Update app.py

app.py

@@ -482,7 +482,7 @@ def display_results(data):
 # Add the generate_literature_survey function below your other function definitions
 def generate_literature_survey(papers, api_key="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"):
     """
-    Generate a literature survey based on paper abstracts using Groq API with Llama-3.3-70B-Versatile
+    Generate a literature survey based on paper abstracts using Groq API with Llama-3.3-70B-Instruct
     
     Parameters:
     papers (list): List of papers with abstracts
@@ -522,14 +522,14 @@ Format your response with markdown headings for better readability.
 """
 
     # Make the API request to Groq
-    url = "https://api.groq.com/openai/v1/completions"  # Updated endpoint
+    url = "https://api.groq.com/openai/v1/chat/completions"  # Ensure this is the correct endpoint
     headers = {
         "Authorization": f"Bearer {api_key}",
         "Content-Type": "application/json"
     }
     
     data = {
-        "model": "llama-3.3-70b-versatile",  
+        "model": "llama-3.3-70b-instruct",  # Updated model name here
         "messages": [
             {"role": "system", "content": "You are an academic research assistant that creates comprehensive literature surveys."},
             {"role": "user", "content": prompt}
@@ -555,7 +555,7 @@ Format your response with markdown headings for better readability.
 
 # Example usage
 papers = [
-    {"Title": "Sample Paper", "Author(s)": "John Doe", "Published": "2023", "Abstract": "This is a sample abstract with more than 50 characters to test the function."}
+    {"Title": "Sample Paper", "Author(s)": "Mahatir Ahmed Tusher", "Published": "2023", "Abstract": "This is a sample abstract with more than 50 characters to test the function."}
 ]
 survey = generate_literature_survey(papers, api_key="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")
 print(survey)