peregrine/docs/getting-started/installation.md
pyr0ball 41c7954b9d docs: mkdocs wiki — installation, user guide, developer guide, reference
Adds a full MkDocs documentation site under docs/ with Material theme.

Getting Started: installation walkthrough, 7-step first-run wizard guide,
Docker Compose profile reference with GPU memory guidance and preflight.py
description.

User Guide: job discovery (search profiles, custom boards, enrichment),
job review (sorting, match scores, batch actions), apply workspace (cover
letter gen, PDF export, mark applied), interviews (kanban stages, company
research auto-trigger, survey assistant), email sync (IMAP, Gmail App
Password, classification labels, stage auto-updates), integrations (all 13
drivers with tier requirements), settings (every tab documented).

Developer Guide: contributing (dev env setup, code style, branch naming, PR
checklist), architecture (ASCII layer diagram, design decisions), adding
scrapers (full scrape() interface, registration, search profile config,
test patterns), adding integrations (IntegrationBase full interface, auto-
discovery, tier gating, test patterns), testing (patterns, fixtures, what
not to test).

Reference: tier system (full FEATURES table, can_use/tier_label API, dev
override, adding gates), LLM router (backend types, complete() signature,
fallback chains, vision routing, __auto__ resolution, adding backends),
config files (every file with field-level docs and gitignore status).

Also adds CONTRIBUTING.md at repo root pointing to the docs site.
2026-02-25 12:05:49 -08:00

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Markdown

# Installation
This page walks through a full Peregrine installation from scratch.
---
## Prerequisites
- **Git** — to clone the repository
- **Internet connection** — `setup.sh` downloads Docker and other dependencies
- **Operating system**: Ubuntu/Debian, Fedora/RHEL, Arch Linux, or macOS (with Docker Desktop)
!!! warning "Windows"
Windows is not supported. Use [WSL2 with Ubuntu](https://docs.microsoft.com/windows/wsl/install) instead.
---
## Step 1 — Clone the repository
```bash
git clone https://git.circuitforge.io/circuitforge/peregrine
cd peregrine
```
---
## Step 2 — Run setup.sh
```bash
bash setup.sh
```
`setup.sh` performs the following automatically:
1. **Detects your platform** (Ubuntu/Debian, Fedora/RHEL, Arch, macOS)
2. **Installs Git** if not already present
3. **Installs Docker Engine** and the Docker Compose v2 plugin via the official Docker repositories
4. **Adds your user to the `docker` group** so you do not need `sudo` for docker commands (Linux only — log out and back in after this)
5. **Detects NVIDIA GPUs** — if `nvidia-smi` is present and working, installs the NVIDIA Container Toolkit and configures Docker to use it
6. **Creates `.env` from `.env.example`** — edit `.env` to customise ports and model storage paths before starting
!!! note "macOS"
`setup.sh` installs Docker Desktop via Homebrew (`brew install --cask docker`) then exits. Open Docker Desktop, start it, then re-run the script.
!!! note "GPU requirement"
For GPU support, `nvidia-smi` must return output before you run `setup.sh`. Install your NVIDIA driver first. The Container Toolkit installation will fail silently if the driver is not present.
---
## Step 3 — (Optional) Edit .env
The `.env` file controls ports and volume mount paths. The defaults work for most single-user installs:
```bash
# Default ports
STREAMLIT_PORT=8501
OLLAMA_PORT=11434
VLLM_PORT=8000
SEARXNG_PORT=8888
VISION_PORT=8002
```
Change `STREAMLIT_PORT` if 8501 is taken on your machine.
---
## Step 4 — Start Peregrine
Choose a profile based on your hardware:
```bash
make start # remote — no GPU, use API-only LLMs
make start PROFILE=cpu # cpu — local models on CPU (slow)
make start PROFILE=single-gpu # single-gpu — one NVIDIA GPU
make start PROFILE=dual-gpu # dual-gpu — GPU 0 = Ollama, GPU 1 = vLLM
```
`make start` runs `preflight.py` first, which checks for port conflicts and writes GPU/RAM recommendations back to `.env`. Then it calls `docker compose --profile <PROFILE> up -d`.
---
## Step 5 — Open the UI
Navigate to **http://localhost:8501** (or whatever `STREAMLIT_PORT` you set).
The first-run wizard launches automatically. See [First-Run Wizard](first-run-wizard.md) for a step-by-step guide through all seven steps.
---
## Supported Platforms
| Platform | Tested | Notes |
|----------|--------|-------|
| Ubuntu 22.04 / 24.04 | Yes | Primary target |
| Debian 12 | Yes | |
| Fedora 39/40 | Yes | |
| RHEL / Rocky / AlmaLinux | Yes | |
| Arch Linux / Manjaro | Yes | |
| macOS (Apple Silicon) | Yes | Docker Desktop required; no GPU support |
| macOS (Intel) | Yes | Docker Desktop required; no GPU support |
| Windows | No | Use WSL2 with Ubuntu |
---
## GPU Support
Only NVIDIA GPUs are supported. AMD ROCm is not currently supported.
Requirements:
- NVIDIA driver installed and `nvidia-smi` working before running `setup.sh`
- CUDA 12.x recommended (CUDA 11.x may work but is untested)
- Minimum 8 GB VRAM for `single-gpu` profile with default models
- For `dual-gpu`: GPU 0 is assigned to Ollama, GPU 1 to vLLM
If your GPU has less than 10 GB VRAM, `preflight.py` will calculate a `CPU_OFFLOAD_GB` value and write it to `.env`. The vLLM container picks this up via `--cpu-offload-gb` to overflow KV cache to system RAM.
---
## Stopping Peregrine
```bash
make stop # stop all containers
make restart # stop then start again (runs preflight first)
```
---
## Reinstalling / Clean State
```bash
make clean # removes containers, images, and data volumes (destructive)
```
You will be prompted to type `yes` to confirm.