import os import requests import zipfile import subprocess import shutil from huggingface_hub import snapshot_download # Clone or update the llama.cpp repository with --depth 1 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.") # Download and extract the latest release of llama.cpp Windows binaries 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-cuda-cu12.2.0-x64.zip" response = requests.get(download_url) if response.status_code == 200: with open(f"llama-{latest_release_tag}-bin-win-cuda-cu12.2.0-x64.zip", "wb") as f: f.write(response.content) with zipfile.ZipFile(f"llama-{latest_release_tag}-bin-win-cuda-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 the Cuda .dll resources if they aren't present in the bin folder 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.") # Ask for user input to download or fetch from cache the specified model repository if it doesn't exist 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) # Check if the model repository already exists if os.path.exists(model_dir): print("Model repository already exists. Using existing repository.") # If the model already exists, prompt the user if they want to delete the model directory delete_model_dir = input("Remove HF model folder after converting original model to GGUF? (yes/no) (default: no): ").strip().lower() # Convert the existing model to GGUF F16 format and generate imatrix.dat convert_model_to_gguf_f16(base_dir, model_dir, model_name, delete_model_dir) else: revision = input("Enter the revision (branch, tag, or commit) to download (default: main): ") or "main" # Ask the user if they want to remove the HF model folder after conversion delete_model_dir = input("Remove HF model folder after converting original model to GGUF? (yes/no) (default: no): ").strip().lower() print("Downloading model repository...") snapshot_download(repo_id=model_id, local_dir=model_dir, revision=revision) print("Model repository downloaded successfully.") # Convert the downloaded model to GGUF F16 format and generate imatrix.dat convert_model_to_gguf_f16(base_dir, model_dir, model_name, delete_model_dir) # Convert the downloaded model to GGUF F16 format def convert_model_to_gguf_f16(base_dir, model_dir, model_name, delete_model_dir): 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) # Check if F16 file already exists if not os.path.exists(gguf_model_path): # Execute the conversion command subprocess.run(["python", convert_script, model_dir, "--outfile", gguf_model_path, "--outtype", "f16"]) # Delete the original model directory under conditions if delete_model_dir == 'yes' or delete_model_dir == 'y': shutil.rmtree(model_dir) print(f"Original model directory '{model_dir}' deleted.") else: print(f"Original model directory '{model_dir}' was not deleted. You can remove it manually.") # Check if imatrix.dat exists within gguf_dir 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): # Execute the imatrix command subprocess.run([imatrix_exe, "-m", gguf_model_path, "-f", imatrix_txt, "-ngl", "13"], cwd=gguf_dir) # Move the imatrix.dat file to the GGUF folder shutil.move(os.path.join(gguf_dir, "imatrix.dat"), gguf_dir) print("imatrix.dat generated successfully.") else: print("Skipping imatrix generation as imatrix.dat already exists.") else: print("Skipping model conversion as F16 file already exists.") # Quantize the models quantize_models(base_dir, model_name) # Quantize 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 = [ "IQ3_M", "IQ3_XXS", "Q4_K_M", "Q4_K_S", "IQ4_NL", "IQ4_XS", "Q5_K_M", "Q5_K_S", "Q6_K", "Q8_0" ] 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()