fixed bug where model item ids didn't match up with tmdb movie ids

app.py

@@ -4,26 +4,25 @@ import gradio as gr
 import wandb
 
 from machine_learning.recommending.app import (
-    MovieLens25m,
     build_app_blocks,
+    load_model,
+    MovieLens25m,
     MovieMarkdownGenerator,
     SVDRecommender,
-    load_model,
 )
 
 project = "Recommending"
 entity = "dkoshman"
+torch_nn_module = SVDRecommender
 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,
+    movielens=movielens, tmdb_api_token=tmdb_api_token
 )
-model = load_model(torch_nn_module=SVDRecommender, state_dict_path=state_dict_path)
+model = load_model(torch_nn_module=torch_nn_module, state_dict_path=state_dict_path)
 model.eval()
 
 with gr.Blocks() as app:
@@ -32,6 +31,13 @@ with gr.Blocks() as app:
         movie_markdown_generator=movie_markdown_generator,
     )
 
-wandb.finish()
-wandb.init(job_type="app", project="Recommending", entity="dkoshman")
+wandb.init(
+    job_type="app",
+    project=project,
+    entity=entity,
+    config=dict(
+        state_dict_path=state_dict_path,
+        movie_lens_25m_directory=movie_lens_25m_directory,
+    ),
+)
 app.launch()

svd.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:16ba92d82dc2fac9629e34f4de0f9c228b123d093c2e9dcf95effd5c63133c26
-size 701072999
+oid sha256:cb328eda7e910c0d8d962394f5625af297b495a5f7dd4b73035e7ffffbef81e0
+size 1227943783