Generalbots

General Bots

Multi-agent AI platform for autonomous agents, agentic AI orchestration and LLM workflow automation.

Self-hosted, open source, and built in Rust. General Bots gives you 80 sovereign applications — Chat, CRM, Mail, Drive, Calendar, Meetings, Documents and Advanced RAG — that run as one platform on your own infrastructure. Your cloud, your data, your rules.

Website · Documentation · Features · Blog · [BotBook](./botbook)

[](./LICENSE) [](https://www.rust-lang.org/) [](https://github.com/generalbots/generalbots/releases) [](https://github.com/generalbots/generalbots/graphs/contributors) [](https://github.com/generalbots/generalbots/stargazers) [](https://github.com/generalbots/generalbots/network/members) [](https://github.com/generalbots/generalbots/issues) [](https://github.com/generalbots/generalbots/commits/main) [](https://github.com/generalbots/generalbots/pulls) [](#getting-started) [](#why-general-bots) [](#why-general-bots) [](#why-general-bots) [](#license)

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What it looks like

Two surfaces on one platform: the desktop suite where people work, and the cloud console where an organisation is run.

Desktop suite — :3000

Every application opens as a window inside one desktop shell, so Chat, CRM, Drive, Mail, Calendar and Meetings sit side by side instead of in separate browser tabs. A theme manager switches the whole workspace between light, dark and wallpapered variants; the capture above is the light one. The suite is a plain web client served by botui, and the same client runs unchanged inside the Tauri wrapper (botapp) on desktop and mobile.

Cloud console — :4000

The control plane for running General Bots as a service: the store, plans and offers, organisation and workspace management, and the usage dashboard. It shares the brand's dark-first visual system, and the capture above is that theme. The console itself never handles credentials — login and signup live on their own surface at :5000.

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Why General Bots

Most "AI agent" tooling stops at a chat window. General Bots is the platform underneath it: an orchestration layer that connects frontier or local LLMs to real business systems, real documents and real workflows.

• Multi-agent, not multi-chat. Orchestrate several bots with distinct personalities, tools and knowledge bases from one dashboard.
• Agentic AI workflows. Autonomous task execution that plans, calls tools and reports back — in chat or over WhatsApp.
• Sovereign by default. Runs entirely offline or air-gapped. No data leaves your network unless you route it out.
• Model-agnostic. DeepSeek, Qwen, GLM, Kimi, MiniMax, Yi, Step, Doubao, OpenAI, Anthropic — or any OpenAI-compatible endpoint, including a local llama.cpp server.
• Advanced RAG. Agentic RAG, Graph RAG, persistent memory and multi-modal retrieval over PDFs, Word, Excel and web pages.
• Low-code by design. Bot behaviour is defined in BASIC dialogs and documents, so domain experts can contribute without a computer science degree.

You write this, and the bot is live:

' start.bas
USE KB "product-manual"
USE TOOL "create_ticket"

ADD_SUGGESTION "Check my order"
ADD_SUGGESTION "Open a support ticket"

TALK "Hi! I can check orders or open a ticket for you."

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Applications

Every application is a self-contained module that can be deployed alone or as part of the whole platform. This repository ships 80 suite applications and 113 backend crates; the catalogue below is the platform map, and every entry has its own icon in [.github/svg/](./.github/svg).

| | Application | What it does | |---|-------------|--------------| | | ServerCore Platform | Web server, WebSocket messaging, REST API and request routing. Serves both the API and the web interface. | | | Auth / IdentityCore Platform | OAuth 2.0, OpenID Connect, JWT validation and session management, with role-based access control on every endpoint. SSO-ready. | | | Shared / DatabaseCore Platform | PostgreSQL with managed schema definitions, shared models and common utilities used across every application. | | | AI EngineCore Platform | LLM provider orchestration across DeepSeek, Qwen, GLM, Kimi, MiniMax, Yi or any OpenAI-compatible API. Automatic failover, token counting, streaming and cost tracking. | | | Drive / StorageCore Platform | S3-compatible object storage with upload, download, versioning and automatic indexing for search and RAG. Works with MinIO, AWS S3 and Wasabi. | | | Dashboards / AnalyticsCore Platform | Real-time dashboards covering system health, business KPIs and custom visualisations. Exportable and embeddable. | | | AI SearchCapabilities | Retrieval-augmented generation over PDFs, Word and Excel with sub-second semantic retrieval and cited answers. | | | Bot FactoryCapabilities | Rapid prototyping and multi-bot orchestration. Run many bots with distinct personalities from one dashboard. | | | BroadcastCapabilities | Omnichannel outbound messaging with AI-driven personalisation across WhatsApp, Telegram and SMS. | | | Content GenerationCapabilities | Generate on-brand, SEO-optimised content in a consistent brand voice. | | | APIs in BASICCapabilities | Build REST endpoints using simplified BASIC syntax, for legacy integration and rapid delivery. | | | LLM ToolsCapabilities | Give the model real capabilities: web search, calculation and custom API calls. | | | Talk to DataCapabilities | Query SQL databases, Excel files and CSVs in plain language. | | | TrainingCapabilities | Ingest institutional knowledge from Word, Excel and PDF documents with no coding. | | | Advanced RAGCapabilities | Agentic RAG, Graph RAG, persistent memory and multi-modal retrieval over the knowledge base. | | | CalendarBusiness & Productivity | CalDAV integration with event creation, conflict detection and automated reminder workflows. Syncs with Google, Outlook and Apple Calendar. | | | EmailBusiness & Productivity | IMAP/SMTP integration with automatic templating, attachment handling and trigger-based workflows across inbox, starred, sent and scheduled folders. | | | Meet / VideoBusiness & Productivity | Video conferencing with screen sharing, recording, transcription and auto-generated meeting notes. | | | Documents, Sheets & SlidesBusiness & Productivity | Office-compatible document processing. Read and generate Word, Excel and PowerPoint files from templates. | | | WhatsApp & TeamsBusiness & Productivity | WhatsApp Business API and the MS Teams bot framework, with template messages, proactive notifications and rich media. | | | People / CRMBusiness & Productivity | Contact management with CRM-style relationship tracking, tagging, deal pipelines and automated follow-up reminders. | | | Knowledge BaseAI & Intelligence | Automatic document ingestion with chunking, embedding and semantic search. PDFs, Word files and web pages all become queryable. | | | Web AutomationAI & Intelligence | Headless browser automation. Scrape sites, fill forms, capture screenshots and trigger workflows when a page changes. | | | SearchAI & Intelligence | Full-text and semantic search across everything indexed, combining keyword and vector matching with faceted filtering. | | | SecurityOperations | Encryption, threat detection, audit logging and compliance reporting, built to LGPD, GDPR and HIPAA expectations. | | | MonitoringOperations | System health monitoring for CPU, memory, disk and network, with alert thresholds, escalation and uptime tracking. | | | AnalyticsOperations | Event tracking, funnel analysis and conversion metrics across every channel. | | | RBAC & Multi-TenancyEnterprise | Fine-grained role-based access control and multi-tenant workspaces with complete data isolation between organisations. | | | On-Premise DeploymentEnterprise | Runs entirely inside your own infrastructure with no cloud dependency and no data leaving the network. Air-gapped deployments supported. | | | Compliance (LGPD, GDPR)Enterprise | Data subject requests, right to erasure, audit trails, retention policies and anonymisation tooling. |

Beyond the in-browser suite, the same agent layer drives WhatsApp Business, MS Teams, Telegram and email.

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Architecture

Two Rust services, one workspace, thirteen platform services behind them.

The full picture, top to bottom. Clients and channels reach Caddy, which routes to botui (three ports, one binary) and botserver (8080, HTTP and WebSocket). Inside botserver a message runs channel_entry → consent_gate → start.bas → kb/RAG → api_catalog → tool_exec → sink, over the BASIC (Rhai) engine, the drive compiler and the app registry that gives the model a UI automation surface. Below that sit the AI layer — botllm routing across Claude, Bedrock, Vertex, GLM, Kimi, Kiro or a local llama.cpp — the data services (PostgreSQL, Vault, Valkey, MinIO, Zitadel, Qdrant, Stalwart, LiveKit) and the drive tenancy model ({org}.gborg → {workspace}.gbai → {bot}) that drive_monitors discovers from object storage at runtime.

botserver is the platform core: 113 domain crates, one per business domain (botcrm, botcalendar, botdrive, botlearn, botcloud, …). Business logic belongs there, not in the API surface.

botui serves the front end on three ports from a single binary: the desktop suite on 3000, the cloud/SaaS pages on 4000, and login/signup on 5000.

A message flows as: WebSocket → session → start.bas (once per session) → knowledge-base injection → LLM or direct tool execution → streamed response. Message type 6 skips the model entirely and runs the compiled .ast through Rhai.

The long-form version — every module, the two security crates, the RAG modes — is in [BotBook → Architecture](botbook/src/02-architecture-packages/architecture.md).

Ports

| Port | Service | What it serves | |------|---------|----------------| | 3000 | botui (suite) | Desktop suite and the 80 applications | | 4000 | botui (cloud) | Store, plans, dashboard, organizations | | 5000 | botui (login) | Login and signup — the only auth surface | | 8080 | botserver | REST API and WebSocket |

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Getting Started

Requirements

• Rust — a recent stable toolchain from rustup.rs (edition 2021)
• Git
• mold (optional, faster linking) — sudo apt-get install mold

Run it

git clone https://github.com/generalbots/generalbots
cd generalbots
./restart.sh

restart.sh stops anything already running, builds botserver and botui in order, and starts both. BotServer then provisions its own stack — PostgreSQL, Vault, MinIO, Valkey, Zitadel, Qdrant and a local llama.cpp server — and reads every credential from Vault. No global database or Redis install is needed or wanted.

Once it is up:

• Suite → http://localhost:3000
• Cloud → http://localhost:4000
• Login → http://localhost:5000/login
• API → http://localhost:8080/health

First boot downloads the stack and models, so give it a few minutes. Logs go to botserver.log and botui.log:

tail -f botserver.log botui.log

Run just the API

cd botserver
cargo run -- --noconsole

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Building Bots

Bots are directories, not code. A bot lives in Drive as {bot}.gbai/ and is picked up automatically:

mybot.gbai/
├── mybot.gbdialog/     # BASIC scripts: start.bas, tables.bas, {tool}.bas
├── mybot.gbkb/         # documents to index for retrieval
├── mybot.gbot/         # bot configuration
└── mybot.gbdrive/      # generated files and reports

Four keywords cover most of it:

USE KB "manual"          ' index documents and retrieve from them
USE TOOL "create_ticket" ' expose a tool to the LLM
TALK "How can I help?"   ' reply to the user
CALL "other_script"      ' run another dialog

See the [BotBook](./botbook) for the full keyword reference and worked examples.

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Repository Layout

| Directory | What it is | |-----------|------------| | botserver/ | Platform core — API, agents, BASIC engine, 113 crates | | botui/ | Web front end — suite, cloud and login servers | | botapp/ | Tauri desktop wrapper | | botlib/ | Shared types and utilities | | botbook/ | Documentation source (mdBook) | | bottemplates/ | Ready-made bot templates | | bottest/ | Cross-crate integration tests | | botdevice/ | Device and IoT integrations | | botplugin/ | Browser extension | | botmodels/ | Data-model tooling |

This is a single repository — there are no git submodules. Push to origin for the public mirror; pushing to alm triggers the CI/CD pipeline that builds and deploys, so confirm first.

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Contributing

Read [AGENTS.md](./AGENTS.md) before opening a pull request. It carries the coding rules, security directives and testing workflow the project holds to: no unwrap()/expect() in production paths, no #[allow()] suppressions, no CDN assets, and files kept under 450 lines.

Before adding a .md file, search botbook/ for existing documentation.

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License

MIT License — see [LICENSE](./LICENSE). Each subproject carries its own copy (botserver/LICENSE, botui/LICENSE, botlib/LICENSE.txt, …).

General Bots has been developed as open source since 2017.

Built in Rust · 536,000+ lines · generalbots.org

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: generalbots
• Source: generalbots/generalbots
• License: MIT
• Homepage: https://generalbots.org

Install and usage instructions live in the source repository linked above.