Delete selectBioModels.py

selectBioModels.py

@@ -1,81 +0,0 @@
-import os
-import re
-import pandas as pd
-import shutil
-
-# Function to search BioModels and create the CSV file
-def search_biomodels(directory, keywords, output_file):
-    biomodel_numbers_list = []
-    matching_biomodels = []
-
-    files = os.listdir(directory)
-    
-    for file in files:
-        file_path = os.path.join(directory, file)
-        
-        try:
-            with open(file_path, 'r', encoding='utf-8', errors='ignore') as f:
-                file_content = f.read()
-                
-                # Find all biomodel numbers using a more flexible regex
-                biomodel_numbers = re.findall(r'biomodels\.db/(\w+)', file_content)
-                
-                # Search for the biomodel name, case-insensitive, and allow variations
-                biomodel_name_match = re.search(rf'{re.escape(keywords[0])} is "([^"]+)"', file_content, re.IGNORECASE)
-                biomodel_name = biomodel_name_match.group(1) if biomodel_name_match else ''
-                
-                def matches_keywords(name, keywords):
-                    # Check for any keyword match in the biomodel name, case-insensitive
-                    return any(keyword.lower() in name.lower() for keyword in keywords)
-                
-                # If a matching biomodel name is found, save it
-                if biomodel_name and matches_keywords(biomodel_name, keywords):
-                    biomodel_numbers_list.extend(biomodel_numbers)
-                    matching_biomodels.extend([biomodel_name] * len(biomodel_numbers))
-        
-        except Exception as e:
-            print(f"Error processing file {file_path}: {e}")
-
-    # Create a DataFrame from the collected data
-    df = pd.DataFrame({
-        'Biomodel Number': biomodel_numbers_list,
-        'Biomodel Name': [matching_biomodels[i] if i < len(matching_biomodels) else '' for i in range(len(biomodel_numbers_list))]
-    })
-
-    # Save the DataFrame to a CSV file
-    df.to_csv(output_file, index=False)
-    print(f"Data saved to {output_file}")
-
-# Function to copy matching files to final_models directory
-def copy_matching_files(csv_file, data_folder, final_models_folder):
-    # Create the final_models folder if it doesn't exist
-    os.makedirs(final_models_folder, exist_ok=True)
-
-    # Load the CSV file into a DataFrame
-    df = pd.read_csv(csv_file)
-
-    # Iterate through the data folder to find and copy matching files
-    for root, dirs, files in os.walk(data_folder):
-        for file in files:
-            file_path = os.path.join(root, file)
-            with open(file_path, 'r', encoding='utf-8', errors='ignore') as f:
-                content = f.read()
-                # Check if any biomodel name or number is in the file
-                for i, row in df.iterrows():
-                    biomodel_number = row['Biomodel Number']
-                    biomodel_name = row['Biomodel Name']
-                    if (biomodel_name and biomodel_name.lower() in content.lower()) or biomodel_number in content:
-                        shutil.copy(file_path, final_models_folder)
-                        print(f"Copied: {file} to final_models")
-
-    print(f"All matching biomodel files have been copied to {final_models_folder}")
-
-# Main execution
-directory = r'C:\Users\navan\Downloads\BioModelsRAG\BioModelsRAG\data'
-output_file = r'C:\Users\navan\Downloads\BioModelsRAG\biomodels_output.csv'
-final_models_folder = r'C:\Users\navan\Downloads\BioModelsRAG\final_models'
-user_keywords = input("Keyword you would like to search for: ").split()
-
-# Search and copy files
-search_biomodels(directory, user_keywords, output_file)
-copy_matching_files(output_file, directory, final_models_folder)