feat: add reasoning format processing to LLMNode for <think> tag handling (#23313)

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

api/core/model_runtime/entities/llm_entities.py

@@ -156,6 +156,7 @@ class LLMResult(BaseModel):
     message: AssistantPromptMessage
     usage: LLMUsage
     system_fingerprint: Optional[str] = None
+    reasoning_content: Optional[str] = None
 
 
 class LLMStructuredOutput(BaseModel):

api/core/workflow/nodes/event/event.py

@@ -30,6 +30,7 @@ class ModelInvokeCompletedEvent(BaseModel):
     text: str
     usage: LLMUsage
     finish_reason: str | None = None
+    reasoning_content: str | None = None
 
 
 class RunRetryEvent(BaseModel):

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

@@ -1,5 +1,5 @@
 from collections.abc import Mapping, Sequence
-from typing import Any, Optional
+from typing import Any, Literal, Optional
 
 from pydantic import BaseModel, Field, field_validator
 
@@ -68,6 +68,23 @@ class LLMNodeData(BaseNodeData):
     structured_output: Mapping[str, Any] | None = None
     # We used 'structured_output_enabled' in the past, but it's not a good name.
     structured_output_switch_on: bool = Field(False, alias="structured_output_enabled")
+    reasoning_format: Literal["separated", "tagged"] = Field(
+        # Keep tagged as default for backward compatibility
+        default="tagged",
+        description=(
+            """
+            Strategy for handling model reasoning output.
+
+            separated: Return clean text (without <think> tags) + reasoning_content field.
+                      Recommended for new workflows. Enables safe downstream parsing and 
+                      workflow variable access: {{#node_id.reasoning_content#}}
+
+            tagged   : Return original text (with <think> tags) + reasoning_content field.
+                      Maintains full backward compatibility while still providing reasoning_content
+                      for workflow automation. Frontend thinking panels work as before.
+            """
+        ),
+    )
 
     @field_validator("prompt_config", mode="before")
     @classmethod

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

@@ -2,8 +2,9 @@ import base64
 import io
 import json
 import logging
+import re
 from collections.abc import Generator, Mapping, Sequence
-from typing import TYPE_CHECKING, Any, Optional, Union
+from typing import TYPE_CHECKING, Any, Literal, Optional, Union
 
 from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
 from core.file import FileType, file_manager
@@ -99,6 +100,9 @@ class LLMNode(BaseNode):
 
     _node_data: LLMNodeData
 
+    # Compiled regex for extracting <think> blocks (with compatibility for attributes)
+    _THINK_PATTERN = re.compile(r"<think[^>]*>(.*?)</think>", re.IGNORECASE | re.DOTALL)
+
     # Instance attributes specific to LLMNode.
     # Output variable for file
     _file_outputs: list["File"]
@@ -167,6 +171,7 @@ class LLMNode(BaseNode):
         result_text = ""
         usage = LLMUsage.empty_usage()
         finish_reason = None
+        reasoning_content = None
         variable_pool = self.graph_runtime_state.variable_pool
 
         try:
@@ -256,6 +261,7 @@ class LLMNode(BaseNode):
                 file_saver=self._llm_file_saver,
                 file_outputs=self._file_outputs,
                 node_id=self.node_id,
+                reasoning_format=self._node_data.reasoning_format,
             )
 
             structured_output: LLMStructuredOutput | None = None
@@ -264,9 +270,20 @@ class LLMNode(BaseNode):
                 if isinstance(event, RunStreamChunkEvent):
                     yield event
                 elif isinstance(event, ModelInvokeCompletedEvent):
+                    # Raw text
                     result_text = event.text
                     usage = event.usage
                     finish_reason = event.finish_reason
+                    reasoning_content = event.reasoning_content or ""
+
+                    # For downstream nodes, determine clean text based on reasoning_format
+                    if self._node_data.reasoning_format == "tagged":
+                        # Keep <think> tags for backward compatibility
+                        clean_text = result_text
+                    else:
+                        # Extract clean text from <think> tags
+                        clean_text, _ = LLMNode._split_reasoning(result_text, self._node_data.reasoning_format)
+
                     # deduct quota
                     llm_utils.deduct_llm_quota(tenant_id=self.tenant_id, model_instance=model_instance, usage=usage)
                     break
@@ -284,7 +301,12 @@ class LLMNode(BaseNode):
                 "model_name": model_config.model,
             }
 
-            outputs = {"text": result_text, "usage": jsonable_encoder(usage), "finish_reason": finish_reason}
+            outputs = {
+                "text": clean_text,
+                "reasoning_content": reasoning_content,
+                "usage": jsonable_encoder(usage),
+                "finish_reason": finish_reason,
+            }
             if structured_output:
                 outputs["structured_output"] = structured_output.structured_output
             if self._file_outputs is not None:
@@ -338,6 +360,7 @@ class LLMNode(BaseNode):
         file_saver: LLMFileSaver,
         file_outputs: list["File"],
         node_id: str,
+        reasoning_format: Literal["separated", "tagged"] = "tagged",
     ) -> Generator[NodeEvent | LLMStructuredOutput, None, None]:
         model_schema = model_instance.model_type_instance.get_model_schema(
             node_data_model.name, model_instance.credentials
@@ -374,6 +397,7 @@ class LLMNode(BaseNode):
             file_saver=file_saver,
             file_outputs=file_outputs,
             node_id=node_id,
+            reasoning_format=reasoning_format,
         )
 
     @staticmethod
@@ -383,6 +407,7 @@ class LLMNode(BaseNode):
         file_saver: LLMFileSaver,
         file_outputs: list["File"],
         node_id: str,
+        reasoning_format: Literal["separated", "tagged"] = "tagged",
     ) -> Generator[NodeEvent | LLMStructuredOutput, None, None]:
         # For blocking mode
         if isinstance(invoke_result, LLMResult):
@@ -390,6 +415,7 @@ class LLMNode(BaseNode):
                 invoke_result=invoke_result,
                 saver=file_saver,
                 file_outputs=file_outputs,
+                reasoning_format=reasoning_format,
             )
             yield event
             return
@@ -430,13 +456,66 @@ class LLMNode(BaseNode):
         except OutputParserError as e:
             raise LLMNodeError(f"Failed to parse structured output: {e}")
 
-        yield ModelInvokeCompletedEvent(text=full_text_buffer.getvalue(), usage=usage, finish_reason=finish_reason)
+        # Extract reasoning content from <think> tags in the main text
+        full_text = full_text_buffer.getvalue()
+
+        if reasoning_format == "tagged":
+            # Keep <think> tags in text for backward compatibility
+            clean_text = full_text
+            reasoning_content = ""
+        else:
+            # Extract clean text and reasoning from <think> tags
+            clean_text, reasoning_content = LLMNode._split_reasoning(full_text, reasoning_format)
+
+        yield ModelInvokeCompletedEvent(
+            # Use clean_text for separated mode, full_text for tagged mode
+            text=clean_text if reasoning_format == "separated" else full_text,
+            usage=usage,
+            finish_reason=finish_reason,
+            # Reasoning content for workflow variables and downstream nodes
+            reasoning_content=reasoning_content,
+        )
 
     @staticmethod
     def _image_file_to_markdown(file: "File", /):
         text_chunk = f"![]({file.generate_url()})"
         return text_chunk
 
+    @classmethod
+    def _split_reasoning(
+        cls, text: str, reasoning_format: Literal["separated", "tagged"] = "tagged"
+    ) -> tuple[str, str]:
+        """
+        Split reasoning content from text based on reasoning_format strategy.
+
+        Args:
+            text: Full text that may contain <think> blocks
+            reasoning_format: Strategy for handling reasoning content
+                - "separated": Remove <think> tags and return clean text + reasoning_content field
+                - "tagged": Keep <think> tags in text, return empty reasoning_content
+
+        Returns:
+            tuple of (clean_text, reasoning_content)
+        """
+
+        if reasoning_format == "tagged":
+            return text, ""
+
+        # Find all <think>...</think> blocks (case-insensitive)
+        matches = cls._THINK_PATTERN.findall(text)
+
+        # Extract reasoning content from all <think> blocks
+        reasoning_content = "\n".join(match.strip() for match in matches) if matches else ""
+
+        # Remove all <think>...</think> blocks from original text
+        clean_text = cls._THINK_PATTERN.sub("", text)
+
+        # Clean up extra whitespace
+        clean_text = re.sub(r"\n\s*\n", "\n\n", clean_text).strip()
+
+        # Separated mode: always return clean text and reasoning_content
+        return clean_text, reasoning_content or ""
+
     def _transform_chat_messages(
         self, messages: Sequence[LLMNodeChatModelMessage] | LLMNodeCompletionModelPromptTemplate, /
     ) -> Sequence[LLMNodeChatModelMessage] | LLMNodeCompletionModelPromptTemplate:
@@ -964,6 +1043,7 @@ class LLMNode(BaseNode):
         invoke_result: LLMResult,
         saver: LLMFileSaver,
         file_outputs: list["File"],
+        reasoning_format: Literal["separated", "tagged"] = "tagged",
     ) -> ModelInvokeCompletedEvent:
         buffer = io.StringIO()
         for text_part in LLMNode._save_multimodal_output_and_convert_result_to_markdown(
@@ -973,10 +1053,24 @@ class LLMNode(BaseNode):
         ):
             buffer.write(text_part)
 
+        # Extract reasoning content from <think> tags in the main text
+        full_text = buffer.getvalue()
+
+        if reasoning_format == "tagged":
+            # Keep <think> tags in text for backward compatibility
+            clean_text = full_text
+            reasoning_content = ""
+        else:
+            # Extract clean text and reasoning from <think> tags
+            clean_text, reasoning_content = LLMNode._split_reasoning(full_text, reasoning_format)
+
         return ModelInvokeCompletedEvent(
-            text=buffer.getvalue(),
+            # Use clean_text for separated mode, full_text for tagged mode
+            text=clean_text if reasoning_format == "separated" else full_text,
             usage=invoke_result.usage,
             finish_reason=None,
+            # Reasoning content for workflow variables and downstream nodes
+            reasoning_content=reasoning_content,
         )
 
     @staticmethod

api/tests/unit_tests/core/workflow/nodes/llm/test_node.py

@@ -69,6 +69,7 @@ def llm_node_data() -> LLMNodeData:
                 detail=ImagePromptMessageContent.DETAIL.HIGH,
             ),
         ),
+        reasoning_format="tagged",
     )
 
 
@@ -689,3 +690,66 @@ class TestSaveMultimodalOutputAndConvertResultToMarkdown:
         assert list(gen) == []
         mock_file_saver.save_binary_string.assert_not_called()
         mock_file_saver.save_remote_url.assert_not_called()
+
+
+class TestReasoningFormat:
+    """Test cases for reasoning_format functionality"""
+
+    def test_split_reasoning_separated_mode(self):
+        """Test separated mode: tags are removed and content is extracted"""
+
+        text_with_think = """
+        <think>I need to explain what Dify is. It's an open source AI platform.
+        </think>Dify is an open source AI platform.
+        """
+
+        clean_text, reasoning_content = LLMNode._split_reasoning(text_with_think, "separated")
+
+        assert clean_text == "Dify is an open source AI platform."
+        assert reasoning_content == "I need to explain what Dify is. It's an open source AI platform."
+
+    def test_split_reasoning_tagged_mode(self):
+        """Test tagged mode: original text is preserved"""
+
+        text_with_think = """
+        <think>I need to explain what Dify is. It's an open source AI platform.
+        </think>Dify is an open source AI platform.
+        """
+
+        clean_text, reasoning_content = LLMNode._split_reasoning(text_with_think, "tagged")
+
+        # Original text unchanged
+        assert clean_text == text_with_think
+        # Empty reasoning content in tagged mode
+        assert reasoning_content == ""
+
+    def test_split_reasoning_no_think_blocks(self):
+        """Test behavior when no <think> tags are present"""
+
+        text_without_think = "This is a simple answer without any thinking blocks."
+
+        clean_text, reasoning_content = LLMNode._split_reasoning(text_without_think, "separated")
+
+        assert clean_text == text_without_think
+        assert reasoning_content == ""
+
+    def test_reasoning_format_default_value(self):
+        """Test that reasoning_format defaults to 'tagged' for backward compatibility"""
+
+        node_data = LLMNodeData(
+            title="Test LLM",
+            model=ModelConfig(provider="openai", name="gpt-3.5-turbo", mode="chat", completion_params={}),
+            prompt_template=[],
+            context=ContextConfig(enabled=False),
+        )
+
+        assert node_data.reasoning_format == "tagged"
+
+        text_with_think = """
+        <think>I need to explain what Dify is. It's an open source AI platform.
+        </think>Dify is an open source AI platform.
+        """
+        clean_text, reasoning_content = LLMNode._split_reasoning(text_with_think, node_data.reasoning_format)
+
+        assert clean_text == text_with_think
+        assert reasoning_content == ""

web/app/components/workflow/constants.ts

@@ -479,6 +479,10 @@ export const LLM_OUTPUT_STRUCT: Var[] = [
     variable: 'text',
     type: VarType.string,
   },
+  {
+    variable: 'reasoning_content',
+    type: VarType.string,
+  },
   {
     variable: 'usage',
     type: VarType.object,

web/app/components/workflow/nodes/llm/components/reasoning-format-config.tsx

@@ -0,0 +1,40 @@
+import type { FC } from 'react'
+import React from 'react'
+import { useTranslation } from 'react-i18next'
+import Field from '@/app/components/workflow/nodes/_base/components/field'
+import Switch from '@/app/components/base/switch'
+
+type ReasoningFormatConfigProps = {
+  value?: 'tagged' | 'separated'
+  onChange: (value: 'tagged' | 'separated') => void
+  readonly?: boolean
+}
+
+const ReasoningFormatConfig: FC<ReasoningFormatConfigProps> = ({
+  value = 'tagged',
+  onChange,
+  readonly = false,
+}) => {
+  const { t } = useTranslation()
+
+  return (
+    <Field
+      title={t('workflow.nodes.llm.reasoningFormat.title')}
+      tooltip={t('workflow.nodes.llm.reasoningFormat.tooltip')}
+      operations={
+        // ON = separated, OFF = tagged
+        <Switch
+          defaultValue={value === 'separated'}
+          onChange={enabled => onChange(enabled ? 'separated' : 'tagged')}
+          size='md'
+          disabled={readonly}
+          key={value}
+        />
+      }
+    >
+      <div />
+    </Field>
+  )
+}
+
+export default ReasoningFormatConfig

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

@@ -17,6 +17,7 @@ import type { NodePanelProps } from '@/app/components/workflow/types'
 import Tooltip from '@/app/components/base/tooltip'
 import Editor from '@/app/components/workflow/nodes/_base/components/prompt/editor'
 import StructureOutput from './components/structure-output'
+import ReasoningFormatConfig from './components/reasoning-format-config'
 import Switch from '@/app/components/base/switch'
 import { RiAlertFill, RiQuestionLine } from '@remixicon/react'
 import { fetchAndMergeValidCompletionParams } from '@/utils/completion-params'
@@ -61,6 +62,7 @@ const Panel: FC<NodePanelProps<LLMNodeType>> = ({
     handleStructureOutputEnableChange,
     handleStructureOutputChange,
     filterJinja2InputVar,
+    handleReasoningFormatChange,
   } = useConfig(id, data)
 
   const model = inputs.model
@@ -239,6 +241,14 @@ const Panel: FC<NodePanelProps<LLMNodeType>> = ({
           config={inputs.vision?.configs}
           onConfigChange={handleVisionResolutionChange}
         />
+
+        {/* Reasoning Format */}
+        <ReasoningFormatConfig
+          // Default to tagged for backward compatibility
+          value={inputs.reasoning_format || 'tagged'}
+          onChange={handleReasoningFormatChange}
+          readonly={readOnly}
+        />
       </div>
       <Split />
       <OutputVars

web/app/components/workflow/nodes/llm/types.ts

@@ -17,6 +17,7 @@ export type LLMNodeType = CommonNodeType & {
   }
   structured_output_enabled?: boolean
   structured_output?: StructuredOutput
+  reasoning_format?: 'tagged' | 'separated'
 }
 
 export enum Type {

web/app/components/workflow/nodes/llm/use-config.ts

@@ -315,6 +315,14 @@ const useConfig = (id: string, payload: LLMNodeType) => {
     return [VarType.arrayObject, VarType.array, VarType.number, VarType.string, VarType.secret, VarType.arrayString, VarType.arrayNumber, VarType.file, VarType.arrayFile].includes(varPayload.type)
   }, [])
 
+  // reasoning format
+  const handleReasoningFormatChange = useCallback((reasoningFormat: 'tagged' | 'separated') => {
+    const newInputs = produce(inputs, (draft) => {
+      draft.reasoning_format = reasoningFormat
+    })
+    setInputs(newInputs)
+  }, [inputs, setInputs])
+
   const {
     availableVars,
     availableNodesWithParent,
@@ -355,6 +363,7 @@ const useConfig = (id: string, payload: LLMNodeType) => {
     setStructuredOutputCollapsed,
     handleStructureOutputEnableChange,
     filterJinja2InputVar,
+    handleReasoningFormatChange,
   }
 }
 

web/i18n/de-DE/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         instruction: 'Anleitung',
         regenerate: 'Regenerieren',
       },
+      reasoningFormat: {
+        tooltip: 'Inhalte aus Denk-Tags extrahieren und im Feld reasoning_content speichern.',
+        separated: 'Separate Denk tags',
+        title: 'Aktivieren Sie die Trennung von Argumentations-Tags',
+        tagged: 'Behalte die Denk-Tags',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'Abfragevariable',

web/i18n/en-US/workflow.ts

@@ -449,6 +449,12 @@ const translation = {
         variable: 'Variable',
       },
       sysQueryInUser: 'sys.query in user message is required',
+      reasoningFormat: {
+        title: 'Enable reasoning tag separation',
+        tagged: 'Keep think tags',
+        separated: 'Separate think tags',
+        tooltip: 'Extract content from think tags and store it in the reasoning_content field.',
+      },
       jsonSchema: {
         title: 'Structured Output Schema',
         instruction: 'Instruction',

web/i18n/es-ES/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         import: 'Importar desde JSON',
         resetDefaults: 'Restablecer',
       },
+      reasoningFormat: {
+        tagged: 'Mantén las etiquetas de pensamiento',
+        separated: 'Separar etiquetas de pensamiento',
+        title: 'Habilitar la separación de etiquetas de razonamiento',
+        tooltip: 'Extraer contenido de las etiquetas de pensamiento y almacenarlo en el campo reasoning_content.',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'Variable de consulta',

web/i18n/fa-IR/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         fieldNamePlaceholder: 'نام میدان',
         generationTip: 'شما می‌توانید از زبان طبیعی برای ایجاد سریع یک طرح‌واره JSON استفاده کنید.',
       },
+      reasoningFormat: {
+        separated: 'تگ‌های تفکر جداگانه',
+        title: 'فعال‌سازی جداسازی برچسب‌های استدلال',
+        tagged: 'به فکر برچسب‌ها باشید',
+        tooltip: 'محتوا را از تگ‌های تفکر استخراج کرده و در فیلد reasoning_content ذخیره کنید.',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'متغیر جستجو',

web/i18n/fr-FR/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         generateJsonSchema: 'Générer un schéma JSON',
         resultTip: 'Voici le résultat généré. Si vous n\'êtes pas satisfait, vous pouvez revenir en arrière et modifier votre demande.',
       },
+      reasoningFormat: {
+        title: 'Activer la séparation des balises de raisonnement',
+        tagged: 'Gardez les étiquettes de pensée',
+        separated: 'Séparer les balises de réflexion',
+        tooltip: 'Extraire le contenu des balises think et le stocker dans le champ reasoning_content.',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'Variable de requête',

web/i18n/hi-IN/workflow.ts

@@ -483,6 +483,12 @@ const translation = {
         required: 'आवश्यक',
         addChildField: 'बच्चे का क्षेत्र जोड़ें',
       },
+      reasoningFormat: {
+        title: 'कारण संबंध टैग विभाजन सक्षम करें',
+        separated: 'अलग सोच टैग',
+        tagged: 'टैग्स के बारे में सोचते रहें',
+        tooltip: 'थिंक टैग से सामग्री निकाले और इसे reasoning_content क्षेत्र में संग्रहित करें।',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'प्रश्न वेरिएबल',

web/i18n/it-IT/workflow.ts

@@ -487,6 +487,12 @@ const translation = {
         generating: 'Generazione dello schema JSON...',
         generatedResult: 'Risultato generato',
       },
+      reasoningFormat: {
+        title: 'Abilita la separazione dei tag di ragionamento',
+        tagged: 'Continua a pensare ai tag',
+        separated: 'Tag di pensiero separati',
+        tooltip: 'Estrai il contenuto dai tag think e conservalo nel campo reasoning_content.',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'Variabile Query',

web/i18n/ja-JP/workflow.ts

@@ -477,6 +477,12 @@ const translation = {
           saveSchema: '編集中のフィールドを確定してから保存してください。',
         },
       },
+      reasoningFormat: {
+        tagged: 'タグを考え続けてください',
+        separated: '思考タグを分ける',
+        title: '推論タグの分離を有効にする',
+        tooltip: 'thinkタグから内容を抽出し、それをreasoning_contentフィールドに保存します。',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: '検索変数',

web/i18n/ko-KR/workflow.ts

@@ -497,6 +497,12 @@ const translation = {
         doc: '구조화된 출력에 대해 더 알아보세요.',
         import: 'JSON 에서 가져오기',
       },
+      reasoningFormat: {
+        title: '추론 태그 분리 활성화',
+        separated: '추론 태그 분리',
+        tooltip: '추론 태그에서 내용을 추출하고 이를 reasoning_content 필드에 저장합니다',
+        tagged: '추론 태그 유지',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: '쿼리 변수',

web/i18n/pl-PL/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         back: 'Tył',
         addField: 'Dodaj pole',
       },
+      reasoningFormat: {
+        tooltip: 'Wyodrębnij treść z tagów think i przechowaj ją w polu reasoning_content.',
+        separated: 'Oddziel tagi myślenia',
+        tagged: 'Zachowaj myśl tagi',
+        title: 'Włącz separację tagów uzasadnienia',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'Zmienna zapytania',

web/i18n/pt-BR/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         apply: 'Aplicar',
         required: 'obrigatório',
       },
+      reasoningFormat: {
+        tagged: 'Mantenha as tags de pensamento',
+        title: 'Ativar separação de tags de raciocínio',
+        separated: 'Separe as tags de pensamento',
+        tooltip: 'Extraia o conteúdo das tags de pensamento e armazene-o no campo reasoning_content.',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'Variável de consulta',

web/i18n/ro-RO/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         back: 'Înapoi',
         promptPlaceholder: 'Descrie schema ta JSON...',
       },
+      reasoningFormat: {
+        tagged: 'Ține minte etichetele',
+        separated: 'Etichete de gândire separate',
+        title: 'Activează separarea etichetelor de raționare',
+        tooltip: 'Extrage conținutul din etichetele think și stochează-l în câmpul reasoning_content.',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'Variabilă de interogare',

web/i18n/ru-RU/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         generating: 'Генерация схемы JSON...',
         promptTooltip: 'Преобразуйте текстовое описание в стандартизированную структуру JSON Schema.',
       },
+      reasoningFormat: {
+        tagged: 'Продолжайте думать о тегах',
+        title: 'Включите разделение тегов на основе логики',
+        tooltip: 'Извлечь содержимое из тегов think и сохранить его в поле reasoning_content.',
+        separated: 'Отдельные теги для мышления',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'Переменная запроса',

web/i18n/sl-SI/workflow.ts

@@ -477,6 +477,12 @@ const translation = {
       context: 'kontekst',
       addMessage: 'Dodaj sporočilo',
       vision: 'vizija',
+      reasoningFormat: {
+        tagged: 'Ohranite oznake za razmišljanje',
+        title: 'Omogoči ločevanje oznak za razsojanje',
+        tooltip: 'Izvleći vsebino iz miselnih oznak in jo shraniti v polje reasoning_content.',
+        separated: 'Ločite oznake za razmišljanje',
+      },
     },
     knowledgeRetrieval: {
       outputVars: {

web/i18n/th-TH/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         stringValidations: 'การตรวจสอบสตริง',
         required: 'จำเป็นต้องใช้',
       },
+      reasoningFormat: {
+        tagged: 'รักษาความคิดเกี่ยวกับแท็ก',
+        separated: 'แยกแท็กความคิดเห็น',
+        tooltip: 'ดึงเนื้อหาจากแท็กคิดและเก็บไว้ในฟิลด์ reasoning_content.',
+        title: 'เปิดใช้งานการแยกแท็กการเหตุผล',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'ตัวแปรแบบสอบถาม',

web/i18n/tr-TR/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         addChildField: 'Çocuk Alanı Ekle',
         resultTip: 'İşte oluşturulan sonuç. Eğer memnun değilseniz, geri dönüp isteminizi değiştirebilirsiniz.',
       },
+      reasoningFormat: {
+        separated: 'Ayrı düşünce etiketleri',
+        title: 'Akıl yürütme etiket ayrımını etkinleştir',
+        tagged: 'Etiketleri düşünmeye devam et',
+        tooltip: 'Düşünce etiketlerinden içeriği çıkarın ve bunu reasoning_content alanında saklayın.',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'Sorgu Değişkeni',

web/i18n/uk-UA/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         title: 'Структурована схема виходу',
         doc: 'Дізнайтеся більше про структурований вихід',
       },
+      reasoningFormat: {
+        separated: 'Окремі теги для думок',
+        tagged: 'Продовжуйте думати про мітки',
+        title: 'Увімкніть розділення тегів для міркування',
+        tooltip: 'Витягніть вміст з тегів think і зберігайте його в полі reasoning_content.',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'Змінна запиту',

web/i18n/vi-VN/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         addChildField: 'Thêm trường trẻ em',
         title: 'Sơ đồ đầu ra có cấu trúc',
       },
+      reasoningFormat: {
+        tagged: 'Giữ lại thẻ suy nghĩ',
+        tooltip: 'Trích xuất nội dung từ các thẻ think và lưu nó vào trường reasoning_content.',
+        separated: 'Tách biệt các thẻ suy nghĩ',
+        title: 'Bật chế độ phân tách nhãn lý luận',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: 'Biến truy vấn',

web/i18n/zh-Hans/workflow.ts

@@ -477,6 +477,12 @@ const translation = {
           saveSchema: '请先完成当前字段的编辑',
         },
       },
+      reasoningFormat: {
+        tooltip: '从think标签中提取内容，并将其存储在reasoning_content字段中。',
+        title: '启用推理标签分离',
+        tagged: '保持思考标签',
+        separated: '分开思考标签',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: '查询变量',

web/i18n/zh-Hant/workflow.ts

@@ -470,6 +470,12 @@ const translation = {
         required: '必需的',
         resultTip: '這是生成的結果。如果您不滿意，可以回去修改您的提示。',
       },
+      reasoningFormat: {
+        title: '啟用推理標籤分離',
+        tooltip: '從 think 標籤中提取內容並將其存儲在 reasoning_content 欄位中。',
+        tagged: '保持思考標籤',
+        separated: '分開思考標籤',
+      },
     },
     knowledgeRetrieval: {
       queryVariable: '查詢變量',