litmind-discussion

name	litmind-discussion
description	LitMind Discussion Generator — 基于证据的 Discussion 草稿生成

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

1. 解析用户输入的研究结果
2. Evidence Finder 检索支持/反对证据
3. DiscussionComposer 逐步生成 7 个 Section
4. 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。