Update app.py

app.py

@@ -886,91 +886,40 @@ def create_interface():
                     interactive=False
                 )
         
-        with gr.Tab("ℹ️ Help & Info"):
-            gr.Markdown("""
-            ## About This Tool
-            
-            ### F Gene Analysis Pipeline
-            This comprehensive pipeline analyzes F genes through multiple computational approaches:
-            
-            #### 🎯 Gene Boundary Detection
-            - Uses deep learning to identify and extract F gene sequences from larger genomic sequences
-            - Provides confidence scores for detected boundaries
-            - Automatically trims sequences to focus on the F gene region
-            
-            #### 🔍 Gene Validation
-            - Employs k-mer based machine learning models to validate extracted sequences
-            - Provides probability scores indicating likelihood of being a genuine F gene
-            - Uses 6-mer frequency patterns for classification
-            
-            #### 🌳 Phylogenetic Analysis
-            
-            **Maximum Likelihood Trees:**
-            - Requires MAFFT (sequence alignment) and IQ-TREE (phylogenetic reconstruction)
-            - Performs model selection and bootstrap analysis
-            - Generates publication-quality phylogenetic trees
-            - Provides detailed evolutionary analysis
-            
-            **Simplified Trees:**
-            - Uses built-in algorithms for quick phylogenetic analysis
-            - Interactive visualization with similarity-based clustering
-            - Faster alternative when external tools are not available
-            
-            ### Input Requirements
-            - **DNA Sequences**: ATCG format, minimum 50 bp for meaningful analysis
-            - **FASTA Files**: Standard FASTA format with single or multiple sequences
-            - **Similarity Threshold**: 1-99% for controlling phylogenetic analysis sensitivity
-            
-            ### Dependencies
-            
-            **Required for ML Trees:**
-            ```bash
-            # Ubuntu/Debian
-            sudo apt-get install mafft iqtree
-            
-            # macOS
-            brew install mafft iqtree
-            
-            # Conda
-            conda install -c bioconda mafft iqtree
-            ```
-            
-            ### Output Files
-            - **Aligned FASTA**: Multiple sequence alignment in FASTA format
-            - **Tree File**: Newick format phylogenetic tree
-            - **HTML Tree**: Interactive visualization for web browsers (ML Simplified Tree)
-            
-            ### Troubleshooting
-            
-            **Common Issues:**
-            - *"No similar sequences found"*: Lower the similarity threshold
-            - *"Sequence too short"*: Provide sequences longer than 50 bp
-            - *"MAFFT/IQ-TREE not found"*: Install required dependencies
-            - *"Model not available"*: Check model files are properly downloaded
-            
-            **Performance Tips:**
-            - Use sequences between 100-2000 bp for optimal performance  
-            - Limit to <50 sequences for faster tree construction
-            - Lower similarity thresholds find more distant relatives
-            - Higher thresholds focus on closely related sequences
-            
-            ### Citation
-            If you use this tool in your research, please cite the appropriate methods and tools used.
-            """)
+        
         
         # Event handlers
         def run_analysis_text(dna_seq, sim_score, build_tree):
-            return run_pipeline(dna_seq, sim_score, build_tree)
-        
+            results = run_pipeline(dna_seq, sim_score, build_tree)
+            html_file_path = results.get('html_file', None)  # Fallback to check dictionary
+            return (results.get('boundary_output', ''),
+                    results.get('keras_output', ''),
+                    results.get('ml_tree_output', ''),
+                    results.get('simplified_ml_output', ''),
+                    tree_html,
+                    results.get('aligned_file', None),
+                    results.get('phy_file', None),
+                    html_file_path if html_file_path and os.path.exists(html_file_path) else None,
+                    "Analysis complete")
+
         def run_analysis_file(file_obj, sim_score, build_tree):
-            return run_pipeline_from_file(file_obj, sim_score, build_tree)
-        
+            results = run_pipeline_from_file(file_obj, sim_score, build_tree)
+            html_file_path = results.get('html_file', None)
+            return (results.get('boundary_output', ''),
+                    results.get('keras_output', ''),
+                    results.get('ml_tree_output', ''),
+                    results.get('simplified_ml_output', ''),
+                    tree_html,
+                    results.get('aligned_file', None),
+                    results.get('phy_file', None),
+                    html_file_path if html_file_path and os.path.exists(html_file_path) else None,
+                    "Analysis complete")
+
         def run_analysis_combined(dna_seq, file_obj, sim_score, build_tree):
-            # Priority: file upload over text input
             if file_obj is not None:
-                return run_pipeline_from_file(file_obj, sim_score, build_tree)
+                return run_analysis_file(file_obj, sim_score, build_tree)
             else:
-                return run_pipeline(dna_seq, sim_score, build_tree)
+                return run_analysis_text(dna_seq, sim_score, build_tree)
         
         def clear_inputs():
             return "", None, 95.0, False, "Ready to analyze"
@@ -978,14 +927,13 @@ def create_interface():
         def show_tree(html_file):
             if html_file and os.path.exists(html_file):
                 try:
-                    # Convert to relative path for Gradio file serving
                     relative_path = os.path.relpath(html_file, os.getcwd())
                     file_url = f"/file={relative_path}"
                     link_html = f'<a href="{file_url}" target="_blank">View ML Simplified Tree</a>'
                     return gr.update(value=link_html), f"File found: {relative_path}"
                 except Exception as e:
-                    return gr.update(value=f"<p>Error generating link: {str(e)}. Please download and open the file manually.</p>"), f"Error: {str(e)}"
-            return gr.update(value="<p>No tree file available. Run analysis to generate one.</p>"), "No file available"
+                    return gr.update(value=f"<p>Error generating link: {str(e)}</p>"), f"Error: {str(e)}"
+            return gr.update(value="<p>No tree file available</p>"), "No file available"
         
         # Connect events
         run_btn.click(
@@ -1023,7 +971,6 @@ def create_interface():
         )
     
     return iface
-    
 # --- Main Execution ---
 if __name__ == "__main__":
     # Initialize and launch interface