Update app.py

app.py

@@ -11,12 +11,11 @@ with open("system_instructions.txt", "r", encoding="utf-8") as f:
 
 # DeepSeek API configuration
 DEEPSEEK_API_KEY = os.environ.get("DEEPSEEK_API_KEY")
-DEEPSEEK_API_URL = "https://api.deepseek.com/v1/chat/completions"  # Verify actual API endpoint
+DEEPSEEK_API_URL = "https://api.deepseek.com/v1/chat/completions"
 
 def score_qa(question, answer):
     """Query DeepSeek API to get a score for Q&A pair"""
     try:
-        # Format the prompt using our template
         prompt = ECO_PROMPT.format(question=question, answer=answer)
         
         headers = {
@@ -26,10 +25,7 @@ def score_qa(question, answer):
 
         payload = {
             "model": "deepseek-chat",
-            "messages": [{
-                "role": "user",
-                "content": prompt
-            }],
+            "messages": [{"role": "user", "content": prompt}],
             "temperature": 0.1,
             "max_tokens": 5
         }
@@ -46,85 +42,79 @@ def score_qa(question, answer):
         return 1
 
 def judge_ecolinguistics_from_csv(csv_file):
-    """
-    Reads CSV of Q&A pairs, scores each,
-    returns a new CSV and a percentage score.
-    """
+    """Process CSV and return results"""
     rows = []
     with open(csv_file.name, "r", encoding="utf-8") as f:
         reader = csv.DictReader(f)
-        for r in reader:
-            rows.append(r)
+        rows = list(reader)
     
     results = []
     total_score = 0
 
     for r in rows:
-        q_num = r.get("question_number", "")
-        question = r.get("question", "")
-        answer = r.get("answer", "")
-
-        sc = score_qa(question, answer)
+        sc = score_qa(r.get("question", ""), r.get("answer", ""))
         total_score += sc
-        results.append({"question_number": q_num, "score": sc})
+        results.append({"question_number": r.get("question_number", ""), "score": sc})
     
-    # Create temporary file with proper path handling
     with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".csv", encoding="utf-8") as out_file:
-        fieldnames = ["question_number", "score"]
-        writer = csv.DictWriter(out_file, fieldnames=fieldnames)
+        writer = csv.DictWriter(out_file, fieldnames=["question_number", "score"])
         writer.writeheader()
-        for row in results:
-            writer.writerow(row)
+        writer.writerows(results)
         writer.writerow({"question_number": "Total", "score": total_score})
         out_path = out_file.name
 
-    num_questions = len(rows)
-    percentage = (total_score / (num_questions * 5)) * 100 if num_questions > 0 else 0.0
-
+    percentage = (total_score / (len(rows) * 5)) * 100 if rows else 0.0
     percentage_display = f"""
-    <div style="text-align: center;">
-        <h2 style="color: #2c3e50; font-size: 1.5em; margin-bottom: 20px;">
-            Ecolinguistics Assessment Results
-        </h2>
-        <img src="https://i.imgur.com/YK3Rk4D.png" alt="Ecology Icon" style="width: 150px; margin: 20px auto;">
-        <div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px;">
-            <p style="font-size: 1.2em; color: #27ae60; font-weight: bold;">
-                Final Score: {percentage:.1f}%
-            </p>
-        </div>
+    <div style="padding: 20px; background: #f0fff4; border-radius: 10px; margin-top: 20px;">
+        <h3 style="color: #22543d; margin: 0;">Overall Score: {percentage:.1f}%</h3>
     </div>
     """
 
     return out_path, percentage_display
 
-# Custom HTML with image support
+# Custom theme
 custom_theme = gr.themes.Default().set(
-    body_background_fill="#e8f5e9",
-    button_primary_background_fill="#2e7d32",
-    button_primary_background_fill_hover="#1b5e20",
+    body_background_fill="#f0fff4",
+    button_primary_background_fill="#38a169",
+    button_primary_text_color="#ffffff",
 )
 
 with gr.Blocks(theme=custom_theme) as demo:
-    gr.Markdown("# 🌱 Ecolinguistics Assessment System")
-    
-    # Add your uploaded image here (replace "your_image.jpg" with your actual filename)
-    gr.Image("banner.jpg", elem_id="banner", show_label=False, height=200)
-    
-    gr.Markdown("""
-    ## Upload CSV for Evaluation
-    Your CSV should contain columns: `question_number`, `question`, and `answer`
-    """)
-    
+    # Header with logo and title
     with gr.Row():
-        csv_input = gr.File(label="Upload CSV File", file_types=[".csv"])
-        csv_output = gr.File(label="Download Results")
+        gr.Image("logo.png", 
+                show_label=False,
+                width=200,
+                height=200,
+                elem_id="logo",
+                show_download_button=False)
+        
+        gr.Markdown("""
+        <div style="margin-left: 20px;">
+            <h1 style="margin-bottom: 0; color: #22543d;">🌿 EcoLingua</h1>
+            <p style="margin-top: 0.5em; color: #38a169; font-size: 1.1em;">
+                Sustainable Communication Evaluator
+            </p>
+        </div>
+        """)
+
+    # Main interface
+    with gr.Column():
+        gr.Markdown("## 📤 Upload Q&A CSV")
+        with gr.Row():
+            csv_input = gr.File(label="Upload your CSV", file_types=[".csv"])
+            csv_output = gr.File(label="Download Results", interactive=False)
+        
         html_output = gr.HTML()
-    
-    csv_input.change(
-        fn=judge_ecolinguistics_from_csv,
-        inputs=csv_input,
-        outputs=[csv_output, html_output]
-    )
+        
+        csv_input.change(
+            judge_ecolinguistics_from_csv,
+            inputs=csv_input,
+            outputs=[csv_output, html_output]
+        )
+
+    # Footer
+    gr.Markdown("---\n*System powered by DeepSeek AI | Sustainable communication analysis*")
 
 if __name__ == "__main__":
     demo.launch()