想用 AI 管理整个科研流程？SciForge 把论文、代码、数据整合成可追溯的工作状态，还帮你做基因发现和蛋白质设计，开源可玩。
arXiv 论文提出 SciForge，一个专为科学研究设计的 AI 原生多模态工作台。该工作台基于五个核心理念构建：目标导向的决策治理、先翻译后推理的多模态处理、可审计的证据链、协作式团队科学以及实际应用场景。论文通过八个端到端用户案例验证，包括基因发现、从头蛋白质设计、分子优化等旗舰演示。SciForge 目前为桌面应用，已开源在 GitHub 上。
SciForge: An AI-Native, Multimodal Workbench for Scientific Discovery
Scientific work increasingly spans heterogeneous artifacts -- papers, code, datasets, scientific file formats, model outputs, figures, manuscripts, and team decisions -- yet general-purpose AI assistants rarely preserve these objects as a coherent, auditable research state. We present SciForge, a multimodal research-native AI workbench that reserves the graphical interface for human judgment while search, parsing, model routing, workflow execution, plotting, writing, and presentation generation run as modular agent-accessible services. SciForge is built around five pillars: (i) \emph{goal-scoped scientific decision governance} for \textbf{goal-oriented} research, with review gates and shared review surfaces; (ii) \emph{translate-then-reason} for \textbf{multimodal} input, routing scientific objects through domain translators before the agent reasons; (iii) \emph{evidence governance} for \textbf{auditable} traceability, linking claims to provenance chains and audit findings; (iv) \emph{collaborative team science} for \textbf{collaborative} research, enabling multi-role decision governance, with shared team workspaces planned for future releases; and (v) \emph{real-world application scenarios} for \textbf{practical} impact, demonstrated through eight end-to-end user cases, with flagship demonstrations including multi-day agentic research sprints for gene discovery, AI-guided de novo protein design, molecular optimization, and genome-to-BGC discovery. The system combines a thin interaction layer, contextual research capability patterns, an Agent Runtime and Workflow Engine, an Evidence-DAG audit sidecar and a Scientific Model Router. SciForge currently runs as a desktop application, with mobile supervision support; future releases will deepen team collaboration. The system is open-source and available at https://github.com/AGI4Sci/SciForge