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import os
import requests
import zipfile
import subprocess
import shutil
from huggingface_hub import snapshot_download
# Clone or update the llama.cpp repository with shallow cloning
def clone_or_update_llama_cpp():
print("Preparing...")
base_dir = os.path.dirname(os.path.abspath(__file__))
os.chdir(base_dir)
if not os.path.exists("llama.cpp"):
subprocess.run(["git", "clone", "--depth", "1", "https://github.com/ggerganov/llama.cpp"])
else:
os.chdir("llama.cpp")
subprocess.run(["git", "pull"])
os.chdir(base_dir)
print("The 'llama.cpp' repository is ready.")
# Cownload and extract the latest release of llama.cpp
def download_llama_release():
base_dir = os.path.dirname(os.path.abspath(__file__))
dl_dir = os.path.join(base_dir, "bin", "dl")
if not os.path.exists(dl_dir):
os.makedirs(dl_dir)
os.chdir(dl_dir)
latest_release_url = "https://github.com/ggerganov/llama.cpp/releases/latest"
response = requests.get(latest_release_url)
if response.status_code == 200:
latest_release_tag = response.url.split("/")[-1]
download_url = f"https://github.com/ggerganov/llama.cpp/releases/download/{latest_release_tag}/llama-{latest_release_tag}-bin-win-cublas-cu12.2.0-x64.zip"
response = requests.get(download_url)
if response.status_code == 200:
with open(f"llama-{latest_release_tag}-bin-win-cublas-cu12.2.0-x64.zip", "wb") as f:
f.write(response.content)
with zipfile.ZipFile(f"llama-{latest_release_tag}-bin-win-cublas-cu12.2.0-x64.zip", "r") as zip_ref:
zip_ref.extractall(os.path.join(base_dir, "bin"))
print("Downloading latest 'llama.cpp' prebuilt Windows binaries...")
print("Download and extraction completed successfully.")
return latest_release_tag
else:
print("Failed to download the release file.")
else:
print("Failed to fetch the latest release information.")
# Download and extract cudart if necessary
def download_cudart_if_necessary(latest_release_tag):
base_dir = os.path.dirname(os.path.abspath(__file__))
cudart_dl_dir = os.path.join(base_dir, "bin", "dl")
if not os.path.exists(cudart_dl_dir):
os.makedirs(cudart_dl_dir)
cudart_zip_file = os.path.join(cudart_dl_dir, "cudart-llama-bin-win-cu12.2.0-x64.zip")
cudart_extracted_files = ["cublas64_12.dll", "cublasLt64_12.dll", "cudart64_12.dll"]
# Check if all required files exist
if all(os.path.exists(os.path.join(base_dir, "bin", file)) for file in cudart_extracted_files):
print("Cuda resources already exist. Skipping download.")
else:
cudart_download_url = f"https://github.com/ggerganov/llama.cpp/releases/download/{latest_release_tag}/cudart-llama-bin-win-cu12.2.0-x64.zip"
response = requests.get(cudart_download_url)
if response.status_code == 200:
with open(cudart_zip_file, "wb") as f:
f.write(response.content)
with zipfile.ZipFile(cudart_zip_file, "r") as zip_ref:
zip_ref.extractall(os.path.join(base_dir, "bin"))
print("Preparing 'cuda' resources...")
print("Download and extraction of cudart completed successfully.")
else:
print("Failed to download the cudart release file.")
# Collect user input and download the specified model repository
def download_model_repo():
base_dir = os.path.dirname(os.path.abspath(__file__))
models_dir = os.path.join(base_dir, "models")
if not os.path.exists(models_dir):
os.makedirs(models_dir)
model_id = input("Enter the model ID to download (e.g., huggingface/transformers): ")
model_name = model_id.split("/")[-1]
model_dir = os.path.join(models_dir, model_name)
# Download the model repository if it doesn't exist
if not os.path.exists(model_dir):
revision = input("Enter the revision (branch, tag, or commit) to download (default: main): ") or "main"
print("Downloading model repository...")
snapshot_download(repo_id=model_id, local_dir=model_dir, revision=revision)
print("Model repository downloaded successfully.")
else:
print("Model already exists.")
# Convert the downloaded model to GGUF F16 format and generate imatrix.dat
convert_model_to_gguf_f16(base_dir, model_dir, model_name)
# Convert the downloaded model to GGUF F16 format
def convert_model_to_gguf_f16(base_dir, model_dir, model_name):
convert_script = os.path.join(base_dir, "llama.cpp", "convert.py")
gguf_dir = os.path.join(base_dir, "models", f"{model_name}-GGUF")
gguf_model_path = os.path.join(gguf_dir, f"{model_name}-F16.gguf")
if not os.path.exists(gguf_dir):
os.makedirs(gguf_dir)
# Execute the conversion command if F16 file doesn't exist
if not os.path.exists(gguf_model_path):
subprocess.run(["python", convert_script, model_dir, "--outfile", gguf_model_path, "--outtype", "f16"])
# Delete the original model directory
shutil.rmtree(model_dir)
print(f"Original model directory '{model_dir}' deleted.")
# Execute the imatrix command if imatrix.dat doesn't exist
imatrix_exe = os.path.join(base_dir, "bin", "imatrix.exe")
imatrix_output = os.path.join(gguf_dir, "imatrix.dat")
imatrix_txt = os.path.join(base_dir, "imatrix", "imatrix.txt")
if not os.path.exists(imatrix_output):
subprocess.run([imatrix_exe, "-m", gguf_model_path, "-f", imatrix_txt, "-ngl", "13"])
# Move the imatrix.dat file to the GGUF folder
shutil.move("imatrix.dat", gguf_dir)
print("imatrix.dat generated successfully.")
# Quantize the models
quantize_models(base_dir, model_name)
# Qantize models with different options
def quantize_models(base_dir, model_name):
gguf_dir = os.path.join(base_dir, "models", f"{model_name}-GGUF")
f16_gguf_path = os.path.join(gguf_dir, f"{model_name}-F16.gguf")
quantization_options = [
"Q4_K_M", "Q4_K_S", "IQ4_NL", "IQ4_XS", "Q5_K_M",
"Q5_K_S", "Q6_K", "Q8_0", "IQ3_M", "IQ3_S", "IQ3_XS", "IQ3_XXS"
]
for quant_option in quantization_options:
quantized_gguf_name = f"{model_name}-{quant_option}-imat.gguf"
quantized_gguf_path = os.path.join(gguf_dir, quantized_gguf_name)
quantize_command = os.path.join(base_dir, "bin", "quantize.exe")
imatrix_path = os.path.join(gguf_dir, "imatrix.dat")
subprocess.run([quantize_command, "--imatrix", imatrix_path,
f16_gguf_path, quantized_gguf_path, quant_option], cwd=gguf_dir)
print(f"Model quantized with {quant_option} option.")
# Main function - Steps
def main():
clone_or_update_llama_cpp()
latest_release_tag = download_llama_release()
download_cudart_if_necessary(latest_release_tag)
download_model_repo()
print("Finished preparing resources.")
if __name__ == "__main__":
main()
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