Update app.py

app.py

@@ -885,77 +885,7 @@ 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):
@@ -981,6 +911,7 @@ def create_interface():
                     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>'
+                    print(f"Generated link for: {file_url}")  # Debug log
                     return gr.update(value=link_html)
                 except Exception as e:
                     return gr.update(value=f"<p>Error generating link: {str(e)}. Please download and open the file manually.</p>")