Downloads · 30 days
0
Isushsbshsh/onyxagent-full-108
onyxagent-full-108 is a machine learning model from Isushsbshsh. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
<p align="center" <img src="docs/images/hero-banner.png" alt="OnyxAgent" width="800" / </p
Downloads · 30 days
0
Access
Public
Updated Jun 18, 2026
Repo size
—
Likes
0
Public
Click a slice to open those files.
.py3 MB · 46%
From the Hugging Face model README
OnyxAgent is an open-source super AI assistant that proactively plans tasks, controls your computer and external services, creates and runs Skills, builds a personal knowledge base and long-term memory, and grows alongside you through self-evolution — a reference implementation of Agent Harness engineering.
OnyxAgent is lightweight, easy to deploy, and built to extend. Plug in any major LLM provider and run it 24/7 on a personal computer or server, across the web and all major IM platforms.
<p align="center"> <a href="https://onyxagent-docs.vercel.app">📚 Docs</a> · <a href="https://huggingface.co/spaces/Isushsbshsh/OnyxAgent">🎮 Demo</a> · <a href="https://github.com/AkshayCoder48/OnyxAgent">🌐 GitHub</a> · <a href="https://github.com/AkshayCoder48/OnyxAgent#-quick-start">🚀 Quick Start</a> · <a href="https://github.com/AkshayCoder48/OnyxAgent#-architecture">📖 Architecture</a> · <a href="https://github.com/AkshayCoder48/OnyxAgent#-models">🤖 Models</a> </p> <br/>| Capability | Description |
|---|---|
| Planning | Decomposes complex tasks and executes them step by step, looping over tools until the goal is reached |
| Memory | Three-tier architecture (context → daily → core), automatic Deep Dream distillation, hybrid keyword + vector retrieval |
| Knowledge | Auto-curates structured knowledge into a Markdown wiki, builds an evolving knowledge graph with visual browsing |
| Evolution | Self-Evolution reviews conversations automatically to improve skills, follow up on unfinished tasks, and consolidate memory and knowledge, growing through everyday use |
| Skills | One-click install from Skill Hub, GitHub; or create custom skills via natural-language conversation |
| Tools | Built-in file I/O, terminal, browser, scheduler, memory retrieval, web search, and 10+ more tools — with native MCP support via terminal |
| Channels | Integrates with Web, WeChat, Feishu, DingTalk, WeCom, QQ, Official Accounts, Telegram, and Slack |
| Multimodal | First-class support for text, images, voice, and files — recognition, generation, and delivery |
| Models | Claude, GPT, Gemini, DeepSeek, Qwen, GLM, Kimi, MiniMax, Doubao, and more — swap providers from the Web console with one click |
OnyxAgent is a complete Agent Harness: messages flow in through Channels; the Agent Core plans and reasons over memory, knowledge, and the available tools and skills; Models generate the response, which is sent back through the originating channel. Every layer is decoupled and independently extensible.
<br/>git clone https://github.com/AkshayCoder48/OnyxAgent.git
cd OnyxAgent
pip install -r requirements.txt
python app.py
git clone https://github.com/AkshayCoder48/OnyxAgent.git
cd OnyxAgent
docker build -t onyxagent .
docker run -p 9899:9899 onyxagent
Once started, open http://localhost:9899 to access the Web console — your one-stop hub to chat with the Agent, configure models, connect channels, and install skills.
Deploying on a server? Set
web_hostto0.0.0.0inconfig.jsonto make the console reachable from outside, and setweb_passwordto protect it. Don't forget to open port9899in your firewall or security group.
After installation, manage the service with the Onyx CLI:
onyx start | stop | restart # service control
onyx status | logs # status and logs
onyx update # pull latest code and restart
onyx skill install <name> # install a skill
onyx install-browser # install browser automation
<br/>
OnyxAgent supports all mainstream LLM providers. Chat, vision, image generation, ASR/TTS, and embeddings can each be routed to a different vendor. Providers are configured directly in the Web console — no manual file editing required.
| Provider | Featured Models | Chat | Vision | Image Gen | ASR | TTS | Embedding |
|---|---|---|---|---|---|---|---|
| Claude | claude-fable-5 | ✅ | ✅ | ||||
| OpenAI | gpt-5.5, o-series | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Gemini | gemini-3.5-flash | ✅ | ✅ | ✅ | |||
| DeepSeek | deepseek-v4-flash / pro | ✅ | |||||
| Qwen | qwen3.7-plus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| GLM | glm-5.1, glm-5v-turbo | ✅ | ✅ | ✅ | ✅ | ||
| Doubao | doubao-seed-2.0 series | ✅ | ✅ | ✅ | ✅ | ||
| Kimi | kimi-k2.6 | ✅ | ✅ | ||||
| MiniMax | MiniMax-M3 | ✅ | ✅ | ✅ | ✅ | ||
| ERNIE | ernie-5.1 | ✅ | ✅ | ||||
| MiMo | mimo-v2.5 / pro | ✅ | ✅ | ✅ | |||
| Custom | Local models / third-party proxy | ✅ |
A single Agent instance can serve multiple channels in parallel. Most channels can be onboarded right from the Web console.
| Channel | Text | Image | File | Voice | Group |
|---|---|---|---|---|---|
| Web Console (default) | ✅ | ✅ | ✅ | ✅ | |
| Telegram | ✅ | ✅ | ✅ | ✅ | ✅ |
| Slack | ✅ | ✅ | ✅ | ✅ | |
| Discord | ✅ | ✅ | ✅ | ✅ | |
| ✅ | ✅ | ✅ | ✅ | ||
| Feishu / Lark | ✅ | ✅ | ✅ | ✅ | ✅ |
| DingTalk | ✅ | ✅ | ✅ | ✅ | ✅ |
| WeCom Bot | ✅ | ✅ | ✅ | ✅ | ✅ |
| ✅ | ✅ | ✅ | ✅ | ||
| WeCom App | ✅ | ✅ | ✅ | ✅ | |
| WeChat Customer Service | ✅ | ✅ | ✅ | ✅ | |
| WeChat Official Account | ✅ | ✅ | ✅ |
The Web console is the default channel and the unified entry point to configure models, channels, skills, memory, and more.
<br/>Long-term memory uses a three-tier architecture: conversation context (short-term) → daily memory (mid-term) → MEMORY.md (long-term). A nightly Deep Dream pass distills scattered memories into refined long-term entries and a narrative journal.
Personal knowledge base complements the time-ordered memory by organizing structured knowledge by topic. The Agent automatically curates valuable information from conversations, maintains cross-references and indexes, and the Web console offers an interactive knowledge-graph view.
<br/>Tools are atomic capabilities the Agent uses to interact with system resources. Skills are higher-level workflows defined by a manifest file that compose multiple tools to accomplish complex tasks.
Built-in tools cover file I/O (read / write / edit / ls), terminal (bash), file sending (send), memory retrieval (memory), environment variables (env_config), web fetching (web_fetch), scheduling (scheduler), web search (web_search), vision (vision), and browser automation (browser).
MCP protocol integrates the open ecosystem of Model Context Protocol servers. Configure MCP servers via the terminal using mcp.json — supports stdio / SSE transports, hot reload, and zero-code integration.
skill-creator; turn any workflow or third-party API into a reusable skill/skill list # list installed skills
/skill search <keyword> # search the marketplace
/skill install <name> # one-click install
<br/>
All kinds of contributions are welcome — new features, bug fixes, performance improvements, docs, or sharing your own skills on the Skill Hub. See CONTRIBUTING.md to get started, then open an Issue to discuss or send a PR directly.
⭐ Star the project to show your support, and Watch → Custom → Releases to get notified of new versions. PRs and Issues are always welcome.
<br/>This project is a rebranded fork of CowAgent (previously chatgpt-on-wechat) and is now officially OnyxAgent. All CLI commands use the onyx prefix, and the primary color scheme has been changed from green to rose/red.
Clone URL: https://github.com/AkshayCoder48/OnyxAgent.git