import json import os from pathlib import Path import gradio as gr import pandas as pd from app.models import GgufParser 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" def process_url(url, context_length): try: res = os.popen( f"./{gguf_parser} --ctx-size={context_length} -url {url} --json" ).read() parser_result = GgufParser.model_validate_json(res) # data = json.loads(res) metadata_df = pd.DataFrame([parser_result.metadata.model_dump()]) architecture_df = pd.DataFrame([parser_result.architecture.model_dump()]) tokenizer_df = pd.DataFrame([parser_result.tokenizer.model_dump()]) estimate_df = pd.DataFrame( [parser_result.estimate.model_dump(exclude_none=True)] ) return metadata_df, architecture_df, tokenizer_df, estimate_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 open("devices.json", "r", encoding="utf-8") as f: device_list = json.load(f) with gr.Blocks(title="GGUF Parser") as iface: url_input = gr.Textbox(placeholder="Enter GGUF URL", value=DEFAULT_URL) context_length = gr.Number(label="Context Length", value=8192) submit_btn = gr.Button("Send") submit_btn.click( fn=process_url, inputs=[url_input, context_length], outputs=[ gr.DataFrame(label="METADATA"), gr.DataFrame(label="ARCHITECTURE"), gr.DataFrame(label="TOKENIZER"), gr.DataFrame(label="ESTIMATE"), ], ) iface.launch()