Update app.py

app.py

@@ -69,28 +69,43 @@ class VeterinaryLiteratureMiner:
 
     def _search_pubmed(self, query: str, max_results: int) -> List[Dict]:
         """Search PubMed for veterinary papers"""
-        # Enhance query with veterinary terms
-        enhanced_query = f"({query}) AND (veterinary OR animal OR pet OR livestock OR zoo OR wildlife)"
-        
-        # Search PubMed
-        search_url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi"
-        search_params = {
-            "db": "pubmed",
-            "term": enhanced_query,
-            "retmax": max_results,
-            "retmode": "json",
-            "sort": "relevance"
-        }
-        
         try:
-            search_response = requests.get(search_url, params=search_params)
+            print(f"Searching PubMed with query: {query}")  # Debug print
+            
+            # Enhance query with veterinary terms
+            enhanced_query = f"({query}) AND (veterinary OR animal OR pet OR livestock OR zoo OR wildlife)"
+            print(f"Enhanced query: {enhanced_query}")  # Debug print
+            
+            # Search PubMed
+            search_url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi"
+            search_params = {
+                "db": "pubmed",
+                "term": enhanced_query,
+                "retmax": max_results,
+                "retmode": "json",
+                "sort": "relevance"
+            }
+            
+            print("Making search request...")  # Debug print
+            search_response = requests.get(search_url, params=search_params, timeout=30)
+            print(f"Search response status: {search_response.status_code}")  # Debug print
+            
+            if search_response.status_code != 200:
+                return [{"error": f"PubMed search failed with status {search_response.status_code}"}]
+            
             search_data = search_response.json()
+            print(f"Search data received: {search_data.get('esearchresult', {}).get('count', 0)} results")  # Debug print
+            
+            if "esearchresult" not in search_data:
+                return [{"error": "Invalid response from PubMed"}]
             
-            if "esearchresult" not in search_data or not search_data["esearchresult"]["idlist"]:
-                return []
+            if not search_data["esearchresult"].get("idlist"):
+                return [{"error": "No papers found matching your query"}]
             
             # Get detailed information
             ids = search_data["esearchresult"]["idlist"]
+            print(f"Fetching details for {len(ids)} papers...")  # Debug print
+            
             fetch_url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi"
             fetch_params = {
                 "db": "pubmed",
@@ -98,13 +113,24 @@ class VeterinaryLiteratureMiner:
                 "retmode": "xml"
             }
             
-            fetch_response = requests.get(fetch_url, params=fetch_params)
+            fetch_response = requests.get(fetch_url, params=fetch_params, timeout=60)
+            print(f"Fetch response status: {fetch_response.status_code}")  # Debug print
+            
+            if fetch_response.status_code != 200:
+                return [{"error": f"Failed to fetch paper details: {fetch_response.status_code}"}]
             
             # Parse XML response
             papers = self._parse_pubmed_xml(fetch_response.text)
+            print(f"Parsed {len(papers)} papers successfully")  # Debug print
+            
             return papers
             
+        except requests.exceptions.Timeout:
+            return [{"error": "Request timed out. Please try again with fewer results."}]
+        except requests.exceptions.ConnectionError:
+            return [{"error": "Connection error. Please check your internet connection."}]
         except Exception as e:
+            print(f"Error in _search_pubmed: {str(e)}")  # Debug print
             return [{"error": f"Search failed: {str(e)}"}]
 
     def _parse_pubmed_xml(self, xml_content: str) -> List[Dict]:
@@ -379,45 +405,66 @@ def create_veterinary_gradio_interface():
     
     def search_and_analyze_vet(query, max_results, database):
         """Main function to search and analyze veterinary literature"""
-        if not query.strip():
-            return "Please enter a search query.", None, None, None, None, None
-        
-        # Search papers
-        papers = miner.search_veterinary_literature(query, max_results, database)
-        
-        if not papers or papers[0].get("error"):
-            error_msg = papers[0].get("error", "No papers found") if papers else "No papers found"
-            return f"Error: {error_msg}", None, None, None, None, None
-        
-        # Analyze papers
-        analysis = miner.analyze_veterinary_papers(papers)
-        
-        # Generate summary
-        summary = miner.generate_veterinary_summary(papers, analysis)
-        
-        # Create visualizations
-        plots = miner.create_veterinary_visualizations(analysis)
-        
-        # Create papers dataframe
-        papers_df = pd.DataFrame([
-            {
-                "PMID": p.get("pmid", "N/A"),
-                "Title": p.get("title", "N/A")[:100] + "..." if len(p.get("title", "")) > 100 else p.get("title", "N/A"),
-                "Authors": p.get("authors", "N/A"),
-                "Journal": p.get("journal", "N/A"),
-                "Year": p.get("year", "N/A")
-            }
-            for p in papers
-        ])
-        
-        return (
-            summary,
-            papers_df,
-            plots.get("year_dist"),
-            plots.get("animal_species"),
-            plots.get("specialties"),
-            plots.get("conditions")
-        )
+        try:
+            print(f"Starting search with query: {query}")  # Debug print
+            
+            if not query.strip():
+                return "Please enter a search query.", None, None, None, None, None
+            
+            # Search papers
+            print("Searching papers...")  # Debug print
+            papers = miner.search_veterinary_literature(query, max_results, database)
+            print(f"Found {len(papers) if papers else 0} papers")  # Debug print
+            
+            if not papers:
+                return "No papers found. Try a different search query.", None, None, None, None, None
+            
+            if papers[0].get("error"):
+                error_msg = papers[0].get("error", "Unknown error occurred")
+                return f"Search Error: {error_msg}", None, None, None, None, None
+            
+            # Analyze papers
+            print("Analyzing papers...")  # Debug print
+            analysis = miner.analyze_veterinary_papers(papers)
+            
+            if analysis.get("error"):
+                return f"Analysis Error: {analysis['error']}", None, None, None, None, None
+            
+            # Generate summary
+            print("Generating summary...")  # Debug print
+            summary = miner.generate_veterinary_summary(papers, analysis)
+            
+            # Create visualizations
+            print("Creating visualizations...")  # Debug print
+            plots = miner.create_veterinary_visualizations(analysis)
+            
+            # Create papers dataframe
+            print("Creating dataframe...")  # Debug print
+            papers_df = pd.DataFrame([
+                {
+                    "PMID": p.get("pmid", "N/A"),
+                    "Title": p.get("title", "N/A")[:100] + "..." if len(p.get("title", "")) > 100 else p.get("title", "N/A"),
+                    "Authors": p.get("authors", "N/A"),
+                    "Journal": p.get("journal", "N/A"),
+                    "Year": p.get("year", "N/A")
+                }
+                for p in papers
+            ])
+            
+            print("Search and analysis complete!")  # Debug print
+            return (
+                summary,
+                papers_df,
+                plots.get("year_dist"),
+                plots.get("animal_species"),
+                plots.get("specialties"),
+                plots.get("conditions")
+            )
+            
+        except Exception as e:
+            error_message = f"Unexpected error: {str(e)}"
+            print(f"Error in search_and_analyze_vet: {error_message}")  # Debug print
+            return error_message, None, None, None, None, None
     
     # Create interface
     with gr.Blocks(title="Veterinary Literature Mining Agent", theme=gr.themes.Soft()) as interface:
@@ -453,7 +500,7 @@ def create_veterinary_gradio_interface():
                         value="pubmed",
                         label="Database"
                     )
-                search_btn = gr.Button("🔍 Search Veterinary Literature", variant="primary")
+                search_btn = gr.Button("🔍 Search Veterinary Literature", variant="primary", size="lg")
             
             with gr.Column(scale=1):
                 gr.Markdown("""
@@ -483,11 +530,12 @@ def create_veterinary_gradio_interface():
                     specialties_plot = gr.Plot(label="Veterinary Specialties")
                     conditions_plot = gr.Plot(label="Common Conditions")
         
-        # Connect the search function
+        # Connect the search function with progress indicator
         search_btn.click(
-            search_and_analyze_vet,
+            fn=search_and_analyze_vet,
             inputs=[query_input, max_results, database_choice],
-            outputs=[summary_output, papers_output, year_plot, species_plot, specialties_plot, conditions_plot]
+            outputs=[summary_output, papers_output, year_plot, species_plot, specialties_plot, conditions_plot],
+            show_progress=True
         )
         
         # Add examples