知源 Agent：可接聊天应用的桌面代理

Open-source desktop AI agent: built-in free model, local GGUF models via llama.cpp, dispatch tasks from WeChat/Feishu/DingTalk. Files, br…

ZhiYuan Agent The open-source, local-first desktop AI agent — start free with a built-in model, run GGUF models locally, and assign tasks from WeChat, Feishu or DingTalk. Repo: rongxinzy/RongxinAI · Product: ZhiYuan Agent · Site: rongxzyai.com ⬇️ Download · Quick start · Build from source · 中文 Why ZhiYuan 🆓 Free to start — built-in ZhiYuan free model, no third-party API key needed (network required; limits shown in app). Bring your own provider anytime. 💻 Runs local models — browse a model marketplace, pick a GGUF model & quantization, tune context / GPU / threads, powered by llama.cpp runtime. 🛠️ Actually does the work — reads & writes files, runs commands, operates a browser through the Playwright connector; creates PPT, Word, PDF, Excel outputs. 💬 Lives in your chat apps — WeChat, WeCom, DingTalk, Feishu/Lark, QQ, Telegram, Discord; plus an email (IMAP/SMTP) skill. 🧩 Extensible — Experts, Skills and MCP; scheduled recurring tasks. 🔒 Local first — sessions, config and task metadata stored locally; approval modes for tool execution. Get started Download from the official website or GitHub Releases: Windows x64 lite, CPU, and CUDA installers (.exe); macOS Apple Silicon and Intel CPU builds (.dmg and .zip); Linux x64 CPU and CUDA packages (.deb and AppImage). Open the app and chat with the built-in free model — no API key required. Pick a project folder, describe your task, then follow progress and approve actions as it works. Developers iterating on the UI can start with bun run web:preview after installation (Node 24.x, Bun 1.4.0). See Developer quick start for setup and desktop development commands. The free model requires a network connection; availability and usage limits are shown in the app. For architectures or editions without a published installer, run from source. Use local models Open the local inference workspace, browse the model marketplace, and choose a GGUF model and quantization suited to your hardware. Install the model and start its service. Adjust context length, GPU allocation, threads, and other options, then use a running local model for agent tasks. Local models reduce reliance on cloud inference. Web search, model downloads, remote MCP services, and messaging channels still require their respective network services. Data and permissions Sessions, configuration, and task metadata are stored locally. The desktop execution environment accesses local files. When you use a cloud model or remote tool, the content needed for that request is sent to the corresponding service. Tool execution follows the permission mode chosen in the task composer. Ask before sensitive actions (the default) requests your approval before sensitive actions; Allow all runs tool calls without prompting, including irreversible ones. Progress and results remain visible in the workspace. How it compares ZhiYuan Manus Claude Desktop Cherry Studio Open Interpreter Assign tasks from WeChat / Feishu / DingTalk ✅ (also WeCom, QQ, email) ❌ (Slack, Gmail connectors) ❌ (Slack connector) ❌ ❌ Open-source desktop app ✅ AGPL-3.0 ❌ closed source ❌ closed source ✅ AGPL-3.0 ❌ Apache-2.0 terminal app; GUI is a separate project Installers for Windows, macOS, and Linux ✅ ❌ ✅ ✅ ❌ Built-in GGUF model market (no Ollama needed) ✅ llama.cpp runtime ❌ cloud only ❌ cloud only ❌ via Ollama / LM Studio ❌ via Ollama / LM Studio Free model + local model + fully open source ✅ all three ❌ free tier only (300 credits/day) ❌ free tier only ✅ CherryAI free (Qwen3-8B) + Ollama/LM Studio ❌ no built-in free model Agent: files + commands + browser ✅ ✅ ✅ paid plans only (Cowork) ? ✅ (browser via QA skill) ⭐ If ZhiYuan helps you, please star the repo — it helps more people find it and keeps us shipping. Star History Choose your workspace appearance ZhiYuan ships one registered theme plugin, Zenith, with paired light and dark appearances. Zenith is a premium futuristic design system: subtle glassmorphism, crisp typography, efficient spacing, and semantic tokens that define backgrounds, control recipes, and interaction states as a single package. In Settings → Appearance, pick the Zenith preview card (shown when only one plugin is bundled) and choose light, dark, or system mode. The preview follows the selected mode. Configurations that still reference removed theme IDs (Codex, Daming Fenghua, Changan Fengwu, Weiyang Jinshi, and earlier styles) resolve to Zenith automatically. To add another bundled theme later, start with the theme authoring guide and design specification. Theme plugins supply presentation data; shared components retain interaction and state ownership. Developer quick start Install Git, Node.js 24.x, and Bun 1.4.0, as pinned in package.json. Native dependencies may require Python and a C/C++ toolchain when prebuilt binaries are unavailable. See the contributing guide for Windows build requirements. git clone https://github.com/rongxinzy/RongxinAI.git ZhiYuanAgent cd ZhiYuanAgent bun install bun run web:preview Open the Vite URL in a browser to iterate on the renderer with hot reload, without starting Electron. To verify real desktop and IPC flows, run bun run electron:dev; it prepares the channel and memory runtimes, then starts Vite and Electron. Initial runtime preparation requires network access. To use local inference, download the inference runtime for your host separately: bun run llamacpp:runtime:download To develop the enterprise client from the same clone, run: bun run electron:dev:enterprise This builds enterprise/, loads this worktree's extension, and starts the same Vite/Electron development flow. Start AEP separately; the default endpoint is http://localhost:8080. Set ZHIYUAN_AEP_BASE_URL to use another endpoint and optionally ZHIYUAN_AGENT_CONTROL_BASE_URL for split deployments. The command generates development configuration under the ignored .work/enterprise-dev/ directory. To use an existing configuration file instead, set ZHIYUAN_ENTERPRISE_CONFIG_DEV_PATH. Packaged applications always use their bundle