| """The main application file for the Gradio app.""" | |
| import gradio as gr | |
| import pandas as pd | |
| import torch | |
| animes_df = pd.read_csv("./data/animes.csv") | |
| anime_embeddings_df = pd.read_csv("./data/anime_embeddings.csv", header=None) | |
| title_list = animes_df["Title"].tolist() | |
| embeddings = torch.tensor(anime_embeddings_df.values) | |
| def recommend(index): | |
| embedding = embeddings[index] | |
| embedding_distances = torch.nn.CosineSimilarity(dim=1)(embeddings, embedding) | |
| recommendation_indexes = embedding_distances.argsort(descending=True)[1:4] | |
| recommendations = [] | |
| for rank, recommendation_index in enumerate(recommendation_indexes): | |
| recommendation = animes_df.iloc[int(recommendation_index)] | |
| value = recommendation["Image URL"] | |
| label = f'{rank + 1}. {recommendation["Title"]}' | |
| recommendations.append((value, label)) | |
| return recommendations | |
| css = """ | |
| .gradio-container {align-items: center} | |
| #container {max-width: 795px} | |
| """ | |
| with gr.Blocks(css=css) as space: | |
| with gr.Column(elem_id="container"): | |
| gr.Markdown( | |
| """ | |
| # Anime Collaborative Filtering System | |
| This is a Pytorch recommendation model that uses neural collaborative filtering. | |
| Enter an anime, and it will suggest similar shows! \ | |
| Source code: [https://github.com/EdZ543/anime-collaborative-filtering-system](https://github.com/EdZ543/anime-collaborative-filtering-system) | |
| """ | |
| ) | |
| dropdown = gr.Dropdown(label="Enter an anime", choices=title_list, type="index") | |
| gallery = gr.Gallery(label="Recommendations", rows=1, columns=3, height="265") | |
| dropdown.change(fn=recommend, inputs=dropdown, outputs=gallery) | |
| space.launch() | |