added instructions

app.py

@@ -200,17 +200,58 @@ def process_file(model_name,inc_slider,progress=Progress(track_tqdm=True)):
 
     Time Taken: {result['time_taken_from_start']:.2f} seconds\n
     Total Schools in test: {len(unique_schools):.4f}\n
-    Total Schools taken: {len(random_schools):.4f}\n
     Total number of instances having Schools with HGR : {len(high_sample):.4f}\n
     Total number of instances having Schools with LGR: {len(low_sample):.4f}\n
     -----------------\n
     """
-    return text_output,plot_path,output_summary
+    return text_output,plot_path
 
 # List of models for the dropdown menu
 
 models = ["ASTRA-FT-HGR", "ASTRA-FT-LGR", "ASTRA-FT-FULL"]
-
+content = """
+<h1 style="color: white;">ASTRA: An AI Model for Analyzing Math Strategies</h1>
+
+<h3 style="color: white;">
+    <a href="https://drive.google.com/file/d/1lbEpg8Se1ugTtkjreD8eXIg7qrplhWan/view" style="color: #1E90FF; text-decoration: none;">Link To Paper</a> | 
+    <a href="https://github.com/Syudu41/ASTRA---Gates-Project" style="color: #1E90FF; text-decoration: none;">GitHub</a> | 
+    <a href="#" style="color: #1E90FF; text-decoration: none;">Project Page</a>
+</h3>
+
+<p style="color: white;">Welcome to a demo of ASTRA. ASTRA is a collaborative research project between researchers at the 
+<a href="https://www.memphis.edu" style="color: #1E90FF; text-decoration: none;">University of Memphis</a> and 
+<a href="https://www.carnegielearning.com" style="color: #1E90FF; text-decoration: none;">Carnegie Learning</a> 
+to utilize AI to improve our understanding of math learning strategies.</p>
+
+<p style="color: white;">This demo has been developed with a pre-trained model (based on an architecture similar to BERT) 
+that learns math strategies using data collected from hundreds of schools in the U.S. who have used 
+Carnegie Learning's MATHia (formerly known as Cognitive Tutor), the flagship Intelligent Tutor 
+that is part of a core, blended math curriculum.</p>
+
+<p style="color: white;">For this demo, we have used data from a specific domain (teaching ratio and proportions) within 
+7th grade math. The fine-tuning based on the pre-trained models learns to predict which strategies 
+lead to correct vs. incorrect solutions.</p>
+
+<p style="color: white;">To use the demo, please follow these steps:</p>
+
+<ol style="color: white;">
+    <li style="color: white;">Select a fine-tuned model:
+        <ul style="color: white;">
+            <li style="color: white;">ASTRA-FT-HGR: Fine-tuned with a small sample of data from schools that have a high graduation rate.</li>
+            <li style="color: white;">ASTRA-FT-LGR: Fine-tuned with a small sample of data from schools that have a low graduation rate.</li>
+            <li style="color: white;">ASTRA-FT-Full: Fine-tuned with a small sample of data from a mix of schools that have high/low graduation rates.</li>
+        </ul>
+    </li>
+    <li style="color: white;">Select a percentage of schools to analyze (selecting a large percentage may take a long time).</li>
+    <li style="color: white;">View Results:
+        <ul>
+            <li style="color: white;">The results from the fine-tuned model are displayed on the dashboard.</li>
+            <li style="color: white;">The results are shown separately for schools that have high and low graduation rates.</li>
+        </ul>
+    </li>
+</ol>
+"""
+# CSS styling for white text
 # Create the Gradio interface
 with gr.Blocks(css="""
     body {
@@ -218,6 +259,7 @@ with gr.Blocks(css="""
         font-family: 'Arial', sans-serif;
         color: #f5f5f5!important;;
     }
+
     .gradio-container {
         max-width: 850px!important;
         margin: 0 auto!important;;
@@ -389,12 +431,15 @@ tbody.svelte-18wv37q>tr.svelte-18wv37q:nth-child(odd) {
     color: white;
     background: #aca7b2;
 }
+
 .gradio-container-4-31-4 .prose h1, .gradio-container-4-31-4 .prose h2, .gradio-container-4-31-4 .prose h3, .gradio-container-4-31-4 .prose h4, .gradio-container-4-31-4 .prose h5 {
 
     color: white;
+}
 """) as demo:
-    gr.Markdown("<h1 id='title'>ASTRA</h1>", elem_id="title")
     
+    gr.Markdown("<h1 id='title'>ASTRA</h1>", elem_id="title")
+    gr.Markdown(content)
     
     with gr.Row():
         # file_input = gr.File(label="Upload a test file", file_types=['.txt'], elem_classes="file-box")
@@ -410,11 +455,11 @@ tbody.svelte-18wv37q>tr.svelte-18wv37q:nth-child(odd) {
     with gr.Row():
         output_text = gr.Textbox(label="")
         output_image = gr.Image(label="ROC")
-        output_summary = gr.Textbox(label="Summary")
+        # output_summary = gr.Textbox(label="Summary")
 
     btn = gr.Button("Submit")
  
-    btn.click(fn=process_file, inputs=[model_dropdown,increment_slider], outputs=[output_text,output_image,output_summary])
+    btn.click(fn=process_file, inputs=[model_dropdown,increment_slider], outputs=[output_text,output_image])
 
 
 # Launch the app

result.txt

@@ -3,5 +3,5 @@ total_acc: 69.02834008097166
 precisions: 0.7233000757179396
 recalls: 0.6902834008097166
 f1_scores: 0.680564448931978
-time_taken_from_start: 37.70641040802002
+time_taken_from_start: 33.72925329208374
 auc_score: 0.7527458335895701