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import json | |
import os | |
from pathlib import Path | |
import gradio as gr | |
from app.devices import Device | |
from app.models import GgufParser | |
from app.tables import get_estimate_df, get_gpus_df, get_model_info_df | |
from app.utils import cleanup_url | |
GGUF_PARSER_VERSION = os.getenv("GGUF_PARSER_VERSION", "v0.12.0") | |
gguf_parser = Path("gguf-parser-linux-amd64") | |
gguf_parser_url = f"https://github.com/gpustack/gguf-parser-go/releases/download/{GGUF_PARSER_VERSION}/{gguf_parser}" | |
DEFAULT_URL = "https://huggingface.co/phate334/Llama-3.1-8B-Instruct-Q4_K_M-GGUF/resolve/main/llama-3.1-8b-instruct-q4_k_m.gguf" | |
with open("devices.json", "r", encoding="utf-8") as f: | |
data = json.load(f) | |
devices = {key: Device(**value) for key, value in data.items()} | |
device_options = [ | |
f"{key} (Memory: {value.memory_size}GB, FLOPS: {value.FLOPS}, Bandwidth: {value.memory_bandwidth}GB/s)" | |
for key, value in devices.items() | |
] | |
def process_url(url, context_length, device_selection): | |
try: | |
device_name = device_selection.split(" (")[0] | |
selected_device = devices[device_name] | |
url = cleanup_url(url) | |
res = os.popen( | |
f'./{gguf_parser} --ctx-size={context_length} -url {url} --device-metric "{selected_device.FLOPS};{selected_device.memory_bandwidth}GBps" --json' | |
).read() | |
parser_result = GgufParser.model_validate_json(res) | |
model_info = get_model_info_df( | |
parser_result.metadata, parser_result.architecture, parser_result.tokenizer | |
) | |
estimate_df = get_estimate_df(parser_result.estimate) | |
gpus_info_df = get_gpus_df(parser_result.estimate, device_name, selected_device) | |
return model_info, estimate_df, gpus_info_df | |
except Exception as e: | |
return e | |
if __name__ == "__main__": | |
if not gguf_parser.exists(): | |
os.system(f"wget {gguf_parser_url}&&chmod +x {gguf_parser}") | |
with gr.Blocks(title="GGUF Parser") as iface: | |
gr.Markdown( | |
"This Space is a web GUI for the [gpustack/gguf-parser-go](https://github.com/gpustack/gguf-parser-go) package, designed for users who are not familiar with CLI. For more detailed output results, please consider using the original tool. If you find this GUI helpful, please give that a star." | |
) | |
url_input = gr.Textbox( | |
label="GGUF File URL", placeholder="Enter GGUF URL", value=DEFAULT_URL | |
) | |
context_length_input = gr.Number(label="Context Length", value=8192) | |
device_dropdown = gr.Dropdown(label="Select Device", choices=device_options) | |
submit_btn = gr.Button("Send") | |
submit_btn.click( | |
fn=process_url, | |
inputs=[url_input, context_length_input, device_dropdown], | |
outputs=[ | |
gr.DataFrame(label="Model Info"), | |
gr.DataFrame(label="ESTIMATE"), | |
gr.DataFrame(label="GPUs INFO"), | |
], | |
) | |
iface.launch() | |