The AI-native engine for building intelligent, action-oriented systems.
HUF sits at the intersection of knowledge, automation, and tools—enabling AI to understand business context and execute real work safely, auditably, and at scale.
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Note: HUF is actively being migrated from an existing implementation. Not recommended for production use at this stage.
AI adoption inside organizations is fragmented:
- Knowledge lives in too many places — scattered across docs, databases, and people's heads
- Automation is rigid and rule-based — breaks on edge cases, requires constant maintenance
- AI tools operate in isolation — each team rebuilds similar assistants
- Costs, behavior, and risk are hard to control — no visibility, no governance
HUF exists to centralize intelligence and execution into a single engine—so AI can be trusted to operate inside real business systems.
HUF is designed to be the core AI layer inside an organization or product, not a surface-level chatbot or a single-purpose assistant.
One engine. Multiple ways to use it.
| Capability | What it enables |
|---|---|
| Multi-Provider AI | Connect to OpenAI, Anthropic, Google, Mistral, and 100+ providers through a unified interface |
| Intelligent Tools | Give AI the ability to read, write, and act on your business data |
| Knowledge Grounding | RAG-powered context from your docs, files, and URLs |
| Event-Driven Execution | Trigger agents on document events, schedules, or webhooks |
| Visual Workflow Builder | Design complex automations with drag-and-drop flows (WIP) |
| Full Auditability | Every run, every tool call, every token—logged and traceable |
| Cost Control | Track usage and spending across models and teams |
Use HUF as the backend AI engine for products that need intelligence, automation, and integration.
Ideal for:
- AI-first startups building on Frappe/ERPNext
- SaaS products adding AI capabilities
- Platforms that need agent orchestration, cost control, and auditability
HUF handles reasoning, knowledge, tool execution, and governance—so product teams can focus on user experience.
Use HUF to power internal AI experiences grounded in company knowledge.
Build:
- Internal chat systems that know your business
- Role-based assistants for Ops, HR, Sales, Support
- Knowledge discovery and employee onboarding tools
Replace disconnected internal AI tools with a single, governed intelligence layer.
Use HUF to build AI-driven workflows that reason and act across systems.
Suited for:
- Multi-step processes that span departments
- Cross-tool automation with conditional logic
- Intelligent approvals, routing, and escalations
Unlike traditional automation, HUF adapts to context instead of breaking on edge cases.
Use HUF to embed AI directly into products without building custom infrastructure.
Enable:
- In-app copilots and assistants
- Customer-facing AI features
- Vertical AI capabilities with clear permission boundaries
HUF provides a shared AI backend with cost, behavior, and access controls built in.
Use HUF as a governed control layer for AI across the organization.
Critical for:
- Cost management and budget allocation
- Auditability and compliance requirements
- Tool and model governance
- Responsible AI deployment at scale
Give leadership visibility and control without slowing down teams.
Create AI agents with custom instructions, connect them to any LLM provider, and equip them with tools to take action:
- CRUD Operations — Read, create, update, delete documents
- Custom Functions — Connect any Python function as a tool
- HTTP Requests — Call external APIs and services
- Agent Chaining — Agents can trigger other agents
- MCP Integration — Connect to external tool providers (Gmail, GitHub, Slack, etc.)
Ground AI responses in your actual business knowledge:
- Multiple Input Types — Files, text, URLs
- Automatic Chunking — Intelligent text segmentation
- Fast Search — BM25-powered retrieval via SQLite FTS5
- Flexible Injection — Mandatory context or on-demand search
Run agents automatically based on events:
- Document Events —
after_insert,on_submit,on_cancel, and more - Schedules — Hourly, daily, weekly, monthly, yearly intervals
- Webhooks — HTTP endpoints with authentication
- Conditional Logic — Python expressions to control execution
Design complex workflows with a modern React-based interface:
- Drag-and-Drop Canvas — Build flows visually
- Node Types — Triggers, actions, utilities, conditions
- Real-Time Editing — See changes instantly
- App Integrations — Gmail, Calendar, Slack, Notion, HubSpot
Full visibility into what your AI is doing:
- Agent Runs — Status, prompt, response, token usage, cost
- Conversations — Complete chat history with context
- Tool Calls — Every tool invocation with arguments and results
- Feedback System — Capture user ratings for quality improvement
git clone https://github.com/tridz-dev/huf.git
cd huf/docker
docker compose upOpen http://localhost:8000 and login:
- User: Administrator
- Password: admin
bench get-app git@github.com:tridz-dev/huf.git
bench install-app huf
bench setup requirements
bench restart┌─────────────────────────────────────────────────────────────────┐
│ HUF Engine │
├─────────────────────────────────────────────────────────────────┤
│ │
│ ┌──────────────┐ ┌──────────────┐ ┌────────────────┐ │
│ │ Agents │ │ Knowledge │ │ Triggers │ │
│ │ │ │ │ │ │ │
│ │ Instructions │ │ RAG/FTS5 │ │ Events │ │
│ │ Tools │ │ Chunking │ │ Schedules │ │
│ │ Parameters │ │ Retrieval │ │ Webhooks (WIP) │ │
│ └──────┬───────┘ └──────┬───────┘ └──────┬─────────┘ │
│ │ │ │ │
│ └────────────────┬┴─────────────────┘ │
│ │ │
│ ┌───────────────────────▼───────────────────────────────────┐ │
│ │ Execution Layer │ │
│ │ │ │
│ │ LiteLLM (100+ providers) │ Tool System │ MCP Client │ │
│ └───────────────────────────────────────────────────────────┘ │
│ │
│ ┌────────────────────────────────────────────────────────────┐ │
│ │ Observability │ │
│ │ │ │
│ │ Runs │ Conversations │ Messages │ Tool Calls │ Costs │ │
│ └────────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────┘
│
┌─────────────────────┼─────────────────────┐
▼ ▼ ▼
┌─────────┐ ┌─────────┐ ┌───────────────┐
│ Chat │ │ API │ │ Flows │
│ UI │ │ Endpoint│ │ Builder (WIP) │
└─────────┘ └─────────┘ └───────────────┘
| Layer | Technology |
|---|---|
| Backend | Frappe Framework, Python 3.10+ |
| AI Integration | LiteLLM |
| Knowledge | SQLite FTS5 (LlamaIndex) & multiple VectorDBs WIP. |
| Frontend | React 18, TypeScript, Tailwind CSS |
| Flow Builder | React Flow / XYFlow |
| Database | MariaDB |
- Full Documentation — Guides, tutorials, and API reference
- AGENTS.md — Technical context for AI agents. Adopts the agents.md standard.
- CLAUDE.md — Defines coding standards, review criteria, and project-specific rules. Claude reads this file during runs and follows your conventions.
MIT License — see LICENSE for details.
Built for teams who want AI that actually works.