From 98030690b3b669db1f69bef098cefed307d31d5a Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Thu, 23 Oct 2025 20:05:43 -0400 Subject: [PATCH 1/8] about-openrag --- docs/docs/get-started/what-is-openrag.mdx | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/docs/docs/get-started/what-is-openrag.mdx b/docs/docs/get-started/what-is-openrag.mdx index 7d2340d0..a1046ade 100644 --- a/docs/docs/get-started/what-is-openrag.mdx +++ b/docs/docs/get-started/what-is-openrag.mdx @@ -3,18 +3,17 @@ title: What is OpenRAG? slug: / --- -OpenRAG is an open-source package for building agentic RAG systems. -It supports integration with a wide range of orchestration tools, vector databases, and LLM providers. +OpenRAG is an open-source package for building agentic RAG systems that integrates with a wide range of orchestration tools, vector databases, and LLM providers. OpenRAG connects and amplifies three popular, proven open-source projects into one powerful platform: -* [Langflow](https://docs.langflow.org) - Langflow is a powerful tool to build and deploy AI agents and MCP servers. It supports all major LLMs, vector databases and a growing library of AI tools. +* [Langflow](https://docs.langflow.org): Langflow is a popular tool for building and deploying AI agents and MCP servers. It supports all major LLMs, vector databases, and a growing library of AI tools. -* [OpenSearch](https://docs.opensearch.org/latest/) - OpenSearch is a community-driven, Apache 2.0-licensed open source search and analytics suite that makes it easy to ingest, search, visualize, and analyze data. +* [OpenSearch](https://docs.opensearch.org/latest/): OpenSearch is a community-driven, Apache 2.0-licensed open source search and analytics suite that makes it easy to ingest, search, visualize, and analyze data. -* [Docling](https://docling-project.github.io/docling/) - Docling simplifies document processing, parsing diverse formats — including advanced PDF understanding — and providing seamless integrations with the gen AI ecosystem. +* [Docling](https://docling-project.github.io/docling/): Docling simplifies document processing, parsing diverse formats — including advanced PDF understanding — and providing seamless integrations with the gen AI ecosystem. -OpenRAG builds on Langflow's familiar interface while adding OpenSearch for vector storage and Docling for simplified document parsing, with opinionated flows that serve as ready-to-use recipes for ingestion, retrieval, and generation from popular sources like OneDrive, Google Drive, and AWS. +OpenRAG builds on Langflow's familiar interface while adding OpenSearch for vector storage and Docling for simplified document parsing, with opinionated flows that serve as ready-to-use recipes for ingestion, retrieval, and generation from popular sources like Google Drive, OneDrive, and Sharepoint. What's more, every part of the stack is swappable. Write your own custom components in Python, try different language models, and customize your flows to build an agentic RAG system. From 459032ad6779b3ceb638aa7f384e0833387ed432 Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Thu, 23 Oct 2025 20:19:16 -0400 Subject: [PATCH 2/8] install-page --- docs/docs/get-started/install.mdx | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/docs/docs/get-started/install.mdx b/docs/docs/get-started/install.mdx index 585bef91..a776cb98 100644 --- a/docs/docs/get-started/install.mdx +++ b/docs/docs/get-started/install.mdx @@ -9,16 +9,16 @@ import PartialOnboarding from '@site/docs/_partial-onboarding.mdx'; [Install the OpenRAG Python wheel](#install-python-wheel), and then run the [OpenRAG Terminal User Interface(TUI)](#setup) to start your OpenRAG deployment with a guided setup process. -If you prefer running Docker commands and manually editing `.env` files, see [Deploy with Docker](/get-started/docker). +If you prefer running Docker commands and manually editing `.env` files, see [Install with Docker](/get-started/docker). ## Prerequisites -- [Python Version 3.10 to 3.13](https://www.python.org/downloads/release/python-3100/) -- [uv](https://docs.astral.sh/uv/getting-started/installation/) -- [Podman](https://podman.io/docs/installation) (recommended) or [Docker](https://docs.docker.com/get-docker/) installed -- [Docker Compose](https://docs.docker.com/compose/install/) installed. If using Podman, use [podman-compose](https://docs.podman.io/en/latest/markdown/podman-compose.1.html) or alias Docker compose commands to Podman commands. +- Install [Python Version 3.10 to 3.13](https://www.python.org/downloads/release/python-3100/) +- Install [uv](https://docs.astral.sh/uv/getting-started/installation/) +- Install [Podman](https://podman.io/docs/installation) (recommended) or [Docker](https://docs.docker.com/get-docker/) +- Install [Docker Compose](https://docs.docker.com/compose/install/). If using Podman, use [podman-compose](https://docs.podman.io/en/latest/markdown/podman-compose.1.html) or alias Docker compose commands to Podman commands. - Create an [OpenAI API key](https://platform.openai.com/api-keys). This key is **required** to start OpenRAG, but you can choose a different model provider during [Application Onboarding](#application-onboarding). -- Optional: GPU support requires an NVIDIA GPU with [CUDA](https://docs.nvidia.com/cuda/) support and compatible NVIDIA drivers installed on the OpenRAG host machine. If you don't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment. +- Optional: Install GPU support with an NVIDIA GPU, [CUDA](https://docs.nvidia.com/cuda/) support, and compatible NVIDIA drivers on the OpenRAG host machine. If you don't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment. ## Install the OpenRAG Python wheel {#install-python-wheel} @@ -57,7 +57,7 @@ The OpenRAG wheel installs the Terminal User Interface (TUI) for configuring and uv run openrag ``` -5. Continue with [Setup OpenRAG with the TUI](#setup). +5. Continue with [Set up OpenRAG with the TUI](#setup). ## Set up OpenRAG with the TUI {#setup} @@ -65,19 +65,19 @@ The TUI creates a `.env` file in your OpenRAG directory root and starts OpenRAG. If the TUI detects a `.env` file in the OpenRAG root directory, it sources any variables from the `.env` file. If the TUI detects OAuth credentials, it enforces the **Advanced Setup** path. -**Basic Setup** generates all of the required values for OpenRAG except the OpenAI API key. -**Basic Setup** does not set up OAuth connections for ingestion from cloud providers. -For OAuth setup, use **Advanced Setup**. - -**Basic Setup** and **Advanced Setup** enforce the same authentication settings for the Langflow server, but manage document access differently. For more information, see [Authentication and document access](/knowledge#auth). - + **Basic Setup** generates all of the required values for OpenRAG except the OpenAI API key. + **Basic Setup** does not set up OAuth connections for ingestion from cloud providers. + For OAuth setup, use **Advanced Setup**. + For information about the difference between basic (no auth) and OAuth in OpenRAG, see [Authentication and document access](/knowledge#auth). + 1. To install OpenRAG with **Basic Setup**, click **Basic Setup** or press 1. 2. Click **Generate Passwords** to generate passwords for OpenSearch and Langflow. 3. Paste your OpenAI API key in the OpenAI API key field. 4. Click **Save Configuration**. + Your passwords are saved in the `.env` file used to start OpenRAG. 5. To start OpenRAG, click **Start Container Services**. Startup pulls container images and runs them, so it can take some time. When startup is complete, the TUI displays the following: From 7186184602132ff55f88bb8b31fb55eb967ef0a6 Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Thu, 23 Oct 2025 20:30:41 -0400 Subject: [PATCH 3/8] docker-page --- docs/docs/_partial-onboarding.mdx | 2 ++ docs/docs/get-started/docker.mdx | 44 +++++++++++++++++-------------- 2 files changed, 26 insertions(+), 20 deletions(-) diff --git a/docs/docs/_partial-onboarding.mdx b/docs/docs/_partial-onboarding.mdx index 3c5c031d..6fc5c87e 100644 --- a/docs/docs/_partial-onboarding.mdx +++ b/docs/docs/_partial-onboarding.mdx @@ -7,6 +7,8 @@ The first time you start OpenRAG, whether using the TUI or a `.env` file, you mu Values from onboarding can be changed later in the OpenRAG **Settings** page. +Choose one LLM provider and complete only those steps: + 1. Enable **Get API key from environment variable** to automatically enter your key from the TUI-generated `.env` file. diff --git a/docs/docs/get-started/docker.mdx b/docs/docs/get-started/docker.mdx index fd098a80..bd4f11a1 100644 --- a/docs/docs/get-started/docker.mdx +++ b/docs/docs/get-started/docker.mdx @@ -3,25 +3,24 @@ title: Install with Docker slug: /get-started/docker --- +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; import PartialOnboarding from '@site/docs/_partial-onboarding.mdx'; -There are two different Docker Compose files. -They deploy the same applications and containers locally, but to different environments. +OpenRAG has two Docker Compose files. Both files deploy the same applications and containers locally, but they are for different environments. -- [`docker-compose.yml`](https://github.com/langflow-ai/openrag/blob/main/docker-compose.yml) is an OpenRAG deployment with GPU support for accelerated AI processing. +- [`docker-compose.yml`](https://github.com/langflow-ai/openrag/blob/main/docker-compose.yml) is an OpenRAG deployment with GPU support for accelerated AI processing. This Docker Compose file requires an NVIDIA GPU with [CUDA](https://docs.nvidia.com/cuda/) support. -- [`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. +- [`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 NVIDIA GPU support. Use this Docker Compose file for environments where GPU drivers aren't available. ## Prerequisites -- [Python Version 3.10 to 3.13](https://www.python.org/downloads/release/python-3100/) -- [uv](https://docs.astral.sh/uv/getting-started/installation/) -- [Podman](https://podman.io/docs/installation) (recommended) or [Docker](https://docs.docker.com/get-docker/) installed -- [Docker Compose](https://docs.docker.com/compose/install/) installed. If you're using Podman, use [podman-compose](https://docs.podman.io/en/latest/markdown/podman-compose.1.html) or alias Docker compose commands to Podman commands. +- Install [Python Version 3.10 to 3.13](https://www.python.org/downloads/release/python-3100/) +- Install [uv](https://docs.astral.sh/uv/getting-started/installation/) +- Install [Podman](https://podman.io/docs/installation) (recommended) or [Docker](https://docs.docker.com/get-docker/) +- Install [Docker Compose](https://docs.docker.com/compose/install/). If using Podman, use [podman-compose](https://docs.podman.io/en/latest/markdown/podman-compose.1.html) or alias Docker compose commands to Podman commands. - Create an [OpenAI API key](https://platform.openai.com/api-keys). This key is **required** to start OpenRAG, but you can choose a different model provider during [Application Onboarding](#application-onboarding). -- Optional: GPU support requires an NVIDIA GPU with CUDA support and compatible NVIDIA drivers installed on the OpenRAG host machine. If you don't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment. +- Optional: Install GPU support with an NVIDIA GPU, [CUDA](https://docs.nvidia.com/cuda/) support, and compatible NVIDIA drivers on the OpenRAG host machine. If you don't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment. ## Install OpenRAG with Docker Compose @@ -49,8 +48,7 @@ To install OpenRAG with Docker Compose, do the following: touch .env ``` -4. Set environment variables. The Docker Compose files will be populated with values from your `.env`. -The following values are **required** to be set: +4. The Docker Compose files are populated with the values from your .env. The following values must be set: ```bash OPENSEARCH_PASSWORD=your_secure_password @@ -63,7 +61,8 @@ The following values are **required** to be set: For more information on configuring OpenRAG with environment variables, see [Environment variables](/reference/configuration). 5. Start `docling serve` on the host machine. - 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. + OpenRAG Docker installations require that `docling serve` is running on port 5001 on the host machine. + This enables [Mac MLX](https://opensource.apple.com/projects/mlx/) support for document processing. ```bash uv run python scripts/docling_ctl.py start --port 5001 @@ -74,7 +73,7 @@ The following values are **required** to be set: uv run python scripts/docling_ctl.py status ``` - Successful result: + Make sure the response shows that `docling serve` is running, for example: ```bash Status: running Endpoint: http://127.0.0.1:5001 @@ -84,16 +83,21 @@ The following values are **required** to be set: 7. Deploy OpenRAG locally with Docker Compose based on your deployment type. - For GPU-enabled systems, run the following commands: + + ```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 | @@ -110,7 +114,7 @@ The following values are **required** to be set: docker compose ps ``` - You can now access the application at: + You can now access OpenRAG at the following endpoints: - **Frontend**: http://localhost:3000 - **Backend API**: http://localhost:8000 From a1f618ac8ffeb475838741cbc9412b38dc906c45 Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Thu, 23 Oct 2025 21:17:21 -0400 Subject: [PATCH 4/8] quickstart --- docs/docs/get-started/quickstart.mdx | 277 ++++------------------ docs/static/img/opensearch-agent-flow.png | Bin 1028298 -> 1081871 bytes 2 files changed, 43 insertions(+), 234 deletions(-) diff --git a/docs/docs/get-started/quickstart.mdx b/docs/docs/get-started/quickstart.mdx index 942433b5..80259617 100644 --- a/docs/docs/get-started/quickstart.mdx +++ b/docs/docs/get-started/quickstart.mdx @@ -11,33 +11,30 @@ Get started with OpenRAG by loading your knowledge, swapping out your language m ## Prerequisites -- [Install and start OpenRAG](/install) +- Install and start OpenRAG with the [TUI](/install) or [Docker](/get-started/docker) -## Find your way around +## Load and chat with your own documents 1. In OpenRAG, click