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page</button></div><div class="theme-doc-markdown markdown"><header><h1>Install OpenRAG with the automatic installer script</h1></header><div class="theme-admonition theme-admonition-tip admonition_xJq3 alert alert--success"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_BuS1"><p>To quickly install and test OpenRAG&#x27;s core features, try the <a class="" href="/quickstart">quickstart</a>.</p></div></div>
<p>The installer script installs <code>uv</code>, Docker or Podman, Docker Compose, and OpenRAG.
Then, it installs and runs OpenRAG with <code>uvx</code>.</p>
<p>When you install OpenRAG with the installer script, you will use the <a class="" href="/tui">Terminal User Interface (TUI)</a> to configure and manage your OpenRAG deployment.</p>
<p>This installation method is best for testing OpenRAG by running it outside of a Python project.
For other installation methods, see <a class="" href="/install-options">Select an installation method</a>.</p>
<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>
<ul>
<li class="">For Microsoft Windows, you must use the Windows Subsystem for Linux (WSL).
See <a class="" href="/install-windows">Install OpenRAG on Windows</a> before proceeding.</li>
</ul>
<ul>
<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>
</ul>
<ul>
<li class="">
<p>Gather the credentials and connection details for your preferred model providers.
You must have access to at least one language model and one embedding model.
If a provider offers both types, you can use the same provider for both models.
If a provider offers only one type, you must select two providers.</p>
<ul>
<li class="">
<p><strong>OpenAI</strong>: Create an <a href="https://platform.openai.com/api-keys" target="_blank" rel="noopener noreferrer" class="">OpenAI API key</a>.</p>
</li>
<li class="">
<p><strong>Anthropic</strong>: Create an <a href="https://www.anthropic.com/docs/api/reference" target="_blank" rel="noopener noreferrer" class="">Anthropic API key</a>.
Anthropic provides language models only; you must select an additional provider for embeddings.</p>
</li>
<li class="">
<p><strong>IBM watsonx.ai</strong>: Get your watsonx.ai API endpoint, IBM project ID, and IBM API key from your watsonx deployment.</p>
</li>
<li class="">
<p><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. Then, get your Ollama server&#x27;s base URL and the names of the models that you want to use.</p>
<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>OpenRAG isn&#x27;t guaranteed to be compatible with all models that are available through Ollama.
For example, some models might produce unexpected results, such as JSON-formatted output instead of natural language responses, and some models aren&#x27;t appropriate for the types of tasks that OpenRAG performs, such as those that generate media.</p>
<p>The OpenRAG team recommends the following models when using Ollama as your model provider:</p>
<ul>
<li class="">
<p><strong>Language models</strong>: <code>gpt-oss:20b</code> or <code>mistral-nemo:12b</code>.</p>
<p>If you choose <code>gpt-oss:20b</code>, consider using Ollama Cloud or running Ollama on a remote machine because this model requires at least 16GB of RAM.</p>
</li>
<li class="">
<p><strong>Embedding models</strong>: <a href="https://ollama.com/library/nomic-embed-text" target="_blank" rel="noopener noreferrer" class=""><code>nomic-embed-text:latest</code></a>, <code>mxbai-embed-large:latest</code>, or <code>embeddinggemma:latest</code>.</p>
</li>
</ul>
<p>You can experiment with other models, but if you encounter issues that you are unable to resolve through other RAG best practices (like context filters and prompt engineering), try switching to one of the recommended models.
You can submit an <a href="https://github.com/langflow-ai/openrag/issues" target="_blank" rel="noopener noreferrer" class="">OpenRAG GitHub issue</a> to request support for specific models.</p></div></div>
</li>
</ul>
</li>
<li class="">
<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&#x27;t have GPU capabilities, OpenRAG provides an alternate CPU-only deployment.</p>
</li>
</ul>
<h2 class="anchor anchorTargetStickyNavbar_Vzrq" id="install">Run the installer script<a href="#install" class="hash-link" aria-label="Direct link to Run the installer script" title="Direct link to Run the installer script" translate="no"></a></h2>
<ol>
<li class="">
<p>Create a directory to store your OpenRAG configuration files and data, and then change to that directory:</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 function" style="color:#d73a49">mkdir</span><span class="token plain"> openrag-workspace</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain"></span><span class="token builtin class-name">cd</span><span class="token plain"> openrag-workspace</span><br></span></code></pre></div></div>
</li>
<li class="">
<p>Get and run the installer script:</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 function" style="color:#d73a49">curl</span><span class="token plain"> </span><span class="token parameter variable" style="color:#36acaa">-fsSL</span><span class="token plain"> https://docs.openr.ag/files/run_openrag_with_prereqs.sh </span><span class="token operator" style="color:#393A34">|</span><span class="token plain"> </span><span class="token function" style="color:#d73a49">bash</span><br></span></code></pre></div></div>
<p>The installer script installs OpenRAG with <a href="https://docs.astral.sh/uv/guides/tools/#running-tools" target="_blank" rel="noopener noreferrer" class=""><code>uvx</code></a> in the directory where you run the script.</p>
</li>
<li class="">
<p>Wait while the installer script prepares your environment and installs OpenRAG.
You might be prompted to install certain dependencies if they aren&#x27;t already present in your environment.</p>
<p>The entire process can take a few minutes.
Once the environment is ready, the OpenRAG TUI starts.</p>
<p><img decoding="async" loading="lazy" alt="OpenRAG TUI Interface" src="/assets/images/openrag_tui_dec_2025-c7022e66cc6675f25aced7b8acd8274d.png" width="653" height="397" class="img_ev3q"></p>
<p>Because the installer script uses <code>uvx</code>, it creates a cached, ephemeral environment in your local <code>uv</code> cache, and your OpenRAG configuration files and data are stored separately from the <code>uv</code> cache.
Clearing the cache doesn&#x27;t delete your entire OpenRAG installation, only the temporary TUI environment.
After clearing the cache, run <code>uvx openrag</code> to <a class="" href="/tui">access the TUI</a> and continue with your preserved configuration and data.</p>
</li>
</ol>
<p>If you encounter errors during installation, see <a class="" href="/support/troubleshoot">Troubleshoot OpenRAG</a>.</p>
<h2 class="anchor anchorTargetStickyNavbar_Vzrq" id="setup">Set up OpenRAG with the TUI<a href="#setup" class="hash-link" aria-label="Direct link to Set up OpenRAG with the TUI" title="Direct link to Set up OpenRAG with the TUI" translate="no"></a></h2>
<p>When you install OpenRAG with the installer script, you manage the OpenRAG services with the TUI.
The TUI guides you through the initial configuration process before you start the OpenRAG services.</p>
<p>Your configuration values are stored in an <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a> that is created automatically at <code>~/.openrag/tui</code>.
If OpenRAG detects an existing <code>.env</code> file in this directory, then the TUI can populate those values automatically during setup and onboarding.</p>
<p>Container definitions are stored in the <code>docker-compose</code> files in the same directory as the OpenRAG <code>.env</code> file.</p>
<p>You can use either <strong>Basic Setup</strong> or <strong>Advanced Setup</strong> to configure OpenRAG.
This choice determines how OpenRAG authenticates with your deployment&#x27;s <a class="" href="/knowledge">OpenSearch instance</a>, and it controls user access to documents stored in your OpenSearch knowledge base:</p>
<ul>
<li class="">
<p><strong>No-auth mode</strong>: If you select <strong>Basic Setup</strong> in the <a class="" href="/tui">TUI</a>, or your <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a> doesn&#x27;t include OAuth credentials, then the OpenRAG OpenSearch instance runs in no-auth mode.</p>
<p>This mode uses one anonymous JWT token for OpenSearch authentication.
There is no differentiation between users; all users that access your OpenRAG instance can access all documents uploaded to your knowledge base.</p>
</li>
<li class="">
<p><strong>OAuth mode</strong>: If you select <strong>Advanced Setup</strong> in the <a class="" href="/tui">TUI</a>, or your <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a> includes OAuth credentials, then the OpenRAG OpenSearch instance runs in OAuth mode.</p>
<p>This mode uses a unique JWT token for each OpenRAG user, and each document is tagged with user ownership.
Documents are filtered by user owner; users see only the documents that they uploaded or have access to through their cloud storage accounts.</p>
<p>To enable OAuth mode after initial setup, see <a class="" href="/ingestion#oauth-ingestion">Ingest files with OAuth connectors</a>.</p>
</li>
</ul>
<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>You must use <strong>Advanced Setup</strong> if you want to <a class="" href="/ingestion#oauth-ingestion">use OAuth connectors to upload documents from cloud storage</a>.</p></div></div>
<p>If OpenRAG detects OAuth credentials during setup, it recommends <strong>Advanced Setup</strong> in the TUI.</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">Basic setup</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_LNqP">Advanced setup</li></ul><div class="margin-top--md"><div role="tabpanel" class="tabItem_Ymn6"><ol>
<li class="">
<p>In the TUI, select <strong>Basic Setup</strong>.</p>
</li>
<li class="">
<p>Enter administrator passwords for the OpenRAG OpenSearch and Langflow services.</p>
<p>The OpenSearch password is required, and a secure password is automatically generated if you don&#x27;t provide one manually.</p>
<p>The Langflow password is recommended but optional.
If the Langflow password is empty, the Langflow server starts without authentication enabled. For more information, see <a class="" href="/reference/configuration#langflow-settings">Langflow settings</a>.</p>
<p>You can click <strong>Generate Password</strong> to create a Langflow password and username automatically.</p>
</li>
<li class="">
<p>Optional: Under <strong>API Keys</strong>, enter your model provider credentials, or leave these fields empty if you want to configure model provider credentials during the application onboarding process.</p>
<p>There is no material difference between providing these values now or during the <a href="#application-onboarding" class="">application onboarding process</a>.
If you provide a credential now, it can be populated automatically during the application onboarding process if you enable the <strong>Use environment API key</strong> option.</p>
<p>OpenRAG&#x27;s core functionality requires access to language and embedding models.
By default, OpenRAG uses OpenAI models.
If you aren&#x27;t sure which models or providers to use, you must provide an OpenAI API key to use OpenRAG&#x27;s default model configuration.</p>
</li>
<li class="">
<p>Optional: Under <strong>Others</strong>, edit the <a class="" href="/knowledge">knowledge base</a> paths if you don&#x27;t want to use the default paths:</p>
<ul>
<li class=""><strong>Documents Paths</strong>: One or more paths to directories are where OpenRAG looks for documents to ingest.</li>
<li class=""><strong>OpenSearch Data Path</strong>: Specify the path where you want OpenRAG to create your OpenSearch index.</li>
</ul>
</li>
<li class="">
<p>Click <strong>Save Configuration</strong>.</p>
<p>Your passwords and API keys, if provided, are stored in the <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a> at <code>~/.openrag/tui</code>.
If you modified any credentials that were pulled from an existing <code>.env</code> file, those values are updated in the <code>.env</code> file.</p>
</li>
<li class="">
<p>Click <strong>Start OpenRAG</strong> to start the OpenRAG services.</p>
<p>This process can take some time while OpenRAG pulls and runs the container images.
If all services start successfully, the TUI prints a confirmation message:</p>
<div class="language-text codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-text 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">Services started successfully</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">Command completed successfully</span><br></span></code></pre></div></div>
</li>
<li class="">
<p>Click <strong>Close</strong>, and then click <strong>Launch OpenRAG</strong> or navigate to <code>localhost:3000</code> in your browser.</p>
</li>
<li class="">
<p>Continue with the <a href="#application-onboarding" class="">application onboarding process</a>.</p>
</li>
</ol></div><div role="tabpanel" class="tabItem_Ymn6" hidden=""><ol>
<li class="">
<p>In the TUI, select <strong>Advanced Setup</strong>.</p>
</li>
<li class="">
<p>Enter administrator passwords for the OpenRAG OpenSearch and Langflow services.</p>
<p>The OpenSearch password is required, and a secure password is automatically generated if you don&#x27;t provide one manually.</p>
<p>The Langflow password is recommended but optional.
If the Langflow password is empty, the Langflow server starts without authentication enabled. For more information, see <a class="" href="/reference/configuration#langflow-settings">Langflow settings</a>.</p>
<p>You can click <strong>Generate Password</strong> to create a Langflow password and username automatically.</p>
</li>
<li class="">
<p>Optional: Under <strong>API Keys</strong>, enter your model provider credentials, or leave the <strong>OpenAI</strong>, <strong>Anthropic</strong>, <strong>Ollama</strong>, and <strong>IBM watsonx.ai</strong> fields empty if you want to configure model provider credentials during the application onboarding process.</p>
<p>There is no material difference between providing these values now or during the <a href="#application-onboarding" class="">application onboarding process</a>.
If you provide a credential now, it can be populated automatically during the application onboarding process if you enable the <strong>Use environment API key</strong> option.</p>
<p>OpenRAG&#x27;s core functionality requires access to language and embedding models.
By default, OpenRAG uses OpenAI models.
If you aren&#x27;t sure which models or providers to use, you must provide an OpenAI API key to use OpenRAG&#x27;s default model configuration.</p>
</li>
<li class="">
<p>Recommended: To upload documents from external storage, such as Google Drive, add the required OAuth credentials for the connectors that you want to use under <strong>API Keys</strong>. These settings can be populated automatically if OpenRAG detects these credentials in an <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a> at <code>~/.openrag/tui</code>.</p>
<ul>
<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>
<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>
</ul>
<p>You can <a class="" href="/ingestion#oauth-ingestion">manage OAuth credentials</a> later, but it is recommended to configure them during initial set up.</p>
</li>
<li class="">
<p>Register the redirect URIs shown in the TUI in your OAuth provider.
These are the URLs your OAuth provider will use to redirect users back to OpenRAG after they sign in.</p>
</li>
<li class="">
<p>Optional: Under <strong>Others</strong>, you can edit the following settings if needed:</p>
<ul>
<li class=""><strong>Documents Paths</strong>: Use the default path or provide one or more paths to directories are where OpenRAG looks for documents to ingest in to your <a class="" href="/knowledge">knowledge base</a>.</li>
<li class=""><strong>OpenSearch Data Path</strong>: Specify the path where you want OpenRAG to create your OpenSearch index.</li>
<li class=""><strong>Langflow Public URL (<code>LANGFLOW_PUBLIC_URL</code>)</strong> : Sets the base address to access the Langflow web interface. This is where users interact with flows in a browser.</li>
<li class=""><strong>Webhook Base URL (<code>WEBHOOK_BASE_URL</code>)</strong>: If applicable, set the base address for your OAuth connector endpoints. If set, the OAuth connector webhook URLs are constructed as <code>WEBHOOK_BASE_URL/connectors/${provider}/webhook</code>.</li>
</ul>
</li>
<li class="">
<p>Click <strong>Save Configuration</strong>.</p>
<p>Your passwords, API key, and OAuth credentials, if provided, are stored in the <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a> at <code>~/.openrag/tui</code>.
If you modified any credentials that were pulled from an existing <code>.env</code> file, those values are updated in the <code>.env</code> file.</p>
</li>
<li class="">
<p>Click <strong>Start OpenRAG</strong> to start the OpenRAG services.</p>
<p>This process can take some time while OpenRAG pulls and runs the container images.
If all services start successfully, the TUI prints a confirmation message:</p>
<div class="language-text codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_QJqH"><pre tabindex="0" class="prism-code language-text 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">Services started successfully</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">Command completed successfully</span><br></span></code></pre></div></div>
</li>
<li class="">
<p>Click <strong>Close</strong>, and then click <strong>Launch OpenRAG</strong> or navigate to <code>localhost:3000</code> in your browser.</p>
</li>
<li class="">
<p>If you enabled OAuth connectors, you must sign in to your OAuth provider before being redirected to your OpenRAG instance.</p>
</li>
<li class="">
<p>Continue with the <a href="#application-onboarding" class="">application onboarding process</a>.</p>
</li>
</ol></div></div></div>
<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&#x27;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>Use environment API key</strong> to pull the key from your <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a>.</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&#x27;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>For <strong>watsonx.ai API Endpoint</strong>, select the base URL for your watsonx.ai model deployment.</p>
</li>
<li class="">
<p>Enter your watsonx.ai deployment&#x27;s project ID and API key.</p>
<p>You can enable <strong>Use environment API key</strong> to pull the key from your <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a>.</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&#x27;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=""><p>Using Ollama as your language and embedding model provider offers greater flexibility and configuration options for hosting models.
However, it requires additional setup because Ollama isn&#x27;t included with OpenRAG.
You must deploy Ollama separately if you want to use Ollama as a model provider.</p><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>OpenRAG isn&#x27;t guaranteed to be compatible with all models that are available through Ollama.
For example, some models might produce unexpected results, such as JSON-formatted output instead of natural language responses, and some models aren&#x27;t appropriate for the types of tasks that OpenRAG performs, such as those that generate media.</p>
<p>The OpenRAG team recommends the following models when using Ollama as your model provider:</p>
<ul>
<li class="">
<p><strong>Language models</strong>: <code>gpt-oss:20b</code> or <code>mistral-nemo:12b</code>.</p>
<p>If you choose <code>gpt-oss:20b</code>, consider using Ollama Cloud or running Ollama on a remote machine because this model requires at least 16GB of RAM.</p>
</li>
<li class="">
<p><strong>Embedding models</strong>: <a href="https://ollama.com/library/nomic-embed-text" target="_blank" rel="noopener noreferrer" class=""><code>nomic-embed-text:latest</code></a>, <code>mxbai-embed-large:latest</code>, or <code>embeddinggemma:latest</code>.</p>
</li>
</ul>
<p>You can experiment with other models, but if you encounter issues that you are unable to resolve through other RAG best practices (like context filters and prompt engineering), try switching to one of the recommended models.
You can submit an <a href="https://github.com/langflow-ai/openrag/issues" target="_blank" rel="noopener noreferrer" class="">OpenRAG GitHub issue</a> to request support for specific models.</p></div></div><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 the OpenRAG onboarding dialog, enter your Ollama server&#x27;s base URL:</p>
<ul>
<li class=""><strong>Local Ollama server</strong>: Enter your Ollama server&#x27;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&#x27;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&#x27;s base URL and port, such as <code>http://your-remote-server:11434</code>.</li>
</ul>
</li>
<li class="">
<p>Select the language model that your Ollama server is running.</p>
<p>If your server isn&#x27;t running any language models, you must either deploy a language model on your Ollama server, or use another provider for the language model.</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>
</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&#x27;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 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>Use environment API key</strong> to pull the key from your <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a>.</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&#x27;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&#x27;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>
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