Update app.py

app.py

@@ -1,9 +1,55 @@
+import gradio as gr
+import csv
+import re
+import tempfile
+import os
+import requests
+
+# 1. Load system prompt from a file
+with open("system_instructions.txt", "r", encoding="utf-8") as f:
+    ECO_PROMPT = f.read()
+
+# 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
+
+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 = {
+            "Authorization": f"Bearer {DEEPSEEK_API_KEY}",
+            "Content-Type": "application/json"
+        }
+
+        payload = {
+            "model": "deepseek-chat",
+            "messages": [{
+                "role": "user",
+                "content": prompt
+            }],
+            "temperature": 0.1,
+            "max_tokens": 5
+        }
+
+        response = requests.post(DEEPSEEK_API_URL, json=payload, headers=headers)
+        response.raise_for_status()
+        
+        output = response.json()['choices'][0]['message']['content']
+        match = re.search(r"\d+", output)
+        return int(match.group(0)) if match else 1
+
+    except Exception as e:
+        print(f"API Error: {str(e)}")
+        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.
     """
-    # Read the CSV
     rows = []
     with open(csv_file.name, "r", encoding="utf-8") as f:
         reader = csv.DictReader(f)
@@ -13,7 +59,6 @@ def judge_ecolinguistics_from_csv(csv_file):
     results = []
     total_score = 0
 
-    # Score each Q&A
     for r in rows:
         q_num = r.get("question_number", "")
         question = r.get("question", "")
@@ -23,7 +68,7 @@ def judge_ecolinguistics_from_csv(csv_file):
         total_score += sc
         results.append({"question_number": q_num, "score": sc})
     
-    # Write results to a new CSV in a temp file
+    # 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)
@@ -31,15 +76,55 @@ def judge_ecolinguistics_from_csv(csv_file):
         for row in results:
             writer.writerow(row)
         writer.writerow({"question_number": "Total", "score": total_score})
-        out_path = out_file.name  # This is the critical line
+        out_path = out_file.name
 
-    # Compute % score: total / (num_questions * 5) * 100
     num_questions = len(rows)
-    if num_questions > 0:
-        percentage = (total_score / (num_questions * 5)) * 100
-    else:
-        percentage = 0.0
+    percentage = (total_score / (num_questions * 5)) * 100 if num_questions > 0 else 0.0
 
-    percentage_display = f"<h2 style='font-size:2em; color:blue;'>Overall Score: {percentage:.1f}%</h2>"
+    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>
+    """
+
+    return out_path, percentage_display
+
+# Custom HTML with image support
+custom_theme = gr.themes.Default().set(
+    body_background_fill="#e8f5e9",
+    button_primary_background_fill="#2e7d32",
+    button_primary_background_fill_hover="#1b5e20",
+)
+
+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`
+    """)
+    
+    with gr.Row():
+        csv_input = gr.File(label="Upload CSV File", file_types=[".csv"])
+        csv_output = gr.File(label="Download Results")
+        html_output = gr.HTML()
+    
+    csv_input.change(
+        fn=judge_ecolinguistics_from_csv,
+        inputs=csv_input,
+        outputs=[csv_output, html_output]
+    )
 
-    return out_path, percentage_display  # Now out_path is defined
+if __name__ == "__main__":
+    demo.launch()