app.py

import gradio as gr
import requests.exceptions
from huggingface_hub import HfApi, hf_hub_download
from huggingface_hub.repocard import metadata_load

def load_agent(model_id):
    """
    This function load the agent's video and results
    :return: video_path
    """
    # Load the metrics
    metadata = get_metadata(model_id)
    
    # Get the accuracy
    results = parse_metrics_accuracy(metadata)
    
    # Load the video
    video_path = hf_hub_download(model_id, filename="replay.mp4")
    
    return video_path, results



def parse_metrics_accuracy(meta):
    if "model-index" not in meta:
        return None
    result = meta["model-index"][0]["results"]
    metrics = result[0]["metrics"]
    accuracy = metrics[0]["value"]
    return accuracy

def get_metadata(model_id):
    """
    Get the metadata of the model repo
    :param model_id:
    :return: metadata
    """
    try:
        readme_path = hf_hub_download(model_id, filename="README.md")
        metadata = metadata_load(readme_path)
        print(metadata)
        return metadata
    except requests.exceptions.HTTPError:
        return None

agent1 = gr.Interface(load_agent_video, "text", ["video", "text"])
agent2 = gr.Interface(load_agent_video, "text", ["video", "text"])

gr.Parallel(agent1, agent2).launch(share=True)