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‎py/build-dash.html‎

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@@ -423,7 +423,7 @@ <h2 class="anchored" data-anchor-id="relevant-methods">Relevant methods</h2>
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<section id="basic-layout" class="level2">
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<h2 class="anchored" data-anchor-id="basic-layout">Basic layout</h2>
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<p>The most common pattern places chat alongside your custom filtered views:</p>
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<details class="code-fold">
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<summary>dash-custom.py</summary>
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<div class="sourceCode cell-code" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> dash_ag_grid <span class="im">as</span> dag</span>
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<section id="data-views" class="level2">
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<h2 class="anchored" data-anchor-id="data-views">Data views</h2>
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<p>The real power of querychat comes from connecting it to visualizations. Here’s an example showing both filtered data and charts:</p>
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<div id="5255cf70" class="cell" data-execution_count="2">
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<div id="733addac" class="cell" data-execution_count="2">
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<div class="sourceCode cell-code" id="cb7"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> dash_bootstrap_components <span class="im">as</span> dbc</span>
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<span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> plotly.express <span class="im">as</span> px</span>
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<span id="cb7-3"><a href="#cb7-3" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> querychat.dash <span class="im">import</span> QueryChat</span>
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<p>When users filter data through the chat (e.g., “show only survivors”), both charts update automatically.</p>
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<p><a href="./images/dash-viz.png" class="lightbox" data-gallery="quarto-lightbox-gallery-3"><img src="./images/dash-viz.png" class="shadow rounded mb-3 img-fluid" alt="Screenshot of Dash data views example."></a></p>
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<p>A more complete example adds metrics:</p>
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<details class="code-fold">
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<summary>dash-complete.py</summary>
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<div class="sourceCode cell-code" id="cb8"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> dash_bootstrap_components <span class="im">as</span> dbc</span>

‎py/build-gradio.html‎

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<section id="data-views" class="level2">
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<h2 class="anchored" data-anchor-id="data-views">Data views</h2>
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<p>The real power of querychat comes from connecting it to visualizations. Here’s an example showing two charts that respond to query changes:</p>
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<div id="c3b8c300" class="cell" data-execution_count="1">
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<div id="1ee46fa0" class="cell" data-execution_count="1">
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<div class="sourceCode cell-code" id="cb7"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> plotly.express <span class="im">as</span> px</span>
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<span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> querychat.data <span class="im">import</span> titanic</span>
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<span id="cb7-3"><a href="#cb7-3" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> querychat.gradio <span class="im">import</span> QueryChat</span>
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<p>When users filter data through the chat (e.g., “show only survivors”), both charts update automatically.</p>
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<p><a href="./images/gradio-viz.png" class="lightbox" data-gallery="quarto-lightbox-gallery-2"><img src="./images/gradio-viz.png" class="shadow rounded mb-3 img-fluid" alt="Screenshot of Gradio data views example."></a></p>
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<p>A more complete example adds metrics:</p>
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<details class="code-fold">
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<summary>gradio-complete.py</summary>
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<div class="sourceCode cell-code" id="cb8"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> plotly.express <span class="im">as</span> px</span>

‎py/build-streamlit.html‎

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<section id="data-views" class="level2">
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<h2 class="anchored" data-anchor-id="data-views">Data views</h2>
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<p>The real power of querychat comes from connecting it to visualizations. Here’s an example showing both filtered data and a chart:</p>
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<div id="8c2a78f7" class="cell" data-execution_count="1">
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<div id="1e83b353" class="cell" data-execution_count="1">
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<div class="sourceCode cell-code" id="cb8"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> plotly.express <span class="im">as</span> px</span>
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<span id="cb8-2"><a href="#cb8-2" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> querychat.data <span class="im">import</span> titanic</span>
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<span id="cb8-3"><a href="#cb8-3" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> querychat.streamlit <span class="im">import</span> QueryChat</span>
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<p>When users filter data through the chat (e.g., “show only survivors”), both views update automatically.</p>
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<p><a href="./images/streamlit-sidebar.png" class="lightbox" data-gallery="quarto-lightbox-gallery-2"><img src="./images/streamlit-sidebar.png" class="shadow rounded mb-3 img-fluid" alt="Screenshot of a querychat Streamlit app with sidebar chat and data views."></a></p>
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<p>A more complete example adds metrics:</p>
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<div id="95543f7b" class="cell" data-execution_count="2">
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<details class="code-fold">
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<summary>streamlit-complete.py</summary>
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<div class="sourceCode cell-code" id="cb9"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> plotly.express <span class="im">as</span> px</span>

‎py/build.html‎

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<p>When users filter data through the chat (e.g., “show only children”), both charts update automatically.</p>
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<p><a href="./images/plotly-data-view.png" class="lightbox" data-gallery="quarto-lightbox-gallery-2"><img src="./images/plotly-data-view.png" class="shadow rounded mb-3 img-fluid" alt="Screenshot of a querychat app showing both a data table and a bar chart of survival by class."></a></p>
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<p>A more complete example adds metrics, tabs, and multiple views:</p>
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<details class="code-fold">
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<summary>titanic-dashboard.py</summary>
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<div class="sourceCode cell-code" id="cb13"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb13-1"><a href="#cb13-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> plotly.express <span class="im">as</span> px</span>
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<p>In some cases, you might be able to “pre-join” datasets into a single table and use one <code>QueryChat</code> instance to explore them together. In the future, we may support multiple filtered tables in one chat interface, but this is not currently available. Please upvote <a href="https://github.com/posit-dev/querychat/issues/6">the relevant issue</a> if this is a feature you’d like to see!</p>
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</div>
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</div>
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<details class="code-fold">
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<summary>multiple-datasets.py</summary>
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<div class="sourceCode cell-code" id="cb16"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb16-1"><a href="#cb16-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> querychat.data <span class="im">import</span> titanic</span>

‎py/sitemap.xml‎

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<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
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<url>
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<loc>https://posit-dev.github.io/querychat/py/build.html</loc>
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</url>
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