9 个 · Agent 智能体 · 数据集
BISHENG 是面向下一代企业 AI 应用的开放 LLM devops 平台。强大且全面的功能包括：GenAI workflow、RAG、Agent、统一模型管理、评估、SFT、数据集管理、企业级系统管理、可观测性等。BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.
CSGHub 是 OpenCSG 团队开发的全新开源 LLM 管理平台，提供开源与本地化/SaaS 解决方案，功能对标 Hugging Face。兼容 Hugging Face Python SDK，全面掌控 LLM、数据集和 agent 的全生命周期。CSGHub is a brand-new open-source platform for managing LLMs, developed by the OpenCSG team. It offers both open-source and on-premise/SaaS solutions, with features comparable to Hugging Face. Gain full control over the lifecycle of LLMs, datasets, and agents, with Python SDK compatibility with Hugging Face. Join us! ⭐️
自托管 MCP 服务器，让你的 Obsidian/markdown 知识库可被任意 MCP 客户端检索——涵盖文本、PDF、Office 文档、图片与音频。基于类型化、可治理语料库的混合检索，5 万条笔记下仍可达亚秒级响应；文件保持纯 markdown。Self-hosted MCP server that makes your Obsidian/markdown vault searchable — text, PDFs, Office docs, images, audio — from any MCP client. Hybrid retrieval over a typed, governed corpus, sub-second at 50k notes; your files stay plain markdown.
研究语料骨架：配置驱动、自动校验的 Agent 文献综述流程Research corpus skeleton: config-driven, auto-validated agentic literature review (papers.yaml → README/stats/reports + CI + GitHub Pages)
音乐研究语料库：面向音乐生成、MIR、感知与认知、AI 音乐系统、评估的 agentic 文献综述 — 覆盖符号、音频、多模态与 agentic 方向Music research corpus: agentic literature review of music generation, MIR, perception & cognition, AI music systems, evaluation — symbolic, audio, multimodal, agentic
Composio AI 产品运营案例研究：可复现的研究 Agent 与 100 个应用集成的就绪数据集。Composio AI Product Ops case study: reproducible research agent and 100-app integration readiness dataset.
面向开源库的机器可读错误知识库——MCP server、REST API 与静态数据集，将每条错误消息映射到抛出该错误的源代码行。Machine-consumable error knowledge base for open-source libraries — MCP server, REST API, and static dataset mapping every error message to the source line that raised it
生产级 multi-agent 系统：接收研究问题、制定调查方案、从实时网络和私有文档语料中收集证据、对自身发现进行批判与事实核查，最终输出完整引用的 Markdown 报告。A production-grade multi-agent system that accepts a research question, plans an investigation, gathers evidence from the live web and a private document corpus, critiques and fact-checks its own findings, and delivers a fully cited Markdown report.
多源科学与文献及数据集搜索引擎，作为 MCP server 为 AI Agent 提供服务。Multi-source scientific literature and dataset search engine, built as an MCP server for AI agents.