Update app.py

app.py

@@ -9,31 +9,42 @@ import requests
 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"
+# Hugging Face configuration
+HF_API_KEY = os.environ.get("HF_API_KEY")
+HF_API_URL = "https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-8B-Instruct"
+
+def format_llama3_prompt(system_prompt, question, answer):
+    """Format prompt according to Llama3's chat template"""
+    return f"""<|begin_of_text|><|start_header_id|>system<|end_header_id|>
+{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
+Question: {question}
+Answer: {answer}
+Please provide a numerical score between 1-5 based on the guidelines.<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+"""
 
 def score_qa(question, answer):
-    """Get score from DeepSeek API"""
+    """Get score from Llama3 via Hugging Face API"""
     try:
-        prompt = ECO_PROMPT.format(question=question, answer=answer)
+        prompt = format_llama3_prompt(ECO_PROMPT, question, answer)
         
         headers = {
-            "Authorization": f"Bearer {DEEPSEEK_API_KEY}",
+            "Authorization": f"Bearer {HF_API_KEY}",
             "Content-Type": "application/json"
         }
 
         payload = {
-            "model": "deepseek-chat",
-            "messages": [{"role": "user", "content": prompt}],
-            "temperature": 0.1,
-            "max_tokens": 5
+            "inputs": prompt,
+            "parameters": {
+                "max_new_tokens": 5,
+                "temperature": 0.1,
+                "return_full_text": False
+            }
         }
 
-        response = requests.post(DEEPSEEK_API_URL, json=payload, headers=headers)
+        response = requests.post(HF_API_URL, json=payload, headers=headers)
         response.raise_for_status()
         
-        output = response.json()['choices'][0]['message']['content']
+        output = response.json()[0]['generated_text']
         match = re.search(r"\d+", output)
         return int(match.group(0)) if match else 1
 
@@ -42,7 +53,7 @@ def score_qa(question, answer):
         return 1  # Fallback score
 
 def judge_ecolinguistics_from_csv(csv_file):
-    """Process CSV and generate results"""
+    """Process CSV and generate results (unchanged from original)"""
     rows = []
     with open(csv_file.name, "r", encoding="utf-8") as f:
         reader = csv.DictReader(f)
@@ -84,7 +95,7 @@ def judge_ecolinguistics_from_csv(csv_file):
 
     return out_path, percentage_display
 
-# Custom theme and styling
+# Custom theme and styling (unchanged from original)
 custom_theme = gr.themes.Default().set(
     body_background_fill="#f8fff9",
     button_primary_background_fill="#38a169",
@@ -194,7 +205,7 @@ with gr.Blocks(theme=custom_theme, css=css) as demo:
     gr.Markdown("""
     <div class="footer">
         <p style="margin: 0; color: #2e7d32; font-size: 0.9em;">
-            🍃 Powered by DeepSeek AI | Environmentally Conscious Language Analysis 🍃
+            🍃 Powered by Meta Llama3 | Environmentally Conscious Language Analysis 🍃
         </p>
     </div>
     """)