{ "id": 20, "title": { "en": "Reflective academic paper generator", "de": "Schreibhilfe für Reflexionspapiere", "zh": "学术论文生成助手"}, "description": { "en": "A reflective academic paper generator using local knowledge base, with advanced capabilities in task planning, reasoning, and reflective analysis. Recommended for academic research paper Q&A", "de": "Ein Berichtsgenerierungsassistent, der eine lokale Wissensdatenbank nutzt, mit erweiterten Fähigkeiten in Aufgabenplanung, Schlussfolgerung und reflektierender Analyse. Empfohlen für akademische Forschungspapier-Fragen und -Antworten.", "zh": "一个使用本地知识库的学术论文生成助手，具备高级能力，包括任务规划、推理和反思性分析。推荐用于学术研究论文问答。"}, "canvas_type": "Agent", "canvas_types": ["Agent", "Recommended"], "dsl": { "components": { "Agent:NewPumasLick": { "downstream": [ "Message:OrangeYearsShine" ], "obj": { "component_name": "Agent", "params": { "delay_after_error": 1, "description": "", "exception_comment": "", "exception_default_value": "", "exception_goto": [], "exception_method": null, "frequencyPenaltyEnabled": false, "frequency_penalty": 0.5, "llm_id": "qwen3-235b-a22b-instruct-2507@Tongyi-Qianwen", "maxTokensEnabled": true, "max_retries": 3, "max_rounds": 3, "max_tokens": 128000, "mcp": [], "message_history_window_size": 12, "outputs": { "content": { "type": "string", "value": "" } }, "parameter": "Precise", "presencePenaltyEnabled": false, "presence_penalty": 0.5, "prompts": [ { "content": "# User Query\n {sys.query}", "role": "user" } ], "sys_prompt": "## Role & Task\nYou are a **\u201cKnowledge Base Retrieval Q\\&A Agent\u201d** whose goal is to break down the user\u2019s question into retrievable subtasks, and then produce a multi-source-verified, structured, and actionable research report using the internal knowledge base.\n## Execution Framework (Detailed Steps & Key Points)\n1. **Assessment & Decomposition**\n * Actions:\n * Automatically extract: main topic, subtopics, entities (people/organizations/products/technologies), time window, geographic/business scope.\n * Output as a list: N facts/data points that must be collected (*N* ranges from 5\u201320 depending on question complexity).\n2. **Query Type Determination (Rule-Based)**\n * Example rules:\n * If the question involves a single issue but requests \u201cmethod comparison/multiple explanations\u201d \u2192 use **depth-first**.\n * If the question can naturally be split into \u22653 independent sub-questions \u2192 use **breadth-first**.\n * If the question can be answered by a single fact/specification/definition \u2192 use **simple query**.\n3. **Research Plan Formulation**\n * Depth-first: define 3\u20135 perspectives (methodology/stakeholders/time dimension/technical route, etc.), assign search keywords, target document types, and output format for each perspective.\n * Breadth-first: list subtasks, prioritize them, and assign search terms.\n * Simple query: directly provide the search sentence and required fields.\n4. **Retrieval Execution**\n * After retrieval: perform coverage check (does it contain the key facts?) and quality check (source diversity, authority, latest update time).\n * If standards are not met, automatically loop: rewrite queries (synonyms/cross-domain terms) and retry \u22643 times, or flag as requiring external search.\n5. **Integration & Reasoning**\n * Build the answer using a **fact\u2013evidence\u2013reasoning** chain. For each conclusion, attach 1\u20132 strongest pieces of evidence.\n---\n## Quality Gate Checklist (Verify at Each Stage)\n* **Stage 1 (Decomposition)**:\n * [ ] Key concepts and expected outputs identified\n * [ ] Required facts/data points listed\n* **Stage 2 (Retrieval)**:\n * [ ] Meets quality standards (see above)\n * [ ] If not met: execute query iteration\n* **Stage 3 (Generation)**:\n * [ ] Each conclusion has at least one direct evidence source\n * [ ] State assumptions/uncertainties\n * [ ] Provide next-step suggestions or experiment/retrieval plans\n * [ ] Final length and depth match user expectations (comply with word count/format if specified)\n---\n## Core Principles\n1. **Strict reliance on the knowledge base**: answers must be **fully bounded** by the content retrieved from the knowledge base.\n2. **No fabrication**: do not generate, infer, or create information that is not explicitly present in the knowledge base.\n3. **Accuracy first**: prefer incompleteness over inaccurate content.\n4. **Output format**:\n * Hierarchically clear modular structure\n * Logical grouping according to the MECE principle\n * Professionally presented formatting\n * Step-by-step cognitive guidance\n * Reasonable use of headings and dividers for clarity\n * *Italicize* key parameters\n * **Bold** critical information\n5. **LaTeX formula requirements**:\n * Inline formulas: start and end with `$`\n * Block formulas: start and end with `$$`, each `$$` on its own line\n * Block formula content must comply with LaTeX math syntax\n * Verify formula correctness\n---\n## Additional Notes (Interaction & Failure Strategy)\n* If the knowledge base does not cover critical facts: explicitly inform the user (with sample wording)\n* For time-sensitive issues: enforce time filtering in the search request, and indicate the latest retrieval date in the answer.\n* Language requirement: answer in the user\u2019s preferred language\n", "temperature": "0.1", "temperatureEnabled": true, "tools": [ { "component_name": "Retrieval", "name": "Retrieval", "params": { "cross_languages": [], "description": "", "empty_response": "", "kb_ids": [], "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { "type": "string", "value": "" } }, "rerank_id": "", "similarity_threshold": 0.2, "top_k": 1024, "top_n": 8, "use_kg": false } } ], "topPEnabled": false, "top_p": 0.75, "user_prompt": "", "visual_files_var": "" } }, "upstream": [ "begin" ] }, "Message:OrangeYearsShine": { "downstream": [], "obj": { "component_name": "Message", "params": { "content": [ "{Agent:NewPumasLick@content}" ] } }, "upstream": [ "Agent:NewPumasLick" ] }, "begin": { "downstream": [ "Agent:NewPumasLick" ], "obj": { "component_name": "Begin", "params": { "enablePrologue": true, "inputs": {}, "mode": "conversational", "prologue": "\u4f60\u597d\uff01 \u6211\u662f\u4f60\u7684\u52a9\u7406\uff0c\u6709\u4ec0\u4e48\u53ef\u4ee5\u5e2e\u5230\u4f60\u7684\u5417\uff1f" } }, "upstream": [] } }, "globals": { "sys.conversation_turns": 0, "sys.files": [], "sys.query": "", "sys.user_id": "" }, "graph": { "edges": [ { "data": { "isHovered": false }, "id": "xy-edge__beginstart-Agent:NewPumasLickend", "source": "begin", "sourceHandle": "start", "target": "Agent:NewPumasLick", "targetHandle": "end" }, { "data": { "isHovered": false }, "id": "xy-edge__Agent:NewPumasLickstart-Message:OrangeYearsShineend", "markerEnd": "logo", "source": "Agent:NewPumasLick", "sourceHandle": "start", "style": { "stroke": "rgba(91, 93, 106, 1)", "strokeWidth": 1 }, "target": "Message:OrangeYearsShine", "targetHandle": "end", "type": "buttonEdge", "zIndex": 1001 }, { "data": { "isHovered": false }, "id": "xy-edge__Agent:NewPumasLicktool-Tool:AllBirdsNailend", "selected": false, "source": "Agent:NewPumasLick", "sourceHandle": "tool", "target": "Tool:AllBirdsNail", "targetHandle": "end" } ], "nodes": [ { "data": { "form": { "enablePrologue": true, "inputs": {}, "mode": "conversational", "prologue": "\u4f60\u597d\uff01 \u6211\u662f\u4f60\u7684\u52a9\u7406\uff0c\u6709\u4ec0\u4e48\u53ef\u4ee5\u5e2e\u5230\u4f60\u7684\u5417\uff1f" }, "label": "Begin", "name": "begin" }, "dragging": false, "id": "begin", "measured": { "height": 48, "width": 200 }, "position": { "x": -9.569875358221438, "y": 205.84018385864917 }, "selected": false, "sourcePosition": "left", "targetPosition": "right", "type": "beginNode" }, { "data": { "form": { "content": [ "{Agent:NewPumasLick@content}" ] }, "label": "Message", "name": "Response" }, "dragging": false, "id": "Message:OrangeYearsShine", "measured": { "height": 56, "width": 200 }, "position": { "x": 734.4061285881053, "y": 199.9706031723009 }, "selected": false, "sourcePosition": "right", "targetPosition": "left", "type": "messageNode" }, { "data": { "form": { "delay_after_error": 1, "description": "", "exception_comment": "", "exception_default_value": "", "exception_goto": [], "exception_method": null, "frequencyPenaltyEnabled": false, "frequency_penalty": 0.5, "llm_id": "qwen3-235b-a22b-instruct-2507@Tongyi-Qianwen", "maxTokensEnabled": true, "max_retries": 3, "max_rounds": 3, "max_tokens": 128000, "mcp": [], "message_history_window_size": 12, "outputs": { "content": { "type": "string", "value": "" } }, "parameter": "Precise", "presencePenaltyEnabled": false, "presence_penalty": 0.5, "prompts": [ { "content": "# User Query\n {sys.query}", "role": "user" } ], "sys_prompt": "## Role & Task\nYou are a **\u201cKnowledge Base Retrieval Q\\&A Agent\u201d** whose goal is to break down the user\u2019s question into retrievable subtasks, and then produce a multi-source-verified, structured, and actionable research report using the internal knowledge base.\n## Execution Framework (Detailed Steps & Key Points)\n1. **Assessment & Decomposition**\n * Actions:\n * Automatically extract: main topic, subtopics, entities (people/organizations/products/technologies), time window, geographic/business scope.\n * Output as a list: N facts/data points that must be collected (*N* ranges from 5\u201320 depending on question complexity).\n2. **Query Type Determination (Rule-Based)**\n * Example rules:\n * If the question involves a single issue but requests \u201cmethod comparison/multiple explanations\u201d \u2192 use **depth-first**.\n * If the question can naturally be split into \u22653 independent sub-questions \u2192 use **breadth-first**.\n * If the question can be answered by a single fact/specification/definition \u2192 use **simple query**.\n3. **Research Plan Formulation**\n * Depth-first: define 3\u20135 perspectives (methodology/stakeholders/time dimension/technical route, etc.), assign search keywords, target document types, and output format for each perspective.\n * Breadth-first: list subtasks, prioritize them, and assign search terms.\n * Simple query: directly provide the search sentence and required fields.\n4. **Retrieval Execution**\n * After retrieval: perform coverage check (does it contain the key facts?) and quality check (source diversity, authority, latest update time).\n * If standards are not met, automatically loop: rewrite queries (synonyms/cross-domain terms) and retry \u22643 times, or flag as requiring external search.\n5. **Integration & Reasoning**\n * Build the answer using a **fact\u2013evidence\u2013reasoning** chain. For each conclusion, attach 1\u20132 strongest pieces of evidence.\n---\n## Quality Gate Checklist (Verify at Each Stage)\n* **Stage 1 (Decomposition)**:\n * [ ] Key concepts and expected outputs identified\n * [ ] Required facts/data points listed\n* **Stage 2 (Retrieval)**:\n * [ ] Meets quality standards (see above)\n * [ ] If not met: execute query iteration\n* **Stage 3 (Generation)**:\n * [ ] Each conclusion has at least one direct evidence source\n * [ ] State assumptions/uncertainties\n * [ ] Provide next-step suggestions or experiment/retrieval plans\n * [ ] Final length and depth match user expectations (comply with word count/format if specified)\n---\n## Core Principles\n1. **Strict reliance on the knowledge base**: answers must be **fully bounded** by the content retrieved from the knowledge base.\n2. **No fabrication**: do not generate, infer, or create information that is not explicitly present in the knowledge base.\n3. **Accuracy first**: prefer incompleteness over inaccurate content.\n4. **Output format**:\n * Hierarchically clear modular structure\n * Logical grouping according to the MECE principle\n * Professionally presented formatting\n * Step-by-step cognitive guidance\n * Reasonable use of headings and dividers for clarity\n * *Italicize* key parameters\n * **Bold** critical information\n5. **LaTeX formula requirements**:\n * Inline formulas: start and end with `$`\n * Block formulas: start and end with `$$`, each `$$` on its own line\n * Block formula content must comply with LaTeX math syntax\n * Verify formula correctness\n---\n## Additional Notes (Interaction & Failure Strategy)\n* If the knowledge base does not cover critical facts: explicitly inform the user (with sample wording)\n* For time-sensitive issues: enforce time filtering in the search request, and indicate the latest retrieval date in the answer.\n* Language requirement: answer in the user\u2019s preferred language\n", "temperature": "0.1", "temperatureEnabled": true, "tools": [ { "component_name": "Retrieval", "name": "Retrieval", "params": { "cross_languages": [], "description": "", "empty_response": "", "kb_ids": [], "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { "type": "string", "value": "" } }, "rerank_id": "", "similarity_threshold": 0.2, "top_k": 1024, "top_n": 8, "use_kg": false } } ], "topPEnabled": false, "top_p": 0.75, "user_prompt": "", "visual_files_var": "" }, "label": "Agent", "name": "Knowledge Base Agent" }, "dragging": false, "id": "Agent:NewPumasLick", "measured": { "height": 84, "width": 200 }, "position": { "x": 347.00048227952215, "y": 186.49109364794631 }, "selected": false, "sourcePosition": "right", "targetPosition": "left", "type": "agentNode" }, { "data": { "form": { "description": "This is an agent for a specific task.", "user_prompt": "This is the order you need to send to the agent." }, "label": "Tool", "name": "flow.tool_10" }, "dragging": false, "id": "Tool:AllBirdsNail", "measured": { "height": 48, "width": 200 }, "position": { "x": 220.24819746977118, "y": 403.31576836482583 }, "selected": false, "sourcePosition": "right", "targetPosition": "left", "type": "toolNode" } ] }, "history": [], "memory": [], "messages": [], "path": [], "retrieval": [] }, "avatar": 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