# Your data. Your AI. **AutoBot is a self-hosted AI platform you own — not a service you rent.** Feed it your docs, your codebase, your business knowledge. Plug in any LLM you trust — local or hosted. Your data stays on your machines. Your AI stays yours. [Get Started](#quick-start) · [Documentation](docs/) · [Community](https://github.com/mrveiss/AutoBot-AI/discussions) · [Sponsor](https://github.com/sponsors/mrveiss) [![Docker Smoke Test](https://github.com/mrveiss/AutoBot-AI/actions/workflows/docker-smoke-test.yml/badge.svg)](https://github.com/mrveiss/AutoBot-AI/actions/workflows/docker-smoke-test.yml) [![codecov](https://codecov.io/gh/mrveiss/AutoBot-AI/branch/main/graph/badge.svg)](https://codecov.io/gh/mrveiss/AutoBot-AI) [![GitHub Sponsors](https://img.shields.io/github/sponsors/mrveiss?label=Sponsor&logo=GitHub&style=flat-square)](https://github.com/sponsors/mrveiss) [![License: Apache 2.0](https://img.shields.io/badge/License-Apache_2.0-blue.svg?style=flat-square)](LICENSE)

--- > **AutoBot is infrastructure you own, not a subscription.** > A small, solid core. A management layer that runs the hard infrastructure for you. > Modules you install on top. Deploy it once, feed it your knowledge, connect whatever > LLM you trust, and run it forever — on your terms. | What you get | What stays yours | |---|---| | Chat interface | Your prompts | | RAG knowledge base | Your documents | | Service lifecycle management (SLM) | Your infrastructure | | Modules (Company OS, Codebase Analytics, Transcriber) | Your data | ## Why, How, What - **Why.** Private AI you trust with your business knowledge shouldn't require handing that knowledge — or control of the intelligence itself — to someone else's server. - **How.** A small, stable Core (RAG + knowledge-graph memory, a provider-agnostic LLM gateway with fallback, governance) plus a management layer that absorbs deploy/operate/scale, plus Modules that inherit all of it instead of rebuilding it. - **What.** A self-hosted AI platform — chat, a private knowledge base, a fleet-management dashboard, and installable modules. Apache-2.0. No subscription. ## The Platform Model AutoBot is three layers, bottom to top: 1. **Platform Core** — small, solid, and yours. Chat and streaming, a RAG knowledge base backed by a knowledge graph (your *institutional memory*), an LLM gateway with provider fallback, local inference, hooks, and governance (auth, RBAC, review gates, budgets). It changes slowly so everything above can depend on it. 2. **Management Layer — Service Lifecycle Manager (SLM).** Private AI has a lot of moving infrastructure: vector DB, cache, database, inference, and background workers, often across several machines. The **Service Lifecycle Manager (SLM)** owns the full lifecycle — **deploy → operate → scale** — so you can run it in production without becoming a full-time operator. *(SLM means Service Lifecycle Manager, never "small language model.")* 3. **Modules** — installable capabilities built on the core's bones. A module inherits institutional memory, local inference at zero marginal cost, hooks, and governance, so it stays small relative to what it delivers. Modules include **Company OS** (an autonomous *agent-company*), **Codebase Analytics**, and the **Transcriber**. → Full picture: [The AutoBot Platform Model](docs/architecture/PLATFORM_MODEL.md) ## Quick Start **Which path?** On a dedicated Ubuntu host, use the one-line installer (Option A). On anything else, use Docker (Option B). Hardware and OS requirements are in one table: [INSTALL.md#requirements](INSTALL.md#requirements). **Option A — One-line installer (dedicated Ubuntu host).** Deploys the **Service Lifecycle Manager (SLM) control plane** — Postgres, the SLM backend and nginx. The SLM then provisions the platform onto your fleet nodes; it is not the platform itself: ```bash curl -fsSL https://raw.githubusercontent.com/mrveiss/AutoBot-AI/main/install.sh | sudo bash ``` When it finishes, the installer prints your **SLM URL** (`https:///slm/`) and the `admin` password. Open that URL and log in — the **Setup Wizard** then walks you through adding fleet nodes, enrolling agents, assigning roles, and provisioning. See [First login](#first-login) for the main chat UI. **Option B — Docker Compose (everyone else; quick eval / development).** A chat needs a language model, and every model tier points at the bundled Ollama container, which only starts with `--profile ollama`. Start it, then pull every model `docker/.env.docker` names -- each agent runs its tier's model (#19332), so pulling only the chat model leaves the others answering "model not found": ```bash git clone https://github.com/mrveiss/AutoBot-AI.git cd AutoBot-AI bash docker/generate-secrets.sh # per-host secrets + a free network range docker compose --env-file docker/.env.docker --env-file docker/.env.secrets --profile ollama up -d --build # every model docker/.env.docker names, read from the file itself (about 21 GB with the defaults) sed -n 's/^AUTOBOT_[A-Z_]*_MODEL=//p' docker/.env.docker | sort -u | \ xargs -n1 docker compose --env-file docker/.env.docker --env-file docker/.env.secrets exec -T autobot-ollama ollama pull ``` User UI at **http://localhost**, SLM admin at **http://localhost/slm/**. Without `--profile ollama` the stack starts but has no model to answer with. To use Anthropic instead of a local model, set `ANTHROPIC_API_KEY` in the environment when you run `docker compose` (compose passes it to the backend). Provider settings live in **SLM Admin > Settings > LLM** (`http://localhost/slm/`, then Settings, then the **LLM** tab). ### First login - **Docker:** log in to the main app at **http://localhost** as `admin`. The password is the `AUTOBOT_ADMIN_PASSWORD` line in `docker/.env.secrets` (generated per host; read it with `grep '^AUTOBOT_ADMIN_PASSWORD=' docker/.env.secrets`). The SLM admin is at **http://localhost/slm/**. - **Native installer:** the printed login is for the SLM at `https:///slm/`. The main app's admin account is seeded from `AUTOBOT_ADMIN_PASSWORD` in `/etc/autobot/slm-secrets.env`, or, when that line is absent, from `SLM_ADMIN_PASSWORD` in the same file -- the SLM admin password (the installer prints it when it generated it). The main app is served by the node you assign the frontend role to. - Until onboarding is complete, the main app sends a newly logged-in user to its `/onboarding` page, which has three steps: **System Check**, **Choose Preset**, and **Review & Apply**. → Full install options and the two-phase deployment flow: [INSTALL.md](INSTALL.md). --- ## What AutoBot Does AutoBot is a **self-hosted AI platform**: conversational AI, a private knowledge base, and the machinery to deploy and operate it all on your own hardware. You keep complete control: - **Unified Self-Hosted Dashboard** — manage AI, infrastructure, fleet operations, and analytics from one place on your servers - **Natural Language Control** — issue commands in plain English; AutoBot handles the complexity locally - **Self-Hosted Knowledge Bases** — build knowledge bases from your docs, code, runbooks, and workflows — RAG-indexed and stored locally - **Vision Processing** — analyze screenshots and diagrams locally to guide decisions - **Self-Hosted Fleet Management** — deploy, operate, and scale multi-server stacks with the Service Lifecycle Manager (SLM) - **Installable Modules** — extend the platform with Company OS (an autonomous agent-company), Codebase Analytics, the Transcriber, and more - **Complete Data Privacy** — full data control, no external dependencies, runs entirely on your hardware, no vendor lock-in - **Governance-Ready Architecture** — audit logging, MFA, a secrets vault, retention policies, and RBAC, on an architecture (self-hosted data, a provider-agnostic LLM gateway, human-oversight-capable governance) designed to help with EU AI Act, NIS2 and data-protection obligations. The standards and regulations we are **working towards**, with their status and open work, are listed in [Compliance Targets](docs/compliance/COMPLIANCE_TARGETS.md); see also [EU AI Act, NIS2 & Governance Fit](docs/architecture/EU_AI_GOVERNANCE.md). No compliance or certification is claimed. → Browse everything in the [Capability Catalog](docs/features/CATALOG.md). --- ## System Requirements Requirements (OS, RAM, disk, init system) are kept in one place, so they cannot drift: see the table in [INSTALL.md#requirements](INSTALL.md#requirements). --- ## Platform Core: Features at a Glance | Feature | Capability | |---------|-----------| | **Chat** | Multi-turn conversations with function calling, streaming responses | | **Knowledge Bases** | RAG-powered retrieval from documents, code, infrastructure docs | | **Knowledge Graph** | Institutional memory shared across sessions and modules | | **LLM Gateway** | One place to plug in any model, with provider routing and fallback | | **Workflow Builder** | Visual and code-based workflow creation | | **Vision** | Image/screenshot analysis for troubleshooting | ## Management Layer: the Service Lifecycle Manager (SLM) The **Service Lifecycle Manager (SLM)** is how AutoBot runs the infrastructure behind private AI for you. It owns the full lifecycle of the stack — vector DB, cache, database, inference, and workers — across one or more machines: | Stage | What the SLM does | |-------|-------------------| | **Deploy** | Stand up the full stack from a blank host or across a fleet (Ansible) | | **Operate** | Upgrades, health monitoring, recovery, certificate rotation, configuration | | **Scale** | Add fleet nodes, add NPU workers, assign roles, provision new capacity | The SLM dashboard lives at **http://localhost/slm/**. See [SLM deployment](docs/guides/slm-docker-ansible-deployment.md). ## Modules Modules are large capabilities you install on the core. Because they inherit the core's institutional memory, local inference, hooks, and governance, they stay small relative to what they deliver. - **Company OS** — an autonomous *agent-company*: define a virtual company of AI agents (and human co-workers), give them goals and a backlog, schedule them to work autonomously, and govern their spend. See [Company OS](docs/llc/_index.md). - **Codebase Analytics** — understand codebases, extract insights, and identify risks entirely on your own hardware: code structure analysis, risk detection, and dependency insights, with no source ever leaving your machines. - **Transcriber** — a general-purpose audio transcription module: organize projects and recordings, transcribe locally, and export transcripts. → Browse all capabilities in the [Capability Catalog](docs/features/CATALOG.md). --- ## Why Self-Hosted AutoBot keeps your AI and your data on infrastructure you control: - **Data privacy** — your data never leaves your hardware, which helps you meet your own data-protection obligations ([what we are working towards](docs/compliance/COMPLIANCE_TARGETS.md)) - **Predictable cost** — local inference runs at zero marginal cost per request; no per-request fees - **Full control** — run custom models, modify the code, no vendor lock-in - **Low latency** — local inference and command execution, no network round-trip - **Scale on your terms** — grow within your own infrastructure with the SLM --- ## Architecture Overview > Full diagrams (data flows, deployment topologies, sequence diagrams): [docs/architecture/system-diagram.md](docs/architecture/system-diagram.md) > The conceptual model (core → SLM → modules): [docs/architecture/PLATFORM_MODEL.md](docs/architecture/PLATFORM_MODEL.md) > Feature walkthroughs and demo recording scripts: [docs/DEMOS.md](docs/DEMOS.md) ```mermaid graph TB User["👤 User
(Browser)"] Frontend["🎨 Frontend
(Vue.js)"] Backend["⚡ Backend
(FastAPI)"] Redis["🔴 Redis
(Cache/Queue)"] PostgreSQL["🐘 PostgreSQL
(Data)"] ChromaDB["🔍 ChromaDB
(Vectors)"] Inference["🧠 Local LLM
(Ollama inference)"] SLM["🛠️ Service Lifecycle Manager
(deploy · operate · scale)"] Ansible["🔧 Ansible
(Fleet Ops)"] Browser["🌐 Browser Automation
(Chromium)"] User -->|HTTP/WS| Frontend Frontend -->|API| Backend Backend -->|Read/Write| Redis Backend -->|Query| PostgreSQL Backend -->|Vector Search| ChromaDB Backend -->|Inference| Inference Backend -->|Control| Browser SLM -->|Manages lifecycle of| Backend SLM -->|Executes| Ansible style User fill:#e1f5ff style Frontend fill:#f3e5f5 style Backend fill:#fff3e0 style Redis fill:#ffebee style PostgreSQL fill:#e8f5e9 style ChromaDB fill:#fce4ec style Inference fill:#f1f8e9 style SLM fill:#ede7f6 style Ansible fill:#ede7f6 style Browser fill:#e0f2f1 ``` --- ## Deployment Options The one-line installer and Docker are described once, in [Quick Start](#quick-start). Full details for both: [INSTALL.md](INSTALL.md). ### Development Mode For contributing to AutoBot: ```bash cp docker-compose.override.example.yml docker-compose.override.yml docker compose --env-file docker/.env.docker --env-file docker/.env.secrets up -d --build ``` --- ## Running AutoBot - **Upgrade:** use the built-in updater in the SLM web UI: **Maintenance > Updates**, then the **Code Sync** tab. See the [Code Update runbook](docs/runbooks/CODE_UPDATE.md). - **Backup, restore and disaster recovery:** [Disaster Recovery](docs/operations/disaster-recovery.md). - **Hardened Docker deployment** (production overlay). `--profile ollama` starts the bundled model server the default provider settings point at; pull the models as in [Quick Start](#quick-start), or configure a hosted provider and drop the profile: ```bash docker compose -f docker-compose.yml -f docker-compose.hardened.yml --env-file docker/.env.docker --env-file docker/.env.secrets --profile ollama up -d ``` - **Uninstall and other installer options:** [INSTALL.md](INSTALL.md). --- ## Core Services AutoBot runs as a coordinated set of services. Ports differ by install mode. **Docker** (host ports from `docker-compose.yml`): | Service | Role | Host port | |---------|------|-----------| | **Frontend** | Vue.js UI, serves `/api` and `/slm/` | 80, 443 | | **Backend** | FastAPI API server | none published; reach it at `http://localhost/api` | | **SLM** | Service Lifecycle Manager | none; at `http://localhost/slm/` | | **Redis** | Cache, message queue | 6379 | | **RedisInsight** | Redis UI | 127.0.0.1:8001 (this is **not** the backend) | | **PostgreSQL** | Relational database | 127.0.0.1:5432 | | **ChromaDB** | Vector embeddings store | 127.0.0.1:8100 | | **Inference (Ollama)** | Local LLM inference | 127.0.0.1:11434 (profile `ollama`) | | **Prometheus** | Metrics collection | 127.0.0.1:9090 (profile `monitoring`) | | **Grafana** | Monitoring dashboards | 127.0.0.1:3000 (profile `monitoring`) | **Native install:** nginx serves HTTPS on 443 and proxies the API at `/api`; the SLM is at `https:///slm/`. Per-service ports on the fleet nodes are set by the roles you assign. **Health check:** Docker `curl http://localhost/api/system/health`; native `curl -k https:///api/system/health` (self-signed certificate). --- ## Usage Guide ### Dashboard Overview Once running, navigate to **http://localhost** (Docker) or your main app node (native) to access: - **Chat Interface** — start conversing with AutoBot about your knowledge and infrastructure - **Knowledge Bases** — upload and manage documents, codebases, runbooks - **Workflows** — create automated tasks and operations - **Fleet Management** — view and orchestrate multiple servers - **Analytics** — monitor system health, performance, and activity The **Service Lifecycle Manager (SLM)** — AutoBot's management layer for deploying, operating, and scaling your AI infrastructure (vector DB, cache, database, inference, and workers) — lives at **http://localhost/slm/**. ### Example: Managing a Fleet ```bash # In the AutoBot chat: # "Deploy the latest application version to all production servers" # AutoBot handles the Ansible orchestration automatically ``` ### Example: Infrastructure Insights ```bash # Ask AutoBot to analyze your codebase: # "What are the critical dependencies in the auth module?" ``` --- ## Configuration Configuration is environment variables, read from these files (#18555): - **Native install:** the installer writes each service's env file under `/etc/autobot/`; `.env.example` documents every option. - **Docker:** `docker/.env.docker` plus the generated `docker/.env.secrets`, passed with `--env-file` (compose reads no root `.env` then). - **Development tooling:** `.env.base` (shared keys) and one overlay, `.env.localhost`, `.env.native-vm` or `.env.network`, loaded in that order. Key settings: - `AUTOBOT_DEPLOYMENT_MODE` — `distributed` (default) or `standalone` (defined in `autobot_shared/env_registry.py`) - `AUTOBOT_LLM_PROVIDER` — `ollama` (default) or others ### LLM Providers and Fallback AutoBot's LLM gateway supports local and hosted providers (Ollama, OpenAI, Anthropic, Groq, vLLM, HuggingFace, and OpenRouter). When a model hits a rate limit or quota cap, requests automatically route to a backup model via configurable fallback chains. - [LLM Fallback Configuration](docs/backend/llm-fallback.md) — configure fallback chains, tune rate limits, and troubleshoot quota issues - [Environment Variables Reference](docs/configuration/environment-variables.md) — full variable listing including `AUTOBOT_FALLBACK_CHAIN_*` and `AUTOBOT_LLM_RL_*` --- ## Contributing We welcome contributions! Whether you're fixing bugs, adding features, or improving documentation: 1. Check out [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines 2. Look for issues tagged `good-first-issue` if you're new 3. Join the community discussion in [GitHub Discussions](https://github.com/mrveiss/AutoBot-AI/discussions) --- ## Support - 💬 **Questions?** Start a discussion in [GitHub Discussions](https://github.com/mrveiss/AutoBot-AI/discussions) - 🐛 **Found a bug?** Open an [issue](https://github.com/mrveiss/AutoBot-AI/issues) - 💡 **Have an idea?** Share it in [Discussions → Ideas](https://github.com/mrveiss/AutoBot-AI/discussions/categories/ideas) --- ## How to Contribute AutoBot is open source and we welcome contributions from the community! Whether you're fixing bugs, adding features, or improving documentation, your contributions help build a better self-hosted AI platform for everyone. ### 🚀 For Beginners (New to Open Source) Start with [**good-first-issue** labeled tasks](https://github.com/mrveiss/AutoBot-AI/issues?q=is%3Aissue+is%3Aopen+label%3Agood-first-issue). These are: - Self-contained and beginner-friendly - Expected to take less than 2 hours - Perfect for learning the codebase - Great introduction to our contribution process ### 💻 For Experienced Developers Find issues matching your skill area: - **🎨 Frontend** (Vue.js, TypeScript, CSS, Vite) - [Help Wanted: Frontend](https://github.com/mrveiss/AutoBot-AI/issues?q=is%3Aissue+is%3Aopen+label%3Afrontend+label%3Ahelp-wanted) - [All Frontend Issues](https://github.com/mrveiss/AutoBot-AI/issues?q=is%3Aissue+is%3Aopen+label%3Afrontend) - **🔧 Backend** (FastAPI, Python, APIs, Databases) - [Help Wanted: Backend](https://github.com/mrveiss/AutoBot-AI/issues?q=is%3Aissue+is%3Aopen+label%3Abackend+label%3Ahelp-wanted) - [All Backend Issues](https://github.com/mrveiss/AutoBot-AI/issues?q=is%3Aissue+is%3Aopen+label%3Abackend) - **🚀 Infrastructure & DevOps** (Docker, Ansible, CI/CD, Deployment) - [Help Wanted: Infrastructure](https://github.com/mrveiss/AutoBot-AI/issues?q=is%3Aissue+is%3Aopen+label%3Ainfrastructure+label%3Ahelp-wanted) - [All Infrastructure Issues](https://github.com/mrveiss/AutoBot-AI/issues?q=is%3Aissue+is%3Aopen+label%3Ainfrastructure) - **📚 Documentation** (Guides, Examples, README, API Docs) - [Help Wanted: Docs](https://github.com/mrveiss/AutoBot-AI/issues?q=is%3Aissue+is%3Aopen+label%3Adocs+label%3Ahelp-wanted) - [All Docs Issues](https://github.com/mrveiss/AutoBot-AI/issues?q=is%3Aissue+is%3Aopen+label%3Adocs) - **🧪 Testing & QA** (Unit Tests, Integration Tests, Test Coverage) - [Help Wanted: Testing](https://github.com/mrveiss/AutoBot-AI/issues?q=is%3Aissue+is%3Aopen+label%3Atesting+label%3Ahelp-wanted) - [All Testing Issues](https://github.com/mrveiss/AutoBot-AI/issues?q=is%3Aissue+is%3Aopen+label%3Atesting) ### 📖 Step-by-Step Contribution Guide Detailed contribution process, code style guidelines, and development setup: → **[Read CONTRIBUTORS.md](CONTRIBUTORS.md)** --- ## Sponsors & Supporters Support AutoBot's development in multiple ways: ### Sponsorship & Donations - **[GitHub Sponsors](https://github.com/sponsors/mrveiss)** — Recurring sponsorship with direct support and updates - **[Ko-fi](https://ko-fi.com/mrveiss)** — One-time or recurring donations for maintenance and features Your support helps us: - Maintain and improve the codebase - Add new features and capabilities - Expand documentation and examples - Grow the community - Enable contributors to participate --- ## License AutoBot is open source under the **[Apache License 2.0](LICENSE)**. Free forever for everyone — use it, modify it, distribute it, and profit from it, no permission or fees required. Attribution is required (see [NOTICE](NOTICE)), and the "AutoBot" / "mrveiss" names may not be used to endorse derived products without permission. **Free forever for individuals and hobbyists.** Nothing you can do with AutoBot today becomes paid tomorrow. Production support is how we keep it funded — see [FUNDING.md](FUNDING.md). ## Production support & funding AutoBot is free to run forever. Paid production support (Community / Production Support / Compliance Pack) is how the project stays funded — tier definitions, sponsorship links, and the support contact path live in **[FUNDING.md](FUNDING.md)**. --- ## Roadmap ### Shipped - [x] Multi-user authentication and RBAC (there is one user mode; single-user mode is retired) ### Upcoming - [ ] Kubernetes orchestration support - [ ] Advanced analytics dashboards - [ ] Module registry for discovering and installing third-party modules (the three modules above ship with the platform; no registry exists yet) - [ ] Mobile companion app ### Under Consideration - Cloud deployment templates - Managed hosting option - SAML Single Logout --- ## Technology Stack - **Frontend**: Vue.js, TypeScript, Vite - **Backend**: FastAPI, Python, AsyncIO - **Database**: PostgreSQL, Redis, ChromaDB - **Inference**: Ollama (local), LangChain - **Orchestration**: Ansible, Docker, Kubernetes (coming) - **Infrastructure**: Docker Compose, systemd --- ## Documentation - [Documentation Index](docs/INDEX.md) — the full documentation home - [The AutoBot Platform Model](docs/architecture/PLATFORM_MODEL.md) — core → SLM → modules - [Capability Catalog](docs/features/CATALOG.md) — everything AutoBot can do - [INSTALL.md](INSTALL.md) — detailed setup instructions - [CONTRIBUTING.md](CONTRIBUTING.md) — get involved --- ## Status **Current version**: see the [GitHub Releases](https://github.com/mrveiss/AutoBot-AI/releases) page and the [CHANGELOG](CHANGELOG.md) (Active Development) AutoBot is actively developed and used for self-hosted AI. It's suitable for: - ✅ Self-hosted deployments on your infrastructure - ✅ Development and testing environments - ✅ Learning AI-driven automation - 🚀 Production use (with monitoring and backups) --- **Made with ❤️ by the AutoBot community**