Used with the `ollama-model-direct-download` software, you can download ollama models with one click.

ollama_model_download.py

"""
Manually download the ollama model
1. You need a software (Linux only): https://github.com/amirrezaDev1378/ollama-model-direct-download
2. Use the software to get the download links of the model, it will output 6 links. (If the file downloaded from the release page is not available, you need to install the Go environment and compile it yourself)
3. You can manually download them, or use this script to download all at once.
"""
import subprocess
import re
import json
import requests
import os
import argparse
from tqdm import tqdm


def run_command(command):
    result = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
    if result.returncode != 0:
        raise RuntimeError(f"Command execution failed: {result.stderr}")
    return result.stdout

def extract_links(output):
    pattern = r'(?:Manifest download link:|^\d+-)\s*(https?://\S+)'
    matches = re.findall(pattern, output, flags=re.MULTILINE)
    
    if not matches:
        raise ValueError("Download links not found")
    
    result = {"manifest": matches[0]}
    for i, url in enumerate(matches[1:], start=1):
        result[str(i)] = url
    return result

def download_files(links, output_dir="downloads"):
    os.makedirs(output_dir, exist_ok=True)
    
    for name, url in links.items():
        try:
            response = requests.get(url, stream=True)
            response.raise_for_status()

            # Replace colons with hyphens in the filename
            filename_part = url.split("/")[-1].replace(":", "-")
            filename = os.path.join(output_dir, filename_part)
            
            # Get total file size
            total_size = int(response.headers.get('content-length', 0))
            
            # Initialize progress bar
            with tqdm(
                total=total_size, 
                unit='B', 
                unit_scale=True,
                desc=filename,
                bar_format='{l_bar}{bar} | {n_fmt}/{total_fmt} [{elapsed}<{remaining}, {rate_fmt}]'
            ) as pbar:
                with open(filename, "wb") as f:
                    for chunk in response.iter_content(chunk_size=8192):
                        f.write(chunk)
                        pbar.update(len(chunk))
                        
            print(f"\nDownloaded: {filename}")
        except Exception as e:
            print(f"\nDownload failed {url}: {str(e)}")

def main():
    parser = argparse.ArgumentParser(description='Model downloading tool')
    parser.add_argument('-m', '--model_name', type=str, required=True, help='Name of the model to download')
    parser.add_argument('-p', '--path', type=str, default='downloads', help='Storage path')
    
    args = parser.parse_args()
    
    try:
        # Run the command and extract links
        cmd = f'./omdd-linux-amd64 get {args.model_name}'
        output = run_command(cmd)
        print(output)

        links = extract_links(output)
        print(json.dumps(links, indent=4))
        
        # Download files to the specified path
        download_files(links, args.path)
        print(f"Files saved at: {os.path.abspath(args.path)}")
    except Exception as e:
        print(f"Program execution error: {str(e)}")


if __name__ == "__main__":
    main()