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conf/index.html

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trulens_eval/gh_top_intro/index.html

@@ -1725,7 +1725,7 @@ <h2 id="trulens-eval">TruLens-Eval<a class="headerlink" href="#trulens-eval" tit
 </li>
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 <p>The process for building your evaluated and tracked LLM application with TruLens is shown below 👇
-<img alt="Architecture Diagram" src="https://www.trulens.org/Assets/image/TruLens_Architecture.png" /></p>
+<img alt="Architecture Diagram" src="https://www.trulens.org/assets/images/TruLens_Architecture.png" /></p>
 <h3 id="installation-and-setup">Installation and setup<a class="headerlink" href="#installation-and-setup" title="Permanent link">&para;</a></h3>
 <p>Install trulens-eval from PyPI.</p>
 <div class="highlight"><pre><span></span><code>pip<span class="w"> </span>install<span class="w"> </span>trulens-eval

trulens_eval/intro/index.html

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 <h1 id="welcome-to-trulens-eval">Welcome to TruLens-Eval!<a class="headerlink" href="#welcome-to-trulens-eval" title="Permanent link">&para;</a></h1>
-<p><img alt="TruLens" src="https://www.trulens.org/Assets/image/Neural_Network_Explainability.png" /></p>
+<p><img alt="TruLens" src="https://www.trulens.org/assets/images/Neural_Network_Explainability.png" /></p>
 <p>Evaluate and track your LLM experiments with TruLens. As you work on your models and prompts TruLens-Eval supports the iterative development and of a wide range of LLM applications by wrapping your application to log key metadata across the entire chain (or off chain if your project does not use chains) on your local machine.</p>
 <p>Using feedback functions, you can objectively evaluate the quality of the responses provided by an LLM to your requests. This is completed with minimal latency, as this is achieved in a sequential call for your application, and evaluations are logged to your local machine. Finally, we provide an easy to use Streamlit dashboard run locally on your machine for you to better understand your LLM’s performance.</p>
 <h2 id="value-propositions">Value Propositions<a class="headerlink" href="#value-propositions" title="Permanent link">&para;</a></h2>
@@ -1732,7 +1732,7 @@ <h2 id="value-propositions">Value Propositions<a class="headerlink" href="#value
 </li>
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 <p>The process for building your evaluated and tracked LLM application with TruLens is below 👇</p>
-<p><img alt="Architecture Diagram" src="https://www.trulens.org/Assets/image/TruLens_Architecture.png" /></p>
+<p><img alt="Architecture Diagram" src="https://www.trulens.org/assets/images/TruLens_Architecture.png" /></p>
 <h2 id="installation-and-setup">Installation and Setup<a class="headerlink" href="#installation-and-setup" title="Permanent link">&para;</a></h2>
 <p>Install the trulens-eval pip package from PyPI.</p>
 <div class="highlight"><pre><span></span><code><span class="w">    </span>pip<span class="w"> </span>install<span class="w"> </span>trulens-eval

trulens_eval/langchain_quickstart/index.html

@@ -3580,13 +3580,13 @@ <h2 id="explore-in-a-dashboard">Explore in a Dashboard<a class="anchor-link" hre
 </div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput " data-mime-type="text/markdown">
 <h3 id="chain-leaderboard">Chain Leaderboard<a class="anchor-link" href="#chain-leaderboard">&#182;</a></h3><p>Understand how your LLM application is performing at a glance. Once you've set up logging and evaluation in your application, you can view key performance statistics including cost and average feedback value across all of your LLM apps using the chain leaderboard. As you iterate new versions of your LLM application, you can compare their performance across all of the different quality metrics you've set up.</p>
 <p>Note: Average feedback values are returned and displayed in a range from 0 (worst) to 1 (best).</p>
-<p><img src="https://www.trulens.org/Assets/image/Leaderboard.png" alt="Chain Leaderboard" /></p>
+<p><img src="https://www.trulens.org/assets/images/Leaderboard.png" alt="Chain Leaderboard" /></p>
 <p>To dive deeper on a particular chain, click &quot;Select Chain&quot;.</p>
 <h3 id="understand-chain-performance-with-evaluations">Understand chain performance with Evaluations<a class="anchor-link" href="#understand-chain-performance-with-evaluations">&#182;</a></h3><p>To learn more about the performance of a particular chain or LLM model, we can select it to view its evaluations at the record level. LLM quality is assessed through the use of feedback functions. Feedback functions are extensible methods for determining the quality of LLM responses and can be applied to any downstream LLM task. Out of the box we provide a number of feedback functions for assessing model agreement, sentiment, relevance and more.</p>
 <p>The evaluations tab provides record-level metadata and feedback on the quality of your LLM application.</p>
-<p><img src="https://www.trulens.org/Assets/image/Leaderboard.png" alt="Evaluations" /></p>
+<p><img src="https://www.trulens.org/assets/images/Leaderboard.png" alt="Evaluations" /></p>
 <h3 id="deep-dive-into-full-chain-metadata">Deep dive into full chain metadata<a class="anchor-link" href="#deep-dive-into-full-chain-metadata">&#182;</a></h3><p>Click on a record to dive deep into all of the details of your chain stack and underlying LLM, captured by tru_chain_recorder.</p>
-<p><img src="https://www.trulens.org/Assets/image/Chain_Explore.png" alt="Explore a Chain" /></p>
+<p><img src="https://www.trulens.org/assets/images/Chain_Explore.png" alt="Explore a Chain" /></p>
 <p>If you prefer the raw format, you can quickly get it using the &quot;Display full chain json&quot; or &quot;Display full record json&quot; buttons at the bottom of the page.</p>
 
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welcome/index.html

@@ -1850,7 +1850,7 @@ <h2 id="trulens-eval">TruLens-Eval<a class="headerlink" href="#trulens-eval" tit
 </li>
 </ol>
 <p>The process for building your evaluated and tracked LLM application with TruLens is shown below 👇
-<img alt="Architecture Diagram" src="https://www.trulens.org/Assets/image/TruLens_Architecture.png" /></p>
+<img alt="Architecture Diagram" src="https://www.trulens.org/assets/images/TruLens_Architecture.png" /></p>
 <h3 id="installation-and-setup">Installation and setup<a class="headerlink" href="#installation-and-setup" title="Permanent link">&para;</a></h3>
 <p>Install trulens-eval from PyPI.</p>
 <div class="highlight"><pre><span></span><code>pip<span class="w"> </span>install<span class="w"> </span>trulens-eval

welcome2/index.html

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 </li>
 </ol>
 <p>The process for building your evaluated and tracked LLM application with TruLens is shown below 👇
-<img alt="Architecture Diagram" src="https://www.trulens.org/Assets/image/TruLens_Architecture.png" /></p>
+<img alt="Architecture Diagram" src="https://www.trulens.org/assets/images/TruLens_Architecture.png" /></p>
 <h3 id="installation-and-setup">Installation and setup<a class="headerlink" href="#installation-and-setup" title="Permanent link">&para;</a></h3>
 <p>Install trulens-eval from PyPI.</p>
 <div class="highlight"><pre><span></span><code>pip<span class="w"> </span>install<span class="w"> </span>trulens-eval