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class="breadcrumbs__item"><a aria-label="Home page" class="breadcrumbs__link" href="/"><svg viewBox="0 0 24 24" class="breadcrumbHomeIcon_YNFT"><path d="M10 19v-5h4v5c0 .55.45 1 1 1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">Installation</span></li><li class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link">Deploy self-managed services</span></li></ul></nav><div class="tocCollapsible_ETCw theme-doc-toc-mobile tocMobile_ITEo"><button type="button" class="clean-btn tocCollapsibleButton_TO0P">On this page</button></div><div class="theme-doc-markdown markdown"><header><h1>Deploy OpenRAG with self-managed services</h1></header><p>To manage your own OpenRAG services, deploy OpenRAG with Docker or Podman.</p>
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<p>Use this installation method if you don't want to <a class="" href="/tui">use the Terminal User Interface (TUI)</a>, or you need to run OpenRAG in an environment where using the TUI is unfeasible.</p>
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<h2 class="anchor anchorTargetStickyNavbar_Vzrq" id="prerequisites">Prerequisites<a href="#prerequisites" class="hash-link" aria-label="Direct link to Prerequisites" title="Direct link to Prerequisites" translate="no"></a></h2>
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<ul>
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<li class="">For Microsoft Windows, you must use the Windows Subsystem for Linux (WSL).
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See <a class="" href="/install-windows">Install OpenRAG on Windows</a> before proceeding.</li>
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</ul>
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<ul>
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<li class="">Install <a href="https://www.python.org/downloads/release/python-3100/" target="_blank" rel="noopener noreferrer" class="">Python</a> version 3.13 or later.</li>
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</ul>
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<ul>
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<li class="">
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<p>Install <a href="https://docs.astral.sh/uv/getting-started/installation/" target="_blank" rel="noopener noreferrer" class="">uv</a>.</p>
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</li>
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<li class="">
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<p>Install <a href="https://podman.io/docs/installation" target="_blank" rel="noopener noreferrer" class="">Podman</a> (recommended) or <a href="https://docs.docker.com/get-docker/" target="_blank" rel="noopener noreferrer" class="">Docker</a>.</p>
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</li>
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<li class="">
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<p>Install <a href="https://docs.podman.io/en/latest/markdown/podman-compose.1.html" target="_blank" rel="noopener noreferrer" class=""><code>podman-compose</code></a> or <a href="https://docs.docker.com/compose/install/" target="_blank" rel="noopener noreferrer" class="">Docker Compose</a>.
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To use Docker Compose with Podman, you must alias Docker Compose commands to Podman commands.</p>
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</li>
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</ul>
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<ul>
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<li class="">
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<p>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.</p>
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<ul>
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<li class=""><strong>OpenAI</strong>: Create an <a href="https://platform.openai.com/api-keys" target="_blank" rel="noopener noreferrer" class="">OpenAI API key</a>.</li>
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<li class=""><strong>Anthropic</strong>: Create an <a href="https://www.anthropic.com/docs/api/reference" target="_blank" rel="noopener noreferrer" class="">Anthropic API key</a>.
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Anthropic provides language models only; you must select an additional provider for embeddings.</li>
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<li class=""><strong>IBM watsonx.ai</strong>: Get your watsonx.ai API endpoint, IBM project ID, and IBM API key from your watsonx deployment.</li>
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<li class=""><strong>Ollama</strong>: Deploy an <a href="https://docs.ollama.com/" target="_blank" rel="noopener noreferrer" class="">Ollama instance and models</a> 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.</li>
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</ul>
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</li>
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<li class="">
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<p>Optional: Install GPU support with an NVIDIA GPU, <a href="https://docs.nvidia.com/cuda/" target="_blank" rel="noopener noreferrer" class="">CUDA</a> support, and compatible NVIDIA drivers on the OpenRAG host machine. If you don't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment.</p>
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</li>
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</ul>
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<h2 class="anchor anchorTargetStickyNavbar_Vzrq" id="setup">Prepare your deployment<a href="#setup" class="hash-link" aria-label="Direct link to Prepare your deployment" title="Direct link to Prepare your deployment" translate="no"></a></h2>
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<ol>
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<li class="">
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<p>Clone the OpenRAG repository:</p>
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<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token function" style="color:#d73a49">git</span><span class="token plain"> clone https://github.com/langflow-ai/openrag.git</span><br></span></code></pre></div></div>
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</li>
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<li class="">
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<p>Change to the root of the cloned repository:</p>
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<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token builtin class-name">cd</span><span class="token plain"> openrag</span><br></span></code></pre></div></div>
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</li>
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<li class="">
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<p>Install dependencies:</p>
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<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token plain">uv </span><span class="token function" style="color:#d73a49">sync</span><br></span></code></pre></div></div>
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</li>
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<li class="">
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<p>Create a <code>.env</code> file at the root of the cloned repository.</p>
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<p>You can create an empty file or copy the repository's <a href="https://github.com/langflow-ai/openrag/blob/main/.env.example" target="_blank" rel="noopener noreferrer" class=""><code>.env.example</code></a> file.
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The example file contains some of the <a class="" href="/reference/configuration">OpenRAG environment variables</a> to get you started with configuring your deployment.</p>
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<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token function" style="color:#d73a49">cp</span><span class="token plain"> .env.example .env</span><br></span></code></pre></div></div>
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</li>
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<li class="">
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<p>Edit the <code>.env</code> file to configure your deployment using <a class="" href="/reference/configuration">OpenRAG environment variables</a>.
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The OpenRAG Docker Compose files pull values from your <code>.env</code> file to configure the OpenRAG containers.
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The following variables are required or recommended:</p>
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<ul>
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<li class="">
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<p><strong><code>OPENSEARCH_PASSWORD</code> (Required)</strong>: Sets the OpenSearch administrator password. It must adhere to the <a href="https://docs.opensearch.org/latest/security/configuration/demo-configuration/#setting-up-a-custom-admin-password" target="_blank" rel="noopener noreferrer" class="">OpenSearch password complexity requirements</a>.</p>
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</li>
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<li class="">
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<p><strong><code>LANGFLOW_SUPERUSER</code></strong>: The username for the Langflow administrator user. If <code>LANGFLOW_SUPERUSER</code> isn't set, then the default value is <code>admin</code>.</p>
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</li>
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<li class="">
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<p><strong><code>LANGFLOW_SUPERUSER_PASSWORD</code> (Strongly recommended)</strong>: Sets the Langflow administrator password, and determines the Langflow server's default authentication mode. If <code>LANGFLOW_SUPERUSER_PASSWORD</code> isn't set, then the Langflow server starts without authentication enabled. For more information, see <a class="" href="/reference/configuration#langflow-settings">Langflow settings</a>.</p>
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</li>
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<li class="">
|
||
<p><strong><code>LANGFLOW_SECRET_KEY</code> (Strongly recommended)</strong>: A secret encryption key for internal Langflow operations. It is recommended to <a href="https://docs.langflow.org/api-keys-and-authentication#langflow-secret-key" target="_blank" rel="noopener noreferrer" class="">generate your own Langflow secret key</a>. If <code>LANGFLOW_SECRET_KEY</code> isn't set, then Langflow generates a secret key automatically.</p>
|
||
</li>
|
||
<li class="">
|
||
<p><strong>Model provider credentials</strong>: Provide credentials for your preferred model providers. If none of these are set in the <code>.env</code> file, you must configure at least one provider during the <a href="#application-onboarding" class="">application onboarding process</a>.</p>
|
||
<ul>
|
||
<li class=""><code>OPENAI_API_KEY</code></li>
|
||
<li class=""><code>ANTHROPIC_API_KEY</code></li>
|
||
<li class=""><code>OLLAMA_ENDPOINT</code></li>
|
||
<li class=""><code>WATSONX_API_KEY</code></li>
|
||
<li class=""><code>WATSONX_ENDPOINT</code></li>
|
||
<li class=""><code>WATSONX_PROJECT_ID</code></li>
|
||
</ul>
|
||
</li>
|
||
<li class="">
|
||
<p><strong>OAuth provider credentials</strong>: 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 <a class="" href="/ingestion#oauth-ingestion">manage OAuth credentials</a> later, but it is recommended to configure them during initial set up so you don't have to rebuild the containers.</p>
|
||
<ul>
|
||
<li class=""><strong>Amazon</strong>: 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 <a href="https://docs.aws.amazon.com/singlesignon/latest/userguide/manage-your-applications.html" target="_blank" rel="noopener noreferrer" class="">Configuring access to AWS applications</a>.</li>
|
||
<li class=""><strong>Google</strong>: Provide your Google OAuth Client ID and Google OAuth Client Secret. You can generate these in the <a href="https://console.cloud.google.com/apis/credentials" target="_blank" rel="noopener noreferrer" class="">Google Cloud Console</a>. For more information, see the <a href="https://developers.google.com/identity/protocols/oauth2" target="_blank" rel="noopener noreferrer" class="">Google OAuth client documentation</a>.</li>
|
||
<li class=""><strong>Microsoft</strong>: For the Microsoft OAuth Client ID and Microsoft OAuth Client Secret, provide <a href="https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/app-registration?view=odsp-graph-online" target="_blank" rel="noopener noreferrer" class="">Azure application registration credentials for SharePoint and OneDrive</a>. For more information, see the <a href="https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/graph-oauth" target="_blank" rel="noopener noreferrer" class="">Microsoft Graph OAuth client documentation</a>.</li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
<p>For more information and variables, see <a class="" href="/reference/configuration">OpenRAG environment variables</a>.</p>
|
||
</li>
|
||
</ol>
|
||
<h2 class="anchor anchorTargetStickyNavbar_Vzrq" id="start-services">Start services<a href="#start-services" class="hash-link" aria-label="Direct link to Start services" title="Direct link to Start services" translate="no"></a></h2>
|
||
<ol>
|
||
<li class="">
|
||
<p>Start <code>docling serve</code> on port 5001 on the host machine:</p>
|
||
<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token plain">uv run python scripts/docling_ctl.py start </span><span class="token parameter variable" style="color:#36acaa">--port</span><span class="token plain"> </span><span class="token number" style="color:#36acaa">5001</span><br></span></code></pre></div></div>
|
||
<p>Docling cannot run inside a Docker container due to system-level dependencies, so you must manage it as a separate service on the host machine.
|
||
For more information, see <a class="" href="/manage-services#start-native-services">Stop, start, and inspect native services</a>.</p>
|
||
<p>This port is required to deploy OpenRAG successfully; don't use a different port.
|
||
Additionally, this enables the <a href="https://opensource.apple.com/projects/mlx/" target="_blank" rel="noopener noreferrer" class="">MLX framework</a> for accelerated performance on Apple Silicon Mac machines.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Confirm <code>docling serve</code> is running.</p>
|
||
<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token plain">uv run python scripts/docling_ctl.py status</span><br></span></code></pre></div></div>
|
||
<p>If <code>docling serve</code> is running, the output includes the status, address, and process ID (PID):</p>
|
||
<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token plain">Status: running</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">Endpoint: http://127.0.0.1:5001</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">Docs: http://127.0.0.1:5001/docs</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">PID: </span><span class="token number" style="color:#36acaa">27746</span><br></span></code></pre></div></div>
|
||
</li>
|
||
<li class="">
|
||
<p>Deploy the OpenRAG containers locally using the appropriate Docker Compose file for your environment.
|
||
Both files deploy the same services.</p>
|
||
<ul>
|
||
<li class="">
|
||
<p><a href="https://github.com/langflow-ai/openrag/blob/main/docker-compose.yml" target="_blank" rel="noopener noreferrer" class=""><code>docker-compose.yml</code></a>: If your host machine has an NVIDIA GPU with CUDA support and compatible NVIDIA drivers, you can use this file to deploy OpenRAG with accelerated processing.</p>
|
||
<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockTitle_OeMC">Docker</div><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token function" style="color:#d73a49">docker</span><span class="token plain"> compose build</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain"></span><span class="token function" style="color:#d73a49">docker</span><span class="token plain"> compose up </span><span class="token parameter variable" style="color:#36acaa">-d</span><br></span></code></pre></div></div>
|
||
<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockTitle_OeMC">Podman</div><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token function" style="color:#d73a49">podman</span><span class="token plain"> compose build</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain"></span><span class="token function" style="color:#d73a49">podman</span><span class="token plain"> compose up </span><span class="token parameter variable" style="color:#36acaa">-d</span><br></span></code></pre></div></div>
|
||
</li>
|
||
<li class="">
|
||
<p><a href="https://github.com/langflow-ai/openrag/blob/main/docker-compose-cpu.yml" target="_blank" rel="noopener noreferrer" class=""><code>docker-compose-cpu.yml</code></a>: If your host machine doesn't have NVIDIA GPU support, use this file for a CPU-only OpenRAG deployment.</p>
|
||
<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockTitle_OeMC">Docker</div><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token function" style="color:#d73a49">docker</span><span class="token plain"> compose </span><span class="token parameter variable" style="color:#36acaa">-f</span><span class="token plain"> docker-compose-cpu.yml up </span><span class="token parameter variable" style="color:#36acaa">-d</span><br></span></code></pre></div></div>
|
||
<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockTitle_OeMC">Podman</div><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token function" style="color:#d73a49">podman</span><span class="token plain"> compose </span><span class="token parameter variable" style="color:#36acaa">-f</span><span class="token plain"> docker-compose-cpu.yml up </span><span class="token parameter variable" style="color:#36acaa">-d</span><br></span></code></pre></div></div>
|
||
</li>
|
||
</ul>
|
||
</li>
|
||
<li class="">
|
||
<p>Wait for the OpenRAG containers to start, and then confirm that all containers are running:</p>
|
||
<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockTitle_OeMC">Docker</div><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token function" style="color:#d73a49">docker</span><span class="token plain"> compose </span><span class="token function" style="color:#d73a49">ps</span><br></span></code></pre></div></div>
|
||
<div class="language-bash codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockTitle_OeMC">Podman</div><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-bash codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token function" style="color:#d73a49">podman</span><span class="token plain"> compose </span><span class="token function" style="color:#d73a49">ps</span><br></span></code></pre></div></div>
|
||
<p>The OpenRAG Docker Compose files deploy the following containers:</p>
|
||
<table><thead><tr><th>Container Name</th><th>Default address</th><th>Purpose</th></tr></thead><tbody><tr><td>OpenRAG Backend</td><td><a href="http://localhost:8000" target="_blank" rel="noopener noreferrer" class="">http://localhost:8000</a></td><td>FastAPI server and core functionality.</td></tr><tr><td>OpenRAG Frontend</td><td><a href="http://localhost:3000" target="_blank" rel="noopener noreferrer" class="">http://localhost:3000</a></td><td>React web interface for user interaction.</td></tr><tr><td>Langflow</td><td><a href="http://localhost:7860" target="_blank" rel="noopener noreferrer" class="">http://localhost:7860</a></td><td><a class="" href="/agents">AI workflow engine</a>.</td></tr><tr><td>OpenSearch</td><td><a href="http://localhost:9200" target="_blank" rel="noopener noreferrer" class="">http://localhost:9200</a></td><td>Datastore for <a class="" href="/knowledge">knowledge</a>.</td></tr><tr><td>OpenSearch Dashboards</td><td><a href="http://localhost:5601" target="_blank" rel="noopener noreferrer" class="">http://localhost:5601</a></td><td>OpenSearch database administration interface.</td></tr></tbody></table>
|
||
<p>When the containers are running, you can access your OpenRAG services at their addresses.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Access the OpenRAG frontend at <code>http://localhost:3000</code>, and then continue with the <a href="#application-onboarding" class="">application onboarding process</a>.</p>
|
||
</li>
|
||
</ol>
|
||
<h2 class="anchor anchorTargetStickyNavbar_Vzrq" id="application-onboarding">Complete the application onboarding process<a href="#application-onboarding" class="hash-link" aria-label="Direct link to Complete the application onboarding process" title="Direct link to Complete the application onboarding process" translate="no"></a></h2>
|
||
<p>The first time you start the OpenRAG application, you must complete the application onboarding process to select language and embedding models that are essential for OpenRAG features like the <a class="" href="/chat"><strong>Chat</strong></a>.</p>
|
||
<p>Some of these variables, such as the embedding models, can be changed seamlessly after onboarding.
|
||
Others are immutable and require you to destroy and recreate the OpenRAG containers.
|
||
For more information, see the <a class="" href="/reference/configuration">OpenRAG environment variables reference</a>.</p>
|
||
<p>You can use different providers for your language model and embedding model, such as Anthropic for the language model and OpenAI for the embedding model.
|
||
Additionally, you can set multiple embedding models.</p>
|
||
<p>You only need to complete onboarding for your preferred providers.</p>
|
||
<div class="theme-tabs-container tabs-container tabList__CuJ"><ul role="tablist" aria-orientation="horizontal" class="tabs"><li role="tab" tabindex="0" aria-selected="true" class="tabs__item tabItem_LNqP tabs__item--active">Anthropic</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_LNqP">IBM watsonx.ai</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_LNqP">Ollama</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_LNqP">OpenAI (default)</li></ul><div class="margin-top--md"><div role="tabpanel" class="tabItem_Ymn6"><div class="theme-admonition theme-admonition-info admonition_xJq3 alert alert--info"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M7 2.3c3.14 0 5.7 2.56 5.7 5.7s-2.56 5.7-5.7 5.7A5.71 5.71 0 0 1 1.3 8c0-3.14 2.56-5.7 5.7-5.7zM7 1C3.14 1 0 4.14 0 8s3.14 7 7 7 7-3.14 7-7-3.14-7-7-7zm1 3H6v5h2V4zm0 6H6v2h2v-2z"></path></svg></span>info</div><div class="admonitionContent_BuS1"><p>Anthropic doesn't provide embedding models. If you select Anthropic for your language model, you must select a different provider for the embedding model.</p></div></div><ol>
|
||
<li class="">
|
||
<p>Enter your Anthropic API key, or enable <strong>Get API key from environment variable</strong> to pull the key from your <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a>.</p>
|
||
<p>If you set <code>ANTHROPIC_API_KEY</code> in your OpenRAG <code>.env</code> file, this value can be populated automatically.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Under <strong>Advanced settings</strong>, select the language model that you want to use.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Click <strong>Complete</strong>.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Select a provider for embeddings, provide the required information, and then select the embedding model you want to use.
|
||
For information about another provider's credentials and settings, see the instructions for that provider.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Click <strong>Complete</strong>.</p>
|
||
<p>After you configure the embedding model, OpenRAG uses your credentials and models to ingest some <a class="" href="/knowledge#default-documents">initial documents</a>. This tests the connection, and it allows you to ask OpenRAG about itself in the <a class="" href="/chat"><strong>Chat</strong></a>.
|
||
If there is a problem with the model configuration, an error occurs and you are redirected back to the application onboarding screen.
|
||
Verify that the credential is valid and has access to the selected model, and then click <strong>Complete</strong> to retry ingestion.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Continue through the overview slides for a brief introduction to OpenRAG, or click <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right" aria-hidden="true"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg> <strong>Skip overview</strong>.
|
||
The overview demonstrates some basic functionality that is covered in the <a class="" href="/quickstart#chat-with-documents">quickstart</a> and in other parts of the OpenRAG documentation.</p>
|
||
</li>
|
||
</ol></div><div role="tabpanel" class="tabItem_Ymn6" hidden=""><ol>
|
||
<li class="">
|
||
<p>Use the values from your IBM watsonx deployment for the <strong>watsonx.ai API Endpoint</strong>, <strong>IBM Project ID</strong>, and <strong>IBM API key</strong> fields.</p>
|
||
<p>If you set <code>WATSONX_API_KEY</code>, <code>WATSONX_API_URL</code>, or <code>WATSONX_PROJECT_ID</code> in your <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a>, these values can be populated automatically.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Under <strong>Advanced settings</strong>, select the language model that you want to use.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Click <strong>Complete</strong>.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Select a provider for embeddings, provide the required information, and then select the embedding model you want to use.
|
||
For information about another provider's credentials and settings, see the instructions for that provider.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Click <strong>Complete</strong>.</p>
|
||
<p>After you configure the embedding model, OpenRAG uses your credentials and models to ingest some <a class="" href="/knowledge#default-documents">initial documents</a>. This tests the connection, and it allows you to ask OpenRAG about itself in the <a class="" href="/chat"><strong>Chat</strong></a>.
|
||
If there is a problem with the model configuration, an error occurs and you are redirected back to the application onboarding screen.
|
||
Verify that the credentials are valid and have access to the selected model, and then click <strong>Complete</strong> to retry ingestion.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Continue through the overview slides for a brief introduction to OpenRAG, or click <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right" aria-hidden="true"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg> <strong>Skip overview</strong>.
|
||
The overview demonstrates some basic functionality that is covered in the <a class="" href="/quickstart#chat-with-documents">quickstart</a> and in other parts of the OpenRAG documentation.</p>
|
||
</li>
|
||
</ol></div><div role="tabpanel" class="tabItem_Ymn6" hidden=""><div class="theme-admonition theme-admonition-info admonition_xJq3 alert alert--info"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M7 2.3c3.14 0 5.7 2.56 5.7 5.7s-2.56 5.7-5.7 5.7A5.71 5.71 0 0 1 1.3 8c0-3.14 2.56-5.7 5.7-5.7zM7 1C3.14 1 0 4.14 0 8s3.14 7 7 7 7-3.14 7-7-3.14-7-7-7zm1 3H6v5h2V4zm0 6H6v2h2v-2z"></path></svg></span>info</div><div class="admonitionContent_BuS1"><p>Ollama isn't installed with OpenRAG. You must install it separately if you want to use Ollama as a model provider.</p></div></div><p>Using Ollama as your language and embedding model provider offers greater flexibility and configuration options for hosting models, but it can be advanced for new users.
|
||
The recommendations given here are a reasonable starting point for users with at least one GPU and experience running LLMs locally.</p><p>The OpenRAG team recommends the OpenAI <code>gpt-oss:20b</code> lanuage model and the <a href="https://ollama.com/library/nomic-embed-text" target="_blank" rel="noopener noreferrer" class=""><code>nomic-embed-text</code></a> embedding model.
|
||
However, <code>gpt-oss:20b</code> uses 16GB of RAM, so consider using Ollama Cloud or running Ollama on a remote machine.</p><ol>
|
||
<li class="">
|
||
<p><a href="https://docs.ollama.com/" target="_blank" rel="noopener noreferrer" class="">Install Ollama locally or on a remote server</a>, or <a href="https://docs.ollama.com/cloud" target="_blank" rel="noopener noreferrer" class="">run models in Ollama Cloud</a>.</p>
|
||
<p>If you are running a remote server, it must be accessible from your OpenRAG deployment.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>In OpenRAG onboarding, connect to your Ollama server:</p>
|
||
<ul>
|
||
<li class=""><strong>Local Ollama server</strong>: Enter your Ollama server's base URL and port. The default Ollama server address is <code>http://localhost:11434</code>.</li>
|
||
<li class=""><strong>Ollama Cloud</strong>: Because Ollama Cloud models run at the same address as a local Ollama server and automatically offload to Ollama's cloud service, you can use the same base URL and port as you would for a local Ollama server. The default address is <code>http://localhost:11434</code>.</li>
|
||
<li class=""><strong>Remote server</strong>: Enter your remote Ollama server's base URL and port, such as <code>http://your-remote-server:11434</code>.</li>
|
||
</ul>
|
||
<p>If the connection succeeds, OpenRAG populates the model lists with the server's available models.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Select the model that your Ollama server is running.</p>
|
||
<p>Language model and embedding model selections are independent.
|
||
You can use the same or different servers for each model.</p>
|
||
<p>To use different providers for each model, you must configure both providers, and select the relevant model for each provider.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Click <strong>Complete</strong>.</p>
|
||
<p>After you configure the embedding model, OpenRAG uses the address and models to ingest some <a class="" href="/knowledge#default-documents">initial documents</a>. This tests the connection, and it allows you to ask OpenRAG about itself in the <a class="" href="/chat"><strong>Chat</strong></a>.
|
||
If there is a problem with the model configuration, an error occurs and you are redirected back to the application onboarding screen.
|
||
Verify that the server address is valid, and that the selected model is running on the server.
|
||
Then, click <strong>Complete</strong> to retry ingestion.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Continue through the overview slides for a brief introduction to OpenRAG, or click <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right" aria-hidden="true"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg> <strong>Skip overview</strong>.
|
||
The overview demonstrates some basic functionality that is covered in the <a class="" href="/quickstart#chat-with-documents">quickstart</a> and in other parts of the OpenRAG documentation.</p>
|
||
</li>
|
||
</ol></div><div role="tabpanel" class="tabItem_Ymn6" hidden=""><ol>
|
||
<li class="">
|
||
<p>Enter your OpenAI API key, or enable <strong>Get API key from environment variable</strong> to pull the key from your <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a>.</p>
|
||
<p>If you set <code>OPENAI_API_KEY</code> in your OpenRAG <code>.env</code> file, this value can be populated automatically.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Under <strong>Advanced settings</strong>, select the language model that you want to use.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Click <strong>Complete</strong>.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Select a provider for embeddings, provide the required information, and then select the embedding model you want to use.
|
||
For information about another provider's credentials and settings, see the instructions for that provider.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Click <strong>Complete</strong>.</p>
|
||
<p>After you configure the embedding model, OpenRAG uses your credentials and models to ingest some <a class="" href="/knowledge#default-documents">initial documents</a>. This tests the connection, and it allows you to ask OpenRAG about itself in the <a class="" href="/chat"><strong>Chat</strong></a>.
|
||
If there is a problem with the model configuration, an error occurs and you are redirected back to the application onboarding screen.
|
||
Verify that the credential is valid and has access to the selected model, and then click <strong>Complete</strong> to retry ingestion.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Continue through the overview slides for a brief introduction to OpenRAG, or click <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-arrow-right" aria-hidden="true"><path d="M5 12h14"></path><path d="m12 5 7 7-7 7"></path></svg> <strong>Skip overview</strong>.
|
||
The overview demonstrates some basic functionality that is covered in the <a class="" href="/quickstart#chat-with-documents">quickstart</a> and in other parts of the OpenRAG documentation.</p>
|
||
</li>
|
||
</ol></div></div></div>
|
||
<h2 class="anchor anchorTargetStickyNavbar_Vzrq" id="next-steps">Next steps<a href="#next-steps" class="hash-link" aria-label="Direct link to Next steps" title="Direct link to Next steps" translate="no"></a></h2>
|
||
<ul>
|
||
<li class="">Try some of OpenRAG's core features in the <a class="" href="/quickstart#chat-with-documents">quickstart</a>.</li>
|
||
<li class="">Learn how to <a class="" href="/manage-services">manage OpenRAG services</a>.</li>
|
||
<li class=""><a class="" href="/ingestion">Upload documents</a>, and then use the <a class="" href="/chat"><strong>Chat</strong></a> to explore your data.</li>
|
||
</ul></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="row margin-top--sm theme-doc-footer-edit-meta-row"><div class="col noPrint_WFHX"><a href="https://github.com/openrag/openrag/tree/main/docs/docs/get-started/docker.mdx" target="_blank" rel="noopener noreferrer" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_JAkA"></div></div></footer></article><nav class="docusaurus-mt-lg pagination-nav" aria-label="Docs pages"><a class="pagination-nav__link pagination-nav__link--prev" href="/install-windows"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Install OpenRAG on Windows</div></a><a class="pagination-nav__link pagination-nav__link--next" href="/upgrade"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Upgrade OpenRAG</div></a></nav></div></div><div class="col col--3"><div class="tableOfContents_bqdL thin-scrollbar theme-doc-toc-desktop"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#prerequisites" class="table-of-contents__link toc-highlight">Prerequisites</a></li><li><a href="#setup" class="table-of-contents__link toc-highlight">Prepare your deployment</a></li><li><a href="#start-services" class="table-of-contents__link toc-highlight">Start services</a></li><li><a href="#application-onboarding" class="table-of-contents__link toc-highlight">Complete the application onboarding process</a></li><li><a href="#next-steps" class="table-of-contents__link toc-highlight">Next steps</a></li></ul></div></div></div></div></main></div></div></div><footer class="theme-layout-footer footer"><div class="container container-fluid"><div class="row footer__links"><div class="theme-layout-footer-column col footer__col"><div class="footer__title"></div><ul class="footer__items clean-list"><li class="footer__item"><div class="footer-links">
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<span>© 2025 OpenRAG</span>
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