ysda==0.1.3

app.py

@@ -1,5 +1,37 @@
+import os
+
+import gradio as gr
 import wandb
-from machine_learning.recommending.app import app
 
+from machine_learning.recommending.app import (
+    MovieLens25m,
+    build_app_blocks,
+    MovieMarkdownGenerator,
+    SVDRecommender,
+    load_model,
+)
+
+project = "Recommending"
+entity = "dkoshman"
+state_dict_path = "svd.pt"
+movie_lens_25m_directory = "ml-25m"
+tmdb_api_token = os.environ["TMDB_API_TOKEN"]
+
+movielens = MovieLens25m(path_to_movielens_folder=movie_lens_25m_directory)
+movie_markdown_generator = MovieMarkdownGenerator(
+    links_dataframe=movielens["links"],
+    movies_dataframe=movielens["movies"],
+    tmdb_api_token=tmdb_api_token,
+)
+model = load_model(torch_nn_module=SVDRecommender, state_dict_path=state_dict_path)
+model.eval()
+
+with gr.Blocks() as app:
+    build_app_blocks(
+        recommender=model,
+        movie_markdown_generator=movie_markdown_generator,
+    )
+
+wandb.finish()
 wandb.init(job_type="app", project="Recommending", entity="dkoshman")
 app.launch()

requirements.txt

@@ -1 +1 @@
-ysda==0.1.2
+ysda==0.1.3