app.py

import os
import pathlib
import random
import string
import tempfile
import time
import threading
from typing import Iterable, List

import gradio as gr
import huggingface_hub
import torch
import yaml
from gradio_logsview.logsview import Log, LogsView, LogsViewRunner
from mergekit.config import MergeConfiguration
from spaces import spaces

has_gpu = torch.cuda.is_available()

cli = "mergekit-yaml config.yaml merge --copy-tokenizer" + (
    " --cuda --low-cpu-memory --allow-crimes" if has_gpu else " --allow-crimes --out-shard-size 1B --lazy-unpickle"
)

MARKDOWN_DESCRIPTION = """
# mergekit-gui
The fastest way to perform a model merge 🔥
Specify a YAML configuration file (see examples below) and a HF token and this app will perform the merge and upload the merged model to your user profile.
"""

MARKDOWN_ARTICLE = """
___
## Merge Configuration
[Mergekit](https://github.com/arcee-ai/mergekit) configurations are YAML documents specifying the operations to perform in order to produce your merged model.
Below are the primary elements of a configuration file:
- `merge_method`: Specifies the method to use for merging models. See [Merge Methods](https://github.com/arcee-ai/mergekit#merge-methods) for a list.
- `slices`: Defines slices of layers from different models to be used. This field is mutually exclusive with `models`.
- `models`: Defines entire models to be used for merging. This field is mutually exclusive with `slices`.
- `base_model`: Specifies the base model used in some merging methods.
- `parameters`: Holds various parameters such as weights and densities, which can also be specified at different levels of the configuration.
- `dtype`: Specifies the data type used for the merging operation.
- `tokenizer_source`: Determines how to construct a tokenizer for the merged model.
## Merge Methods
A quick overview of the currently supported merge methods:
| Method                                                                                       | `merge_method` value | Multi-Model | Uses base model |
| -------------------------------------------------------------------------------------------- | -------------------- | ----------- | --------------- |
| Linear ([Model Soups](https://arxiv.org/abs/2203.05482))                                     | `linear`             | ✅          | ❌              |
| SLERP                                                                                        | `slerp`              | ❌          | ✅              |
| [Task Arithmetic](https://arxiv.org/abs/2212.04089)                                          | `task_arithmetic`    | ✅          | ✅              |
| [TIES](https://arxiv.org/abs/2306.01708)                                                     | `ties`               | ✅          | ✅              |
| [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708)            | `dare_ties`          | ✅          | ✅              |
| [DARE](https://arxiv.org/abs/2311.03099) [Task Arithmetic](https://arxiv.org/abs/2212.04089) | `dare_linear`        | ✅          | ✅              |
| Passthrough                                                                                  | `passthrough`        | ❌          | ❌              |
| [Model Stock](https://arxiv.org/abs/2403.19522)                                              | `model_stock`        | ✅          | ✅              |
## Citation
This GUI is powered by [Arcee's MergeKit](https://arxiv.org/abs/2403.13257).
If you use it in your research, please cite the following paper:
@article{goddard2024arcee,
  title={Arcee's MergeKit: A Toolkit for Merging Large Language Models},
  author={Goddard, Charles and Siriwardhana, Shamane and Ehghaghi, Malikeh and Meyers, Luke and Karpukhin, Vlad and Benedict, Brian and McQuade, Mark and Solawetz, Jacob},
  journal={arXiv preprint arXiv:2403.13257},
  year={2024}
}
This Space is heavily inspired by LazyMergeKit by Maxime Labonne (see [Colab](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb)).
"""

examples = [[str(f)] for f in pathlib.Path("examples").glob("*.yaml")]
COMMUNITY_HF_TOKEN = os.getenv("COMMUNITY_HF_TOKEN")

def merge_process(yaml_config, hf_token, repo_name, profile_name, logs_queue):
    runner = LogsViewRunner(logs_queue)

    if not yaml_config:
        runner.log("Empty yaml, pick an example below", level="ERROR")
        return

    try:
        merge_config = MergeConfiguration.model_validate(yaml.safe_load(yaml_config))
    except Exception as e:
        runner.log(f"Invalid yaml {e}", level="ERROR")
        return

    is_community_model = False
    if not hf_token:
        if "/" in repo_name and not repo_name.startswith("mergekit-community/"):
            runner.log(f"Cannot upload merge model to namespace {repo_name.split('/')[0]}: you must provide a valid token.", level="ERROR")
            return
        runner.log("No HF token provided. Your merged model will be uploaded to the https://huggingface.co/mergekit-community organization.")
        is_community_model = True
        if not COMMUNITY_HF_TOKEN:
            raise gr.Error("Cannot upload to community org: community token not set by Space owner.")
        hf_token = COMMUNITY_HF_TOKEN

    api = huggingface_hub.HfApi(token=hf_token)

    with tempfile.TemporaryDirectory(ignore_cleanup_errors=True) as tmpdirname:
        tmpdir = pathlib.Path(tmpdirname)
        merged_path = tmpdir / "merged"
        merged_path.mkdir(parents=True, exist_ok=True)
        config_path = merged_path / "config.yaml"
        config_path.write_text(yaml_config)
        current_time = time.strftime("%Y-%m-%d %H:%M:%S")
        runner.log(f"[{current_time}] Merge configuration saved in {config_path}")

        if not repo_name:
            runner.log("No repo name provided. Generating a random one.")
            repo_name = f"{profile_name}/mergekit-{merge_config.merge_method}" if profile_name else f"mergekit-{merge_config.merge_method}"
            repo_name += "-" + "".join(random.choices(string.ascii_lowercase, k=7))
            repo_name = repo_name.replace("/", "-").strip("-")

        if is_community_model and not repo_name.startswith("mergekit-community/"):
            repo_name = f"mergekit-community/{repo_name}"

        try:
            runner.log(f"Creating repo {repo_name}")
            repo_url = api.create_repo(repo_name, exist_ok=True)
            runner.log(f"Repo created: {repo_url}")
        except Exception as e:
            runner.log(f"Error creating repo {e}", level="ERROR")
            return

        tmp_env = os.environ.copy()
        tmp_env["HF_HOME"] = f"{tmpdirname}/.cache"
        full_cli = cli + f" --lora-merge-cache {tmpdirname}/.lora_cache"
        runner.run_command(full_cli.split(), cwd=merged_path, env=tmp_env)

        if runner.exit_code != 0:
            runner.log("Merge failed. Deleting repo as no model is uploaded.", level="ERROR")
            api.delete_repo(repo_url.repo_id)
            return

        runner.log("Model merged successfully. Uploading to HF.")
        runner.run_python(api.upload_folder, repo_id=repo_url.repo_id, folder_path=merged_path / "merge")
        current_time = time.strftime("%Y-%m-%d %H:%M:%S")
        runner.log(f"[{current_time}] Model successfully uploaded to HF: {repo_url.repo_id}")


def merge(yaml_config, hf_token, repo_name, profile_name):
    logs_queue = []
    thread = threading.Thread(target=merge_process, args=(yaml_config, hf_token, repo_name, profile_name, logs_queue))
    thread.start()

    while thread.is_alive():
        if logs_queue:
            yield logs_queue[:]
            logs_queue.clear()
        time.sleep(0.1)

    if logs_queue:
        yield logs_queue

with gr.Blocks() as demo:
    gr.Markdown(MARKDOWN_DESCRIPTION)

    with gr.Row():
        filename = gr.Textbox(visible=False, label="filename")
        config = gr.Code(language="yaml", lines=10, label="config.yaml")
        with gr.Column():
            token = gr.Textbox(lines=1, label="HF Write Token", info="https://hf.co/settings/token", type="password", placeholder="Optional")
            repo_name = gr.Textbox(lines=1, label="Repo name", placeholder="Optional")
            profile_name = gr.Textbox(lines=1, label="Hugging Face Profile Name", placeholder="Enter your HF profile name")
    button = gr.Button("Merge", variant="primary")
    logs = LogsView(label="Terminal output")
    gr.Examples(examples, fn=lambda s: (s,), run_on_click=True, label="Examples", inputs=[filename], outputs=[config])
    gr.Markdown(MARKDOWN_ARTICLE)

    button.click(fn=merge, inputs=[config, token, repo_name, profile_name], outputs=[logs])

@spaces(duration=0)
def launch():
    demo.launch(share=True)


if __name__ == "__main__":
    launch()