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Merge pull request #321 from langflow-ai/docs-use-uvx-commands

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docs: use uvx to install
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111
README.md
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@ -28,100 +28,37 @@ OpenRAG is a comprehensive Retrieval-Augmented Generation platform that enables
Use the OpenRAG Terminal User Interface (TUI) to manage your OpenRAG installation without complex command-line operations.
To launch OpenRAG with the TUI, do the following:
To quickly install and start OpenRAG, run `uvx openrag`.
1. Clone the OpenRAG repository.
```bash
git clone https://github.com/langflow-ai/openrag.git
cd openrag
```
To first set up a project and then install OpenRAG, do the following:
2. To start the TUI, from the repository root, run:
```bash
# Install dependencies first
uv sync
# Launch the TUI
uv run openrag
```
1. Create a new project with a virtual environment using `uv init`.
The TUI opens and guides you through OpenRAG setup.
```bash
uv init YOUR_PROJECT_NAME
cd YOUR_PROJECT_NAME
```
The `(venv)` prompt doesn't change, but `uv` commands will automatically use the project's virtual environment.
For more information on virtual environments, see the [uv documentation](https://docs.astral.sh/uv/pip/environments).
2. Ensure all dependencies are installed and updated in your virtual environment.
```bash
uv sync
```
3. Install and start the OpenRAG TUI.
```bash
uvx openrag
```
To install a specific version of the Langflow package, add the required version to the command, such as `uvx --from openrag==0.1.25 openrag`.
For the full TUI installation guide, see [TUI](https://docs.openr.ag/install).
## Docker installation
## Docker or Podman installation
If you prefer to use Docker to run OpenRAG, the repository includes two Docker Compose `.yml` files.
They deploy the same applications and containers locally, but to different environments.
- [`docker-compose.yml`](https://github.com/langflow-ai/openrag/blob/main/docker-compose.yml) is an OpenRAG deployment for environments with GPU support. GPU support requires an NVIDIA GPU with CUDA support and compatible NVIDIA drivers installed on the OpenRAG host machine.
- [`docker-compose-cpu.yml`](https://github.com/langflow-ai/openrag/blob/main/docker-compose-cpu.yml) is a CPU-only version of OpenRAG for systems without GPU support. Use this Docker compose file for environments where GPU drivers aren't available.
Both Docker deployments depend on `docling serve` to be running on port `5001` on the host machine. This enables [Mac MLX](https://opensource.apple.com/projects/mlx/) support for document processing. Installing OpenRAG with the TUI starts `docling serve` automatically, but for a Docker deployment you must manually start the `docling serve` process.
To install OpenRAG with Docker:
1. Clone the OpenRAG repository.
```bash
git clone https://github.com/langflow-ai/openrag.git
cd openrag
```
2. Install dependencies.
```bash
uv sync
```
3. Start `docling serve` on the host machine.
```bash
uv run python scripts/docling_ctl.py start --port 5001
```
4. Confirm `docling serve` is running.
```
uv run python scripts/docling_ctl.py status
```
Successful result:
```bash
Status: running
Endpoint: http://127.0.0.1:5001
Docs: http://127.0.0.1:5001/docs
PID: 27746
```
5. Build and start all services.
For the GPU-accelerated deployment, run:
```bash
docker compose build
docker compose up -d
```
For environments without GPU support, run:
```bash
docker compose -f docker-compose-cpu.yml up -d
```
The OpenRAG Docker Compose file starts five containers:
| Container Name | Default Address | Purpose |
|---|---|---|
| OpenRAG Backend | http://localhost:8000 | FastAPI server and core functionality. |
| OpenRAG Frontend | http://localhost:3000 | React web interface for users. |
| Langflow | http://localhost:7860 | AI workflow engine and flow management. |
| OpenSearch | http://localhost:9200 | Vector database for document storage. |
| OpenSearch Dashboards | http://localhost:5601 | Database administration interface. |
6. Access the OpenRAG application at `http://localhost:3000` and continue with the [Quickstart](https://docs.openr.ag/quickstart).
To stop `docling serve`, run:
```bash
uv run python scripts/docling_ctl.py stop
```
For more information, see [Install with Docker](https://docs.openr.ag/get-started/docker).
For more information, see [Install OpenRAG containers](https://docs.openr.ag/get-started/docker).
## Troubleshooting

55
docs/docs/get-started/install.mdx
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@ -17,7 +17,7 @@ Instead of starting OpenRAG using Docker commands and manually editing values in
Once OpenRAG is running, use the TUI to monitor your application, control your containers, and retrieve logs.
If you prefer running Docker commands and manually editing `.env` files, see [Install with Docker](/get-started/docker).
If you prefer running Podman or Docker containers and manually editing `.env` files, see [Install OpenRAG Containers](/get-started/docker).
## Prerequisites
@ -30,12 +30,12 @@ If you prefer running Docker commands and manually editing `.env` files, see [In
## Install the OpenRAG Python wheel {#install-python-wheel}
:::important
The `.whl` file is currently available as an internal download during public preview, and will be published to PyPI in a future release.
:::
The OpenRAG wheel installs the Terminal User Interface (TUI) for configuring and running OpenRAG.
To quickly install and start OpenRAG, run `uvx openrag`.
To first set up a project and then install OpenRAG, do the following:
1. Create a new project with a virtual environment using `uv init`.
```bash
@ -46,26 +46,45 @@ The OpenRAG wheel installs the Terminal User Interface (TUI) for configuring and
The `(venv)` prompt doesn't change, but `uv` commands will automatically use the project's virtual environment.
For more information on virtual environments, see the [uv documentation](https://docs.astral.sh/uv/pip/environments).
2. Add the local OpenRAG wheel to your project's virtual environment.
```bash
uv add PATH/TO/openrag-VERSION-py3-none-any.whl
```
Replace `PATH/TO/` and `VERSION` with the path and version of your downloaded OpenRAG `.whl` file.
For example, if your `.whl` file is in the `~/Downloads` directory, the command is `uv add ~/Downloads/openrag-0.1.8-py3-none-any.whl`.
3. Ensure all dependencies are installed and updated in your virtual environment.
2. Ensure all dependencies are installed and updated in your virtual environment.
```bash
uv sync
```
4. Start the OpenRAG TUI.
3. Install and start the OpenRAG TUI.
```bash
uv run openrag
uvx openrag
```
To install a specific version of the Langflow package, add the required version to the command, such as `uvx --from openrag==0.1.25 openrag`.
5. Continue with [Set up OpenRAG with the TUI](#setup).
<details closed>
<summary>Install a local wheel without uvx</summary>
If you downloaded the OpenRAG wheel to your local machine, follow these steps:
1. Add the wheel to your project's virtual environment.
```bash
uv add PATH/TO/openrag-VERSION-py3-none-any.whl
```
Replace `PATH/TO/` and `VERSION` with the path and version of your downloaded OpenRAG `.whl` file.
For example, if your `.whl` file is in the `~/Downloads` directory:
```bash
uv add ~/Downloads/openrag-0.1.8-py3-none-any.whl
```
2. Run OpenRAG.
```bash
uv run openrag
```
</details>
4. Continue with [Set up OpenRAG with the TUI](#setup).
## Set up OpenRAG with the TUI {#setup}