)

@@ -22,7 +22,7 @@ from controllers.console.error import (
    EmailSendIpLimitError,
    NotAllowedCreateWorkspace,
 )
-from controllers.console.wraps import email_password_login_enabled, setup_required
+from controllers.console.wraps import setup_required
 from events.tenant_event import tenant_was_created
 from libs.helper import email, extract_remote_ip
 from libs.password import valid_password
@@ -38,7 +38,6 @@ class LoginApi(Resource):
    """Resource for user login."""

    @setup_required
-    @email_password_login_enabled
    def post(self):
        """Authenticate user and login."""
        parser = reqparse.RequestParser()
@@ -111,7 +110,6 @@ class LogoutApi(Resource):

 class ResetPasswordSendEmailApi(Resource):
    @setup_required
-    @email_password_login_enabled
    def post(self):
        parser = reqparse.RequestParser()
        parser.add_argument("email", type=email, required=True, location="json")
@@ -310,7 +310,7 @@ class DatasetInitApi(Resource):
    @cloud_edition_billing_resource_check("vector_space")
    def post(self):
        # The role of the current user in the ta table must be admin, owner, or editor
-        if not current_user.is_editor:
+        if not current_user.is_dataset_editor:
            raise Forbidden()

        parser = reqparse.RequestParser()
@@ -684,7 +684,7 @@ class DocumentProcessingApi(DocumentResource):
        document = self.get_document(dataset_id, document_id)

        # The role of the current user in the ta table must be admin, owner, or editor
-        if not current_user.is_editor:
+        if not current_user.is_dataset_editor:
            raise Forbidden()

        if action == "pause":
@@ -748,7 +748,7 @@ class DocumentMetadataApi(DocumentResource):
        doc_metadata = req_data.get("doc_metadata")

        # The role of the current user in the ta table must be admin, owner, or editor
-        if not current_user.is_editor:
+        if not current_user.is_dataset_editor:
            raise Forbidden()

        if doc_type is None or doc_metadata is None:
@@ -122,7 +122,7 @@ class DatasetDocumentSegmentListApi(Resource):
        segment_ids = request.args.getlist("segment_id")

        # The role of the current user in the ta table must be admin or owner
-        if not current_user.is_editor:
+        if not current_user.is_dataset_editor:
            raise Forbidden()
        try:
            DatasetService.check_dataset_permission(dataset, current_user)
@@ -149,7 +149,7 @@ class DatasetDocumentSegmentApi(Resource):
        # check user's model setting
        DatasetService.check_dataset_model_setting(dataset)
        # The role of the current user in the ta table must be admin, owner, or editor
-        if not current_user.is_editor:
+        if not current_user.is_dataset_editor:
            raise Forbidden()

        try:
@@ -202,7 +202,7 @@ class DatasetDocumentSegmentAddApi(Resource):
        document = DocumentService.get_document(dataset_id, document_id)
        if not document:
            raise NotFound("Document not found.")
-        if not current_user.is_editor:
+        if not current_user.is_dataset_editor:
            raise Forbidden()
        # check embedding model setting
        if dataset.indexing_technique == "high_quality":
@@ -277,7 +277,7 @@ class DatasetDocumentSegmentUpdateApi(Resource):
        if not segment:
            raise NotFound("Segment not found.")
        # The role of the current user in the ta table must be admin, owner, or editor
-        if not current_user.is_editor:
+        if not current_user.is_dataset_editor:
            raise Forbidden()
        try:
            DatasetService.check_dataset_permission(dataset, current_user)
@@ -320,7 +320,7 @@ class DatasetDocumentSegmentUpdateApi(Resource):
        if not segment:
            raise NotFound("Segment not found.")
        # The role of the current user in the ta table must be admin or owner
-        if not current_user.is_editor:
+        if not current_user.is_dataset_editor:
            raise Forbidden()
        try:
            DatasetService.check_dataset_permission(dataset, current_user)
@@ -420,7 +420,7 @@ class ChildChunkAddApi(Resource):
        ).first()
        if not segment:
            raise NotFound("Segment not found.")
-        if not current_user.is_editor:
+        if not current_user.is_dataset_editor:
            raise Forbidden()
        # check embedding model setting
        if dataset.indexing_technique == "high_quality":
@@ -520,7 +520,7 @@ class ChildChunkAddApi(Resource):
        if not segment:
            raise NotFound("Segment not found.")
        # The role of the current user in the ta table must be admin, owner, or editor
-        if not current_user.is_editor:
+        if not current_user.is_dataset_editor:
            raise Forbidden()
        try:
            DatasetService.check_dataset_permission(dataset, current_user)
@@ -570,7 +570,7 @@ class ChildChunkUpdateApi(Resource):
        if not child_chunk:
            raise NotFound("Child chunk not found.")
        # The role of the current user in the ta table must be admin or owner
-        if not current_user.is_editor:
+        if not current_user.is_dataset_editor:
            raise Forbidden()
        try:
            DatasetService.check_dataset_permission(dataset, current_user)
@@ -614,7 +614,7 @@ class ChildChunkUpdateApi(Resource):
        if not child_chunk:
            raise NotFound("Child chunk not found.")
        # The role of the current user in the ta table must be admin or owner
-        if not current_user.is_editor:
+        if not current_user.is_dataset_editor:
            raise Forbidden()
        try:
            DatasetService.check_dataset_permission(dataset, current_user)
@@ -154,16 +154,3 @@ def enterprise_license_required(view):
        return view(*args, **kwargs)

    return decorated
-
-
-def email_password_login_enabled(view):
-    @wraps(view)
-    def decorated(*args, **kwargs):
-        features = FeatureService.get_system_features()
-        if features.enable_email_password_login:
-            return view(*args, **kwargs)
-
-        # otherwise, return 403
-        abort(403)
-
-    return decorated
@@ -104,6 +104,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):

            # recalc llm max tokens
            prompt_messages = self._organize_prompt_messages()
+            self.recalc_llm_max_tokens(self.model_config, prompt_messages)
            # invoke model
            chunks = model_instance.invoke_llm(
                prompt_messages=prompt_messages,
@@ -84,6 +84,7 @@ class FunctionCallAgentRunner(BaseAgentRunner):

            # recalc llm max tokens
            prompt_messages = self._organize_prompt_messages()
+            self.recalc_llm_max_tokens(self.model_config, prompt_messages)
            # invoke model
            chunks: Union[Generator[LLMResultChunk, None, None], LLMResult] = model_instance.invoke_llm(
                prompt_messages=prompt_messages,
@@ -55,6 +55,20 @@ class AgentChatAppRunner(AppRunner):
        query = application_generate_entity.query
        files = application_generate_entity.files

+        # Pre-calculate the number of tokens of the prompt messages,
+        # and return the rest number of tokens by model context token size limit and max token size limit.
+        # If the rest number of tokens is not enough, raise exception.
+        # Include: prompt template, inputs, query(optional), files(optional)
+        # Not Include: memory, external data, dataset context
+        self.get_pre_calculate_rest_tokens(
+            app_record=app_record,
+            model_config=application_generate_entity.model_conf,
+            prompt_template_entity=app_config.prompt_template,
+            inputs=inputs,
+            files=files,
+            query=query,
+        )
+
        memory = None
        if application_generate_entity.conversation_id:
            # get memory of conversation (read-only)
@@ -15,8 +15,10 @@ from core.app.features.annotation_reply.annotation_reply import AnnotationReplyF
 from core.app.features.hosting_moderation.hosting_moderation import HostingModerationFeature
 from core.external_data_tool.external_data_fetch import ExternalDataFetch
 from core.memory.token_buffer_memory import TokenBufferMemory
+from core.model_manager import ModelInstance
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
 from core.model_runtime.entities.message_entities import AssistantPromptMessage, PromptMessage
+from core.model_runtime.entities.model_entities import ModelPropertyKey
 from core.model_runtime.errors.invoke import InvokeBadRequestError
 from core.moderation.input_moderation import InputModeration
 from core.prompt.advanced_prompt_transform import AdvancedPromptTransform
@@ -29,6 +31,106 @@ if TYPE_CHECKING:


 class AppRunner:
+    def get_pre_calculate_rest_tokens(
+        self,
+        app_record: App,
+        model_config: ModelConfigWithCredentialsEntity,
+        prompt_template_entity: PromptTemplateEntity,
+        inputs: Mapping[str, str],
+        files: Sequence["File"],
+        query: Optional[str] = None,
+    ) -> int:
+        """
+        Get pre calculate rest tokens
+        :param app_record: app record
+        :param model_config: model config entity
+        :param prompt_template_entity: prompt template entity
+        :param inputs: inputs
+        :param files: files
+        :param query: query
+        :return:
+        """
+        # Invoke model
+        model_instance = ModelInstance(
+            provider_model_bundle=model_config.provider_model_bundle, model=model_config.model
+        )
+
+        model_context_tokens = model_config.model_schema.model_properties.get(ModelPropertyKey.CONTEXT_SIZE)
+
+        max_tokens = 0
+        for parameter_rule in model_config.model_schema.parameter_rules:
+            if parameter_rule.name == "max_tokens" or (
+                parameter_rule.use_template and parameter_rule.use_template == "max_tokens"
+            ):
+                max_tokens = (
+                    model_config.parameters.get(parameter_rule.name)
+                    or model_config.parameters.get(parameter_rule.use_template or "")
+                ) or 0
+
+        if model_context_tokens is None:
+            return -1
+
+        if max_tokens is None:
+            max_tokens = 0
+
+        # get prompt messages without memory and context
+        prompt_messages, stop = self.organize_prompt_messages(
+            app_record=app_record,
+            model_config=model_config,
+            prompt_template_entity=prompt_template_entity,
+            inputs=inputs,
+            files=files,
+            query=query,
+        )
+
+        prompt_tokens = model_instance.get_llm_num_tokens(prompt_messages)
+
+        rest_tokens: int = model_context_tokens - max_tokens - prompt_tokens
+        if rest_tokens < 0:
+            raise InvokeBadRequestError(
+                "Query or prefix prompt is too long, you can reduce the prefix prompt, "
+                "or shrink the max token, or switch to a llm with a larger token limit size."
+            )
+
+        return rest_tokens
+
+    def recalc_llm_max_tokens(
+        self, model_config: ModelConfigWithCredentialsEntity, prompt_messages: list[PromptMessage]
+    ):
+        # recalc max_tokens if sum(prompt_token +  max_tokens) over model token limit
+        model_instance = ModelInstance(
+            provider_model_bundle=model_config.provider_model_bundle, model=model_config.model
+        )
+
+        model_context_tokens = model_config.model_schema.model_properties.get(ModelPropertyKey.CONTEXT_SIZE)
+
+        max_tokens = 0
+        for parameter_rule in model_config.model_schema.parameter_rules:
+            if parameter_rule.name == "max_tokens" or (
+                parameter_rule.use_template and parameter_rule.use_template == "max_tokens"
+            ):
+                max_tokens = (
+                    model_config.parameters.get(parameter_rule.name)
+                    or model_config.parameters.get(parameter_rule.use_template or "")
+                ) or 0
+
+        if model_context_tokens is None:
+            return -1
+
+        if max_tokens is None:
+            max_tokens = 0
+
+        prompt_tokens = model_instance.get_llm_num_tokens(prompt_messages)
+
+        if prompt_tokens + max_tokens > model_context_tokens:
+            max_tokens = max(model_context_tokens - prompt_tokens, 16)
+
+            for parameter_rule in model_config.model_schema.parameter_rules:
+                if parameter_rule.name == "max_tokens" or (
+                    parameter_rule.use_template and parameter_rule.use_template == "max_tokens"
+                ):
+                    model_config.parameters[parameter_rule.name] = max_tokens
+
    def organize_prompt_messages(
        self,
        app_record: App,
@@ -50,6 +50,20 @@ class ChatAppRunner(AppRunner):
        query = application_generate_entity.query
        files = application_generate_entity.files

+        # Pre-calculate the number of tokens of the prompt messages,
+        # and return the rest number of tokens by model context token size limit and max token size limit.
+        # If the rest number of tokens is not enough, raise exception.
+        # Include: prompt template, inputs, query(optional), files(optional)
+        # Not Include: memory, external data, dataset context
+        self.get_pre_calculate_rest_tokens(
+            app_record=app_record,
+            model_config=application_generate_entity.model_conf,
+            prompt_template_entity=app_config.prompt_template,
+            inputs=inputs,
+            files=files,
+            query=query,
+        )
+
        memory = None
        if application_generate_entity.conversation_id:
            # get memory of conversation (read-only)
@@ -180,6 +194,9 @@ class ChatAppRunner(AppRunner):
        if hosting_moderation_result:
            return

+        # Re-calculate the max tokens if sum(prompt_token +  max_tokens) over model token limit
+        self.recalc_llm_max_tokens(model_config=application_generate_entity.model_conf, prompt_messages=prompt_messages)
+
        # Invoke model
        model_instance = ModelInstance(
            provider_model_bundle=application_generate_entity.model_conf.provider_model_bundle,
@@ -43,6 +43,20 @@ class CompletionAppRunner(AppRunner):
        query = application_generate_entity.query
        files = application_generate_entity.files

+        # Pre-calculate the number of tokens of the prompt messages,
+        # and return the rest number of tokens by model context token size limit and max token size limit.
+        # If the rest number of tokens is not enough, raise exception.
+        # Include: prompt template, inputs, query(optional), files(optional)
+        # Not Include: memory, external data, dataset context
+        self.get_pre_calculate_rest_tokens(
+            app_record=app_record,
+            model_config=application_generate_entity.model_conf,
+            prompt_template_entity=app_config.prompt_template,
+            inputs=inputs,
+            files=files,
+            query=query,
+        )
+
        # organize all inputs and template to prompt messages
        # Include: prompt template, inputs, query(optional), files(optional)
        prompt_messages, stop = self.organize_prompt_messages(
@@ -138,6 +152,9 @@ class CompletionAppRunner(AppRunner):
        if hosting_moderation_result:
            return

+        # Re-calculate the max tokens if sum(prompt_token +  max_tokens) over model token limit
+        self.recalc_llm_max_tokens(model_config=application_generate_entity.model_conf, prompt_messages=prompt_messages)
+
        # Invoke model
        model_instance = ModelInstance(
            provider_model_bundle=application_generate_entity.model_conf.provider_model_bundle,
@@ -26,7 +26,7 @@ class TokenBufferMemory:
        self.model_instance = model_instance

    def get_history_prompt_messages(
-        self, max_token_limit: int = 100000, message_limit: Optional[int] = None
+        self, max_token_limit: int = 2000, message_limit: Optional[int] = None
    ) -> Sequence[PromptMessage]:
        """
        Get history prompt messages.
@@ -1,115 +0,0 @@
-model: us.anthropic.claude-3-7-sonnet-20250219-v1:0
-label:
-  en_US: Claude 3.7 Sonnet(US.Cross Region Inference)
-icon: icon_s_en.svg
-model_type: llm
-features:
-  - agent-thought
-  - vision
-  - tool-call
-  - stream-tool-call
-model_properties:
-  mode: chat
-  context_size: 200000
-# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
-parameter_rules:
-  - name: enable_cache
-    label:
-      zh_Hans: 启用提示缓存
-      en_US: Enable Prompt Cache
-    type: boolean
-    required: false
-    default: true
-    help:
-      zh_Hans: 启用提示缓存可以提高性能并降低成本。Claude 3.7 Sonnet支持在system、messages和tools字段中使用缓存检查点。
-      en_US: Enable prompt caching to improve performance and reduce costs. Claude 3.7 Sonnet supports cache checkpoints in system, messages, and tools fields.
-  - name: reasoning_type
-    label:
-      zh_Hans: 推理配置
-      en_US: Reasoning Type
-    type: boolean
-    required: false
-    default: false
-    placeholder:
-      zh_Hans: 设置推理配置
-      en_US: Set reasoning configuration
-    help:
-      zh_Hans: 控制模型的推理能力。启用时，temperature将固定为1且top_p将被禁用。
-      en_US: Controls the model's reasoning capability. When enabled, temperature will be fixed to 1 and top_p will be disabled.
-  - name: reasoning_budget
-    show_on:
-      - variable: reasoning_type
-        value: true
-    label:
-      zh_Hans: 推理预算
-      en_US: Reasoning Budget
-    type: int
-    default: 1024
-    min: 0
-    max: 128000
-    help:
-      zh_Hans: 推理的预算限制（最小1024），必须小于max_tokens。仅在推理类型为enabled时可用。
-      en_US: Budget limit for reasoning (minimum 1024), must be less than max_tokens. Only available when reasoning type is enabled.
-
-  - name: max_tokens
-    use_template: max_tokens
-    required: true
-    label:
-      zh_Hans: 最大token数
-      en_US: Max Tokens
-    type: int
-    default: 8192
-    min: 1
-    max: 128000
-    help:
-      zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
-      en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
-  - name: temperature
-    use_template: temperature
-    required: false
-    label:
-      zh_Hans: 模型温度
-      en_US: Model Temperature
-    type: float
-    default: 1
-    min: 0.0
-    max: 1.0
-    help:
-      zh_Hans: 生成内容的随机性。当推理功能启用时，该值将被固定为1。
-      en_US: The amount of randomness injected into the response. When reasoning is enabled, this value will be fixed to 1.
-  - name: top_p
-    show_on:
-      - variable: reasoning_type
-        value: disabled
-    use_template: top_p
-    label:
-      zh_Hans: Top P
-      en_US: Top P
-    required: false
-    type: float
-    default: 0.999
-    min: 0.000
-    max: 1.000
-    help:
-      zh_Hans: 在核采样中的概率阈值。当推理功能启用时，该参数将被禁用。
-      en_US: The probability threshold in nucleus sampling. When reasoning is enabled, this parameter will be disabled.
-  - name: top_k
-    label:
-      zh_Hans: 取样数量
-      en_US: Top k
-    required: false
-    type: int
-    default: 0
-    min: 0
-    # tip docs from aws has error, max value is 500
-    max: 500
-    help:
-      zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
-      en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
-  - name: response_format
-    use_template: response_format
-pricing:
-  input: '0.003'
-  output: '0.015'
-  unit: '0.001'
-  currency: USD
@@ -58,7 +58,6 @@ class BedrockLargeLanguageModel(LargeLanguageModel):
    # TODO There is invoke issue: context limit on Cohere Model, will add them after fixed.
    CONVERSE_API_ENABLED_MODEL_INFO = [
        {"prefix": "anthropic.claude-v2", "support_system_prompts": True, "support_tool_use": False},
-        {"prefix": "us.deepseek", "support_system_prompts": True, "support_tool_use": False},
        {"prefix": "anthropic.claude-v1", "support_system_prompts": True, "support_tool_use": False},
        {"prefix": "us.anthropic.claude-3", "support_system_prompts": True, "support_tool_use": True},
        {"prefix": "eu.anthropic.claude-3", "support_system_prompts": True, "support_tool_use": True},
@@ -1,63 +0,0 @@
-model: us.deepseek.r1-v1:0
-label:
-  en_US: DeepSeek-R1(US.Cross Region Inference)
-icon: icon_s_en.svg
-model_type: llm
-features:
-  - agent-thought
-  - vision
-  - tool-call
-  - stream-tool-call
-model_properties:
-  mode: chat
-  context_size: 32768
-parameter_rules:
-  - name: max_tokens
-    use_template: max_tokens
-    required: true
-    label:
-      zh_Hans: 最大token数
-      en_US: Max Tokens
-    type: int
-    default: 8192
-    min: 1
-    max: 128000
-    help:
-      zh_Hans: 停止前生成的最大令牌数。
-      en_US: The maximum number of tokens to generate before stopping.
-  - name: temperature
-    use_template: temperature
-    required: false
-    label:
-      zh_Hans: 模型温度
-      en_US: Model Temperature
-    type: float
-    default: 1
-    min: 0.0
-    max: 1.0
-    help:
-      zh_Hans: 生成内容的随机性。当推理功能启用时，该值将被固定为1。
-      en_US: The amount of randomness injected into the response. When reasoning is enabled, this value will be fixed to 1.
-  - name: top_p
-    show_on:
-      - variable: reasoning_type
-        value: disabled
-    use_template: top_p
-    label:
-      zh_Hans: Top P
-      en_US: Top P
-    required: false
-    type: float
-    default: 0.999
-    min: 0.000
-    max: 1.000
-    help:
-      zh_Hans: 在核采样中的概率阈值。当推理功能启用时，该参数将被禁用。
-      en_US: The probability threshold in nucleus sampling. When reasoning is enabled, this parameter will be disabled.
-  - name: response_format
-    use_template: response_format
-pricing:
-  input: '0.001'
-  output: '0.005'
-  unit: '0.001'
-  currency: USD
@@ -19,8 +19,8 @@ class GoogleProvider(ModelProvider):
        try:
            model_instance = self.get_model_instance(ModelType.LLM)

-            # Use `gemini-2.0-flash` model for validate,
-            model_instance.validate_credentials(model="gemini-2.0-flash", credentials=credentials)
+            # Use `gemini-pro` model for validate,
+            model_instance.validate_credentials(model="gemini-pro", credentials=credentials)
        except CredentialsValidateFailedError as ex:
            raise ex
        except Exception as ex:
@@ -19,3 +19,5 @@
 - gemini-exp-1206
 - gemini-exp-1121
 - gemini-exp-1114
+- gemini-pro
+- gemini-pro-vision
@@ -0,0 +1,35 @@
+model: gemini-pro-vision
+label:
+  en_US: Gemini Pro Vision
+model_type: llm
+features:
+  - vision
+model_properties:
+  mode: chat
+  context_size: 12288
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: top_k
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    type: int
+    help:
+      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
+  - name: max_tokens_to_sample
+    use_template: max_tokens
+    required: true
+    default: 4096
+    min: 1
+    max: 4096
+pricing:
+  input: '0.00'
+  output: '0.00'
+  unit: '0.000001'
+  currency: USD
+deprecated: true
@@ -0,0 +1,39 @@
+model: gemini-pro
+label:
+  en_US: Gemini Pro
+model_type: llm
+features:
+  - agent-thought
+  - tool-call
+  - stream-tool-call
+model_properties:
+  mode: chat
+  context_size: 30720
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: top_k
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    type: int
+    help:
+      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
+  - name: max_tokens_to_sample
+    use_template: max_tokens
+    required: true
+    default: 2048
+    min: 1
+    max: 2048
+  - name: response_format
+    use_template: response_format
+pricing:
+  input: '0.00'
+  output: '0.00'
+  unit: '0.000001'
+  currency: USD
+deprecated: true
@@ -1,4 +1,3 @@
- gpt-4.1
 - o1
 - o1-2024-12-17
 - o1-mini
@@ -1,60 +0,0 @@
-model: gpt-4.1
-label:
-  zh_Hans: gpt-4.1
-  en_US: gpt-4.1
-model_type: llm
-features:
-  - multi-tool-call
-  - agent-thought
-  - stream-tool-call
-  - vision
-model_properties:
-  mode: chat
-  context_size: 1047576
-parameter_rules:
-  - name: temperature
-    use_template: temperature
-  - name: top_p
-    use_template: top_p
-  - name: presence_penalty
-    use_template: presence_penalty
-  - name: frequency_penalty
-    use_template: frequency_penalty
-  - name: max_tokens
-    use_template: max_tokens
-    default: 512
-    min: 1
-    max: 32768
-  - name: reasoning_effort
-    label:
-      zh_Hans: 推理工作
-      en_US: Reasoning Effort
-    type: string
-    help:
-      zh_Hans: 限制推理模型的推理工作
-      en_US: Constrains effort on reasoning for reasoning models
-    required: false
-    options:
-      - low
-      - medium
-      - high
-  - name: response_format
-    label:
-      zh_Hans: 回复格式
-      en_US: Response Format
-    type: string
-    help:
-      zh_Hans: 指定模型必须输出的格式
-      en_US: specifying the format that the model must output
-    required: false
-    options:
-      - text
-      - json_object
-      - json_schema
-  - name: json_schema
-    use_template: json_schema
-pricing:
-  input: '2.00'
-  output: '8.00'
-  unit: '0.000001'
-  currency: USD
@@ -1057,7 +1057,7 @@ class OpenAILargeLanguageModel(_CommonOpenAI, LargeLanguageModel):
            model = "gpt-4o"

        try:
-            encoding = tiktoken.get_encoding(model)
+            encoding = tiktoken.encoding_for_model(model)
        except KeyError:
            logger.warning("Warning: model not found. Using cl100k_base encoding.")
            model = "cl100k_base"
@@ -5,6 +5,11 @@ model_type: llm
 features:
  - agent-thought
  - vision
+  - tool-call
+  - stream-tool-call
+  - document
+  - video
+  - audio
 model_properties:
  mode: chat
  context_size: 1048576
@@ -15,21 +20,20 @@ parameter_rules:
    use_template: top_p
  - name: top_k
    label:
+      zh_Hans: 取样数量
      en_US: Top k
    type: int
    help:
+      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
-  - name: presence_penalty
-    use_template: presence_penalty
-  - name: frequency_penalty
-    use_template: frequency_penalty
  - name: max_output_tokens
    use_template: max_tokens
-    required: true
    default: 8192
    min: 1
    max: 8192
+  - name: json_schema
+    use_template: json_schema
 pricing:
  input: '0.00'
  output: '0.00'
@@ -77,4 +77,5 @@
 - onebot
 - regex
 - trello
+- vanna
 - fal
@@ -0,0 +1,134 @@
+from typing import Any, Union
+
+from vanna.remote import VannaDefault  # type: ignore
+
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from core.tools.errors import ToolProviderCredentialValidationError
+from core.tools.tool.builtin_tool import BuiltinTool
+
+
+class VannaTool(BuiltinTool):
+    def _invoke(
+        self, user_id: str, tool_parameters: dict[str, Any]
+    ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
+        """
+        invoke tools
+        """
+        # Ensure runtime and credentials
+        if not self.runtime or not self.runtime.credentials:
+            raise ToolProviderCredentialValidationError("Tool runtime or credentials are missing")
+        api_key = self.runtime.credentials.get("api_key", None)
+        if not api_key:
+            raise ToolProviderCredentialValidationError("Please input api key")
+
+        model = tool_parameters.get("model", "")
+        if not model:
+            return self.create_text_message("Please input RAG model")
+
+        prompt = tool_parameters.get("prompt", "")
+        if not prompt:
+            return self.create_text_message("Please input prompt")
+
+        url = tool_parameters.get("url", "")
+        if not url:
+            return self.create_text_message("Please input URL/Host/DSN")
+
+        db_name = tool_parameters.get("db_name", "")
+        username = tool_parameters.get("username", "")
+        password = tool_parameters.get("password", "")
+        port = tool_parameters.get("port", 0)
+
+        base_url = self.runtime.credentials.get("base_url", None)
+        vn = VannaDefault(model=model, api_key=api_key, config={"endpoint": base_url})
+
+        db_type = tool_parameters.get("db_type", "")
+        if db_type in {"Postgres", "MySQL", "Hive", "ClickHouse"}:
+            if not db_name:
+                return self.create_text_message("Please input database name")
+            if not username:
+                return self.create_text_message("Please input username")
+            if port < 1:
+                return self.create_text_message("Please input port")
+
+        schema_sql = "SELECT * FROM INFORMATION_SCHEMA.COLUMNS"
+        match db_type:
+            case "SQLite":
+                schema_sql = "SELECT type, sql FROM sqlite_master WHERE sql is not null"
+                vn.connect_to_sqlite(url)
+            case "Postgres":
+                vn.connect_to_postgres(host=url, dbname=db_name, user=username, password=password, port=port)
+            case "DuckDB":
+                vn.connect_to_duckdb(url=url)
+            case "SQLServer":
+                vn.connect_to_mssql(url)
+            case "MySQL":
+                vn.connect_to_mysql(host=url, dbname=db_name, user=username, password=password, port=port)
+            case "Oracle":
+                vn.connect_to_oracle(user=username, password=password, dsn=url)
+            case "Hive":
+                vn.connect_to_hive(host=url, dbname=db_name, user=username, password=password, port=port)
+            case "ClickHouse":
+                vn.connect_to_clickhouse(host=url, dbname=db_name, user=username, password=password, port=port)
+
+        enable_training = tool_parameters.get("enable_training", False)
+        reset_training_data = tool_parameters.get("reset_training_data", False)
+        if enable_training:
+            if reset_training_data:
+                existing_training_data = vn.get_training_data()
+                if len(existing_training_data) > 0:
+                    for _, training_data in existing_training_data.iterrows():
+                        vn.remove_training_data(training_data["id"])
+
+            ddl = tool_parameters.get("ddl", "")
+            question = tool_parameters.get("question", "")
+            sql = tool_parameters.get("sql", "")
+            memos = tool_parameters.get("memos", "")
+            training_metadata = tool_parameters.get("training_metadata", False)
+
+            if training_metadata:
+                if db_type == "SQLite":
+                    df_ddl = vn.run_sql(schema_sql)
+                    for ddl in df_ddl["sql"].to_list():
+                        vn.train(ddl=ddl)
+                else:
+                    df_information_schema = vn.run_sql(schema_sql)
+                    plan = vn.get_training_plan_generic(df_information_schema)
+                    vn.train(plan=plan)
+
+            if ddl:
+                vn.train(ddl=ddl)
+
+            if sql:
+                if question:
+                    vn.train(question=question, sql=sql)
+                else:
+                    vn.train(sql=sql)
+            if memos:
+                vn.train(documentation=memos)
+
+        #########################################################################################
+        # Due to CVE-2024-5565, we have to disable the chart generation feature
+        # The Vanna library uses a prompt function to present the user with visualized results,
+        # it is possible to alter the prompt using prompt injection and run arbitrary Python code
+        # instead of the intended visualization code.
+        # Specifically - allowing external input to the library’s “ask” method
+        # with "visualize" set to True (default behavior) leads to remote code execution.
+        # Affected versions: <= 0.5.5
+        #########################################################################################
+        allow_llm_to_see_data = tool_parameters.get("allow_llm_to_see_data", False)
+        res = vn.ask(
+            prompt, print_results=False, auto_train=True, visualize=False, allow_llm_to_see_data=allow_llm_to_see_data
+        )
+
+        result = []
+
+        if res is not None:
+            result.append(self.create_text_message(res[0]))
+            if len(res) > 1 and res[1] is not None:
+                result.append(self.create_text_message(res[1].to_markdown()))
+            if len(res) > 2 and res[2] is not None:
+                result.append(
+                    self.create_blob_message(blob=res[2].to_image(format="svg"), meta={"mime_type": "image/svg+xml"})
+                )
+
+        return result
@@ -0,0 +1,213 @@
+identity:
+  name: vanna
+  author: QCTC
+  label:
+    en_US: Vanna.AI
+    zh_Hans: Vanna.AI
+description:
+  human:
+    en_US: The fastest way to get actionable insights from your database just by asking questions.
+    zh_Hans: 一个基于大模型和RAG的Text2SQL工具。
+  llm: A tool for converting text to SQL.
+parameters:
+  - name: prompt
+    type: string
+    required: true
+    label:
+      en_US: Prompt
+      zh_Hans: 提示词
+      pt_BR: Prompt
+    human_description:
+      en_US: used for generating SQL
+      zh_Hans: 用于生成SQL
+    llm_description: key words for generating SQL
+    form: llm
+  - name: model
+    type: string
+    required: true
+    label:
+      en_US: RAG Model
+      zh_Hans: RAG模型
+    human_description:
+      en_US: RAG Model for your database DDL
+      zh_Hans: 存储数据库训练数据的RAG模型
+    llm_description: RAG Model for generating SQL
+    form: llm
+  - name: db_type
+    type: select
+    required: true
+    options:
+      - value: SQLite
+        label:
+          en_US: SQLite
+          zh_Hans: SQLite
+      - value: Postgres
+        label:
+          en_US: Postgres
+          zh_Hans: Postgres
+      - value: DuckDB
+        label:
+          en_US: DuckDB
+          zh_Hans: DuckDB
+      - value: SQLServer
+        label:
+          en_US: Microsoft SQL Server
+          zh_Hans: 微软 SQL Server
+      - value: MySQL
+        label:
+          en_US: MySQL
+          zh_Hans: MySQL
+      - value: Oracle
+        label:
+          en_US: Oracle
+          zh_Hans: Oracle
+      - value: Hive
+        label:
+          en_US: Hive
+          zh_Hans: Hive
+      - value: ClickHouse
+        label:
+          en_US: ClickHouse
+          zh_Hans: ClickHouse
+    default: SQLite
+    label:
+      en_US: DB Type
+      zh_Hans: 数据库类型
+    human_description:
+      en_US: Database type.
+      zh_Hans: 选择要链接的数据库类型。
+    form: form
+  - name: url
+    type: string
+    required: true
+    label:
+      en_US: URL/Host/DSN
+      zh_Hans: URL/Host/DSN
+    human_description:
+      en_US: Please input depending on DB type, visit https://vanna.ai/docs/ for more specification
+      zh_Hans: 请根据数据库类型，填入对应值，详情参考https://vanna.ai/docs/
+    form: form
+  - name: db_name
+    type: string
+    required: false
+    label:
+      en_US: DB name
+      zh_Hans: 数据库名
+    human_description:
+      en_US: Database name
+      zh_Hans: 数据库名
+    form: form
+  - name: username
+    type: string
+    required: false
+    label:
+      en_US: Username
+      zh_Hans: 用户名
+    human_description:
+      en_US: Username
+      zh_Hans: 用户名
+    form: form
+  - name: password
+    type: secret-input
+    required: false
+    label:
+      en_US: Password
+      zh_Hans: 密码
+    human_description:
+      en_US: Password
+      zh_Hans: 密码
+    form: form
+  - name: port
+    type: number
+    required: false
+    label:
+      en_US: Port
+      zh_Hans: 端口
+    human_description:
+      en_US: Port
+      zh_Hans: 端口
+    form: form
+  - name: ddl
+    type: string
+    required: false
+    label:
+      en_US: Training DDL
+      zh_Hans: 训练DDL
+    human_description:
+      en_US: DDL statements for training data
+      zh_Hans: 用于训练RAG Model的建表语句
+    form: llm
+  - name: question
+    type: string
+    required: false
+    label:
+      en_US: Training Question
+      zh_Hans: 训练问题
+    human_description:
+      en_US: Question-SQL Pairs
+      zh_Hans: Question-SQL中的问题
+    form: llm
+  - name: sql
+    type: string
+    required: false
+    label:
+      en_US: Training SQL
+      zh_Hans: 训练SQL
+    human_description:
+      en_US: SQL queries to your training data
+      zh_Hans: 用于训练RAG Model的SQL语句
+    form: llm
+  - name: memos
+    type: string
+    required: false
+    label:
+      en_US: Training Memos
+      zh_Hans: 训练说明
+    human_description:
+      en_US: Sometimes you may want to add documentation about your business terminology or definitions
+      zh_Hans: 添加更多关于数据库的业务说明
+    form: llm
+  - name: enable_training
+    type: boolean
+    required: false
+    default: false
+    label:
+      en_US: Training Data
+      zh_Hans: 训练数据
+    human_description:
+      en_US: You only need to train once. Do not train again unless you want to add more training data
+      zh_Hans: 训练数据无更新时，训练一次即可
+    form: form
+  - name: reset_training_data
+    type: boolean
+    required: false
+    default: false
+    label:
+      en_US: Reset Training Data
+      zh_Hans: 重置训练数据
+    human_description:
+      en_US: Remove all training data in the current RAG Model
+      zh_Hans: 删除当前RAG Model中的所有训练数据
+    form: form
+  - name: training_metadata
+    type: boolean
+    required: false
+    default: false
+    label:
+      en_US: Training Metadata
+      zh_Hans: 训练元数据
+    human_description:
+      en_US: If enabled, it will attempt to train on the metadata of that database
+      zh_Hans: 是否自动从数据库获取元数据来训练
+    form: form
+  - name: allow_llm_to_see_data
+    type: boolean
+    required: false
+    default: false
+    label:
+      en_US: Whether to allow the LLM to see the data
+      zh_Hans: 是否允许LLM查看数据
+    human_description:
+      en_US: Whether to allow the LLM to see the data
+      zh_Hans: 是否允许LLM查看数据
+    form: form
@@ -0,0 +1,46 @@
+import re
+from typing import Any
+from urllib.parse import urlparse
+
+from core.tools.errors import ToolProviderCredentialValidationError
+from core.tools.provider.builtin.vanna.tools.vanna import VannaTool
+from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController
+
+
+class VannaProvider(BuiltinToolProviderController):
+    def _get_protocol_and_main_domain(self, url):
+        parsed_url = urlparse(url)
+        protocol = parsed_url.scheme
+        hostname = parsed_url.hostname
+        port = f":{parsed_url.port}" if parsed_url.port else ""
+
+        # Check if the hostname is an IP address
+        is_ip = re.match(r"^\d{1,3}(\.\d{1,3}){3}$", hostname) is not None
+
+        # Return the full hostname (with port if present) for IP addresses, otherwise return the main domain
+        main_domain = f"{hostname}{port}" if is_ip else ".".join(hostname.split(".")[-2:]) + port
+        return f"{protocol}://{main_domain}"
+
+    def _validate_credentials(self, credentials: dict[str, Any]) -> None:
+        base_url = credentials.get("base_url")
+        if not base_url:
+            base_url = "https://ask.vanna.ai/rpc"
+        else:
+            base_url = base_url.removesuffix("/")
+        credentials["base_url"] = base_url
+        try:
+            VannaTool().fork_tool_runtime(
+                runtime={
+                    "credentials": credentials,
+                }
+            ).invoke(
+                user_id="",
+                tool_parameters={
+                    "model": "chinook",
+                    "db_type": "SQLite",
+                    "url": f"{self._get_protocol_and_main_domain(credentials['base_url'])}/Chinook.sqlite",
+                    "query": "What are the top 10 customers by sales?",
+                },
+            )
+        except Exception as e:
+            raise ToolProviderCredentialValidationError(str(e))
@@ -0,0 +1,35 @@
+identity:
+  author: QCTC
+  name: vanna
+  label:
+    en_US: Vanna.AI
+    zh_Hans: Vanna.AI
+  description:
+    en_US: The fastest way to get actionable insights from your database just by asking questions.
+    zh_Hans: 一个基于大模型和RAG的Text2SQL工具。
+  icon: icon.png
+  tags:
+    - utilities
+    - productivity
+credentials_for_provider:
+  api_key:
+    type: secret-input
+    required: true
+    label:
+      en_US: API key
+      zh_Hans: API key
+    placeholder:
+      en_US: Please input your API key
+      zh_Hans: 请输入你的 API key
+      pt_BR: Please input your API key
+    help:
+      en_US: Get your API key from Vanna.AI
+      zh_Hans: 从 Vanna.AI 获取你的 API key
+    url: https://vanna.ai/account/profile
+  base_url:
+    type: text-input
+    required: false
+    label:
+      en_US: Vanna.AI Endpoint Base URL
+    placeholder:
+      en_US: https://ask.vanna.ai/rpc
@@ -968,12 +968,14 @@ def _handle_memory_chat_mode(
    *,
    memory: TokenBufferMemory | None,
    memory_config: MemoryConfig | None,
-    model_config: ModelConfigWithCredentialsEntity,  # TODO(-LAN-): Needs to remove
+    model_config: ModelConfigWithCredentialsEntity,
 ) -> Sequence[PromptMessage]:
    memory_messages: Sequence[PromptMessage] = []
    # Get messages from memory for chat model
    if memory and memory_config:
+        rest_tokens = _calculate_rest_token(prompt_messages=[], model_config=model_config)
        memory_messages = memory.get_history_prompt_messages(
+            max_token_limit=rest_tokens,
            message_limit=memory_config.window.size if memory_config.window.enabled else None,
        )
    return memory_messages
@@ -10473,44 +10473,44 @@ client = ["SQLAlchemy (>=1.4,<3)"]

 [[package]]
 name = "tiktoken"
-version = "0.9.0"
+version = "0.8.0"
 description = "tiktoken is a fast BPE tokeniser for use with OpenAI's models"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 markers = "python_version == \"3.11\" or python_version >= \"3.12\""
 files = [
-    {file = "tiktoken-0.9.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:586c16358138b96ea804c034b8acf3f5d3f0258bd2bc3b0227af4af5d622e382"},
-    {file = "tiktoken-0.9.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d9c59ccc528c6c5dd51820b3474402f69d9a9e1d656226848ad68a8d5b2e5108"},
-    {file = "tiktoken-0.9.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f0968d5beeafbca2a72c595e8385a1a1f8af58feaebb02b227229b69ca5357fd"},
-    {file = "tiktoken-0.9.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:92a5fb085a6a3b7350b8fc838baf493317ca0e17bd95e8642f95fc69ecfed1de"},
-    {file = "tiktoken-0.9.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:15a2752dea63d93b0332fb0ddb05dd909371ededa145fe6a3242f46724fa7990"},
-    {file = "tiktoken-0.9.0-cp310-cp310-win_amd64.whl", hash = "sha256:26113fec3bd7a352e4b33dbaf1bd8948de2507e30bd95a44e2b1156647bc01b4"},
-    {file = "tiktoken-0.9.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:f32cc56168eac4851109e9b5d327637f15fd662aa30dd79f964b7c39fbadd26e"},
-    {file = "tiktoken-0.9.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:45556bc41241e5294063508caf901bf92ba52d8ef9222023f83d2483a3055348"},
-    {file = "tiktoken-0.9.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:03935988a91d6d3216e2ec7c645afbb3d870b37bcb67ada1943ec48678e7ee33"},
-    {file = "tiktoken-0.9.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8b3d80aad8d2c6b9238fc1a5524542087c52b860b10cbf952429ffb714bc1136"},
-    {file = "tiktoken-0.9.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:b2a21133be05dc116b1d0372af051cd2c6aa1d2188250c9b553f9fa49301b336"},
-    {file = "tiktoken-0.9.0-cp311-cp311-win_amd64.whl", hash = "sha256:11a20e67fdf58b0e2dea7b8654a288e481bb4fc0289d3ad21291f8d0849915fb"},
-    {file = "tiktoken-0.9.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:e88f121c1c22b726649ce67c089b90ddda8b9662545a8aeb03cfef15967ddd03"},
-    {file = "tiktoken-0.9.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:a6600660f2f72369acb13a57fb3e212434ed38b045fd8cc6cdd74947b4b5d210"},
-    {file = "tiktoken-0.9.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:95e811743b5dfa74f4b227927ed86cbc57cad4df859cb3b643be797914e41794"},
-    {file = "tiktoken-0.9.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:99376e1370d59bcf6935c933cb9ba64adc29033b7e73f5f7569f3aad86552b22"},
-    {file = "tiktoken-0.9.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:badb947c32739fb6ddde173e14885fb3de4d32ab9d8c591cbd013c22b4c31dd2"},
-    {file = "tiktoken-0.9.0-cp312-cp312-win_amd64.whl", hash = "sha256:5a62d7a25225bafed786a524c1b9f0910a1128f4232615bf3f8257a73aaa3b16"},
-    {file = "tiktoken-0.9.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:2b0e8e05a26eda1249e824156d537015480af7ae222ccb798e5234ae0285dbdb"},
-    {file = "tiktoken-0.9.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:27d457f096f87685195eea0165a1807fae87b97b2161fe8c9b1df5bd74ca6f63"},
-    {file = "tiktoken-0.9.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2cf8ded49cddf825390e36dd1ad35cd49589e8161fdcb52aa25f0583e90a3e01"},
-    {file = "tiktoken-0.9.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cc156cb314119a8bb9748257a2eaebd5cc0753b6cb491d26694ed42fc7cb3139"},
-    {file = "tiktoken-0.9.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:cd69372e8c9dd761f0ab873112aba55a0e3e506332dd9f7522ca466e817b1b7a"},
-    {file = "tiktoken-0.9.0-cp313-cp313-win_amd64.whl", hash = "sha256:5ea0edb6f83dc56d794723286215918c1cde03712cbbafa0348b33448faf5b95"},
-    {file = "tiktoken-0.9.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:c6386ca815e7d96ef5b4ac61e0048cd32ca5a92d5781255e13b31381d28667dc"},
-    {file = "tiktoken-0.9.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:75f6d5db5bc2c6274b674ceab1615c1778e6416b14705827d19b40e6355f03e0"},
-    {file = "tiktoken-0.9.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e15b16f61e6f4625a57a36496d28dd182a8a60ec20a534c5343ba3cafa156ac7"},
-    {file = "tiktoken-0.9.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3ebcec91babf21297022882344c3f7d9eed855931466c3311b1ad6b64befb3df"},
-    {file = "tiktoken-0.9.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:e5fd49e7799579240f03913447c0cdfa1129625ebd5ac440787afc4345990427"},
-    {file = "tiktoken-0.9.0-cp39-cp39-win_amd64.whl", hash = "sha256:26242ca9dc8b58e875ff4ca078b9a94d2f0813e6a535dcd2205df5d49d927cc7"},
-    {file = "tiktoken-0.9.0.tar.gz", hash = "sha256:d02a5ca6a938e0490e1ff957bc48c8b078c88cb83977be1625b1fd8aac792c5d"},
+    {file = "tiktoken-0.8.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b07e33283463089c81ef1467180e3e00ab00d46c2c4bbcef0acab5f771d6695e"},
+    {file = "tiktoken-0.8.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9269348cb650726f44dd3bbb3f9110ac19a8dcc8f54949ad3ef652ca22a38e21"},
+    {file = "tiktoken-0.8.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25e13f37bc4ef2d012731e93e0fef21dc3b7aea5bb9009618de9a4026844e560"},
+    {file = "tiktoken-0.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f13d13c981511331eac0d01a59b5df7c0d4060a8be1e378672822213da51e0a2"},
+    {file = "tiktoken-0.8.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:6b2ddbc79a22621ce8b1166afa9f9a888a664a579350dc7c09346a3b5de837d9"},
+    {file = "tiktoken-0.8.0-cp310-cp310-win_amd64.whl", hash = "sha256:d8c2d0e5ba6453a290b86cd65fc51fedf247e1ba170191715b049dac1f628005"},
+    {file = "tiktoken-0.8.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:d622d8011e6d6f239297efa42a2657043aaed06c4f68833550cac9e9bc723ef1"},
+    {file = "tiktoken-0.8.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2efaf6199717b4485031b4d6edb94075e4d79177a172f38dd934d911b588d54a"},
+    {file = "tiktoken-0.8.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5637e425ce1fc49cf716d88df3092048359a4b3bbb7da762840426e937ada06d"},
+    {file = "tiktoken-0.8.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fb0e352d1dbe15aba082883058b3cce9e48d33101bdaac1eccf66424feb5b47"},
+    {file = "tiktoken-0.8.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:56edfefe896c8f10aba372ab5706b9e3558e78db39dd497c940b47bf228bc419"},
+    {file = "tiktoken-0.8.0-cp311-cp311-win_amd64.whl", hash = "sha256:326624128590def898775b722ccc327e90b073714227175ea8febbc920ac0a99"},
+    {file = "tiktoken-0.8.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:881839cfeae051b3628d9823b2e56b5cc93a9e2efb435f4cf15f17dc45f21586"},
+    {file = "tiktoken-0.8.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:fe9399bdc3f29d428f16a2f86c3c8ec20be3eac5f53693ce4980371c3245729b"},
+    {file = "tiktoken-0.8.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9a58deb7075d5b69237a3ff4bb51a726670419db6ea62bdcd8bd80c78497d7ab"},
+    {file = "tiktoken-0.8.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d2908c0d043a7d03ebd80347266b0e58440bdef5564f84f4d29fb235b5df3b04"},
+    {file = "tiktoken-0.8.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:294440d21a2a51e12d4238e68a5972095534fe9878be57d905c476017bff99fc"},
+    {file = "tiktoken-0.8.0-cp312-cp312-win_amd64.whl", hash = "sha256:d8f3192733ac4d77977432947d563d7e1b310b96497acd3c196c9bddb36ed9db"},
+    {file = "tiktoken-0.8.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:02be1666096aff7da6cbd7cdaa8e7917bfed3467cd64b38b1f112e96d3b06a24"},
+    {file = "tiktoken-0.8.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:c94ff53c5c74b535b2cbf431d907fc13c678bbd009ee633a2aca269a04389f9a"},
+    {file = "tiktoken-0.8.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b231f5e8982c245ee3065cd84a4712d64692348bc609d84467c57b4b72dcbc5"},
+    {file = "tiktoken-0.8.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4177faa809bd55f699e88c96d9bb4635d22e3f59d635ba6fd9ffedf7150b9953"},
+    {file = "tiktoken-0.8.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5376b6f8dc4753cd81ead935c5f518fa0fbe7e133d9e25f648d8c4dabdd4bad7"},
+    {file = "tiktoken-0.8.0-cp313-cp313-win_amd64.whl", hash = "sha256:18228d624807d66c87acd8f25fc135665617cab220671eb65b50f5d70fa51f69"},
+    {file = "tiktoken-0.8.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:7e17807445f0cf1f25771c9d86496bd8b5c376f7419912519699f3cc4dc5c12e"},
+    {file = "tiktoken-0.8.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:886f80bd339578bbdba6ed6d0567a0d5c6cfe198d9e587ba6c447654c65b8edc"},
+    {file = "tiktoken-0.8.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6adc8323016d7758d6de7313527f755b0fc6c72985b7d9291be5d96d73ecd1e1"},
+    {file = "tiktoken-0.8.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b591fb2b30d6a72121a80be24ec7a0e9eb51c5500ddc7e4c2496516dd5e3816b"},
+    {file = "tiktoken-0.8.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:845287b9798e476b4d762c3ebda5102be87ca26e5d2c9854002825d60cdb815d"},
+    {file = "tiktoken-0.8.0-cp39-cp39-win_amd64.whl", hash = "sha256:1473cfe584252dc3fa62adceb5b1c763c1874e04511b197da4e6de51d6ce5a02"},
+    {file = "tiktoken-0.8.0.tar.gz", hash = "sha256:9ccbb2740f24542534369c5635cfd9b2b3c2490754a78ac8831d99f89f94eeb2"},
 ]

 [package.dependencies]
@@ -12389,4 +12389,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.11,<3.13"
-content-hash = "0df8aef68385b6596306fd18af317a835023d648eb5028cd57ec463f176e4c0f"
+content-hash = "d197cdff507a70323c1d6aca11609188f54970f67715af744fe6def15b7776fd"
@@ -85,7 +85,7 @@ sentry-sdk = { version = "~1.44.1", extras = ["flask"] }
 sqlalchemy = "~2.0.29"
 starlette = "0.41.0"
 tencentcloud-sdk-python-hunyuan = "~3.0.1294"
-tiktoken = "^0.9.0"
+tiktoken = "~0.8.0"
 tokenizers = "~0.15.0"
 transformers = "~4.35.0"
 unstructured = { version = "~0.16.1", extras = ["docx", "epub", "md", "msg", "ppt", "pptx"] }
@@ -406,8 +406,10 @@ class AccountService:

            raise PasswordResetRateLimitExceededError()

-        code, token = cls.generate_reset_password_token(account_email, account)
-
+        code = "".join([str(random.randint(0, 9)) for _ in range(6)])
+        token = TokenManager.generate_token(
+            account=account, email=email, token_type="reset_password", additional_data={"code": code}
+        )
        send_reset_password_mail_task.delay(
            language=language,
            to=account_email,
@@ -416,22 +418,6 @@ class AccountService:
        cls.reset_password_rate_limiter.increment_rate_limit(account_email)
        return token

-    @classmethod
-    def generate_reset_password_token(
-        cls,
-        email: str,
-        account: Optional[Account] = None,
-        code: Optional[str] = None,
-        additional_data: dict[str, Any] = {},
-    ):
-        if not code:
-            code = "".join([str(random.randint(0, 9)) for _ in range(6)])
-        additional_data["code"] = code
-        token = TokenManager.generate_token(
-            account=account, email=email, token_type="reset_password", additional_data=additional_data
-        )
-        return code, token
-
    @classmethod
    def revoke_reset_password_token(cls, token: str):
        TokenManager.revoke_token(token, "reset_password")
@@ -55,19 +55,13 @@ def _check_version_compatibility(imported_version: str) -> ImportStatus:
    except version.InvalidVersion:
        return ImportStatus.FAILED

-    # If imported version is newer than current, always return PENDING
-    if imported_ver > current_ver:
+    # Compare major version and minor version
+    if current_ver.major != imported_ver.major or current_ver.minor != imported_ver.minor:
        return ImportStatus.PENDING

-    # If imported version is older than current's major, return PENDING
-    if imported_ver.major < current_ver.major:
-        return ImportStatus.PENDING
-
-    # If imported version is older than current's minor, return COMPLETED_WITH_WARNINGS
-    if imported_ver.minor < current_ver.minor:
+    if current_ver.micro != imported_ver.micro:
        return ImportStatus.COMPLETED_WITH_WARNINGS

-    # If imported version equals or is older than current's micro, return COMPLETED
    return ImportStatus.COMPLETED


@@ -932,6 +932,3 @@ MAX_SUBMIT_COUNT=100

 # The maximum number of top-k value for RAG.
 TOP_K_MAX_VALUE=10
-
-# Prevent Clickjacking
-ALLOW_EMBED=false
@@ -1,8 +1,8 @@
-x-shared-env: &shared-api-worker-env 
+x-shared-env: &shared-api-worker-env
 services:
  # API service
  api:
-    image: langgenius/dify-api:0.15.7
+    image: langgenius/dify-api:0.15.3
    restart: always
    environment:
      # Use the shared environment variables.
@@ -25,7 +25,7 @@ services:
  # worker service
  # The Celery worker for processing the queue.
  worker:
-    image: langgenius/dify-api:0.15.7
+    image: langgenius/dify-api:0.15.3
    restart: always
    environment:
      # Use the shared environment variables.
@@ -47,7 +47,7 @@ services:

  # Frontend web application.
  web:
-    image: langgenius/dify-web:0.15.7
+    image: langgenius/dify-web:0.15.3
    restart: always
    environment:
      CONSOLE_API_URL: ${CONSOLE_API_URL:-}
@@ -56,7 +56,6 @@ services:
      NEXT_TELEMETRY_DISABLED: ${NEXT_TELEMETRY_DISABLED:-0}
      TEXT_GENERATION_TIMEOUT_MS: ${TEXT_GENERATION_TIMEOUT_MS:-60000}
      CSP_WHITELIST: ${CSP_WHITELIST:-}
-      ALLOW_EMBED: ${ALLOW_EMBED:-false}
      TOP_K_MAX_VALUE: ${TOP_K_MAX_VALUE:-}
      INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH: ${INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH:-}

@@ -99,7 +98,7 @@ services:

  # The DifySandbox
  sandbox:
-    image: langgenius/dify-sandbox:0.2.11
+    image: langgenius/dify-sandbox:0.2.10
    restart: always
    environment:
      # The DifySandbox configurations
@@ -43,7 +43,7 @@ services:

  # The DifySandbox
  sandbox:
-    image: langgenius/dify-sandbox:0.2.11
+    image: langgenius/dify-sandbox:0.2.10
    restart: always
    environment:
      # The DifySandbox configurations
@@ -389,12 +389,11 @@ x-shared-env: &shared-api-worker-env
  CREATE_TIDB_SERVICE_JOB_ENABLED: ${CREATE_TIDB_SERVICE_JOB_ENABLED:-false}
  MAX_SUBMIT_COUNT: ${MAX_SUBMIT_COUNT:-100}
  TOP_K_MAX_VALUE: ${TOP_K_MAX_VALUE:-10}
-  ALLOW_EMBED: ${ALLOW_EMBED:-false}

 services:
  # API service
  api:
-    image: langgenius/dify-api:0.15.7
+    image: langgenius/dify-api:0.15.3
    restart: always
    environment:
      # Use the shared environment variables.
@@ -417,7 +416,7 @@ services:
  # worker service
  # The Celery worker for processing the queue.
  worker:
-    image: langgenius/dify-api:0.15.7
+    image: langgenius/dify-api:0.15.3
    restart: always
    environment:
      # Use the shared environment variables.
@@ -439,7 +438,7 @@ services:

  # Frontend web application.
  web:
-    image: langgenius/dify-web:0.15.7
+    image: langgenius/dify-web:0.15.3
    restart: always
    environment:
      CONSOLE_API_URL: ${CONSOLE_API_URL:-}
@@ -448,7 +447,6 @@ services:
      NEXT_TELEMETRY_DISABLED: ${NEXT_TELEMETRY_DISABLED:-0}
      TEXT_GENERATION_TIMEOUT_MS: ${TEXT_GENERATION_TIMEOUT_MS:-60000}
      CSP_WHITELIST: ${CSP_WHITELIST:-}
-      ALLOW_EMBED: ${ALLOW_EMBED:-false}
      TOP_K_MAX_VALUE: ${TOP_K_MAX_VALUE:-}
      INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH: ${INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH:-}

@@ -491,7 +489,7 @@ services:

  # The DifySandbox
  sandbox:
-    image: langgenius/dify-sandbox:0.2.11
+    image: langgenius/dify-sandbox:0.2.10
    restart: always
    environment:
      # The DifySandbox configurations
@@ -31,6 +31,3 @@ NEXT_PUBLIC_TOP_K_MAX_VALUE=10

 # The maximum number of tokens for segmentation
 NEXT_PUBLIC_INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH=4000
-
-# Default is not allow to embed into iframe to prevent Clickjacking: https://owasp.org/www-community/attacks/Clickjacking
-NEXT_PUBLIC_ALLOW_EMBED=
@@ -186,17 +186,15 @@ const Apps = ({
        <div className='w-[180px] h-8'></div>
      </div>
      <div className='relative flex flex-1 overflow-y-auto'>
-        {!searchKeywords && <div className='h-full w-[200px] p-4'>
-          <Sidebar current={currCategory as AppCategories} categories={categories} onClick={(category) => { setCurrCategory(category) }} onCreateFromBlank={onCreateFromBlank} />
+        {!searchKeywords && <div className='w-[200px] h-full p-4'>
+          <Sidebar current={currCategory as AppCategories} onClick={(category) => { setCurrCategory(category) }} onCreateFromBlank={onCreateFromBlank} />
        </div>}
        <div className='flex-1 h-full overflow-auto shrink-0 grow p-6 pt-2 border-l border-divider-burn'>
          {searchFilteredList && searchFilteredList.length > 0 && <>
            <div className='pt-4 pb-1'>
              {searchKeywords
                ? <p className='title-md-semi-bold text-text-tertiary'>{searchFilteredList.length > 1 ? t('app.newApp.foundResults', { count: searchFilteredList.length }) : t('app.newApp.foundResult', { count: searchFilteredList.length })}</p>
-                : <div className='flex h-[22px] items-center'>
-                  <AppCategoryLabel category={currCategory as AppCategories} className='title-md-semi-bold text-text-primary' />
-                </div>}
+                : <AppCategoryLabel category={currCategory as AppCategories} className='title-md-semi-bold text-text-primary' />}
            </div>
            <div
              className={cn(
@@ -1,29 +1,39 @@
 'use client'
-import { RiStickyNoteAddLine, RiThumbUpLine } from '@remixicon/react'
+import { RiAppsFill, RiChatSmileAiFill, RiExchange2Fill, RiPassPendingFill, RiQuillPenAiFill, RiSpeakAiFill, RiStickyNoteAddLine, RiTerminalBoxFill, RiThumbUpFill } from '@remixicon/react'
 import { useTranslation } from 'react-i18next'
 import classNames from '@/utils/classnames'
 import Divider from '@/app/components/base/divider'

 export enum AppCategories {
  RECOMMENDED = 'Recommended',
+  ASSISTANT = 'Assistant',
+  AGENT = 'Agent',
+  HR = 'HR',
+  PROGRAMMING = 'Programming',
+  WORKFLOW = 'Workflow',
+  WRITING = 'Writing',
 }

 type SidebarProps = {
-  current: AppCategories | string
-  categories: string[]
-  onClick?: (category: AppCategories | string) => void
+  current: AppCategories
+  onClick?: (category: AppCategories) => void
  onCreateFromBlank?: () => void
 }

-export default function Sidebar({ current, categories, onClick, onCreateFromBlank }: SidebarProps) {
+export default function Sidebar({ current, onClick, onCreateFromBlank }: SidebarProps) {
  const { t } = useTranslation()
-  return <div className="flex h-full w-full flex-col">
-    <ul className='pt-0.5'>
+  return <div className="w-full h-full flex flex-col">
+    <ul>
      <CategoryItem category={AppCategories.RECOMMENDED} active={current === AppCategories.RECOMMENDED} onClick={onClick} />
    </ul>
-    <div className='system-xs-medium-uppercase mb-0.5 mt-3 px-3 pb-1 pt-2 text-text-tertiary'>{t('app.newAppFromTemplate.byCategories')}</div>
-    <ul className='flex grow flex-col gap-0.5'>
-      {categories.map(category => (<CategoryItem key={category} category={category} active={current === category} onClick={onClick} />))}
+    <div className='px-3 pt-2 pb-1 system-xs-medium-uppercase text-text-tertiary'>{t('app.newAppFromTemplate.byCategories')}</div>
+    <ul className='flex-grow flex flex-col gap-0.5'>
+      <CategoryItem category={AppCategories.ASSISTANT} active={current === AppCategories.ASSISTANT} onClick={onClick} />
+      <CategoryItem category={AppCategories.AGENT} active={current === AppCategories.AGENT} onClick={onClick} />
+      <CategoryItem category={AppCategories.HR} active={current === AppCategories.HR} onClick={onClick} />
+      <CategoryItem category={AppCategories.PROGRAMMING} active={current === AppCategories.PROGRAMMING} onClick={onClick} />
+      <CategoryItem category={AppCategories.WORKFLOW} active={current === AppCategories.WORKFLOW} onClick={onClick} />
+      <CategoryItem category={AppCategories.WRITING} active={current === AppCategories.WRITING} onClick={onClick} />
    </ul>
    <Divider bgStyle='gradient' />
    <div className='px-3 py-1 flex items-center gap-1 text-text-tertiary cursor-pointer' onClick={onCreateFromBlank}>
@@ -35,26 +45,47 @@ export default function Sidebar({ current, categories, onClick, onCreateFromBlan

 type CategoryItemProps = {
  active: boolean
-  category: AppCategories | string
-  onClick?: (category: AppCategories | string) => void
+  category: AppCategories
+  onClick?: (category: AppCategories) => void
 }
 function CategoryItem({ category, active, onClick }: CategoryItemProps) {
  return <li
-    className={classNames('p-1 pl-3 h-8 rounded-lg flex items-center gap-2 group cursor-pointer hover:bg-state-base-hover [&.active]:bg-state-base-active', active && 'active')}
+    className={classNames('p-1 pl-3 rounded-lg flex items-center gap-2 group cursor-pointer hover:bg-state-base-hover [&.active]:bg-state-base-active', active && 'active')}
    onClick={() => { onClick?.(category) }}>
-    {category === AppCategories.RECOMMENDED && <div className='inline-flex h-5 w-5 items-center justify-center rounded-md'>
-      <RiThumbUpLine className='h-4 w-4 text-components-menu-item-text group-[.active]:text-components-menu-item-text-active' />
-    </div>}
+    <div className='w-5 h-5 inline-flex items-center justify-center rounded-md border border-divider-regular bg-components-icon-bg-midnight-solid group-[.active]:bg-components-icon-bg-blue-solid'>
+      <AppCategoryIcon category={category} />
+    </div>
    <AppCategoryLabel category={category}
      className={classNames('system-sm-medium text-components-menu-item-text group-[.active]:text-components-menu-item-text-active group-hover:text-components-menu-item-text-hover', active && 'system-sm-semibold')} />
  </li >
 }

 type AppCategoryLabelProps = {
-  category: AppCategories | string
+  category: AppCategories
  className?: string
 }
 export function AppCategoryLabel({ category, className }: AppCategoryLabelProps) {
  const { t } = useTranslation()
-  return <span className={className}>{category === AppCategories.RECOMMENDED ? t('app.newAppFromTemplate.sidebar.Recommended') : category}</span>
+  return <span className={className}>{t(`app.newAppFromTemplate.sidebar.${category}`)}</span>
+}
+
+type AppCategoryIconProps = {
+  category: AppCategories
+}
+function AppCategoryIcon({ category }: AppCategoryIconProps) {
+  if (category === AppCategories.AGENT)
+    return <RiSpeakAiFill className='w-3.5 h-3.5 text-components-avatar-shape-fill-stop-100' />
+  if (category === AppCategories.ASSISTANT)
+    return <RiChatSmileAiFill className='w-3.5 h-3.5 text-components-avatar-shape-fill-stop-100' />
+  if (category === AppCategories.HR)
+    return <RiPassPendingFill className='w-3.5 h-3.5 text-components-avatar-shape-fill-stop-100' />
+  if (category === AppCategories.PROGRAMMING)
+    return <RiTerminalBoxFill className='w-3.5 h-3.5 text-components-avatar-shape-fill-stop-100' />
+  if (category === AppCategories.RECOMMENDED)
+    return <RiThumbUpFill className='w-3.5 h-3.5 text-components-avatar-shape-fill-stop-100' />
+  if (category === AppCategories.WRITING)
+    return <RiQuillPenAiFill className='w-3.5 h-3.5 text-components-avatar-shape-fill-stop-100' />
+  if (category === AppCategories.WORKFLOW)
+    return <RiExchange2Fill className='w-3.5 h-3.5 text-components-avatar-shape-fill-stop-100' />
+  return <RiAppsFill className='w-3.5 h-3.5 text-components-avatar-shape-fill-stop-100' />
 }
@@ -312,7 +312,7 @@ function AppPreview({ mode }: { mode: AppMode }) {
    'chat': {
      title: t('app.types.chatbot'),
      description: t('app.newApp.chatbotUserDescription'),
-      link: 'https://docs.dify.ai/guides/application-orchestrate#application_type',
+      link: 'https://docs.dify.ai/guides/application-orchestrate/conversation-application?fallback=true',
    },
    'advanced-chat': {
      title: t('app.types.advanced'),
@@ -1,46 +0,0 @@
-import { useTranslation } from 'react-i18next'
-import Modal from '@/app/components/base/modal'
-import Button from '@/app/components/base/button'
-
-type DSLConfirmModalProps = {
-  versions?: {
-    importedVersion: string
-    systemVersion: string
-  }
-  onCancel: () => void
-  onConfirm: () => void
-  confirmDisabled?: boolean
-}
-const DSLConfirmModal = ({
-  versions = { importedVersion: '', systemVersion: '' },
-  onCancel,
-  onConfirm,
-  confirmDisabled = false,
-}: DSLConfirmModalProps) => {
-  const { t } = useTranslation()
-
-  return (
-    <Modal
-      isShow
-      onClose={() => onCancel()}
-      className='w-[480px]'
-    >
-      <div className='flex flex-col items-start gap-2 self-stretch pb-4'>
-        <div className='title-2xl-semi-bold text-text-primary'>{t('app.newApp.appCreateDSLErrorTitle')}</div>
-        <div className='system-md-regular flex grow flex-col text-text-secondary'>
-          <div>{t('app.newApp.appCreateDSLErrorPart1')}</div>
-          <div>{t('app.newApp.appCreateDSLErrorPart2')}</div>
-          <br />
-          <div>{t('app.newApp.appCreateDSLErrorPart3')}<span className='system-md-medium'>{versions.importedVersion}</span></div>
-          <div>{t('app.newApp.appCreateDSLErrorPart4')}<span className='system-md-medium'>{versions.systemVersion}</span></div>
-        </div>
-      </div>
-      <div className='flex items-start justify-end gap-2 self-stretch pt-6'>
-        <Button variant='secondary' onClick={() => onCancel()}>{t('app.newApp.Cancel')}</Button>
-        <Button variant='primary' destructive onClick={onConfirm} disabled={confirmDisabled}>{t('app.newApp.Confirm')}</Button>
-      </div>
-    </Modal>
-  )
-}
-
-export default DSLConfirmModal
@@ -24,7 +24,7 @@ const OPTION_MAP = {
  iframe: {
    getContent: (url: string, token: string) =>
      `<iframe
- src="${url}/chat/${token}"
+ src="${url}/chatbot/${token}"
 style="width: 100%; height: 100%; min-height: 700px"
 frameborder="0"
 allow="microphone">
@@ -35,12 +35,12 @@ const OPTION_MAP = {
      `<script>
 window.difyChatbotConfig = {
  token: '${token}'${isTestEnv
-        ? `,
+  ? `,
  isDev: true`
-        : ''}${IS_CE_EDITION
-          ? `,
+  : ''}${IS_CE_EDITION
+  ? `,
  baseUrl: '${url}'`
-          : ''}
+  : ''}
 }
 </script>
 <script
@@ -11,12 +11,10 @@ import { useLocalStorageState } from 'ahooks'
 import produce from 'immer'
 import type {
  ChatConfig,
-  ChatItem,
  Feedback,
 } from '../types'
 import { CONVERSATION_ID_INFO } from '../constants'
-import { buildChatItemTree, getProcessedInputsFromUrlParams } from '../utils'
-import { getProcessedFilesFromResponse } from '../../file-uploader/utils'
+import { getPrevChatList, getProcessedInputsFromUrlParams } from '../utils'
 import {
  fetchAppInfo,
  fetchAppMeta,
@@ -34,33 +32,6 @@ import { useToastContext } from '@/app/components/base/toast'
 import { changeLanguage } from '@/i18n/i18next-config'
 import { InputVarType } from '@/app/components/workflow/types'
 import { TransferMethod } from '@/types/app'
-import { addFileInfos, sortAgentSorts } from '@/app/components/tools/utils'
-
-function getFormattedChatList(messages: any[]) {
-  const newChatList: ChatItem[] = []
-  messages.forEach((item) => {
-    const questionFiles = item.message_files?.filter((file: any) => file.belongs_to === 'user') || []
-    newChatList.push({
-      id: `question-${item.id}`,
-      content: item.query,
-      isAnswer: false,
-      message_files: getProcessedFilesFromResponse(questionFiles.map((item: any) => ({ ...item, related_id: item.id }))),
-      parentMessageId: item.parent_message_id || undefined,
-    })
-    const answerFiles = item.message_files?.filter((file: any) => file.belongs_to === 'assistant') || []
-    newChatList.push({
-      id: item.id,
-      content: item.answer,
-      agent_thoughts: addFileInfos(item.agent_thoughts ? sortAgentSorts(item.agent_thoughts) : item.agent_thoughts, item.message_files),
-      feedback: item.feedback,
-      isAnswer: true,
-      citation: item.retriever_resources,
-      message_files: getProcessedFilesFromResponse(answerFiles.map((item: any) => ({ ...item, related_id: item.id }))),
-      parentMessageId: `question-${item.id}`,
-    })
-  })
-  return newChatList
-}

 export const useEmbeddedChatbot = () => {
  const isInstalledApp = false
@@ -106,7 +77,7 @@ export const useEmbeddedChatbot = () => {

  const appPrevChatList = useMemo(
    () => (currentConversationId && appChatListData?.data.length)
-      ? buildChatItemTree(getFormattedChatList(appChatListData.data))
+      ? getPrevChatList(appChatListData.data)
      : [],
    [appChatListData, currentConversationId],
  )
@@ -1,8 +1,6 @@
 import { UUID_NIL } from './constants'
 import type { IChatItem } from './chat/type'
 import type { ChatItem, ChatItemInTree } from './types'
-import { addFileInfos, sortAgentSorts } from '../../tools/utils'
-import { getProcessedFilesFromResponse } from '../file-uploader/utils'

 async function decodeBase64AndDecompress(base64String: string) {
  const binaryString = atob(base64String)
@@ -21,60 +19,6 @@ function getProcessedInputsFromUrlParams(): Record<string, any> {
  return inputs
 }

-function appendQAToChatList(chatList: ChatItem[], item: any) {
-  // we append answer first and then question since will reverse the whole chatList later
-  const answerFiles = item.message_files?.filter((file: any) => file.belongs_to === 'assistant') || []
-  chatList.push({
-    id: item.id,
-    content: item.answer,
-    agent_thoughts: addFileInfos(item.agent_thoughts ? sortAgentSorts(item.agent_thoughts) : item.agent_thoughts, item.message_files),
-    feedback: item.feedback,
-    isAnswer: true,
-    citation: item.retriever_resources,
-    message_files: getProcessedFilesFromResponse(answerFiles.map((item: any) => ({ ...item, related_id: item.id }))),
-  })
-  const questionFiles = item.message_files?.filter((file: any) => file.belongs_to === 'user') || []
-  chatList.push({
-    id: `question-${item.id}`,
-    content: item.query,
-    isAnswer: false,
-    message_files: getProcessedFilesFromResponse(questionFiles.map((item: any) => ({ ...item, related_id: item.id }))),
-  })
-}
-
-/**
- * Computes the latest thread messages from all messages of the conversation.
- * Same logic as backend codebase `api/core/prompt/utils/extract_thread_messages.py`
- *
- * @param fetchedMessages - The history chat list data from the backend, sorted by created_at in descending order. This includes all flattened history messages of the conversation.
- * @returns An array of ChatItems representing the latest thread.
- */
-
-
-function getPrevChatList(fetchedMessages: any[]) {
-  const ret: ChatItem[] = []
-  let nextMessageId = null
-
-  for (const item of fetchedMessages) {
-    if (!item.parent_message_id) {
-      appendQAToChatList(ret, item)
-      break
-    }
-
-    if (!nextMessageId) {
-      appendQAToChatList(ret, item)
-      nextMessageId = item.parent_message_id
-    }
-    else {
-      if (item.id === nextMessageId || nextMessageId === UUID_NIL) {
-        appendQAToChatList(ret, item)
-        nextMessageId = item.parent_message_id
-      }
-    }
-  }
-  return ret.reverse()
-}
-
 function isValidGeneratedAnswer(item?: ChatItem | ChatItemInTree): boolean {
  return !!item && item.isAnswer && !item.id.startsWith('answer-placeholder-') && !item.isOpeningStatement
 }
@@ -220,7 +164,6 @@ function getThreadMessages(tree: ChatItemInTree[], targetMessageId?: string): Ch
 export {
  getProcessedInputsFromUrlParams,
  isValidGeneratedAnswer,
-  getPrevChatList,
  getLastAnswer,
  buildChatItemTree,
  getThreadMessages,
@@ -10,7 +10,6 @@ import SyntaxHighlighter from 'react-syntax-highlighter'
 import { atelierHeathLight } from 'react-syntax-highlighter/dist/esm/styles/hljs'
 import { Component, memo, useMemo, useRef, useState } from 'react'
 import type { CodeComponent } from 'react-markdown/lib/ast-to-react'
-import SVGRenderer from './svg-gallery'
 import cn from '@/utils/classnames'
 import CopyBtn from '@/app/components/base/copy-btn'
 import SVGBtn from '@/app/components/base/svg'
@@ -19,7 +18,7 @@ import ImageGallery from '@/app/components/base/image-gallery'
 import { useChatContext } from '@/app/components/base/chat/chat/context'
 import VideoGallery from '@/app/components/base/video-gallery'
 import AudioGallery from '@/app/components/base/audio-gallery'
-// import SVGRenderer from '@/app/components/base/svg-gallery'
+import SVGRenderer from '@/app/components/base/svg-gallery'
 import MarkdownButton from '@/app/components/base/markdown-blocks/button'
 import MarkdownForm from '@/app/components/base/markdown-blocks/form'

@@ -1,6 +1,5 @@
 import { useEffect, useRef, useState } from 'react'
 import { SVG } from '@svgdotjs/svg.js'
-import DOMPurify from 'dompurify'
 import ImagePreview from '@/app/components/base/image-uploader/image-preview'

 export const SVGRenderer = ({ content }: { content: string }) => {
@@ -45,7 +44,7 @@ export const SVGRenderer = ({ content }: { content: string }) => {

        svgRef.current.style.width = `${Math.min(originalWidth, 298)}px`

-        const rootElement = draw.svg(DOMPurify.sanitize(content))
+        const rootElement = draw.svg(content)

        rootElement.click(() => {
          setImagePreview(svgToDataURL(svgElement as Element))
@@ -1,10 +1,12 @@
 'use client'

-import React, { useCallback, useMemo, useState } from 'react'
+import React, { useMemo, useState } from 'react'
+import { useRouter } from 'next/navigation'
 import { useTranslation } from 'react-i18next'
 import { useContext } from 'use-context-selector'
 import useSWR from 'swr'
 import { useDebounceFn } from 'ahooks'
+import Toast from '../../base/toast'
 import s from './style.module.css'
 import cn from '@/utils/classnames'
 import ExploreContext from '@/context/explore-context'
@@ -12,17 +14,17 @@ import type { App } from '@/models/explore'
 import Category from '@/app/components/explore/category'
 import AppCard from '@/app/components/explore/app-card'
 import { fetchAppDetail, fetchAppList } from '@/service/explore'
+import { importDSL } from '@/service/apps'
 import { useTabSearchParams } from '@/hooks/use-tab-searchparams'
 import CreateAppModal from '@/app/components/explore/create-app-modal'
 import AppTypeSelector from '@/app/components/app/type-selector'
 import type { CreateAppModalProps } from '@/app/components/explore/create-app-modal'
 import Loading from '@/app/components/base/loading'
+import { NEED_REFRESH_APP_LIST_KEY } from '@/config'
+import { useAppContext } from '@/context/app-context'
+import { getRedirection } from '@/utils/app-redirection'
 import Input from '@/app/components/base/input'
-import {
-  DSLImportMode,
-} from '@/models/app'
-import { useImportDSL } from '@/hooks/use-import-dsl'
-import DSLConfirmModal from '@/app/components/app/create-from-dsl-modal/dsl-confirm-modal'
+import { DSLImportMode } from '@/models/app'

 type AppsProps = {
  pageType?: PageType
@@ -39,6 +41,8 @@ const Apps = ({
  onSuccess,
 }: AppsProps) => {
  const { t } = useTranslation()
+  const { isCurrentWorkspaceEditor } = useAppContext()
+  const { push } = useRouter()
  const { hasEditPermission } = useContext(ExploreContext)
  const allCategoriesEn = t('explore.apps.allCategories', { lng: 'en' })

@@ -113,14 +117,6 @@ const Apps = ({

  const [currApp, setCurrApp] = React.useState<App | null>(null)
  const [isShowCreateModal, setIsShowCreateModal] = React.useState(false)
-
-  const {
-    handleImportDSL,
-    handleImportDSLConfirm,
-    versions,
-    isFetching,
-  } = useImportDSL()
-  const [showDSLConfirmModal, setShowDSLConfirmModal] = useState(false)
  const onCreate: CreateAppModalProps['onConfirm'] = async ({
    name,
    icon_type,
@@ -131,31 +127,31 @@ const Apps = ({
    const { export_data } = await fetchAppDetail(
      currApp?.app.id as string,
    )
-    const payload = {
-      mode: DSLImportMode.YAML_CONTENT,
-      yaml_content: export_data,
-      name,
-      icon_type,
-      icon,
-      icon_background,
-      description,
+    try {
+      const app = await importDSL({
+        mode: DSLImportMode.YAML_CONTENT,
+        yaml_content: export_data,
+        name,
+        icon_type,
+        icon,
+        icon_background,
+        description,
+      })
+      setIsShowCreateModal(false)
+      Toast.notify({
+        type: 'success',
+        message: t('app.newApp.appCreated'),
+      })
+      if (onSuccess)
+        onSuccess()
+      localStorage.setItem(NEED_REFRESH_APP_LIST_KEY, '1')
+      getRedirection(isCurrentWorkspaceEditor, { id: app.app_id }, push)
+    }
+    catch (e) {
+      Toast.notify({ type: 'error', message: t('app.newApp.appCreateFailed') })
    }
-    await handleImportDSL(payload, {
-      onSuccess: () => {
-        setIsShowCreateModal(false)
-      },
-      onPending: () => {
-        setShowDSLConfirmModal(true)
-      },
-    })
  }

-  const onConfirmDSL = useCallback(async () => {
-    await handleImportDSLConfirm({
-      onSuccess,
-    })
-  }, [handleImportDSLConfirm, onSuccess])
-
  if (!categories || categories.length === 0) {
    return (
      <div className="flex h-full items-center">
@@ -238,20 +234,9 @@ const Apps = ({
          appDescription={currApp?.app.description || ''}
          show={isShowCreateModal}
          onConfirm={onCreate}
-          confirmDisabled={isFetching}
          onHide={() => setIsShowCreateModal(false)}
        />
      )}
-      {
-        showDSLConfirmModal && (
-          <DSLConfirmModal
-            versions={versions}
-            onCancel={() => setShowDSLConfirmModal(false)}
-            onConfirm={onConfirmDSL}
-            confirmDisabled={isFetching}
-          />
-        )
-      }
    </div>
  )
 }
@@ -33,7 +33,6 @@ export type CreateAppModalProps = {
    description: string
    use_icon_as_answer_icon?: boolean
  }) => Promise<void>
-  confirmDisabled?: boolean
  onHide: () => void
 }

@@ -49,7 +48,6 @@ const CreateAppModal = ({
  appMode,
  appUseIconAsAnswerIcon,
  onConfirm,
-  confirmDisabled,
  onHide,
 }: CreateAppModalProps) => {
  const { t } = useTranslation()
@@ -147,7 +145,7 @@ const CreateAppModal = ({
          {!isEditModal && isAppsFull && <AppsFull loc='app-explore-create' />}
        </div>
        <div className='flex flex-row-reverse'>
-          <Button disabled={(!isEditModal && isAppsFull) || !name.trim() || confirmDisabled} className='w-24 ml-2' variant='primary' onClick={submit}>{!isEditModal ? t('common.operation.create') : t('common.operation.save')}</Button>
+          <Button disabled={!isEditModal && isAppsFull} className='w-24 ml-2' variant='primary' onClick={submit}>{!isEditModal ? t('common.operation.create') : t('common.operation.save')}</Button>
          <Button className='w-24' onClick={onHide}>{t('common.operation.cancel')}</Button>
        </div>
      </Modal>
@@ -39,11 +39,7 @@ export default function CheckCode() {
      }
      setIsLoading(true)
      const ret = await verifyResetPasswordCode({ email, code, token })
-      if (ret.is_valid) {
-        const params = new URLSearchParams(searchParams)
-        params.set('token', encodeURIComponent(ret.token))
-        router.push(`/reset-password/set-password?${params.toString()}`)
-      }
+      ret.is_valid && router.push(`/reset-password/set-password?${searchParams.toString()}`)
    }
    catch (error) { console.error(error) }
    finally {
@@ -23,7 +23,6 @@ export NEXT_TELEMETRY_DISABLED=${NEXT_TELEMETRY_DISABLED}

 export NEXT_PUBLIC_TEXT_GENERATION_TIMEOUT_MS=${TEXT_GENERATION_TIMEOUT_MS}
 export NEXT_PUBLIC_CSP_WHITELIST=${CSP_WHITELIST}
-export NEXT_PUBLIC_ALLOW_EMBED=${ALLOW_EMBED}
 export NEXT_PUBLIC_TOP_K_MAX_VALUE=${TOP_K_MAX_VALUE}
 export NEXT_PUBLIC_INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH=${INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH}

@@ -1,158 +0,0 @@
-import {
-  useCallback,
-  useRef,
-  useState,
-} from 'react'
-import { useTranslation } from 'react-i18next'
-import { useRouter } from 'next/navigation'
-import type {
-  DSLImportMode,
-  DSLImportResponse,
-} from '@/models/app'
-import { DSLImportStatus } from '@/models/app'
-import {
-  importDSL,
-  importDSLConfirm,
-} from '@/service/apps'
-import type { AppIconType } from '@/types/app'
-import { useToastContext } from '@/app/components/base/toast'
-import { getRedirection } from '@/utils/app-redirection'
-import { useSelector } from '@/context/app-context'
-import { NEED_REFRESH_APP_LIST_KEY } from '@/config'
-
-type DSLPayload = {
-  mode: DSLImportMode
-  yaml_content?: string
-  yaml_url?: string
-  name?: string
-  icon_type?: AppIconType
-  icon?: string
-  icon_background?: string
-  description?: string
-}
-type ResponseCallback = {
-  onSuccess?: () => void
-  onPending?: (payload: DSLImportResponse) => void
-  onFailed?: () => void
-}
-export const useImportDSL = () => {
-  const { t } = useTranslation()
-  const { notify } = useToastContext()
-  const [isFetching, setIsFetching] = useState(false)
-  const isCurrentWorkspaceEditor = useSelector(s => s.isCurrentWorkspaceEditor)
-  const { push } = useRouter()
-  const [versions, setVersions] = useState<{ importedVersion: string; systemVersion: string }>()
-  const importIdRef = useRef<string>('')
-
-  const handleImportDSL = useCallback(async (
-    payload: DSLPayload,
-    {
-      onSuccess,
-      onPending,
-      onFailed,
-    }: ResponseCallback,
-  ) => {
-    if (isFetching)
-      return
-    setIsFetching(true)
-
-    try {
-      const response = await importDSL(payload)
-
-      if (!response)
-        return
-
-      const {
-        id,
-        status,
-        app_id,
-        imported_dsl_version,
-        current_dsl_version,
-      } = response
-
-      if (status === DSLImportStatus.COMPLETED || status === DSLImportStatus.COMPLETED_WITH_WARNINGS) {
-        if (!app_id)
-          return
-
-        notify({
-          type: status === DSLImportStatus.COMPLETED ? 'success' : 'warning',
-          message: t(status === DSLImportStatus.COMPLETED ? 'app.newApp.appCreated' : 'app.newApp.caution'),
-          children: status === DSLImportStatus.COMPLETED_WITH_WARNINGS && t('app.newApp.appCreateDSLWarning'),
-        })
-        onSuccess?.()
-        localStorage.setItem(NEED_REFRESH_APP_LIST_KEY, '1')
-        getRedirection(isCurrentWorkspaceEditor, { id: app_id }, push)
-      }
-      else if (status === DSLImportStatus.PENDING) {
-        setVersions({
-          importedVersion: imported_dsl_version ?? '',
-          systemVersion: current_dsl_version ?? '',
-        })
-        importIdRef.current = id
-        onPending?.(response)
-      }
-      else {
-        notify({ type: 'error', message: t('app.newApp.appCreateFailed') })
-        onFailed?.()
-      }
-    }
-    catch {
-      notify({ type: 'error', message: t('app.newApp.appCreateFailed') })
-      onFailed?.()
-    }
-    finally {
-      setIsFetching(false)
-    }
-  }, [t, notify, isCurrentWorkspaceEditor, push, isFetching])
-
-  const handleImportDSLConfirm = useCallback(async (
-    {
-      onSuccess,
-      onFailed,
-    }: Pick<ResponseCallback, 'onSuccess' | 'onFailed'>,
-  ) => {
-    if (isFetching)
-      return
-    setIsFetching(true)
-    if (!importIdRef.current)
-      return
-
-    try {
-      const response = await importDSLConfirm({
-        import_id: importIdRef.current,
-      })
-
-      const { status, app_id } = response
-      if (!app_id)
-        return
-
-      if (status === DSLImportStatus.COMPLETED) {
-        onSuccess?.()
-        notify({
-          type: 'success',
-          message: t('app.newApp.appCreated'),
-        })
-        localStorage.setItem(NEED_REFRESH_APP_LIST_KEY, '1')
-        getRedirection(isCurrentWorkspaceEditor, { id: app_id! }, push)
-      }
-      else if (status === DSLImportStatus.FAILED) {
-        notify({ type: 'error', message: t('app.newApp.appCreateFailed') })
-        onFailed?.()
-      }
-    }
-    catch {
-      notify({ type: 'error', message: t('app.newApp.appCreateFailed') })
-      onFailed?.()
-    }
-    finally {
-      setIsFetching(false)
-    }
-  }, [t, notify, isCurrentWorkspaceEditor, push, isFetching])
-
-  return {
-    handleImportDSL,
-    handleImportDSLConfirm,
-    versions,
-    isFetching,
-  }
-}
@@ -3,26 +3,10 @@ import { NextResponse } from 'next/server'

 const NECESSARY_DOMAIN = '*.sentry.io http://localhost:* http://127.0.0.1:* https://analytics.google.com googletagmanager.com *.googletagmanager.com https://www.google-analytics.com https://api.github.com'

-const wrapResponseWithXFrameOptions = (response: NextResponse, pathname: string) => {
-  // prevent clickjacking: https://owasp.org/www-community/attacks/Clickjacking
-  // Chatbot page should be allowed to be embedded in iframe. It's a feature
-  if (process.env.NEXT_PUBLIC_ALLOW_EMBED !== 'true' && !pathname.startsWith('/chat'))
-    response.headers.set('X-Frame-Options', 'DENY')
-
-  return response
-}
 export function middleware(request: NextRequest) {
-  const { pathname } = request.nextUrl
-  const requestHeaders = new Headers(request.headers)
-  const response = NextResponse.next({
-    request: {
-      headers: requestHeaders,
-    },
-  })
-
  const isWhiteListEnabled = !!process.env.NEXT_PUBLIC_CSP_WHITELIST && process.env.NODE_ENV === 'production'
  if (!isWhiteListEnabled)
-    return wrapResponseWithXFrameOptions(response, pathname)
+    return NextResponse.next()

  const whiteList = `${process.env.NEXT_PUBLIC_CSP_WHITELIST} ${NECESSARY_DOMAIN}`
  const nonce = Buffer.from(crypto.randomUUID()).toString('base64')
@@ -49,6 +33,7 @@ export function middleware(request: NextRequest) {
    .replace(/\s{2,}/g, ' ')
    .trim()

+  const requestHeaders = new Headers(request.headers)
  requestHeaders.set('x-nonce', nonce)

  requestHeaders.set(
@@ -56,12 +41,17 @@ export function middleware(request: NextRequest) {
    contentSecurityPolicyHeaderValue,
  )

+  const response = NextResponse.next({
+    request: {
+      headers: requestHeaders,
+    },
+  })
  response.headers.set(
    'Content-Security-Policy',
    contentSecurityPolicyHeaderValue,
  )

-  return wrapResponseWithXFrameOptions(response, pathname)
+  return response
 }

 export const config = {
@@ -83,4 +73,4 @@ export const config = {
      // ],
    },
  ],
-}
+}
@@ -1,6 +1,6 @@
 {
  "name": "dify-web",
-  "version": "0.15.7",
+  "version": "0.15.3",
  "private": true,
  "engines": {
    "node": ">=18.17.0"
@@ -51,7 +51,6 @@
    "crypto-js": "^4.2.0",
    "dayjs": "^1.11.7",
    "decimal.js": "^10.4.3",
-    "dompurify": "^3.2.4",
    "echarts": "^5.5.1",
    "echarts-for-react": "^3.0.2",
    "elkjs": "^0.9.3",
@@ -71,7 +70,7 @@
    "mermaid": "11.4.1",
    "mime": "^4.0.4",
    "negotiator": "^0.6.3",
-    "next": "^14.2.25",
+    "next": "^14.2.10",
    "pinyin-pro": "^3.23.0",
    "qrcode.react": "^3.1.0",
    "qs": "^6.11.1",
@@ -40,7 +40,7 @@ import type { SystemFeatures } from '@/types/feature'

 type LoginSuccess = {
  result: 'success'
-  data: { access_token: string; refresh_token: string }
+  data: { access_token: string;refresh_token: string }
 }
 type LoginFail = {
  result: 'fail'
@@ -331,20 +331,20 @@ export const uploadRemoteFileInfo = (url: string, isPublic?: boolean) => {
 export const sendEMailLoginCode = (email: string, language = 'en-US') =>
  post<CommonResponse & { data: string }>('/email-code-login', { body: { email, language } })

-export const emailLoginWithCode = (data: { email: string; code: string; token: string }) =>
+export const emailLoginWithCode = (data: { email: string;code: string;token: string }) =>
  post<LoginResponse>('/email-code-login/validity', { body: data })

 export const sendResetPasswordCode = (email: string, language = 'en-US') =>
-  post<CommonResponse & { data: string; message?: string; code?: string }>('/forgot-password', { body: { email, language } })
+  post<CommonResponse & { data: string;message?: string ;code?: string }>('/forgot-password', { body: { email, language } })

-export const verifyResetPasswordCode = (body: { email: string; code: string; token: string }) =>
-  post<CommonResponse & { is_valid: boolean; token: string }>('/forgot-password/validity', { body })
+export const verifyResetPasswordCode = (body: { email: string;code: string;token: string }) =>
+  post<CommonResponse & { is_valid: boolean }>('/forgot-password/validity', { body })

 export const sendDeleteAccountCode = () =>
  get<CommonResponse & { data: string }>('/account/delete/verify')

-export const verifyDeleteAccountCode = (body: { code: string; token: string }) =>
+export const verifyDeleteAccountCode = (body: { code: string;token: string }) =>
  post<CommonResponse & { is_valid: boolean }>('/account/delete', { body })

-export const submitDeleteAccountFeedback = (body: { feedback: string; email: string }) =>
+export const submitDeleteAccountFeedback = (body: { feedback: string;email: string }) =>
  post<CommonResponse>('/account/delete/feedback', { body })
@@ -2066,10 +2066,10 @@
  dependencies:
    "@monaco-editor/loader" "^1.4.0"

-"@next/env@14.2.25":
-  version "14.2.25"
-  resolved "https://registry.yarnpkg.com/@next/env/-/env-14.2.25.tgz#936d10b967e103e49a4bcea1e97292d5605278dd"
-  integrity sha512-JnzQ2cExDeG7FxJwqAksZ3aqVJrHjFwZQAEJ9gQZSoEhIow7SNoKZzju/AwQ+PLIR4NY8V0rhcVozx/2izDO0w==
+"@next/env@14.2.17":
+  version "14.2.17"
+  resolved "https://registry.npmjs.org/@next/env/-/env-14.2.17.tgz"
+  integrity sha512-MCgO7VHxXo8sYR/0z+sk9fGyJJU636JyRmkjc7ZJY8Hurl8df35qG5hoAh5KMs75FLjhlEo9bb2LGe89Y/scDA==

 "@next/eslint-plugin-next@14.0.4":
  version "14.0.4"
@@ -2085,50 +2085,50 @@
  dependencies:
    source-map "^0.7.0"

-"@next/swc-darwin-arm64@14.2.25":
-  version "14.2.25"
-  resolved "https://registry.yarnpkg.com/@next/swc-darwin-arm64/-/swc-darwin-arm64-14.2.25.tgz#7bcccfda0c0ff045c45fbe34c491b7368e373e3d"
-  integrity sha512-09clWInF1YRd6le00vt750s3m7SEYNehz9C4PUcSu3bAdCTpjIV4aTYQZ25Ehrr83VR1rZeqtKUPWSI7GfuKZQ==
+"@next/swc-darwin-arm64@14.2.17":
+  version "14.2.17"
+  resolved "https://registry.npmjs.org/@next/swc-darwin-arm64/-/swc-darwin-arm64-14.2.17.tgz"
+  integrity sha512-WiOf5nElPknrhRMTipXYTJcUz7+8IAjOYw3vXzj3BYRcVY0hRHKWgTgQ5439EvzQyHEko77XK+yN9x9OJ0oOog==

-"@next/swc-darwin-x64@14.2.25":
-  version "14.2.25"
-  resolved "https://registry.yarnpkg.com/@next/swc-darwin-x64/-/swc-darwin-x64-14.2.25.tgz#b489e209d7b405260b73f69a38186ed150fb7a08"
-  integrity sha512-V+iYM/QR+aYeJl3/FWWU/7Ix4b07ovsQ5IbkwgUK29pTHmq+5UxeDr7/dphvtXEq5pLB/PucfcBNh9KZ8vWbug==
+"@next/swc-darwin-x64@14.2.17":
+  version "14.2.17"
+  resolved "https://registry.yarnpkg.com/@next/swc-darwin-x64/-/swc-darwin-x64-14.2.17.tgz#e29a17ef28d97c347c7d021f391e13b6c8e4c813"
+  integrity sha512-29y425wYnL17cvtxrDQWC3CkXe/oRrdt8ie61S03VrpwpPRI0XsnTvtKO06XCisK4alaMnZlf8riwZIbJTaSHQ==

-"@next/swc-linux-arm64-gnu@14.2.25":
-  version "14.2.25"
-  resolved "https://registry.yarnpkg.com/@next/swc-linux-arm64-gnu/-/swc-linux-arm64-gnu-14.2.25.tgz#ba064fabfdce0190d9859493d8232fffa84ef2e2"
-  integrity sha512-LFnV2899PJZAIEHQ4IMmZIgL0FBieh5keMnriMY1cK7ompR+JUd24xeTtKkcaw8QmxmEdhoE5Mu9dPSuDBgtTg==
+"@next/swc-linux-arm64-gnu@14.2.17":
+  version "14.2.17"
+  resolved "https://registry.yarnpkg.com/@next/swc-linux-arm64-gnu/-/swc-linux-arm64-gnu-14.2.17.tgz#10e99c7aa60cc33f8b7633e045f74be9a43e7b0c"
+  integrity sha512-SSHLZls3ZwNEHsc+d0ynKS+7Af0Nr8+KTUBAy9pm6xz9SHkJ/TeuEg6W3cbbcMSh6j4ITvrjv3Oi8n27VR+IPw==

-"@next/swc-linux-arm64-musl@14.2.25":
-  version "14.2.25"
-  resolved "https://registry.yarnpkg.com/@next/swc-linux-arm64-musl/-/swc-linux-arm64-musl-14.2.25.tgz#bf0018267e4e0fbfa1524750321f8cae855144a3"
-  integrity sha512-QC5y5PPTmtqFExcKWKYgUNkHeHE/z3lUsu83di488nyP0ZzQ3Yse2G6TCxz6nNsQwgAx1BehAJTZez+UQxzLfw==
+"@next/swc-linux-arm64-musl@14.2.17":
+  version "14.2.17"
+  resolved "https://registry.yarnpkg.com/@next/swc-linux-arm64-musl/-/swc-linux-arm64-musl-14.2.17.tgz#9a5bb809d3c6aef96c409959aedae28b4e5db53d"
+  integrity sha512-VFge37us5LNPatB4F7iYeuGs9Dprqe4ZkW7lOEJM91r+Wf8EIdViWHLpIwfdDXinvCdLl6b4VyLpEBwpkctJHA==

-"@next/swc-linux-x64-gnu@14.2.25":
-  version "14.2.25"
-  resolved "https://registry.yarnpkg.com/@next/swc-linux-x64-gnu/-/swc-linux-x64-gnu-14.2.25.tgz#64f5a6016a7148297ee80542e0fd788418a32472"
-  integrity sha512-y6/ML4b9eQ2D/56wqatTJN5/JR8/xdObU2Fb1RBidnrr450HLCKr6IJZbPqbv7NXmje61UyxjF5kvSajvjye5w==
+"@next/swc-linux-x64-gnu@14.2.17":
+  version "14.2.17"
+  resolved "https://registry.yarnpkg.com/@next/swc-linux-x64-gnu/-/swc-linux-x64-gnu-14.2.17.tgz#64e0ce01870e6dc45ae48f676d7cce82aedcdc62"
+  integrity sha512-aaQlpxUVb9RZ41adlTYVQ3xvYEfBPUC8+6rDgmQ/0l7SvK8S1YNJzPmDPX6a4t0jLtIoNk7j+nroS/pB4nx7vQ==

-"@next/swc-linux-x64-musl@14.2.25":
-  version "14.2.25"
-  resolved "https://registry.yarnpkg.com/@next/swc-linux-x64-musl/-/swc-linux-x64-musl-14.2.25.tgz#58dc636d7c55828478159546f7b95ab1e902301c"
-  integrity sha512-sPX0TSXHGUOZFvv96GoBXpB3w4emMqKeMgemrSxI7A6l55VBJp/RKYLwZIB9JxSqYPApqiREaIIap+wWq0RU8w==
+"@next/swc-linux-x64-musl@14.2.17":
+  version "14.2.17"
+  resolved "https://registry.yarnpkg.com/@next/swc-linux-x64-musl/-/swc-linux-x64-musl-14.2.17.tgz#93114164b6ccfc533908193ab9065f0c3970abc3"
+  integrity sha512-HSyEiFaEY3ay5iATDqEup5WAfrhMATNJm8dYx3ZxL+e9eKv10XKZCwtZByDoLST7CyBmyDz+OFJL1wigyXeaoA==

-"@next/swc-win32-arm64-msvc@14.2.25":
-  version "14.2.25"
-  resolved "https://registry.yarnpkg.com/@next/swc-win32-arm64-msvc/-/swc-win32-arm64-msvc-14.2.25.tgz#93562d447c799bded1e89c1a62d5195a2a8c6c0d"
-  integrity sha512-ReO9S5hkA1DU2cFCsGoOEp7WJkhFzNbU/3VUF6XxNGUCQChyug6hZdYL/istQgfT/GWE6PNIg9cm784OI4ddxQ==
+"@next/swc-win32-arm64-msvc@14.2.17":
+  version "14.2.17"
+  resolved "https://registry.yarnpkg.com/@next/swc-win32-arm64-msvc/-/swc-win32-arm64-msvc-14.2.17.tgz#4b99dea02178c112e5c33c742f9ff2a49b3b2939"
+  integrity sha512-h5qM9Btqv87eYH8ArrnLoAHLyi79oPTP2vlGNSg4CDvUiXgi7l0+5KuEGp5pJoMhjuv9ChRdm7mRlUUACeBt4w==

-"@next/swc-win32-ia32-msvc@14.2.25":
-  version "14.2.25"
-  resolved "https://registry.yarnpkg.com/@next/swc-win32-ia32-msvc/-/swc-win32-ia32-msvc-14.2.25.tgz#ad85a33466be1f41d083211ea21adc0d2c6e6554"
-  integrity sha512-DZ/gc0o9neuCDyD5IumyTGHVun2dCox5TfPQI/BJTYwpSNYM3CZDI4i6TOdjeq1JMo+Ug4kPSMuZdwsycwFbAw==
+"@next/swc-win32-ia32-msvc@14.2.17":
+  version "14.2.17"
+  resolved "https://registry.yarnpkg.com/@next/swc-win32-ia32-msvc/-/swc-win32-ia32-msvc-14.2.17.tgz#f1c23955405a259b6d45c65f918575b01bcf0106"
+  integrity sha512-BD/G++GKSLexQjdyoEUgyo5nClU7er5rK0sE+HlEqnldJSm96CIr/+YOTT063LVTT/dUOeQsNgp5DXr86/K7/A==

-"@next/swc-win32-x64-msvc@14.2.25":
-  version "14.2.25"
-  resolved "https://registry.yarnpkg.com/@next/swc-win32-x64-msvc/-/swc-win32-x64-msvc-14.2.25.tgz#3969c66609e683ec63a6a9f320a855f7be686a08"
-  integrity sha512-KSznmS6eFjQ9RJ1nEc66kJvtGIL1iZMYmGEXsZPh2YtnLtqrgdVvKXJY2ScjjoFnG6nGLyPFR0UiEvDwVah4Tw==
+"@next/swc-win32-x64-msvc@14.2.17":
+  version "14.2.17"
+  resolved "https://registry.yarnpkg.com/@next/swc-win32-x64-msvc/-/swc-win32-x64-msvc-14.2.17.tgz#44f5a4fcd8df1396a8d4326510ca2d92fb809cb3"
+  integrity sha512-vkQfN1+4V4KqDibkW2q0sJ6CxQuXq5l2ma3z0BRcfIqkAMZiiW67T9yCpwqJKP68QghBtPEFjPAlaqe38O6frw==

 "@nodelib/fs.scandir@2.1.5":
  version "2.1.5"
@@ -5864,13 +5864,6 @@ dompurify@^3.2.1:
  optionalDependencies:
    "@types/trusted-types" "^2.0.7"

-dompurify@^3.2.4:
-  version "3.2.4"
-  resolved "https://registry.yarnpkg.com/dompurify/-/dompurify-3.2.4.tgz#af5a5a11407524431456cf18836c55d13441cd8e"
-  integrity sha512-ysFSFEDVduQpyhzAob/kkuJjf5zWkZD8/A9ywSp1byueyuCfHamrCBa14/Oc2iiB0e51B+NpxSl5gmzn+Ms/mg==
-  optionalDependencies:
-    "@types/trusted-types" "^2.0.7"
-
 domutils@^2.5.2, domutils@^2.8.0:
  version "2.8.0"
  resolved "https://registry.npmjs.org/domutils/-/domutils-2.8.0.tgz"
@@ -9918,12 +9911,12 @@ neo-async@^2.6.2:
  resolved "https://registry.npmjs.org/neo-async/-/neo-async-2.6.2.tgz"
  integrity sha512-Yd3UES5mWCSqR+qNT93S3UoYUkqAZ9lLg8a7g9rimsWmYGK8cVToA4/sF3RrshdyV3sAGMXVUmpMYOw+dLpOuw==

-next@^14.2.25:
-  version "14.2.25"
-  resolved "https://registry.yarnpkg.com/next/-/next-14.2.25.tgz#0657551fde6a97f697cf9870e9ccbdaa465c6008"
-  integrity sha512-N5M7xMc4wSb4IkPvEV5X2BRRXUmhVHNyaXwEM86+voXthSZz8ZiRyQW4p9mwAoAPIm6OzuVZtn7idgEJeAJN3Q==
+next@^14.2.10:
+  version "14.2.17"
+  resolved "https://registry.npmjs.org/next/-/next-14.2.17.tgz"
+  integrity sha512-hNo/Zy701DDO3nzKkPmsLRlDfNCtb1OJxFUvjGEl04u7SFa3zwC6hqsOUzMajcaEOEV8ey1GjvByvrg0Qr5AiQ==
  dependencies:
-    "@next/env" "14.2.25"
+    "@next/env" "14.2.17"
    "@swc/helpers" "0.5.5"
    busboy "1.6.0"
    caniuse-lite "^1.0.30001579"
@@ -9931,15 +9924,15 @@ next@^14.2.25:
    postcss "8.4.31"
    styled-jsx "5.1.1"
  optionalDependencies:
-    "@next/swc-darwin-arm64" "14.2.25"
-    "@next/swc-darwin-x64" "14.2.25"
-    "@next/swc-linux-arm64-gnu" "14.2.25"
-    "@next/swc-linux-arm64-musl" "14.2.25"
-    "@next/swc-linux-x64-gnu" "14.2.25"
-    "@next/swc-linux-x64-musl" "14.2.25"
-    "@next/swc-win32-arm64-msvc" "14.2.25"
-    "@next/swc-win32-ia32-msvc" "14.2.25"
-    "@next/swc-win32-x64-msvc" "14.2.25"
+    "@next/swc-darwin-arm64" "14.2.17"
+    "@next/swc-darwin-x64" "14.2.17"
+    "@next/swc-linux-arm64-gnu" "14.2.17"
+    "@next/swc-linux-arm64-musl" "14.2.17"
+    "@next/swc-linux-x64-gnu" "14.2.17"
+    "@next/swc-linux-x64-musl" "14.2.17"
+    "@next/swc-win32-arm64-msvc" "14.2.17"
+    "@next/swc-win32-ia32-msvc" "14.2.17"
+    "@next/swc-win32-x64-msvc" "14.2.17"

 no-case@^3.0.4:
  version "3.0.4"