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Add complete Pipeline DSL system including:
- Rust backend (zclaw-pipeline crate) with parser, executor, and state management
- Frontend components: PipelinesPanel, PipelineResultPreview, ClassroomPreviewer
- Pipeline recommender for Agent conversation integration
- 5 pipeline templates: education, marketing, legal, research, productivity
- Documentation for Pipeline DSL architecture
Pipeline DSL enables declarative workflow definitions with:
- YAML-based configuration
- Expression resolution (${inputs.topic}, ${steps.step1.output})
- LLM integration, parallel execution, file export
- Agent smart recommendations in conversations
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
337 lines
9.7 KiB
YAML
337 lines
9.7 KiB
YAML
# ZCLAW Pipeline - Literature Review
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# 文献综述：输入研究主题，自动检索文献并生成综述报告
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apiVersion: zclaw/v1
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kind: Pipeline
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metadata:
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name: literature-review
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displayName: 文献综述生成器
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category: research
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description: 输入研究主题，自动检索相关文献、分析关键观点、生成结构化综述报告
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tags:
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- 研究
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- 文献
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- 学术
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- 综述
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icon: 📚
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author: ZCLAW
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version: 1.0.0
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spec:
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# 输入参数定义
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inputs:
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- name: research_topic
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type: string
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required: true
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label: 研究主题
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placeholder: 例如：人工智能在医疗诊断中的应用
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validation:
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min_length: 5
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max_length: 200
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- name: research_field
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type: select
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required: false
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label: 研究领域
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default: 计算机科学
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options:
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- 计算机科学
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- 医学
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- 生物学
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- 物理学
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- 化学
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- 经济学
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- 心理学
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- 社会学
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- 教育学
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- 其他
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- name: review_depth
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type: select
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required: false
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label: 综述深度
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default: 标准
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options:
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- 快速概览
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- 标准
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- 深度分析
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- name: time_range
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type: select
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required: false
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label: 文献时间范围
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default: 近5年
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options:
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- 近1年
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- 近3年
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- 近5年
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- 近10年
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- 全部
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- name: language_preference
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type: select
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required: false
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label: 语言偏好
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default: 中英混合
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options:
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- 仅中文
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- 仅英文
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- 中英混合
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- name: export_formats
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type: multi-select
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required: false
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label: 导出格式
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default: [html, markdown]
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options:
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- html
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- markdown
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- pdf
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# 执行步骤
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steps:
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# Step 1: 解析研究主题
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- id: parse_topic
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description: 解析研究主题，提取关键词
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action:
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type: llm_generate
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template: |
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作为学术研究专家，请分析以下研究主题，提取关键概念和搜索词。
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研究主题: {{research_topic}}
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研究领域: {{research_field}}
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请提取以下信息：
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1. 核心概念（3-5个）
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2. 相关关键词（10-15个）
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3. 同义词和变体
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4. 相关研究领域
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5. 建议的搜索策略
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以 JSON 格式输出：
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{
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"core_concepts": ["概念1", "概念2"],
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"keywords": ["关键词1", "关键词2"],
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"synonyms": {
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"概念1": ["同义词1", "同义词2"]
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},
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"related_fields": ["领域1", "领域2"],
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"search_strategy": "搜索策略说明"
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}
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input:
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research_topic: ${inputs.research_topic}
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research_field: ${inputs.research_field}
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json_mode: true
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temperature: 0.3
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max_tokens: 2000
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# Step 2: 生成文献搜索查询
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- id: generate_queries
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description: 生成学术搜索查询
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action:
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type: llm_generate
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template: |
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基于以下关键词，生成用于学术数据库搜索的查询语句。
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核心概念: ${steps.parse_topic.output.core_concepts}
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关键词: ${steps.parse_topic.output.keywords}
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时间范围: {{time_range}}
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语言偏好: {{language_preference}}
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请生成适合以下数据库的搜索查询：
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1. Google Scholar
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2. PubMed (如果是医学/生物相关)
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3. IEEE Xplore (如果是工程/计算机相关)
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4. CNKI (中国知网)
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以 JSON 格式输出：
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{
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"queries": [
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{
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"database": "数据库名称",
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"query": "搜索查询语句",
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"expected_results": "预期结果描述"
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}
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],
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"inclusion_criteria": ["纳入标准1", "纳入标准2"],
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"exclusion_criteria": ["排除标准1", "排除标准2"]
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}
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input:
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parsed_topic: ${steps.parse_topic.output}
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time_range: ${inputs.time_range}
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language_preference: ${inputs.language_preference}
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json_mode: true
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temperature: 0.4
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max_tokens: 1500
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# Step 3: 分析研究趋势
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- id: analyze_trends
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description: 分析研究趋势和发展脉络
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action:
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type: llm_generate
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template: |
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基于以下研究主题，分析该领域的研究趋势。
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研究主题: {{research_topic}}
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核心概念: ${steps.parse_topic.output.core_concepts}
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综述深度: {{review_depth}}
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请分析以下方面：
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1. 研究历史脉络
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2. 主要研究方向
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3. 关键突破和里程碑
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4. 当前研究热点
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5. 未来发展趋势
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6. 主要挑战和争议
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以 JSON 格式输出：
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{
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"historical_development": {
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"early_stage": "早期发展阶段描述",
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"middle_stage": "中期发展阶段描述",
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"current_stage": "当前阶段描述"
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},
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"main_research_directions": [
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{
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"direction": "研究方向名称",
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"description": "方向描述",
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"key_contributors": ["主要贡献者"]
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}
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],
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"key_milestones": [
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{
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"year": "年份",
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"event": "里程碑事件",
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"significance": "意义"
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}
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],
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"current_hotspots": ["热点1", "热点2"],
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"future_trends": ["趋势1", "趋势2"],
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"challenges": ["挑战1", "挑战2"]
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}
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input:
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research_topic: ${inputs.research_topic}
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parsed_topic: ${steps.parse_topic.output}
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review_depth: ${inputs.review_depth}
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json_mode: true
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temperature: 0.5
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max_tokens: 3000
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# Step 4: 生成关键观点分析
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- id: analyze_key_points
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description: 分析领域关键观点和理论
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action:
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type: llm_generate
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template: |
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基于以下信息，分析该研究领域的核心观点和理论框架。
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研究主题: {{research_topic}}
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研究趋势: ${steps.analyze_trends.output}
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综述深度: {{review_depth}}
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请分析以下内容：
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1. 主要理论框架
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2. 核心观点和假说
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3. 研究方法论
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4. 主要争议和不同学派
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5. 共识和结论
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以 JSON 格式输出：
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{
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"theoretical_frameworks": [
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{
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"name": "理论名称",
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"proponents": ["提出者"],
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"core_concepts": ["核心概念"],
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"applications": ["应用领域"]
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}
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],
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"core_viewpoints": [
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{
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"viewpoint": "观点描述",
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"evidence": ["支持证据"],
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"counter_evidence": ["反对证据"]
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}
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],
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"methodologies": [
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{
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"method": "方法名称",
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"description": "方法描述",
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"advantages": ["优点"],
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"limitations": ["局限"]
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}
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],
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"debates": [
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{
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"topic": "争议话题",
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"positions": ["立场1", "立场2"],
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"current_status": "当前状态"
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}
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],
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"consensus": ["共识1", "共识2"]
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}
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input:
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research_topic: ${inputs.research_topic}
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trends: ${steps.analyze_trends.output}
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review_depth: ${inputs.review_depth}
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json_mode: true
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temperature: 0.6
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max_tokens: 4000
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# Step 5: 生成综述报告
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- id: generate_review
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description: 生成完整文献综述报告
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action:
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type: llm_generate
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template: |
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基于以上分析，生成一份完整的文献综述报告。
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报告应包含以下结构：
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1. 摘要
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2. 引言（研究背景、目的、意义）
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3. 研究方法（文献检索策略、筛选标准）
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4. 研究现状分析
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5. 主要研究发现
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6. 讨论与展望
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7. 结论
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8. 参考文献建议
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分析数据:
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- 主题解析: ${steps.parse_topic.output}
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- 搜索策略: ${steps.generate_queries.output}
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- 研究趋势: ${steps.analyze_trends.output}
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- 关键观点: ${steps.analyze_key_points.output}
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请生成结构化的综述内容。
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input:
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topic_analysis: ${steps.parse_topic.output}
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search_queries: ${steps.generate_queries.output}
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trends: ${steps.analyze_trends.output}
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key_points: ${steps.analyze_key_points.output}
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json_mode: true
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temperature: 0.7
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max_tokens: 5000
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# Step 6: 导出报告
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- id: export_review
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description: 导出综述报告
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action:
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type: file_export
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formats: ${inputs.export_formats}
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input: ${steps.generate_review.output}
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# 输出映射
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outputs:
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review_title: ${steps.generate_review.output.title}
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abstract: ${steps.generate_review.output.abstract}
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key_findings: ${steps.generate_review.output.key_findings}
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future_directions: ${steps.analyze_trends.output.future_trends}
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export_files: ${steps.export_review.output}
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# 错误处理
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on_error: stop
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# 超时设置
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timeout_secs: 300
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