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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)
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