Huf

bench get-app https://github.com/tridz-dev/huf

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# HUF **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. [**Documentation**](https://docs.huf.ai/) | [**Report Issue**](https://github.com/tridz-dev/huf/issues) | [**Discussions**](https://github.com/tridz-dev/huf/discussions) > ⚠️ **Security notice (LiteLLM):** LiteLLM (a HUF dependency) reported compromised PyPI releases `1.82.7` and `1.82.8` on **March 24, 2026**. HUF blocks these versions and shows an install-time alert if detected. Incident: https://github.com/BerriAI/litellm/issues/24518

> **Note:** HUF is actively being migrated from an existing implementation. Not recommended for production use at this stage. --- ## Why HUF Exists 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. --- ## What HUF Does 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 ### AI Infrastructure for Products 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. --- ### Internal Intelligence Platform 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. --- ### Automation & Orchestration Engine 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. --- ### Embedded AI Layer for SaaS 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. --- ### Enterprise AI Control Plane 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. --- ## Core Capabilities ### Agent System 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.) ### Knowledge Management 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 ### Trigger System 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 ### Visual Flow Builder 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 ### Observability 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 --- ## Quick Start ### Try with Docker ```bash git clone https://github.com/tridz-dev/huf.git cd huf/docker docker compose up ``` Open http://localhost:8000 and login: - **User:** Administrator - **Password:** admin ### Install on Existing Bench ```bash bench get-app git@github.com:tridz-dev/huf.git bench install-app huf bench setup requirements bench restart ``` --- ## Architecture at a Glance ``` ┌─────────────────────────────────────────────────────────────────┐ │ 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) │ └─────────┘ └─────────┘ └───────────────┘ ``` --- ## Tech Stack | 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 | (WIP) | **Database** | MariaDB | --- ## Security Notice (LiteLLM) LiteLLM is a core dependency of Huf. On **March 24, 2026**, the LiteLLM team reported a supply-chain compromise affecting published releases (`1.82.7` and `1.82.8`) that included a malicious `.pth` startup payload. What Huf has done: - Blocked compromised versions in dependency constraints (`litellm>=1.0.0,!=1.82.7,!=1.82.8`). - Added install-time detection in `huf/install.py` to show a critical alert if a compromised LiteLLM version is already present in the environment. Upstream incident thread: - https://github.com/BerriAI/litellm/issues/24518 --- ## Documentation - [**Full Documentation**](https://docs.huf.ai/) — Guides, tutorials, and API reference - [**AGENTS.md**](./AGENTS.md) — Technical context for AI agents. Adopts the [agents.md](https://agents.md) standard. - [**CLAUDE.md**](./CLAUDE.md) — Defines coding standards, review criteria, and project-specific rules. Claude reads this file during runs and follows your conventions. --- ## License MIT License — see [LICENSE](./LICENSE) for details. ---

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