Delete app.py

app.py

@@ -1,117 +0,0 @@
-import gradio as gr
-from huggingface_hub import hf_hub_download
-from huggingface_hub import HfApi, login
-import os
-import yaml
-from pathlib import Path
-from loguru import logger
-from PIL import Image
-
-SPACE_REPO = "c-gohlke/litrl"
-SPACE_REPO_TYPE = "space"
-MODEL_REPO = "c-gohlke/litrl"
-MODEL_REPO_TYPE = "model"
-
-ENV_RESULTS_FILE_DEPTH = 3
-
-hf_api = HfApi()
-login(  # type: ignore[no-untyped-call]
-    token=os.environ.get("HUGGINGFACE_TOKEN"),
-    add_to_git_credential=True,
-    new_session=False,
-)
-
-# def get_best_gif(env: str) -> Path:
-#     hf_env_results_path = f"models/{env}/results.yaml"
-#     local_env_results_path = hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=hf_env_results_path)
-#     with open(local_env_results_path, "r") as f:
-#         env_results = yaml.load(f, Loader=yaml.FullLoader)
-#     best_model_type = max(env_results, key=lambda model: env_results[model])
-#     model_results_path = f"models/{env}/{best_model_type}/results.yaml"
-#     local_model_results_path = hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=model_results_path)
-#     with open(local_model_results_path, "r") as f:
-#         model_results = yaml.load(f, Loader=yaml.FullLoader)
-
-#     best_model = max(model_results, key=lambda model: model_results[model])
-#     hf_gif_path = f"models/{env}/{best_model_type}/{best_model}/demo.gif"
-#     return Path(hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=hf_gif_path))
-
-def get_best_mp4(env: str) -> Path:
-    hf_env_results_path = f"models/{env}/results.yaml"
-    local_env_results_path = hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=hf_env_results_path)
-    with open(local_env_results_path, "r") as f:
-        env_results = yaml.load(f, Loader=yaml.FullLoader)
-    best_model_type = max(env_results, key=lambda model: env_results[model])
-    model_results_path = f"models/{env}/{best_model_type}/results.yaml"
-    local_model_results_path = hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=model_results_path)
-    with open(local_model_results_path, "r") as f:
-        model_results = yaml.load(f, Loader=yaml.FullLoader)
-
-    best_model = max(model_results, key=lambda model: model_results[model])
-    hf_gif_path = f"models/{env}/{best_model_type}/{best_model}/demo.mp4"
-    return Path(hf_hub_download(repo_id=MODEL_REPO, repo_type=MODEL_REPO_TYPE, filename=hf_gif_path))
-
-def get_environments() -> list[str]:
-    environments: list[str] = []
-    files = hf_api.list_repo_files(MODEL_REPO, repo_type=MODEL_REPO_TYPE)
-    for file in files:
-        vals = file.split("/")
-        # e.g. ['models', 'CartPole-v1', 'results.yaml']
-        if len(vals) == ENV_RESULTS_FILE_DEPTH and vals[2] == "results.yaml" and vals[0] == "models":
-            environments.append(vals[1])
-    return environments
-
-# def get_gif_paths(environments: list[str]) -> dict[str, Path]:
-#     gif_paths: dict[str, Path] = {}
-#     for env in environments:
-#         gif_paths[env] = get_best_gif(env)
-#     return gif_paths
-
-def get_mp4_paths(environments: list[str]) -> dict[str, Path]:
-    mp4_paths: dict[str, Path] = {}
-    for env in environments:
-        mp4_paths[env] = get_best_mp4(env)
-    return mp4_paths
-
-def run_demo() -> None:
-    environments = get_environments()
-    # gif_paths = get_gif_paths(environments)
-    mp4_paths = get_mp4_paths(environments)
-
-    def api_get_text(env_id: str)-> gr.Markdown:
-        logger.info(f"Getting text for {env_id}")
-        return gr.Markdown("# Greetings from LitRL!")
-
-    def api_predict(env_id: str)-> bytes:
-        # if env_id not in gif_paths:
-        #     logger.error(f"Environment {env_id} not found in {gif_paths}")
-        #     return None
-        # return Image.open(gif_paths[env_id], formats=["gif"])
-        if env_id not in mp4_paths:
-            logger.error(f"Environment {env_id} not found in {mp4_paths}")
-            return None
-        return gr.Video(mp4_paths[env_id])
-
-    with gr.Blocks() as demo:
-        md = gr.Markdown("# Greetings from LitRL!")
-        env = gr.Dropdown(choices=list(mp4_paths.keys()), value="CartPole-v1", label="Environment")
-        button = gr.Button(value="Submit")
-        cartpole_out = gr.Video(mp4_paths[env.value], autoplay=True)
-
-        button.click(  # type: ignore[no-untyped-call]
-            fn=api_get_text,
-            inputs=env,
-            outputs=md,
-            api_name="get_text",
-        )
-        button.click( # type: ignore[no-untyped-call]
-            fn=api_predict,
-            inputs=env,
-            outputs=cartpole_out,
-            api_name="predict",
-        )
-
-        demo.launch()  # type: ignore[no-untyped-call]
-
-if __name__ == "__main__":
-    run_demo()