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-Instruct
+    Generate a literature survey based on paper abstracts using Groq API with Llama-3.3-70B-Versatile
     
     Parameters:
     papers (list): List of papers with abstracts
@@ -491,19 +491,16 @@ def generate_literature_survey(papers, api_key="gsk_G80LBPxmvDjQZ77zX0FIWGdyb3FY
     Returns:
     str: Generated literature survey
     """
-    # Check if we have papers with abstracts
     if not papers or len(papers) == 0:
         return "No papers found to generate a literature survey."
     
-    # Filter papers that have abstracts
     papers_with_abstracts = [p for p in papers if p.get("Abstract") and len(p.get("Abstract")) > 50]
     
     if len(papers_with_abstracts) == 0:
         return "Cannot generate a literature survey because none of the papers have substantial abstracts."
     
-    # Construct the prompt for the LLM
     paper_info = []
-    for i, paper in enumerate(papers_with_abstracts[:10]):  # Limit to 10 papers to avoid token limits
+    for i, paper in enumerate(papers_with_abstracts[:10]):
         paper_info.append(f"Paper {i+1}:\nTitle: {paper.get('Title', 'Unknown')}\nAuthors: {paper.get('Author(s)', 'Unknown')}\nYear: {paper.get('Published', 'Unknown')}\nAbstract: {paper.get('Abstract', 'No abstract available')}\n")
     
     papers_text = "\n".join(paper_info)
@@ -515,24 +512,20 @@ write a concise literature survey that:
 3. Summarizes key findings
 4. Points out research gaps if evident
 5. Suggests potential future research directions
-
 Here are the papers:
-
 {papers_text}
-
 Please organize the survey by themes rather than by individual papers, creating connections between studies.
 Format your response with markdown headings for better readability.
 """
 
-    # Make the API request to Groq
-    url = "https://api.groq.com/openai/v1/chat/completions"
+    url = "https://api.groq.com/v1/chat/completions"  # Updated endpoint
     headers = {
         "Authorization": f"Bearer {api_key}",
         "Content-Type": "application/json"
     }
     
     data = {
-        "model": "meta-llama/Llama-3.3-70B-Instruct",
+        "model": "llama-70b",  # Adjust this based on Groq's available models
         "messages": [
             {"role": "system", "content": "You are an academic research assistant that creates comprehensive literature surveys."},
             {"role": "user", "content": prompt}
@@ -548,9 +541,15 @@ Format your response with markdown headings for better readability.
         survey_text = result["choices"][0]["message"]["content"]
         return survey_text
     except Exception as e:
-        st.error(f"Error generating literature survey: {e}")
         return f"Failed to generate literature survey due to an error: {str(e)}"
 
+# 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."}
+]
+survey = generate_literature_survey(papers, api_key="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")
+print(survey)
+
 # Add the add_literature_survey_button function
 def add_literature_survey_button(search_results_df):
     """