meishiwhy LitMind Discussion Generator
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。
工作流程
- 解析用户输入的研究结果
- Evidence Finder 检索支持/反对证据
- DiscussionComposer 逐步生成 7 个 Section
- CitationManager 确保所有论述可追溯
输出结构
| 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 |
调用方式
Python API
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)}")
引用安全
所有引用均来自 Knowledge Base，LLM 只能引用白名单内的 paperId。