environment variables
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@ -4,8 +4,8 @@ import TabItem from '@theme/TabItem';
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1. Open the **OpenRAG OpenSearch Agent** flow in the Langflow visual editor: From the **Chat** window, click <Icon name="Settings2" aria-hidden="true"/> **Settings**, click **Edit in Langflow**, and then click **Proceed**.
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2. Create a [Langflow API key](https://docs.langflow.org/api-keys-and-authentication), which is a user-specific token required to send requests to the Langflow server.
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This key doesn't grant access to OpenRAG.
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2. Optional: If you don't want to use the Langflow API key that is generated automatically when you install OpenRAG, you can create a [Langflow API key](https://docs.langflow.org/api-keys-and-authentication).
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This key doesn't grant access to OpenRAG; it is only for authenticating with the Langflow API.
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1. In the Langflow visual editor, click your user icon in the header, and then select **Settings**.
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2. Click **Langflow API Keys**, and then click <Icon name="Plus" aria-hidden="true"/> **Add New**.
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@ -31,7 +31,7 @@ Anthropic doesn't provide embedding models. If you select Anthropic for your lan
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3. Click **Complete**.
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4. Select a provider for embeddings, provide the required information, and then select the embedding model you want to use.
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For information about another provider's credentials and settings, see the instructions for your chosen provider.
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For information about another provider's credentials and settings, see the instructions for that provider.
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5. Continue through the overview slides for a brief introduction to OpenRAG, or click <Icon name="ArrowRight" aria-hidden="true"/> **Skip overview**.
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The overview demonstrates some basic functionality that is covered in the [quickstart](/quickstart#chat-with-documents) and in other parts of the OpenRAG documentation.
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@ -46,7 +46,7 @@ The overview demonstrates some basic functionality that is covered in the [quick
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3. Click **Complete**.
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4. Select a provider for embeddings, provide the required information, and then select the embedding model you want to use.
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For information about another provider's credentials and settings, see the instructions for your chosen provider.
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For information about another provider's credentials and settings, see the instructions for that provider.
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5. Continue through the overview slides for a brief introduction to OpenRAG, or click <Icon name="ArrowRight" aria-hidden="true"/> **Skip overview**.
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The overview demonstrates some basic functionality that is covered in the [quickstart](/quickstart#chat-with-documents) and in other parts of the OpenRAG documentation.
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@ -97,7 +97,7 @@ The overview demonstrates some basic functionality that is covered in the [quick
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3. Click **Complete**.
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4. Select a provider for embeddings, provide the required information, and then select the embedding model you want to use.
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For information about another provider's credentials and settings, see the instructions for your chosen provider.
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For information about another provider's credentials and settings, see the instructions for that provider.
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5. Continue through the overview slides for a brief introduction to OpenRAG, or click <Icon name="ArrowRight" aria-hidden="true"/> **Skip overview**.
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The overview demonstrates some basic functionality that is covered in the [quickstart](/quickstart#chat-with-documents) and in other parts of the OpenRAG documentation.
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@ -1,12 +1,12 @@
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- Gather the credentials and connection details for your preferred model providers.
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* Gather the credentials and connection details for your preferred model providers.
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You must have access to at least one language model and one embedding model.
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If a provider offers both types, you can use the same provider for both models.
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If a provider offers only one type, you must select two providers.
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- OpenAI: Create an [OpenAI API key](https://platform.openai.com/api-keys).
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- Anthropic language models: Create an [Anthropic API key](https://www.anthropic.com/docs/api/reference).
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- IBM watsonx.ai: Get your watsonx.ai API endpoint, IBM project ID, and IBM API key from your watsonx deployment.
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- Ollama: Use the [Ollama documentation](https://docs.ollama.com/) to set up your Ollama instance locally, in the cloud, or on a remote server, and then get your Ollama server's base URL.
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* **OpenAI**: Create an [OpenAI API key](https://platform.openai.com/api-keys).
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* **Anthropic**: Create an [Anthropic API key](https://www.anthropic.com/docs/api/reference).
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Anthropic provides language models only; you must select an additional provider for embeddings.
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* **IBM watsonx.ai**: Get your watsonx.ai API endpoint, IBM project ID, and IBM API key from your watsonx deployment.
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* **Ollama**: Deploy an [Ollama instance and models](https://docs.ollama.com/) locally, in the cloud, or on a remote server, and then get your Ollama server's base URL and the names of the models that you want to use.
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You must have access to at least one language model and one embedding model.
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If your chosen provider offers both types, you can use the same provider for both models.
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If your provider offers only one type, such as Anthropic, you must select two providers.
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- 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.
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* 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.
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@ -1,6 +1,6 @@
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- Install [uv](https://docs.astral.sh/uv/getting-started/installation/).
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* Install [uv](https://docs.astral.sh/uv/getting-started/installation/).
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- Install [Podman](https://podman.io/docs/installation) (recommended) or [Docker](https://docs.docker.com/get-docker/).
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* Install [Podman](https://podman.io/docs/installation) (recommended) or [Docker](https://docs.docker.com/get-docker/).
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- Install [`podman-compose`](https://docs.podman.io/en/latest/markdown/podman-compose.1.html) or [Docker Compose](https://docs.docker.com/compose/install/).
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To use Docker Compose with Podman, you must alias Docker Compose commands to Podman commands.
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* Install [`podman-compose`](https://docs.podman.io/en/latest/markdown/podman-compose.1.html) or [Docker Compose](https://docs.docker.com/compose/install/).
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To use Docker Compose with Podman, you must alias Docker Compose commands to Podman commands.
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@ -1 +1 @@
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- Install [Python](https://www.python.org/downloads/release/python-3100/) version 3.13 or later.
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* Install [Python](https://www.python.org/downloads/release/python-3100/) version 3.13 or later.
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@ -1,2 +1,2 @@
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- For Microsoft Windows, you must use the Windows Subsystem for Linux (WSL).
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* For Microsoft Windows, you must use the Windows Subsystem for Linux (WSL).
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See [Install OpenRAG on Windows](/install-windows) before proceeding.
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@ -19,8 +19,8 @@ If OpenRAG detects OAuth credentials during setup, it recommends **Advanced Setu
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The OpenSearch password is required.
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The Langflow password is optional.
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If the Langflow password is empty, Langflow runs in [autologin mode](https://docs.langflow.org/api-keys-and-authentication#langflow-auto-login) without password authentication.
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The Langflow password is recommended but optional.
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If the Langflow password is empty, the Langflow server starts without authentication enabled. For more information, see [Langflow settings](/reference/configuration#langflow-settings).
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3. Optional: Enter your OpenAI API key, or leave this field empty if you want to configure model provider credentials later during application onboarding.
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@ -57,8 +57,8 @@ If OpenRAG detects OAuth credentials during setup, it recommends **Advanced Setu
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The OpenSearch password is required.
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The Langflow password is optional.
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If the Langflow password is empty, Langflow runs in [autologin mode](https://docs.langflow.org/api-keys-and-authentication#langflow-auto-login) without password authentication.
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The Langflow password is recommended but optional.
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If the Langflow password is empty, the Langflow server starts without authentication enabled. For more information, see [Langflow settings](/reference/configuration#langflow-settings).
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3. Optional: Enter your OpenAI API key, or leave this field empty if you want to configure model provider credentials later during application onboarding.
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@ -76,7 +76,7 @@ If OpenRAG detects OAuth credentials during setup, it recommends **Advanced Setu
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6. Click **Save Configuration**.
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Your passwords, API key (if provided), and OAuth credentials (if provided) are stored in the `.env` file in your OpenRAG installation directory.
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Your passwords, API key, and OAuth credentials, if provided, are stored in the `.env` file in your OpenRAG installation directory.
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If you modified any credentials that were pulled from an existing `.env` file, those values are updated in the `.env` file.
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7. Click **Start All Services** to start the OpenRAG services that run in containers.
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@ -105,10 +105,10 @@ If OpenRAG detects OAuth credentials during setup, it recommends **Advanced Setu
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* `WEBHOOK_BASE_URL`: Sets the base address for the following OpenRAG OAuth connector endpoints:
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- Amazon S3: Not applicable.
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- Google Drive: `WEBHOOK_BASE_URL/connectors/google_drive/webhook`
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- OneDrive: `WEBHOOK_BASE_URL/connectors/onedrive/webhook`
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- SharePoint: `WEBHOOK_BASE_URL/connectors/sharepoint/webhook`
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* Amazon S3: Not applicable.
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* Google Drive: `WEBHOOK_BASE_URL/connectors/google_drive/webhook`
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* OneDrive: `WEBHOOK_BASE_URL/connectors/onedrive/webhook`
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* SharePoint: `WEBHOOK_BASE_URL/connectors/sharepoint/webhook`
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12. Continue with [application onboarding](#application-onboarding).
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@ -34,12 +34,12 @@ When you [install OpenRAG](/install-options), you provide the initial configurat
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This includes authentication credentials for OpenSearch and OAuth connectors.
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This configuration determines how OpenRAG authenticates with OpenSearch and controls access to documents in your knowledge base:
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* **No-auth mode (basic setup)**: If you choose **Basic Setup** in the [TUI](/tui), or your `.env` file doesn't include OAuth credentials, then OpenRAG runs in no-auth mode.
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* **No-auth mode (basic setup)**: If you select **Basic Setup** in the [TUI](/tui), or your `.env` file doesn't include OAuth credentials, then the OpenRAG OpenSearch instance runs in no-auth mode.
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This mode uses one anonymous JWT token for OpenSearch authentication.
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There is no differentiation between users; all users that access your OpenRAG instance can access all documents uploaded to your knowledge base.
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* **OAuth mode (advanced setup)**: If you choose **Advanced Setup** in the [TUI](/tui), or your `.env` file includes OAuth credentials, then OpenRAG runs in OAuth mode.
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* **OAuth mode (advanced setup)**: If you select **Advanced Setup** in the [TUI](/tui), or your `.env` file includes OAuth credentials, then the OpenRAG OpenSearch instance runs in OAuth mode.
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This mode uses a unique JWT token for each OpenRAG user, and each document is tagged with user ownership.
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Documents are filtered by user owner; users see only the documents that they uploaded or have access to through their cloud storage accounts.
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@ -26,67 +26,73 @@ Use this installation method if you don't want to [use the Terminal User Interfa
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<PartialPrereqNoScript />
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## Install OpenRAG with Docker Compose
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## Prepare your deployment
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To install OpenRAG with Docker Compose, do the following:
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1. Clone the OpenRAG repository:
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1. Clone the OpenRAG repository.
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```bash
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git clone https://github.com/langflow-ai/openrag.git
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```
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2. Change to the root of the cloned repository:
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```bash
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cd openrag
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```
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2. Install dependencies.
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3. Install dependencies:
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```bash
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uv sync
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```
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3. Copy the example `.env` file included in the repository root.
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The example file includes all environment variables with comments to guide you in finding and setting their values.
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4. Create a `.env` file at the root of the cloned repository.
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You can create an empty file or copy the repository's [`.env.example`](https://github.com/langflow-ai/openrag/blob/main/.env.example) file.
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The example file contains some of the [OpenRAG environment variables](/reference/configuration) to get you started with configuring your deployment.
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```bash
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cp .env.example .env
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```
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Alternatively, create a new `.env` file in the repository root.
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```
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touch .env
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```
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5. Edit the `.env` file to configure your deployment using [OpenRAG environment variables](/reference/configuration).
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The OpenRAG Docker Compose files pull values from your `.env` file to configure the OpenRAG containers.
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The following variables are required or recommended:
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4. The Docker Compose files are populated with the values from your `.env` file.
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The `OPENSEARCH_PASSWORD` value must be set.
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`OPENSEARCH_PASSWORD` can be automatically generated when using the TUI, but for a Docker Compose installation, you can set it manually instead. To generate an OpenSearch admin password, see the [OpenSearch documentation](https://docs.opensearch.org/latest/security/configuration/demo-configuration/#setting-up-a-custom-admin-password).
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* **`OPENSEARCH_PASSWORD` (Required)**: Sets the OpenSearch administrator password. It must adhere to the [OpenSearch password complexity requirements](https://docs.opensearch.org/latest/security/configuration/demo-configuration/#setting-up-a-custom-admin-password).
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The following values are optional:
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* **`LANGFLOW_SUPERUSER`**: The username for the Langflow administrator user. Defaults to `admin` if not set.
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```env
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OPENAI_API_KEY=your_openai_api_key
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LANGFLOW_SECRET_KEY=your_secret_key
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```
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* **`LANGFLOW_SUPERUSER_PASSWORD` (Strongly recommended)**: Sets the Langflow administrator password, and determines the Langflow server's default authentication mode. If not set, the Langflow server starts without authentication enabled. For more information, see [Langflow settings](/reference/configuration#langflow-settings).
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`OPENAI_API_KEY` is optional. You can provide it during [application onboarding](#application-onboarding) or choose a different model provider. If you want to set it in your `.env` file, you can find your OpenAI API key in your [OpenAI account](https://platform.openai.com/api-keys).
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* **`LANGFLOW_SECRET_KEY` (Strongly recommended)**: A secret encryption key for internal Langflow operations. It is recommended to [generate your own Langflow secret key](https://docs.langflow.org/api-keys-and-authentication#langflow-secret-key). If not set, Langflow generates a secret key automatically.
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`LANGFLOW_SECRET_KEY` is optional. Langflow will auto-generate it if not set. For more information, see the [Langflow documentation](https://docs.langflow.org/api-keys-and-authentication#langflow-secret-key).
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* **Model provider credentials**: Provide credentials for your preferred model providers. If not set in the `.env` file, you must configure at least one provider during [application onboarding](#application-onboarding).
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The following Langflow configuration values are optional but important to consider:
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* `OPENAI_API_KEY`
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* `ANTHROPIC_API_KEY`
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* `OLLAMA_ENDPOINT`
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* `WATSONX_API_KEY`
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* `WATSONX_ENDPOINT`
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* `WATSONX_PROJECT_ID`
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```env
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LANGFLOW_SUPERUSER=admin
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LANGFLOW_SUPERUSER_PASSWORD=your_langflow_password
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```
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* **OAuth provider credentials**: To upload documents from external storage, such as Google Drive, set the required OAuth credentials for the connectors that you want to use. You can [manage OAuth credentials](/ingestion#oauth-ingestion) later, but it is recommended to configure them during initial set up so you don't have to rebuild the containers.
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`LANGFLOW_SUPERUSER` defaults to `admin`. You can omit it or set it to a different username. `LANGFLOW_SUPERUSER_PASSWORD` is optional. If omitted, Langflow runs in [autologin mode](https://docs.langflow.org/api-keys-and-authentication#langflow-auto-login) with no password required. If set, Langflow requires password authentication.
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For more information on configuring OpenRAG with environment variables, see [Environment variables](/reference/configuration).
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* **Amazon**: Provide your AWS Access Key ID and AWS Secret Access Key with access to your S3 instance. For more information, see the AWS documentation on [Configuring access to AWS applications](https://docs.aws.amazon.com/singlesignon/latest/userguide/manage-your-applications.html).
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* **Google**: Provide your Google OAuth Client ID and Google OAuth Client Secret. You can generate these in the [Google Cloud Console](https://console.cloud.google.com/apis/credentials). For more information, see the [Google OAuth client documentation](https://developers.google.com/identity/protocols/oauth2).
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* **Microsoft**: For the Microsoft OAuth Client ID and Microsoft OAuth Client Secret, provide [Azure application registration credentials for SharePoint and OneDrive](https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/app-registration?view=odsp-graph-online). For more information, see the [Microsoft Graph OAuth client documentation](https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/graph-oauth).
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5. Start `docling serve` on the host machine.
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For more information and variables, see [Environment variables](/reference/configuration).
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6. Start `docling serve` on the host machine.
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OpenRAG Docker installations require that `docling serve` is running on port 5001 on the host machine.
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This enables [Mac MLX](https://opensource.apple.com/projects/mlx/) support for document processing.
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```bash
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uv run python scripts/docling_ctl.py start --port 5001
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```
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6. Confirm `docling serve` is running.
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7. Confirm `docling serve` is running.
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```
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uv run python scripts/docling_ctl.py status
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```
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PID: 27746
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```
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7. Deploy OpenRAG locally with the appropriate Docker Compose file for your environment.
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8. Deploy OpenRAG locally with the appropriate Docker Compose file for your environment.
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Both files deploy the same services.
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* [`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.
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@ -142,7 +148,7 @@ Both files deploy the same services.
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| OpenSearch | http://localhost:9200 | Datastore for [knowledge](/knowledge). |
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| OpenSearch Dashboards | http://localhost:5601 | OpenSearch database administration interface. |
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8. Wait while the containers start, and then confirm all containers are running:
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9. Wait while the containers start, and then confirm all containers are running:
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* Docker Compose:
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If all containers are running, you can access your OpenRAG services at their addresses.
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9. Access the OpenRAG frontend at `http://localhost:3000` to continue with [application onboarding](#application-onboarding).
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10. Access the OpenRAG frontend at `http://localhost:3000` to continue with [application onboarding](#application-onboarding).
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<PartialOnboarding />
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---
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title: Choose an installation method
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title: Select an installation method
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slug: /install-options
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---
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The [OpenRAG architecture](/#openrag-architecture) is lightweight and container-based with a central OpenRAG backend that orchestrates the various services and external connectors.
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Depending on your use case, OpenRAG can assist with service management, or you can manage the services yourself.
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Choose the installation method that best fits your needs:
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Select the installation method that best fits your needs:
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* **Use the [Terminal User Interface (TUI)](/tui) to manage services**: For guided configuration and simplified service management, install OpenRAG with TUI-managed services.
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@ -23,9 +23,9 @@ Choose the installation method that best fits your needs:
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The first time you start OpenRAG, you must complete application onboarding.
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This is required for all installation methods because it prepares the minimum required configuration for OpenRAG to run.
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For TUI-managed services, you must also complete initial setup before you start the OpenRAG services.
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For more information, see the instructions for your chosen installation method.
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For more information, see the instructions for your preferred installation method.
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Your OpenRAG configuration is stored in a `.env` file in the OpenRAG installation directory.
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When using TUI-managed services, the TUI prompts you for any missing values during setup and onboarding, and any values detected in a preexisting `.env` file are automatically populated.
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When using self-managed services, you must predefine these values in a `.env` file, as you would for any Docker or Podman deployment.
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For more information, see the instructions for your chosen installation method and [Environment variables](/reference/configuration).
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For more information, see the instructions for your preferred installation method and [Environment variables](/reference/configuration).
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@ -17,7 +17,7 @@ For guided configuration and simplified service management, install OpenRAG with
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You can use [`uv`](https://docs.astral.sh/uv/getting-started/installation/) to install OpenRAG as a managed or unmanaged dependency in a new or existing Python project.
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For other installation methods, see [Choose an installation method](/install-options).
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For other installation methods, see [Select an installation method](/install-options).
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## Prerequisites
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@ -22,7 +22,7 @@ The [automatic installer script](/install) also uses `uvx` to install OpenRAG.
|
|||
:::
|
||||
|
||||
This installation method is best for testing OpenRAG by running it outside of a Python project.
|
||||
For other installation methods, see [Choose an installation method](/install-options).
|
||||
For other installation methods, see [Select an installation method](/install-options).
|
||||
|
||||
## Prerequisites
|
||||
|
||||
|
|
|
|||
|
|
@ -21,7 +21,7 @@ For guided configuration and simplified service management, install OpenRAG with
|
|||
The installer script installs `uv`, Docker or Podman, Docker Compose, and OpenRAG.
|
||||
|
||||
This installation method is best for testing OpenRAG by running it outside of a Python project.
|
||||
For other installation methods, see [Choose an installation method](/install-options).
|
||||
For other installation methods, see [Select an installation method](/install-options).
|
||||
|
||||
## Prerequisites
|
||||
|
||||
|
|
|
|||
|
|
@ -16,7 +16,7 @@ Use this quickstart to install OpenRAG, and then try some of OpenRAG's core feat
|
|||
|
||||
<PartialPrereqWindows />
|
||||
|
||||
- Get an [OpenAI API key](https://platform.openai.com/api-keys).
|
||||
* Get an [OpenAI API key](https://platform.openai.com/api-keys).
|
||||
This quickstart uses OpenAI for simplicity.
|
||||
For other providers, see the other [installation methods](/install-options).
|
||||
|
||||
|
|
|
|||
|
|
@ -90,36 +90,42 @@ Control how OpenRAG [processes and ingests documents](/ingestion) into your know
|
|||
| `OPENRAG_DOCUMENTS_PATHS` | `./openrag-documents` | Document paths for ingestion. |
|
||||
| `PICTURE_DESCRIPTIONS_ENABLED` | `false` | Enable picture descriptions. |
|
||||
|
||||
### Langflow settings
|
||||
### Langflow settings {#langflow-settings}
|
||||
|
||||
Configure Langflow authentication.
|
||||
Configure the OpenRAG Langflow server's authentication, contact point, and built-in flow definitions.
|
||||
|
||||
:::info
|
||||
The `LANGFLOW_SUPERUSER_PASSWORD` is set in your `.env` file, and this value determines the default values for several other Langflow authentication variables.
|
||||
|
||||
If the `LANGFLOW_SUPERUSER_PASSWORD` variable isn't set, then the Langflow server starts _without_ authentication enabled.
|
||||
|
||||
For better security, it is recommended to set `LANGFLOW_SUPERUSER_PASSWORD` so the [Langflow server starts with authentication enabled](https://docs.langflow.org/api-keys-and-authentication#start-a-langflow-server-with-authentication-enabled).
|
||||
:::
|
||||
|
||||
| Variable | Default | Description |
|
||||
|----------|---------|-------------|
|
||||
| `LANGFLOW_AUTO_LOGIN` | `False` | Enable auto-login for Langflow. |
|
||||
| `LANGFLOW_CHAT_FLOW_ID` | Built-in flow ID | This value is automatically set to the ID of the chat [flow](/agents). The default value is found in [`.env.example`](https://github.com/langflow-ai/openrag/blob/main/.env.example). Only change this value if you explicitly don't want to use this built-in flow. |
|
||||
| `LANGFLOW_ENABLE_SUPERUSER_CLI` | `False` | Enable superuser privileges for Langflow CLI commands. |
|
||||
| `LANGFLOW_INGEST_FLOW_ID` | Built-in flow ID | This value is automatically set to the ID of the ingestion [flow](/agents). The default value is found in [`.env.example`](https://github.com/langflow-ai/openrag/blob/main/.env.example). Only change this value if you explicitly don't want to use this built-in flow. |
|
||||
| `LANGFLOW_KEY` | Automatically generated | Explicit Langflow API key. |
|
||||
| `LANGFLOW_NEW_USER_IS_ACTIVE` | `False` | Whether new Langflow users are active by default. |
|
||||
| `LANGFLOW_PUBLIC_URL` | `http://localhost:7860` | Public URL for the Langflow instance. |
|
||||
| `LANGFLOW_SECRET_KEY` | Not set | Secret key for Langflow internal operations. |
|
||||
| `LANGFLOW_SUPERUSER` | None, must be explicitly set | Langflow admin username. Required. |
|
||||
| `LANGFLOW_SUPERUSER_PASSWORD` | None, must be explicitly set | Langflow admin password. Required. |
|
||||
| `LANGFLOW_AUTO_LOGIN` | Determined by `LANGFLOW_SUPERUSER_PASSWORD` | Whether to enable [auto-login mode](https://docs.langflow.org/api-keys-and-authentication#langflow-auto-login) for the Langflow visual editor and CLI. If `LANGFLOW_SUPERUSER_PASSWORD` isn't set, then `LANGFLOW_AUTO_LOGIN` is `True` and auto-login mode is enabled. If `LANGFLOW_SUPERUSER_PASSWORD` is set, then `LANGFLOW_AUTO_LOGIN` is `False` and auto-login mode is disabled. Langflow API calls always require authentication with a Langflow API key regardless of the auto-login setting. |
|
||||
| `LANGFLOW_ENABLE_SUPERUSER_CLI` | Determined by `LANGFLOW_SUPERUSER_PASSWORD` | Whether to enable the [Langflow CLI `langflow superuser` command](https://docs.langflow.org/api-keys-and-authentication#langflow-enable-superuser-cli). If `LANGFLOW_SUPERUSER_PASSWORD` isn't set, then `LANGFLOW_ENABLE_SUPERUSER_CLI` is `True` and superuser accounts can be created with the Langflow CLI. If `LANGFLOW_SUPERUSER_PASSWORD` is set, then `LANGFLOW_ENABLE_SUPERUSER_CLI` is `False` and the `langflow superuser` command is disabled. |
|
||||
| `LANGFLOW_NEW_USER_IS_ACTIVE` | Determined by `LANGFLOW_SUPERUSER_PASSWORD` | Whether new [Langflow user accounts are active by default](https://docs.langflow.org/api-keys-and-authentication#langflow-new-user-is-active). If `LANGFLOW_SUPERUSER_PASSWORD` isn't set, then `LANGFLOW_NEW_USER_IS_ACTIVE` is `True` and new user accounts are active by default. If `LANGFLOW_SUPERUSER_PASSWORD` is set, then `LANGFLOW_NEW_USER_IS_ACTIVE` is `False` and new user accounts are inactive by default. |
|
||||
| `LANGFLOW_PUBLIC_URL` | `http://localhost:7860` | Public URL for the Langflow instance. Forms the base URL for Langflow API calls and other interfaces with your OpenRAG Langflow instance. |
|
||||
| `LANGFLOW_KEY` | Automatically generated | A Langflow API key to run flows with Langflow API calls. Because Langflow API keys are server-specific, allow OpenRAG to generate this key initially. You can create additional Langflow API keys after deploying OpenRAG. |
|
||||
| `LANGFLOW_SECRET_KEY` | Automatically generated | Secret encryption key for Langflow internal operations. It is recommended to [generate your own Langflow secret key](https://docs.langflow.org/api-keys-and-authentication#langflow-secret-key) for this variable. If not set, Langflow generates a secret key automatically. |
|
||||
| `LANGFLOW_SUPERUSER` | `admin` | Username for the Langflow administrator user. |
|
||||
| `LANGFLOW_SUPERUSER_PASSWORD` | Not set | Langflow administrator password. If not set, the Langflow server starts _without_ authentication enabled. It is recommended to set `LANGFLOW_SUPERUSER_PASSWORD` so the [Langflow server starts with authentication enabled](https://docs.langflow.org/api-keys-and-authentication#start-a-langflow-server-with-authentication-enabled). |
|
||||
| `LANGFLOW_URL` | `http://localhost:7860` | URL for the Langflow instance. |
|
||||
| `NUDGES_FLOW_ID` | Built-in flow ID | This value is automatically set to the ID of the nudges [flow](/agents). The default value is found in [`.env.example`](https://github.com/langflow-ai/openrag/blob/main/.env.example). Only change this value if you explicitly don't want to use this built-in flow. |
|
||||
| `LANGFLOW_CHAT_FLOW_ID`, `LANGFLOW_INGEST_FLOW_ID`, `NUDGES_FLOW_ID` | Built-in flow IDs | These variables are set automatically to the IDs of the chat, ingestion, and nudges [flows](/agents). The default values are found in [`.env.example`](https://github.com/langflow-ai/openrag/blob/main/.env.example). Only change these values if you want to replace a built-in flow with your own custom flow. The flow JSON must be present in your version of the OpenRAG codebase. For example, if you [deploy self-managed services](/docker), you can add the flow JSON to your local clone of the OpenRAG repository before deploying OpenRAG. |
|
||||
| `SYSTEM_PROMPT` | `You are a helpful AI assistant with access to a knowledge base. Answer questions based on the provided context.` | System prompt instructions for the agent driving the **Chat** flow. |
|
||||
|
||||
### OAuth provider settings
|
||||
|
||||
Configure OAuth providers and external service integrations.
|
||||
Configure [OAuth providers](/ingestion#oauth-ingestion) and external service integrations.
|
||||
|
||||
| Variable | Default | Description |
|
||||
|----------|---------|-------------|
|
||||
| `AWS_ACCESS_KEY_ID` / `AWS_SECRET_ACCESS_KEY` | - | AWS integrations. |
|
||||
| `GOOGLE_OAUTH_CLIENT_ID` / `GOOGLE_OAUTH_CLIENT_SECRET` | - | Google OAuth authentication. |
|
||||
| `MICROSOFT_GRAPH_OAUTH_CLIENT_ID` / `MICROSOFT_GRAPH_OAUTH_CLIENT_SECRET` | - | Microsoft OAuth. |
|
||||
| `WEBHOOK_BASE_URL` | - | Base URL for webhook endpoints. |
|
||||
| `AWS_ACCESS_KEY_ID`<br/>`AWS_SECRET_ACCESS_KEY` | Not set | Enable access to AWS S3 with an [AWS OAuth app](https://docs.aws.amazon.com/singlesignon/latest/userguide/manage-your-applications.html) integration. |
|
||||
| `GOOGLE_OAUTH_CLIENT_ID`<br/>`GOOGLE_OAUTH_CLIENT_SECRET` | Not set | Enable the [Google OAuth client](https://developers.google.com/identity/protocols/oauth2) integration. You can generate these values in the [Google Cloud Console](https://console.cloud.google.com/apis/credentials). |
|
||||
| `MICROSOFT_GRAPH_OAUTH_CLIENT_ID`<br/>`MICROSOFT_GRAPH_OAUTH_CLIENT_SECRET` | Not set | Enable the [Microsoft Graph OAuth client](https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/graph-oauth) integration by providing [Azure application registration credentials for SharePoint and OneDrive](https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/app-registration?view=odsp-graph-online). |
|
||||
| `WEBHOOK_BASE_URL` | Not set | Base URL for OAuth connector webhook endpoints. If not set, a default base URL is used. |
|
||||
|
||||
### OpenSearch settings
|
||||
|
||||
|
|
@ -127,10 +133,10 @@ Configure OpenSearch database authentication.
|
|||
|
||||
| Variable | Default | Description |
|
||||
|----------|---------|-------------|
|
||||
| `OPENSEARCH_HOST` | `localhost` | OpenSearch host. |
|
||||
| `OPENSEARCH_PASSWORD` | - | Password for OpenSearch admin user. Required. |
|
||||
| `OPENSEARCH_PORT` | `9200` | OpenSearch port. |
|
||||
| `OPENSEARCH_USERNAME` | `admin` | OpenSearch username. |
|
||||
| `OPENSEARCH_HOST` | `localhost` | OpenSearch instance host. |
|
||||
| `OPENSEARCH_PORT` | `9200` | OpenSearch instance port. |
|
||||
| `OPENSEARCH_USERNAME` | `admin` | OpenSearch administrator username. |
|
||||
| `OPENSEARCH_PASSWORD` | Must be set at start up | Required. OpenSearch administrator password. Must adhere to the [OpenSearch password complexity requirements](https://docs.opensearch.org/latest/security/configuration/demo-configuration/#setting-up-a-custom-admin-password). You must set this directly in the `.env` or in the TUI's [**Basic/Advanced Setup**(/install#setup)]. |
|
||||
|
||||
### System settings
|
||||
|
||||
|
|
@ -141,8 +147,8 @@ Configure general system components, session management, and logging.
|
|||
| `LANGFLOW_KEY_RETRIES` | `15` | Number of retries for Langflow key generation. |
|
||||
| `LANGFLOW_KEY_RETRY_DELAY` | `2.0` | Delay between retries in seconds. |
|
||||
| `LANGFLOW_VERSION` | `OPENRAG_VERSION` | Langflow Docker image version. By default, OpenRAG uses the `OPENRAG_VERSION` for the Langflow Docker image version. |
|
||||
| `LOG_FORMAT` | Disabled | Set to `json` to enabled JSON-formatted log output. |
|
||||
| `LOG_LEVEL` | `INFO` | Logging level (DEBUG, INFO, WARNING, ERROR). |
|
||||
| `LOG_FORMAT` | Not set | Set to `json` to enabled JSON-formatted log output. If not set, the default format is used. |
|
||||
| `LOG_LEVEL` | `INFO` | Logging level. Can be one of `DEBUG`, `INFO`, `WARNING`, or `ERROR`. `DEBUG` provides the most detailed logs but can impact performance. |
|
||||
| `MAX_WORKERS` | `1` | Maximum number of workers for document processing. |
|
||||
| `OPENRAG_VERSION` | `latest` | The version of the OpenRAG Docker images to run. For more information, see [Upgrade OpenRAG](/upgrade) |
|
||||
| `SERVICE_NAME` | `openrag` | Service name for logging. |
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue