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import os
import gradio as gr
import wandb
from my_recommending.app import build_app_blocks, MovieMarkdownGenerator
from my_recommending.movielens.lit import MovieLensNonGradientRecommender
from my_recommending.movielens.data import MovieLens25m
project = "Recommending"
tmdb_api_token = os.environ["TMDB_API_TOKEN"]
lightning_class = MovieLensNonGradientRecommender
config = dict(
model_artifact="my_mf_slim_movielens_25m:v9",
data_artifact="movielens25m:v4",
media_directory="media",
n_recommendations_from_imdb_ratings=50,
)
wandb.init(job_type="app", project=project, config=config)
model_artifact = wandb.use_artifact(config["model_artifact"])
checkpoint_path = model_artifact.file()
lightning_module = lightning_class.load_from_checkpoint(
checkpoint_path, map_location="cpu"
)
recommender = lightning_module.model.eval()
data_artifact = wandb.use_artifact(config["data_artifact"])
data_directory = data_artifact.download()
movielens = MovieLens25m(directory=data_directory)
movie_markdown_generator = MovieMarkdownGenerator(
movielens=movielens, tmdb_api_token=tmdb_api_token
)
with gr.Blocks() as app:
build_app_blocks(
recommender=recommender,
movie_markdown_generator=movie_markdown_generator,
media_directory=config["media_directory"],
n_recommendations_from_imdb_ratings=config[
"n_recommendations_from_imdb_ratings"
],
)
app.launch()
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