fix: logo location and description width

app.py

@@ -61,7 +61,7 @@ EXAMPLES = [
 
 HEADER = """
 <div style="width: 100%; display: flex; flex-direction: column; gap: 24px; padding-top: 24px; position: relative">
-    <img src="https://postimage.me/images/2024/12/19/ICONGLIDER.md.png" width="350" style="position: absolute; top: 0; right: 36px">
+    <img src="https://postimage.me/images/2024/12/19/ICONGLIDER.md.png" width="400" style="position: absolute; top: 0; right: 12px">
     <div style="display: flex; justify-content: space-between; z-index: 1;">
         <a href="https://www.patronus.ai">
             <img src="https://postimage.me/images/2024/12/19/patronuslogo-white.png" width="250">
@@ -83,10 +83,10 @@ HEADER = """
         <h2 style="color: #fff !important">Patronus GLIDER Demo</h2>
     </div>
 </div>
-<br><br>
-<div style="color: #fff !important"><span style="color: inherit; font-weight: 600">GLIDER</span> is a powerful 3B evaluator LLM that can score any text input and associated context on arbitrary user defined criteria.</div>
-<br><br>
-<div style="color: #fff !important"><span style="color: inherit; font-weight: 600">Getting Started</span>: First, provide a model output (text generated by your model) and user input (text used to prompt your model) and optionally a gold answer (label or gold answer to the prompt) and retrieved context (context used for text generated by your model). Next, provide a pass criteria (description of a passing evaluation). Finally, provide an optional rubric (scoring scales with explanations) and then click submit. The GLIDER Output panel will provide a score and reasoning which is a human readable explanation of the score.</div>
+<br>
+<div style="color: #fff !important; width: 60%"><span style="color: inherit; font-weight: 600">GLIDER</span> is a powerful 3B evaluator LLM that can score any text input and associated context on arbitrary user defined criteria.</div>
+<br>
+<div style="color: #fff !important; width: 60%;"><span style="color: inherit; font-weight: 600">Getting Started</span>: First, provide a model output (text generated by your model) and user input (text used to prompt your model) and optionally a gold answer (label or gold answer to the prompt) and retrieved context (context used for text generated by your model). Next, provide a pass criteria (description of a passing evaluation). Finally, provide an optional rubric (scoring scales with explanations) and then click submit. The GLIDER Output panel will provide a score and reasoning which is a human readable explanation of the score.</div>
 
 """