Update app.py

app.py

@@ -64,42 +64,33 @@ def extract_keywords_with_gpt(user_input, max_tokens=100, temperature=0.3):
     
     return extracted_keywords
 
-def fetch_nasa_ads_references(prompt):
+def fetch_nasa_ads_references(user_input):
     try:
-        # Step 1: Extract keywords using GPT (or another keyword extraction method)
-        keywords = extract_keywords_with_gpt(prompt)  # Assuming you have this function
+        # Step 1: Extract keywords using GPT (assuming you have this function)
+        keywords = extract_keywords_with_gpt(user_input)
 
-        # Step 2: Refine the query using the extracted keywords
-        simplified_query = keywords  # Or use the full prompt if no keyword extraction is done
+        # Step 2: Build a query using the extracted keywords
+        simplified_query = keywords  # Use keywords as the query
 
         # Step 3: Query NASA ADS for relevant papers
         papers = ADS.query_simple(simplified_query)
 
         if not papers or len(papers) == 0:
-            return [("No results found", "N/A", "N/A", "N/A", "N/A", "N/A")]
-
-        # Step 4: Extract references with title, authors, bibcode, DOI, journal, and publication date
-        references = []
-        for paper in papers[:5]:  # Limit to 5 references
-            title = paper['title'][0]
-            authors = ", ".join(paper['author'][:3]) + (" et al." if len(paper['author']) > 3 else "")
-            bibcode = paper['bibcode']
-
-            # Fetch DOI if available
-            doi = paper.get('doi', ['N/A'])[0]
-            doi_link = f"https://doi.org/{doi}" if doi != "N/A" else "N/A"
-
-            # Fetch journal and publication date
-            journal = paper.get('pub', 'Unknown Journal')
-            pubdate = paper.get('pubdate', 'Unknown Date')
-
-            # Add the extracted info to the list of references
-            references.append((title, authors, journal, pubdate, bibcode, doi_link))
-
+            return [("No results found", "N/A", "N/A")]
+        
+        # Step 4: Extract title, authors, and bibcode from the papers
+        references = [
+            (
+                paper['title'][0], 
+                ", ".join(paper['author'][:3]) + (" et al." if len(paper['author']) > 3 else ""), 
+                paper['bibcode']
+            ) 
+            for paper in papers[:5]  # Limit to 5 references
+        ]
         return references
-
+    
     except Exception as e:
-        return [("Error fetching references", str(e), "N/A", "N/A", "N/A", "N/A")]
+        return [("Error fetching references", str(e), "N/A")]
 
 def fetch_exoplanet_data():
     # Connect to NASA Exoplanet Archive TAP Service
@@ -142,7 +133,7 @@ def generate_response(user_input, relevant_context="", references=[], max_tokens
     if references:
         response_content = response.choices[0].message.content.strip()
         references_text = "\n\nADS References:\n" + "\n".join(
-            [f"- {title} by {authors}, {journal}, published on {pubdate} (Bibcode: {bibcode}) [DOI: {doi_link}]" for title, authors, journal, pubdate, bibcode, doi_link in references]
+            [f"- {title} by {authors} (Bibcode: {bibcode})" for title, authors, bibcode in references]
         )
         return f"{response_content}\n{references_text}"