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.gitattributes +5 -0
assets/__pycache__/model_tools.cpython-313.pyc +0 -0
assets/calculate-model-hashes.py +21 -0
assets/download_models.py +28 -0
assets/json_link_processor.py +7 -0
assets/list_duplicate_remove.py +9 -0
assets/luvr5-ui-models.txt +248 -0
assets/model_data/mdx_model_data.json +384 -0
assets/model_tools.py +297 -0
assets/model_url_sorter.py +6 -0
assets/upload_models.py +33 -0

.gitattributes ADDED Viewed

	@@ -0,0 +1,5 @@

+UVR-DeNoise.pth filter=lfs diff=lfs merge=lfs -text
+MDX23C-8KFFT-InstVoc_HQ.ckpt filter=lfs diff=lfs merge=lfs -text
+MDX23C-8KFFT-InstVoc_HQ_2.ckpt filter=lfs diff=lfs merge=lfs -text
+mel_band_roformer_instrumental_fullness_v3_gabox.ckpt filter=lfs diff=lfs merge=lfs -text
+mel_band_roformer_instrumental_fullness_v2_gabox.ckpt filter=lfs diff=lfs merge=lfs -text

assets/__pycache__/model_tools.cpython-313.pyc ADDED Viewed

Binary file (12.6 kB). View file

assets/calculate-model-hashes.py ADDED Viewed

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+#!/usr/bin/env python3
+import os
+import sys
+import json
+import hashlib
+import requests
+import model_tools as mt
+MODEL_CACHE_PATH = "/tmp/audio-separator-models"
+VR_MODEL_DATA_LOCAL_PATH = f"{MODEL_CACHE_PATH}/vr_model_data.json"
+MDX_MODEL_DATA_LOCAL_PATH = f"{MODEL_CACHE_PATH}/mdx_model_data.json"
+MODEL_DATA_URL_PREFIX = "https://raw.githubusercontent.com/TRvlvr/application_data/main"
+VR_MODEL_DATA_URL = f"{MODEL_DATA_URL_PREFIX}/vr_model_data/model_data_new.json"
+MDX_MODEL_DATA_URL = f"{MODEL_DATA_URL_PREFIX}/mdx_model_data/model_data_new.json"
+OUTPUT_PATH = f"{MODEL_CACHE_PATH}/model_hashes.json"
+if __name__ == "__main__":
+    mt.iterate_and_hash(MODEL_CACHE_PATH)

assets/download_models.py ADDED Viewed

	@@ -0,0 +1,28 @@

+import requests
+import os
+import argparse
+from huggingface_hub import snapshot_download
+import model_tools as mt
+REPO_OWNER = "lainlives"
+REPO_NAME = "audio-separator-models"
+repo_type = "model"
+if __name__ == "__main__":
+    token = os.getenv("HF_TOKEN")
+    repo_id = f"{REPO_OWNER}/{REPO_NAME}"
+    parser = argparse.ArgumentParser(description="Model Download Tool")
+    local_dir = os.getcwd()
+    # action="store_true" makes the flag a boolean (True if present, False if not)
+    parser.add_argument(
+        "--fromtxt",
+        action="store_true",
+        help="Download or process based on a text file instead of cloning repo",
+    )
+    args = parser.parse_args()
+    if args.fromtxt:
+        mt.download_files_from_txt("assets/links.txt", local_dir)
+    else:
+        mt.download_hf_repo(repo_id, local_dir, token)

assets/json_link_processor.py ADDED Viewed

	@@ -0,0 +1,7 @@

+import json
+import urllib.request
+import os
+import model_tools as mt
+if __name__ == "__main__":
+    mt.get_links_from_json("models.json")

assets/list_duplicate_remove.py ADDED Viewed

	@@ -0,0 +1,9 @@

+import model_tools as mt
+# --- Example Usage ---
+# Make sure you have a file named 'input_data.txt' in the same directory
+input_filename = "file.txt"
+output_filename = "processed_links.txt"
+if __name__ == "__main__":
+    mt.remove_duplicate_lines(input_filename, output_filename)

assets/luvr5-ui-models.txt ADDED Viewed

	@@ -0,0 +1,248 @@

+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_aspiration_mel_band_roformer.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_aspiration_mel_band_roformer.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_bs_roformer_instrumental_resurrection_unwa.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_bs_roformer_vocals_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_bs_roformer_vocals_resurrection_unwa.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_bs_roformer_vocals_revive_unwa.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_bs_roformer_vocals_revive_unwa.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_bs_roformer_vocals_revive_unwa.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_chorus_male_female_bs_roformer.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_chorus_male_female_bs_roformer.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_dereverb-echo_mel_band_roformer.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_dereverb-echo_mel_band_roformer_sdr_13.4843_v2.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_dereverb_echo_mel_band_roformer_v2.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_dereverb_echo_mel_band_roformer_v2.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_dereverb_echo_mel_band_roformer_v2.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_dereverb_mdx23c.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_drumsep_mdx23c.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_bleed_suppressor_v1.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_becruily.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_instrumental_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_karaoke_becruily.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_karaoke_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_karaoke_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_kim_ft_unwa.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_kim_ft_unwa.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_kim_ft_unwa.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_kim_ft_unwa.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_vocal_fullness_aname.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_vocals_becruily.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_vocals_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_vocals_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_vocals_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_vocals_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_vocals_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_vocals_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_vocals_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_mel_band_roformer_vocals_gabox.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_melband_roformer_big_beta5e.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_melbandroformer_big_beta4.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_melbandroformer_big_beta6.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_melbandroformer_big_beta6x.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_melbandroformer_inst.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_melbandroformer_inst.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_melbandroformer_inst.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_melbandroformer_inst.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_melbandroformer_inst_v2.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_melbandroformer_instvoc_duality.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_melbandroformer_instvoc_duality.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_vocals_mel_band_roformer_big_v1_ft.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_vocals_mel_band_roformer_ft.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_vocals_mel_band_roformer_ft.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_vocals_mel_band_roformer_ft.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/config_vocals_mel_band_roformer_ft.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/denoise_mel_band_roformer_aufr33_aggr_sdr_27.9768_config.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/denoise_mel_band_roformer_aufr33_sdr_27.9959_config.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/dereverb_mel_band_roformer_anvuew.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/dereverb_mel_band_roformer_anvuew.yaml
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+https://huggingface.co/lainlives/audio-separator-models/resolve/main/deverb_bs_roformer_8_384dim_10depth_config.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/mel_band_roformer_crowd_aufr33_viperx_sdr_8.7144_config.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/mel_band_roformer_karaoke_aufr33_viperx_sdr_10.1956_config.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/model_2_stem_061321.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/model_2_stem_full_band_8k.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/model_2_stem_full_band_8k.yaml
+https://huggingface.co/lainlives/audio-separator-models/resolve/main/model_bs_roformer_ep_317_sdr_12.9755.yaml
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+https://huggingface.co/lainlives/audio-separator-models/resolve/main/model_mel_band_roformer_ep_3005_sdr_11.4360.yaml
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+        "primary_stem": "Instrumental"
+    },
+    "8a88db95c7fb5dbe6a095ff2ffb428b1": {
+        "compensate": 1.026,
+        "mdx_dim_f_set": 2048,
+        "mdx_dim_t_set": 8,
+        "mdx_n_fft_scale_set": 5120,
+        "primary_stem": "Instrumental"
+    },
+    "b78da4afc6512f98e4756f5977f5c6b9": {
+        "compensate": 1.021,
+        "mdx_dim_f_set": 3072,
+        "mdx_dim_t_set": 8,
+        "mdx_n_fft_scale_set": 7680,
+        "primary_stem": "Instrumental"
+    },
+    "77d07b2667ddf05b9e3175941b4454a0": {
+        "compensate": 1.021,
+        "mdx_dim_f_set": 3072,
+        "mdx_dim_t_set": 8,
+        "mdx_n_fft_scale_set": 7680,
+        "primary_stem": "Vocals"
+    },
+    "0f2a6bc5b49d87d64728ee40e23bceb1": {
+        "compensate": 1.019,
+        "mdx_dim_f_set": 2560,
+        "mdx_dim_t_set": 8,
+        "mdx_n_fft_scale_set": 5120,
+        "primary_stem": "Instrumental"
+    },
+    "b02be2d198d4968a121030cf8950b492": {
+        "compensate": 1.020,
+        "mdx_dim_f_set": 2560,
+        "mdx_dim_t_set": 8,
+        "mdx_n_fft_scale_set": 5120,
+        "primary_stem": "No Crowd"
+    },
+    "2154254ee89b2945b97a7efed6e88820": {
+        "config_yaml": "model_2_stem_061321.yaml"
+    },
+    "063aadd735d58150722926dcbf5852a9": {
+        "config_yaml": "model_2_stem_061321.yaml"
+    },
+    "c09f714d978b41d718facfe3427e6001": {
+        "config_yaml": "model_2_stem_061321.yaml"
+    },
+    "fe96801369f6a148df2720f5ced88c19": {
+        "config_yaml": "model3.yaml"
+    },
+    "02e8b226f85fb566e5db894b9931c640": {
+        "config_yaml": "model2.yaml"
+    },
+    "e3de6d861635ab9c1d766149edd680d6": {
+        "config_yaml": "model1.yaml"
+    },
+    "3f2936c554ab73ce2e396d54636bd373": {
+        "config_yaml": "modelB.yaml"
+    },
+    "890d0f6f82d7574bca741a9e8bcb8168": {
+        "config_yaml": "modelB.yaml"
+    },
+    "63a3cb8c37c474681049be4ad1ba8815": {
+        "config_yaml": "modelB.yaml"
+    },
+    "a7fc5d719743c7fd6b61bd2b4d48b9f0": {
+        "config_yaml": "modelA.yaml"
+    },
+    "3567f3dee6e77bf366fcb1c7b8bc3745": {
+        "config_yaml": "modelA.yaml"
+    },
+    "a28f4d717bd0d34cd2ff7a3b0a3d065e": {
+        "config_yaml": "modelA.yaml"
+    },
+    "c9971a18da20911822593dc81caa8be9": {
+        "config_yaml": "sndfx.yaml"
+    },
+    "57d94d5ed705460d21c75a5ac829a605": {
+        "config_yaml": "sndfx.yaml"
+    },
+    "e7a25f8764f25a52c1b96c4946e66ba2": {
+        "config_yaml": "sndfx.yaml"
+    },
+    "104081d24e37217086ce5fde09147ee1": {
+        "config_yaml": "model_2_stem_061321.yaml"
+    },
+    "1e6165b601539f38d0a9330f3facffeb": {
+        "config_yaml": "model_2_stem_061321.yaml"
+    },
+    "fe0108464ce0d8271be5ab810891bd7c": {
+        "config_yaml": "model_2_stem_full_band.yaml"
+    },
+    "e9b82ec90ee56c507a3a982f1555714c": {
+        "config_yaml": "model_2_stem_full_band_2.yaml"
+    },
+    "99b6ceaae542265a3b6d657bf9fde79f": {
+        "config_yaml": "model_2_stem_full_band_8k.yaml"
+    },
+    "116f6f9dabb907b53d847ed9f7a9475f": {
+        "config_yaml": "model_2_stem_full_band_8k.yaml"
+    },
+    "53f707017bfcbb56f5e1bfac420d6732": {
+        "config_yaml": "model_bs_roformer_ep_317_sdr_12.9755.yaml",
+        "is_roformer": true
+    },
+    "63e41acc264bf681a73aa9f7e5f606cc": {
+        "config_yaml": "model_mel_band_roformer_ep_3005_sdr_11.4360.yaml",
+        "is_roformer": true
+    },
+    "e733736763234047587931fc35322fd9": {
+        "config_yaml": "model_bs_roformer_ep_937_sdr_10.5309.yaml",
+        "is_roformer": true
+    },
+    "d789065adfd747d6f585b27b495bcdae": {
+        "config_yaml": "model_bs_roformer_ep_368_sdr_12.9628.yaml",
+        "is_roformer": true
+    }
+}

assets/model_tools.py ADDED Viewed

	@@ -0,0 +1,297 @@

+import argparse
+import hashlib
+import json
+import os
+import sys
+import urllib.request
+import requests
+from huggingface_hub import HfApi, snapshot_download
+def download_files_from_txt(filename, local_dir):
+    """
+    Reads a text file containing a list of URLs and downloads each,
+    skipping any that already exist in the local directory.
+    """
+    if not os.path.exists(filename):
+        print(f"Error: {filename} not found.")
+        return
+    # Create the directory if it doesn't exist
+    if local_dir and not os.path.exists(local_dir):
+        os.makedirs(local_dir)
+    with open(filename, "r") as f:
+        urls = [line.strip() for line in f if line.strip()]
+    print(f"Found {len(urls)} links to process.")
+    for url in urls:
+        # Determine local filename
+        base_name = url.split("/")[-1] or "downloaded_file"
+        local_filename = os.path.join(local_dir, base_name) if local_dir else base_name
+        # SKIP if file already exists
+        if os.path.isfile(local_filename):
+            print(f"⏭️ Skipping (already exists): {local_filename}")
+            continue
+        try:
+            print(f"Downloading: {local_filename} from {url}")
+            response = requests.get(url, allow_redirects=True, stream=True)
+            response.raise_for_status()
+            with open(local_filename, "wb") as file:
+                for chunk in response.iter_content(chunk_size=8192):
+                    file.write(chunk)
+            print(f"✅ Successfully downloaded: {local_filename}")
+        except requests.exceptions.RequestException as e:
+            print(f"❌ Failed to download {url}: {e}")
+        except Exception as e:
+            print(f"An unexpected error occurred while processing {url}: {e}")
+def download_hf_repo(repo_id, local_dir, repo_type, token):
+    if not token:
+        token = os.getenv("HF_TOKEN")
+    """
+    Downloads an entire Hugging Face repository to a specified local directory.
+    """
+    print(f"Downloading {repo_id} to {local_dir}...")
+    # Ensure the target directory exists
+    os.makedirs(local_dir, exist_ok=True)
+    # Download the snapshot
+    downloaded_path = snapshot_download(
+        repo_id=repo_id,
+        local_dir=local_dir,
+        token=token,
+        local_dir_use_symlinks=False,  # Set to False to ensure actual files are moved to local_dir
+        repo_type=repo_type,
+    )
+    print(f"Download complete! Files are located in: {downloaded_path}")
+    return downloaded_path
+def remove_duplicate_lines(input_file_path, output_file_path):
+    """
+    Reads lines from input_file_path, removes duplicates, and writes
+    unique lines to output_file_path while preserving order.
+    """
+    try:
+        # Use an ordered set to maintain the original file's line order.
+        # An easy way to do this in Python 3.7+ is using a dictionary's keys.
+        unique_lines_dict = {}
+        with open(input_file_path, "r") as input_file:
+            for line in input_file:
+                # Store line as a dictionary key; duplicates will be ignored
+                unique_lines_dict[line] = None
+        unique_lines = unique_lines_dict.keys()
+        with open(output_file_path, "w") as output_file:
+            # Write all unique lines to the new file
+            output_file.writelines(unique_lines)
+        print(f"Duplicates removed. Unique lines saved to '{output_file_path}'")
+    except FileNotFoundError:
+        print(f"Error: The file '{input_file_path}' was not found.")
+    except Exception as e:
+        print(f"An error occurred: {e}")
+def push_to_hf(repo_id, repo_type):
+    api = HfApi()
+    print(f"Uploading current directory to: {repo_id}")
+    # Upload everything in the current directory ('.') to the repo root
+    api.upload_folder(
+        folder_path=".",
+        repo_id=repo_id,
+        repo_type=repo_type,
+        commit_message="Initial model upload",
+    )
+    print("Upload complete!")
+def push_large_folder_to_hf(repo_id, repo_type):
+    api = HfApi()
+    print(f"Starting large folder upload to: {repo_id}")
+    # 3. Use upload_large_folder for resilience and speed
+    # This automatically handles multi-threading and local caching for resuming
+    api.upload_large_folder(
+        folder_path=".",
+        repo_id=repo_id,
+        repo_type=repo_type,
+        # Optional: ignore large junk files to save time
+        ignore_patterns=[
+            ".git/",
+            "__pycache__/",
+            "*.tmp",
+            ".DS_Store",
+            "*.cache",
+            "*.trash",
+        ],
+    )
+    print(
+        "\nUpload complete! Progress was cached locally; if it failed, just run again to resume."
+    )
+def get_model_hash(model_path):
+    """
+    Get the hash of a model file
+    """
+    # print(f"Getting hash for model at {model_path}")
+    try:
+        with open(model_path, "rb") as f:
+            f.seek(
+                -10000 * 1024, 2
+            )  # Move the file pointer 10MB before the end of the file
+            hash_result = hashlib.md5(f.read()).hexdigest()
+            # print(f"Hash for {model_path}: {hash_result}")
+            return hash_result
+    except IOError:
+        with open(model_path, "rb") as f:
+            hash_result = hashlib.md5(f.read()).hexdigest()
+            # print(f"IOError encountered, hash for {model_path}: {hash_result}")
+            return hash_result
+def download_file_if_missing(url, local_path):
+    """
+    Download a file from a URL if it doesn't exist locally
+    """
+    print(f"Checking if {local_path} needs to be downloaded from {url}")
+    if not os.path.exists(local_path):
+        print(f"Downloading {url} to {local_path}")
+        with requests.get(url, stream=True, timeout=10) as r:
+            r.raise_for_status()
+            with open(local_path, "wb") as f:
+                for chunk in r.iter_content(chunk_size=8192):
+                    f.write(chunk)
+        print(f"Downloaded {url} to {local_path}")
+    else:
+        print(f"{local_path} already exists. Skipping download.")
+def load_json_data(file_path):
+    """
+    Load JSON data from a file
+    """
+    print(f"Loading JSON data from {file_path}")
+    try:
+        with open(file_path, "r", encoding="utf-8") as file:
+            data = json.load(file)
+            print(f"Loaded JSON data successfully from {file_path}")
+            return data
+    except FileNotFoundError:
+        print(f"{file_path} not found.")
+        sys.exit(1)
+def iterate_and_hash(
+    directory,
+    vr_model_data_url,
+    mdx_model_data_url,
+    vr_model_data_local_path,
+    mdx_model_data_local_path,
+):
+    """
+    Iterate through a directory and hash all model files
+    """
+    print(f"Iterating through directory {directory} to hash model files")
+    model_files = [
+        (file, os.path.join(root, file))
+        for root, _, files in os.walk(directory)
+        for file in files
+        if file.endswith((".pth", ".onnx"))
+    ]
+    download_file_if_missing(vr_model_data_url, vr_model_data_local_path)
+    download_file_if_missing(mdx_model_data_url, mdx_model_data_local_path)
+    vr_model_data = load_json_data(vr_model_data_local_path)
+    mdx_model_data = load_json_data(mdx_model_data_local_path)
+    combined_model_params = {
+        **vr_model_data,
+        **mdx_model_data,
+    }
+    model_info_list = []
+    for file, file_path in sorted(model_files):
+        file_hash = get_model_hash(file_path)
+        model_info = {
+            "file": file,
+            "hash": file_hash,
+            "params": combined_model_params.get(file_hash, "Parameters not found"),
+        }
+        model_info_list.append(model_info)
+    print(f"Writing model info list to {OUTPUT_PATH}")
+    with open(OUTPUT_PATH, "w", encoding="utf-8") as json_file:
+        json.dump(model_info_list, json_file, indent=4)
+        print(f"Successfully wrote model info list to {OUTPUT_PATH}")
+def sort_links_by_extension(input_file, output_file):
+    # Define the custom priority order
+    priority = {
+        ".json": 0,
+        ".yaml": 1,
+        ".th": 2,
+        ".pth": 3,
+        ".ckpt": 4,
+        ".onnx": 5,  # Added .onnx (common typo for .onnx or .onx)
+    }
+    # Handle the specific user request for .onnx
+    # Example: Map .onnx to priority 5
+    # priority['.onnx'] = 5
+    try:
+        with open(input_file, "r") as f:
+            # Read lines and strip whitespace/newlines
+            links = [line.strip() for line in f if line.strip()]
+        def sort_key(link):
+            # Extract extension (case-insensitive)
+            _, ext = os.path.splitext(link.lower())
+            # Return priority index; if not in list, place at the end (index 100)
+            return priority.get(ext, 100), link
+        # Sort the links
+        sorted_links = sorted(links, key=sort_key)
+        with open(output_file, "w") as f:
+            for link in sorted_links:
+                f.write(link + "\n")
+        print(f"Successfully sorted links into: {output_file}")
+    except FileNotFoundError:
+        print(f"Error: The file '{input_file}' was not found.")
+# 1. Load the JSON data
+# Ensure 'models.json' is in your current directory
+def get_links_from_json(file_input):
+    try:
+        with open(file_input, "r") as file:
+            data = json.load(file)
+    except FileNotFoundError:
+        print("Error: 'models.json' not found.")
+        data = {}
+    # 2. Process and Download
+    for model_name, links in data.items():
+        if not isinstance(links, list) or len(links) == 0:
+            continue

assets/model_url_sorter.py ADDED Viewed

	@@ -0,0 +1,6 @@

+import os
+import model_tools as mt
+if __name__ == "__main__":
+    # Ensure you have a file named 'links.txt' in the same directory
+    mt.sort_links_by_extension("links.txt", "sorted_links.txt")

assets/upload_models.py ADDED Viewed

	@@ -0,0 +1,33 @@

+#! /usr/bin/env python3
+import os
+import argparse
+from huggingface_hub import HfApi
+import model_tools as mt
+REPO_OWNER = "lainlives"
+REPO_NAME = "audio-separator-models"
+repo_type = "model"
+HF_TOKEN = os.getenv("HF_TOKEN")
+if __name__ == "__main__":
+    repo_id = f"{REPO_OWNER}/{REPO_NAME}"
+    parser = argparse.ArgumentParser(description="Model Upload Tool")
+    parser.add_argument(
+        "--large",
+        action="store_true",
+        help="Upload using upload-large-folder",
+    )
+    parser.add_argument(
+        "--token",
+        type=str,
+        default=HF_TOKEN,
+        dest="HF_TOKEN",
+        help=f"Your access token.",
+    )
+    args = parser.parse_args()
+    if args.large:
+        mt.push_large_folder_to_hf(repo_id, repo_type)
+    else:
+        mt.push_to_hf(repo_id, repo_type)