> ## Documentation Index
> Fetch the complete documentation index at: https://docs.qredence.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Install fleet-rlm

> Install fleet-rlm with uv from PyPI or from source for contributors, plus the Python, Daytona, and pnpm prerequisites needed for the frontend build.

## Prerequisites

* **Python 3.10+**
* **[uv](https://docs.astral.sh/uv/)** package manager
* **Daytona credentials** for sandbox execution
* **[pnpm](https://pnpm.io/)** — only if you build the frontend from source

## Install from PyPI

For most users, install the published package into a `uv`-managed project:

```bash theme={null}
uv init           # skip if you already have a uv project
uv add fleet-rlm
```

Verify the installation:

```bash theme={null}
uv run fleet --help
uv run fleet-rlm --help
```

Launch the Web UI:

```bash theme={null}
uv run fleet web
```

## Install from source

For contributors who need to modify fleet-rlm itself.

### 1. Clone and sync dependencies

```bash theme={null}
git clone https://github.com/Qredence/fleet-rlm.git
cd fleet-rlm
uv sync --all-extras
```

`--all-extras` installs the `dev`, `server`, and `full` optional extras. `uv sync` also installs the default `dev` dependency group.

### 2. Configure environment

```bash theme={null}
cp .env.example .env
```

Edit `.env` and set at minimum:

```ini theme={null}
DSPY_LM_MODEL=openai/gpt-4o
DSPY_LLM_API_KEY=sk-...
DAYTONA_API_KEY=...
```

If you use MLflow locally, keep `MLFLOW_TRACKING_URI=http://127.0.0.1:5001` aligned with the `make mlflow-server` target. In `APP_ENV=local`, the API server auto-starts that local MLflow target unless `MLFLOW_AUTO_START=false`.

### 3. Frontend setup (optional)

For frontend development, install dependencies in `src/frontend/`:

```bash theme={null}
cd src/frontend
pnpm install --frozen-lockfile
```

Run the frontend gate:

```bash theme={null}
pnpm run api:check
pnpm run type-check
pnpm run lint:robustness
pnpm run test:unit
```

### 4. Verify the source install

```bash theme={null}
uv run fleet-rlm chat --trace-mode compact
uv run fleet web
```

## Common Makefile targets

| Target               | What it does                                          |
| -------------------- | ----------------------------------------------------- |
| `make sync-all`      | `uv sync --all-extras`                                |
| `make test-fast`     | Run tests excluding `live_llm` and `benchmark`        |
| `make quality-gate`  | Backend lint/type/tests, metadata/docs, frontend gate |
| `make release-check` | Quality gate + security checks + UI build + packaging |
| `make mlflow-server` | Start local MLflow server on port 5001                |

## Frontend dev commands

| Command                    | Description                                            |
| -------------------------- | ------------------------------------------------------ |
| `pnpm run dev`             | Start the development server                           |
| `pnpm run api:check`       | Verify frontend OpenAPI artifacts match `openapi.yaml` |
| `pnpm run type-check`      | TypeScript type checks                                 |
| `pnpm run lint:robustness` | Lint lane used by repo validation                      |
| `pnpm run test:unit`       | Unit tests                                             |
| `pnpm run build`           | Production build                                       |
| `pnpm run check`           | Full suite: type-check, lint, unit, build, e2e         |

## Next steps

<CardGroup cols={2}>
  <Card title="Configuration reference" icon="gear" href="/fleet-rlm/reference/configuration">
    Full environment variable reference.
  </Card>

  <Card title="Deployment guide" icon="cloud-arrow-up" href="/fleet-rlm/guides/deployment">
    Run the API server in production.
  </Card>
</CardGroup>