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April M 2025-12-04 22:28:04 -08:00
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2
docs/docs/core-components/agents.mdx
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@ -4,8 +4,6 @@ slug: /agents
--- ---
import Icon from "@site/src/components/icon/icon"; import Icon from "@site/src/components/icon/icon";
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
OpenRAG includes a built-in [Langflow](https://docs.langflow.org/) instance for creating and managing functional application workflows called _flows_. OpenRAG includes a built-in [Langflow](https://docs.langflow.org/) instance for creating and managing functional application workflows called _flows_.
In a flow, the individual workflow steps are represented by [_components_](https://docs.langflow.org/concepts-components) that are connected together to form a complete process. In a flow, the individual workflow steps are represented by [_components_](https://docs.langflow.org/concepts-components) that are connected together to form a complete process.

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docs/docs/core-components/knowledge-filters.mdx
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@ -4,8 +4,6 @@ slug: /knowledge-filters
--- ---
import Icon from "@site/src/components/icon/icon"; import Icon from "@site/src/components/icon/icon";
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
OpenRAG's knowledge filters help you organize and manage your [knowledge base](/knowledge) by creating pre-defined views of your documents. OpenRAG's knowledge filters help you organize and manage your [knowledge base](/knowledge) by creating pre-defined views of your documents.

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docs/docs/core-components/knowledge.mdx
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@ -4,8 +4,6 @@ slug: /knowledge
--- ---
import Icon from "@site/src/components/icon/icon"; import Icon from "@site/src/components/icon/icon";
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
OpenRAG includes a built-in [OpenSearch](https://docs.opensearch.org/latest/) instance that serves as the underlying datastore for your _knowledge_ (documents). OpenRAG includes a built-in [OpenSearch](https://docs.opensearch.org/latest/) instance that serves as the underlying datastore for your _knowledge_ (documents).
This specialized database is used to store and retrieve your documents and the associated vector data (embeddings). This specialized database is used to store and retrieve your documents and the associated vector data (embeddings).
@ -98,23 +96,14 @@ When you [upload documents](/ingestion), Docling processes the files, splits the
You can use either Docling Serve or OpenRAG's built-in Docling ingestion pipeline to process documents. You can use either Docling Serve or OpenRAG's built-in Docling ingestion pipeline to process documents.
<Tabs> * **Docling Serve ingestion**: By default, OpenRAG uses [Docling Serve](https://github.com/docling-project/docling-serve).
<TabItem value="serve" label="Docling Serve ingestion" default>
By default, OpenRAG uses [Docling Serve](https://github.com/docling-project/docling-serve).
This means that OpenRAG starts a `docling serve` process on your local machine and runs Docling ingestion through an API service. This means that OpenRAG starts a `docling serve` process on your local machine and runs Docling ingestion through an API service.
</TabItem> * **Built-in Docling ingestion**: If you want to use OpenRAG's built-in Docling ingestion pipeline instead of the separate Docling Serve service, set `DISABLE_INGEST_WITH_LANGFLOW=true` in your [OpenRAG environment variables](/reference/configuration#document-processing).
<TabItem value="docling" label="Built-in Docling ingestion">
If you want to use OpenRAG's built-in Docling ingestion pipeline instead of the separate Docling Serve service, set `DISABLE_INGEST_WITH_LANGFLOW=true` in your [OpenRAG environment variables](/reference/configuration#document-processing). The built-in pipeline uses the Docling processor directly instead of through the Docling Serve API.
The built-in pipeline uses the Docling processor directly instead of through the Docling Serve API. For the underlying functionality, see [`processors.py`](https://github.com/langflow-ai/openrag/blob/main/src/models/processors.py#L58) in the OpenRAG repository.
For the underlying functionality, see [`processors.py`](https://github.com/langflow-ai/openrag/blob/main/src/models/processors.py#L58) in the OpenRAG repository.
</TabItem>
</Tabs>
To modify the Docling ingestion and embedding parameters, click <Icon name="Settings2" aria-hidden="true"/> **Settings** in the OpenRAG user interface. To modify the Docling ingestion and embedding parameters, click <Icon name="Settings2" aria-hidden="true"/> **Settings** in the OpenRAG user interface.

31
docs/docs/get-started/docker.mdx
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@ -102,27 +102,20 @@ To install OpenRAG with Docker Compose, do the following:
7. Deploy OpenRAG locally with the appropriate Docker Compose file for your environment. 7. Deploy OpenRAG locally with the appropriate Docker Compose file for your environment.
Both files deploy the same services. Both files deploy the same services.
- [`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.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 NVIDIA GPU support. Use this Docker Compose file for environments where GPU drivers aren't available. ```bash
docker compose build
docker compose up -d
```
<Tabs groupId="Compose file"> - [`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.
<TabItem value="docker-compose.yml" label="docker-compose.yml" default>
```bash
docker compose build
docker compose up -d
```
</TabItem>
<TabItem value="docker-compose-cpu.yml" label="docker-compose-cpu.yml">
```bash
docker compose -f docker-compose-cpu.yml up -d
```
</TabItem>
</Tabs>
<!-- add podman compose --> ```bash
docker compose -f docker-compose-cpu.yml up -d
```
<!-- add podman compose -->
The OpenRAG Docker Compose file starts five containers: The OpenRAG Docker Compose file starts five containers:
| Container Name | Default Address | Purpose | | Container Name | Default Address | Purpose |
@ -135,7 +128,7 @@ Both files deploy the same services.
8. Verify installation by confirming all services are running. 8. Verify installation by confirming all services are running.
<!-- add podman compose --> <!-- add podman compose -->
```bash ```bash
docker compose ps docker compose ps
``` ```

51
docs/docs/get-started/upgrade.mdx
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@ -27,11 +27,12 @@ This is a two part process because upgrading the OpenRAG Python package updates
In the **Status** menu, click **Stop Services**. In the **Status** menu, click **Stop Services**.
3. Upgrade the OpenRAG Python package to the latest version from [PyPI](https://pypi.org/project/openrag/). 3. Upgrade the OpenRAG Python package to the latest version from [PyPI](https://pypi.org/project/openrag/).
The commands to upgrade the package depend on how you installed OpenRAG.
<Tabs groupId="Installation method"> <Tabs groupId="Installation method">
<TabItem value="installer" label="Automatic installer or uvx" default> <TabItem value="installer" label="Script or uvx" default>
Use these steps to upgrade the Python package if you installed OpenRAG using the automatic installer or `uvx`: Use these steps to upgrade the Python package if you installed OpenRAG using the [installer script](/install) or [`uvx`](/install-uvx):
1. Navigate to your OpenRAG workspace directory: 1. Navigate to your OpenRAG workspace directory:
@ -45,16 +46,16 @@ In the **Status** menu, click **Stop Services**.
uvx --from openrag openrag uvx --from openrag openrag
``` ```
To upgrade to a specific version: You can invoke a specific version using any of the [`uvx` version specifiers](https://docs.astral.sh/uv/guides/tools/#requesting-specific-versions), such as `--from`:
```bash ```bash
uvx --from openrag==0.1.33 openrag uvx --from openrag==0.1.30 openrag
``` ```
</TabItem> </TabItem>
<TabItem value="uv-add" label="Python project (uv add)"> <TabItem value="uv-add" label="uv add">
Use these steps to upgrade the Python package if you installed OpenRAG in a Python project with `uv add`: Use these steps to upgrade the Python package if you installed OpenRAG with [`uv add`](/install-uv):
1. Navigate to your project directory: 1. Navigate to your project directory:
@ -81,9 +82,9 @@ In the **Status** menu, click **Stop Services**.
``` ```
</TabItem> </TabItem>
<TabItem value="uv-pip" label="Virtual environment (uv pip install)"> <TabItem value="uv-pip" label="uv pip install">
Use these steps to upgrade the Python package if you installed OpenRAG in a venv with `uv pip install`: Use these steps to upgrade the Python package if you installed OpenRAG with [`uv pip install`](/install-uv):
1. Activate your virtual environment. 1. Activate your virtual environment.
@ -108,18 +109,20 @@ In the **Status** menu, click **Stop Services**.
</TabItem> </TabItem>
</Tabs> </Tabs>
4. Start the upgraded OpenRAG containers: In the OpenRAG TUI, click **Start All Services**, and then wait while the containers start. 4. In the OpenRAG TUI, click **Start All Services**, and then wait while the upgraded containers start.
After upgrading the Python package, OpenRAG runs `docker compose pull` to get the appropriate container images matching the version specified in your OpenRAG `.env` file. Then, it recreates the containers with the new images using `docker compose up -d --force-recreate`. When you start services after upgrading the Python package, OpenRAG runs `docker compose pull` to get the appropriate container images matching the version specified in your OpenRAG `.env` file. Then, it recreates the containers with the new images using `docker compose up -d --force-recreate`.
In the `.env` file, the `OPENRAG_VERSION` [environment variable](/reference/configuration#system-settings) is set to `latest` by default, which it pulls the `latest` available container images. :::tip Pin container versions
To pin a specific container image version, you can set `OPENRAG_VERSION` to the desired container image version, such as `OPENRAG_VERSION=0.1.33`. In the `.env` file, the `OPENRAG_VERSION` [environment variable](/reference/configuration#system-settings) is set to `latest` by default, which it pulls the `latest` available container images.
To pin a specific container image version, you can set `OPENRAG_VERSION` to the desired container image version, such as `OPENRAG_VERSION=0.1.33`.
However, when you upgrade the Python package, OpenRAG automatically attempts to keep the `OPENRAG_VERSION` synchronized with the Python package version. However, when you upgrade the Python package, OpenRAG automatically attempts to keep the `OPENRAG_VERSION` synchronized with the Python package version.
You might need to edit the `.env` file after upgrading the Python package to enforce a different container version. You might need to edit the `.env` file after upgrading the Python package to enforce a different container version.
The TUI warns you if it detects a version mismatch. The TUI warns you if it detects a version mismatch.
:::
If you get an error that `langflow container already exists` error during upgrade, see [Langflow container already exists during upgrade](/support/troubleshoot#langflow-container-already-exists-during-upgrade). If you get an error that `langflow container already exists` error during upgrade, see [Langflow container already exists during upgrade](/support/troubleshoot#langflow-container-already-exists-during-upgrade).
5. Under [**Native Services**](/manage-services), click **Start** to start the Docling service. 5. Under [**Native Services**](/manage-services), click **Start** to start the Docling service.
@ -133,17 +136,17 @@ To fetch and apply the latest container images while preserving your OpenRAG dat
* Docker Compose: * Docker Compose:
```bash ```bash
docker compose pull docker compose pull
docker compose up -d --force-recreate docker compose up -d --force-recreate
``` ```
* Podman Compose: * Podman Compose:
```bash ```bash
podman compose pull podman compose pull
podman compose up -d --force-recreate podman compose up -d --force-recreate
``` ```
## See also ## See also

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docs/docs/reference/configuration.mdx
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@ -3,10 +3,6 @@ title: Environment variables
slug: /reference/configuration slug: /reference/configuration
--- ---
import Icon from "@site/src/components/icon/icon";
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
OpenRAG recognizes environment variables from the following sources: OpenRAG recognizes environment variables from the following sources:
* [Environment variables](#configure-environment-variables): Values set in the `.env` file. * [Environment variables](#configure-environment-variables): Values set in the `.env` file.

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docs/docs/support/troubleshoot.mdx
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@ -3,9 +3,6 @@ title: Troubleshoot OpenRAG
slug: /support/troubleshoot slug: /support/troubleshoot
--- ---
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
This page provides troubleshooting advice for issues you might encounter when using OpenRAG or contributing to OpenRAG. This page provides troubleshooting advice for issues you might encounter when using OpenRAG or contributing to OpenRAG.
## OpenSearch fails to start ## OpenSearch fails to start
@ -101,38 +98,33 @@ To resolve this issue, do the following:
1. Remove only the Langflow container: 1. Remove only the Langflow container:
<Tabs groupId="Container software">
<TabItem value="Podman" label="Podman">
1. Stop the Langflow container: 1. Stop the Langflow container:
```bash * Docker:
podman stop langflow
``` ```bash
docker stop langflow
```
* Podman:
```bash
podman stop langflow
```
2. Remove the Langflow container: 2. Remove the Langflow container:
```bash * Docker:
podman rm langflow --force
```
</TabItem> ```bash
<TabItem value="Docker" label="Docker" default> docker rm langflow --force
```
1. Stop the Langflow container: * Podman:
```bash ```bash
docker stop langflow podman rm langflow --force
``` ```
2. Remove the Langflow container:
```bash
docker rm langflow --force
```
</TabItem>
</Tabs>
2. Retry the [upgrade](/upgrade). 2. Retry the [upgrade](/upgrade).