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LitMind Discussion Generator — 基于证据的 Discussion 草稿生成
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Based on SOC occupation classification
| name | litmind-discussion |
| description | LitMind Discussion Generator — 基于证据的 Discussion 草稿生成 |
输入研究主题和结果，自动检索 Knowledge Base 中的文献证据，生成具有科学依据和可追溯引用的 Discussion 草稿。
| Section | 内容 |
|---|---|
| Main Finding Interpretation | 主要发现解读 |
| Supporting Evidence | 支持证据对比 |
| Contradictory Evidence | 矛盾证据讨论 |
| Potential Mechanisms | 潜在机制解释 |
| Practical Implications | 实践意义 |
| Study Limitations | 研究局限性 |
| Future Directions | 未来方向 |
from litmind_knowledge.service import KnowledgeBase
from litmind_evidence import EvidenceFinderService
from litmind_discussion import DiscussionGeneratorService, DiscussionInput
from litmind_analyzer.providers import AnthropicProvider
kb = KnowledgeBase()
provider = AnthropicProvider()
ev_service = EvidenceFinderService(kb=kb, llm_provider=provider)
service = DiscussionGeneratorService(evidence_service=ev_service, llm_provider=provider)
inp = DiscussionInput(studyTopic="Footwear stiffness", results=["High stiffness increased MTP ROM"])
result = service.generate_discussion(inp)
print(result.discussionDraft)
print("Citations:", len(result.citations))
from litmind_knowledge.service import KnowledgeBase
from litmind_evidence import EvidenceFinderService
from litmind_discussion import DiscussionGeneratorService, DiscussionInput
from litmind_analyzer.providers import AnthropicProvider
kb = KnowledgeBase()
provider = AnthropicProvider()
ev_service = EvidenceFinderService(kb=kb, llm_provider=provider)
service = DiscussionGeneratorService(evidence_service=ev_service, llm_provider=provider)
inp = DiscussionInput(studyTopic="Footwear stiffness", results=["High stiffness increased MTP ROM"])
result = service.generate_discussion(inp)
print(result.discussionDraft)
print(f"Citations: {len(result.citations)}")
所有引用均来自 Knowledge Base，LLM 只能引用白名单内的 paperId。
LitMind Paper Analyzer — 将论文全文转为结构化科研知识 (PaperAnalysis)
LitMind Evidence Finder — 科研证据检索与归纳系统
LitMind Knowledge Base — 存储、索引、检索、更新科研知识库
LitMind Paper Parser — 从 PDF 读取全文、清洗噪声、识别标准章节，输出结构化 PaperContent
LitMind Review Generator — 基于科研知识库的综述生成系统
LitMind Zotero Connector — 从 Zotero 本地数据库导出全部文献（期刊/学位论文/会议论文等）+ 独立PDF附件为统一 PaperMetadata 模型