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breadcrumbs__item--active"><span class="breadcrumbs__link">Install OpenRAG with uv</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>Install OpenRAG in a Python project with uv</h1></header><p>Use <a href="https://docs.astral.sh/uv/getting-started/installation/" target="_blank" rel="noopener noreferrer" class=""><code>uv</code></a> to install OpenRAG as a managed or unmanaged dependency in a new or existing Python project.</p>
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<p>When you install OpenRAG with <code>uv</code>, you will use the <a class="" href="/tui">Terminal User Interface (TUI)</a> to configure and manage your OpenRAG deployment.</p>
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<p>For other installation methods, see <a class="" href="/install-options">Select an installation method</a>.</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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<p>The OpenRAG team recommends, at minimum, 8 GB of RAM for container VMs.
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However, if you plan to upload large files regularly, more RAM is recommended.
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For more information, see <a class="" href="/support/troubleshoot">Troubleshoot OpenRAG</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="">
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<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>
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</li>
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<li class="">
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<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>.
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Anthropic provides language models only; you must select an additional provider for embeddings.</p>
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</li>
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<li class="">
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<p><strong>IBM watsonx.ai</strong>: Get your watsonx.ai API endpoint, IBM project ID, and IBM API key from your watsonx deployment.</p>
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</li>
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<li class="">
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<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's base URL and the names of the models that you want to use.</p>
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<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't guaranteed to be compatible with all models that are available through Ollama.
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For example, some models might produce unexpected results, such as JSON-formatted output instead of natural language responses, and some models aren't appropriate for the types of tasks that OpenRAG performs, such as those that generate media.</p>
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<p>The OpenRAG team recommends the following models when using Ollama as your model provider:</p>
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<ul>
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<li class="">
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<p><strong>Language models</strong>: <code>gpt-oss:20b</code> or <code>mistral-nemo:12b</code>.</p>
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<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>
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</li>
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<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't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment that is suitable for most use cases.
|
||
The default CPU-only deployment doesn't prevent you from using GPU acceleration in external services, such as Ollama servers.</p>
|
||
</li>
|
||
</ul>
|
||
<h2 class="anchor anchorTargetStickyNavbar_Vzrq" id="install-and-start-openrag-with-uv">Install and start OpenRAG with uv<a href="#install-and-start-openrag-with-uv" class="hash-link" aria-label="Direct link to Install and start OpenRAG with uv" title="Direct link to Install and start OpenRAG with uv" translate="no"></a></h2>
|
||
<p>There are two ways to install OpenRAG with <code>uv</code>:</p>
|
||
<ul>
|
||
<li class="">
|
||
<p><a href="#uv-add" class=""><strong><code>uv add</code></strong> (Recommended)</a>: Install OpenRAG as a managed dependency in a new or existing <code>uv</code> Python project.
|
||
This is recommended because it adds OpenRAG to your <code>pyproject.toml</code> and lockfile for better management of dependencies and the virtual environment.</p>
|
||
</li>
|
||
<li class="">
|
||
<p><a href="#uv-pip-install" class=""><strong><code>uv pip install</code></strong></a>: Use the <a href="https://docs.astral.sh/uv/pip/" target="_blank" rel="noopener noreferrer" class=""><code>uv pip</code> interface</a> to install OpenRAG into an existing Python project that uses <code>pip</code>, <code>pip-tools</code>, and <code>virtualenv</code> commands.</p>
|
||
</li>
|
||
</ul>
|
||
<p>If you encounter errors during installation, see <a class="" href="/support/troubleshoot">Troubleshoot OpenRAG</a>.</p>
|
||
<h3 class="anchor anchorTargetStickyNavbar_Vzrq" id="uv-add">Use uv add<a href="#uv-add" class="hash-link" aria-label="Direct link to Use uv add" title="Direct link to Use uv add" translate="no"></a></h3>
|
||
<ol>
|
||
<li class="">
|
||
<p>Create a new <code>uv</code>-managed Python project:</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 init PROJECT_NAME</span><br></span></code></pre></div></div>
|
||
</li>
|
||
<li class="">
|
||
<p>Change into your new project 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 builtin class-name">cd</span><span class="token plain"> PROJECT_NAME</span><br></span></code></pre></div></div>
|
||
<p>Because <code>uv</code> manages the virtual environment for you, you won't see a <code>(venv)</code> prompt.
|
||
<code>uv</code> commands automatically use the project's virtual environment.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Add OpenRAG to your project:</p>
|
||
<ul>
|
||
<li class="">
|
||
<p>Add the latest version:</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 </span><span class="token function" style="color:#d73a49">add</span><span class="token plain"> openrag</span><br></span></code></pre></div></div>
|
||
</li>
|
||
<li class="">
|
||
<p>Add a specific version:</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 </span><span class="token function" style="color:#d73a49">add</span><span class="token plain"> </span><span class="token assign-left variable" style="color:#36acaa">openrag</span><span class="token operator" style="color:#393A34">==</span><span class="token number" style="color:#36acaa">0.1</span><span class="token plain">.30</span><br></span></code></pre></div></div>
|
||
</li>
|
||
<li class="">
|
||
<p>Add a local wheel:</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 </span><span class="token function" style="color:#d73a49">add</span><span class="token plain"> path/to/openrag-VERSION-py3-none-any.whl</span><br></span></code></pre></div></div>
|
||
</li>
|
||
</ul>
|
||
<p>For more options, see <a href="https://docs.astral.sh/uv/concepts/projects/dependencies/" target="_blank" rel="noopener noreferrer" class="">Managing dependencies with <code>uv</code></a>.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Optional: If you want to use a pre-populated <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a>, create one at <code>~/.openrag/tui</code> before starting OpenRAG.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Start the OpenRAG TUI:</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 openrag</span><br></span></code></pre></div></div>
|
||
</li>
|
||
</ol>
|
||
<h3 class="anchor anchorTargetStickyNavbar_Vzrq" id="uv-pip-install">Use uv pip install<a href="#uv-pip-install" class="hash-link" aria-label="Direct link to Use uv pip install" title="Direct link to Use uv pip install" translate="no"></a></h3>
|
||
<ol>
|
||
<li class="">
|
||
<p>Activate your virtual environment.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Install the OpenRAG Python package:</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 pip </span><span class="token function" style="color:#d73a49">install</span><span class="token plain"> openrag</span><br></span></code></pre></div></div>
|
||
</li>
|
||
<li class="">
|
||
<p>Optional: If you want to use a pre-populated <a class="" href="/reference/configuration">OpenRAG <code>.env</code> file</a>, create one at <code>~/.openrag/tui</code> before starting OpenRAG.</p>
|
||
</li>
|
||
<li class="">
|
||
<p>Start the OpenRAG TUI:</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 openrag</span><br></span></code></pre></div></div>
|
||
</li>
|
||
</ol>
|
||
<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 <code>uv</code>, 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'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'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'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's core functionality requires access to language and embedding models.
|
||
By default, OpenRAG uses OpenAI models.
|
||
If you aren't sure which models or providers to use, you must provide an OpenAI API key to use OpenRAG'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'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'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's core functionality requires access to language and embedding models.
|
||
By default, OpenRAG uses OpenAI models.
|
||
If you aren't sure which models or providers to use, you must provide an OpenAI API key to use OpenRAG'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'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'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'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'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'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'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'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's base URL:</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>
|
||
</li>
|
||
<li class="">
|
||
<p>Select the language model that your Ollama server is running.</p>
|
||
<p>If your server isn'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'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'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/install-uv.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"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Run the installer script</div></a><a class="pagination-nav__link pagination-nav__link--next" href="/install-uvx"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Invoke OpenRAG with uvx</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="#install-and-start-openrag-with-uv" class="table-of-contents__link toc-highlight">Install and start OpenRAG with uv</a><ul><li><a href="#uv-add" class="table-of-contents__link toc-highlight">Use uv add</a></li><li><a href="#uv-pip-install" class="table-of-contents__link toc-highlight">Use uv pip install</a></li></ul></li><li><a href="#setup" class="table-of-contents__link toc-highlight">Set up OpenRAG with the TUI</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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