# Chatflow that exercises separated-mode reasoning (PR #37460): the LLM node sets # reasoning_format=separated, so the server strips ... from the # answer and streams the chain-of-thought on the out-of-band `reasoning_chunk` # channel instead. The system prompt forces a block, so the separated # path triggers with any chat model — no dedicated reasoning model required. # # NOTE: the LLM node leaves model.provider/name empty and relies on the target # workspace's configured default chat model. The run-app-reasoning E2E suite is # gated on DIFY_E2E_REASONING_APP_ID, so it is skipped unless a server with a # working model is wired up. app: description: e2e-test reasoning (separated mode) icon: 🧠 icon_background: '#FFEAD5' icon_type: emoji mode: advanced-chat name: reasoning-bot use_icon_as_answer_icon: false dependencies: [] kind: app version: 0.6.0 workflow: conversation_variables: [] environment_variables: [] features: file_upload: {} opening_statement: '' retriever_resource: enabled: true sensitive_word_avoidance: enabled: false speech_to_text: enabled: false suggested_questions: [] suggested_questions_after_answer: enabled: false text_to_speech: enabled: false language: '' voice: '' graph: edges: - id: start-llm source: '1755189262236' sourceHandle: source target: llm targetHandle: target - id: llm-answer source: llm sourceHandle: source target: answer targetHandle: target nodes: - data: desc: '' title: Start type: start variables: [] id: '1755189262236' position: x: 80 y: 282 sourcePosition: right targetPosition: left type: custom - data: context: enabled: false variable_selector: [] desc: '' memory: query_prompt_template: '{{#sys.query#}}' window: enabled: false size: 10 model: completion_params: temperature: 0.7 mode: chat name: '' provider: '' prompt_template: - role: system text: >- You are a helpful assistant. Always reason step by step INSIDE a single ... block first, then write the final answer AFTER the closing tag. The final answer must not contain any tags. reasoning_format: separated selected: false title: LLM type: llm variables: [] vision: enabled: false id: llm position: x: 380 y: 282 sourcePosition: right targetPosition: left type: custom - data: answer: '{{#llm.text#}}' desc: '' title: Answer type: answer variables: [] id: answer position: x: 680 y: 282 sourcePosition: right targetPosition: left type: custom viewport: x: 0 y: 0 zoom: 1 rag_pipeline_variables: []