# Zeph
You have an LLM. You want it to actually do things — run commands, search files, remember context, learn new skills. But wiring all that together means dealing with token bloat, provider lock-in, and context that evaporates between sessions.
Zeph is a lightweight AI agent written in Rust that connects to any LLM provider (local Ollama, Claude, OpenAI, Gemini, or HuggingFace models), equips it with tools and skills, and manages conversation memory — all while keeping prompt size minimal. Only the skills relevant to your current query are loaded, so adding more capabilities never inflates your token bill.
## What You Can Do with Zeph
**Development assistant.** Point Zeph at your project directory, and it reads files, runs shell commands, searches code, and answers questions with full context. Drop a `zeph.md` file in your repo to give it project-specific instructions.
**Chat bot.** Deploy Zeph as a Telegram, Discord, or Slack bot with streaming responses, user whitelisting, and voice message transcription. Your team gets an AI assistant in the channels they already use.
**Self-hosted agent.** Run fully local with Ollama — no data leaves your machine. Encrypt API keys with an age vault. Sandbox tool access with path restrictions and command confirmation. You control everything.
## Get Started
```bash
zeph
```
Three commands: install the binary, generate a config, start talking.
**Cross-platform**: Linux, macOS, Windows (x86_64 + ARM64).
## Next Steps
- [Why Zeph?](why-zeph.md) — what sets Zeph apart from other agent frameworks
- [Installation](getting-started/installation.md) — all installation methods (source, binaries, Docker)
- [First Conversation](getting-started/first-conversation.md) — from zero to productive in 5 minutes