Upload app.py

app.py

@@ -0,0 +1,176 @@
+import gradio as gr
+from src.llm import query_chroma
+from src.reranker_warm import rank_anime_warm
+import pandas as pd
+from pathlib import Path
+import requests
+
+css = """
+footer {display: none !important}
+.gradio-container {
+    max-width: 1200px;
+    margin: auto;
+}
+.contain {
+    background: rgba(255, 255, 255, 0.05);
+    border-radius: 12px;
+    padding: 20px;
+}
+.submit-btn {
+    background: linear-gradient(90deg, #4B79A1 0%, #283E51 100%) !important;
+    border: none !important;
+    color: white !important;
+}
+.submit-btn:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 5px 15px rgba(0,0,0,0.2);
+}
+.title {
+    text-align: center;
+    font-size: 2.5em;
+    font-weight: bold;
+    margin-bottom: 1em;
+    background: linear-gradient(90deg, #4B79A1 0%, #283E51 100%);
+    -webkit-background-clip: text;
+    -webkit-text-fill-color: transparent;
+}
+.output-image {
+    width: 100% !important;
+    max-width: 100% !important;
+}
+"""
+
+
+def download_pic(names: list[str]):
+    df = pd.read_csv(str(Path(Path(__file__).parent, "src/data/final_anime_list.csv")))
+    pic_dir = Path(Path(__file__).parent, "src/data/pics")
+
+    if not pic_dir.exists():
+        pic_dir.mkdir(exist_ok=True)
+
+    df = df[df.Name.isin(names)]
+    df = df[["Name", "Image URL", "Synopsis"]].set_index("Name").reindex(names)
+    synopsis_list = df['Synopsis'].tolist()
+    file_paths = []
+    for url in df["Image URL"]:
+        file_name = "_".join(url.split("/")[-2:])
+        file_path = Path(pic_dir, file_name)
+
+        if file_path.exists():
+            file_paths.append(str(file_path))
+            continue
+
+        response = requests.get(url)
+        response.raise_for_status()  # Raise an exception for bad status codes
+
+        with open(Path(pic_dir, file_name), 'wb') as file:
+            file.write(response.content)
+        file_paths.append(str(file_path))
+
+        print(f"Image downloaded successfully: {url}")
+    return file_paths, synopsis_list
+    # return url
+
+
+def integration_warm(query: str):
+    anime_name_list = query_chroma(query=query, anime_count=100)
+
+    # you need to have the following datasets in src/data/ to call this function
+    # 1. warm_rerank_data.csv
+    # 2. user_similarities.csv
+    # we saved the intermediate matrix for calculation efficiency
+    anime_name_list = rank_anime_warm(userid=12, anime_list=anime_name_list)[:4]
+    final_names = [x[0] for x in anime_name_list]
+
+    anime_pic_list, synopsis_list = download_pic(list(final_names))
+
+    return [*anime_name_list, *anime_pic_list, *synopsis_list]
+
+
+
+
+def clear_prompt():
+    """Function to clear the prompt box."""
+    return ""
+
+
+def feedback_button(action, anime_name):
+    # Store or log feedback (can be expanded to save in a database)
+    return f"You {action}d {anime_name}!"
+
+
+with gr.Blocks(theme=gr.themes.Soft(), css=css) as demo:
+    gr.HTML('<div class="title">AniQuest</div>')
+    gr.HTML(
+        '<div style="text-align: center; margin-bottom: 2em; color: #666; font-size: 24px;">We recommendate animes based on your description</div>')
+    gr.HTML("""
+                <div style="color: red; margin-bottom: 1em; text-align: center; padding: 10px; background: rgba(255,0,0,0.1); border-radius: 8px;">
+                    ⚠️ Welcome, [user_id: 12] to this recommendation system ⚠️
+                </div>
+            """)
+
+    with gr.Column():
+        prompt = gr.Textbox(
+            label="Query",
+            placeholder="Describe the anime you want to watch next ...",
+            lines=1
+        )
+        with gr.Row():
+            generate_btn = gr.Button(
+                "🙆 Submit",
+                elem_classes=["submit-btn"]
+            )
+            clear_btn = gr.Button(
+                "🙅 Clear",
+                elem_classes=["submit-btn"]
+            )
+    with gr.Row():
+        for i in range(4):
+
+            anime_names = []  # Store references to the anime name components
+            feedback_texts = []  # List to store feedback components
+
+            with gr.Column(scale=1, elem_classes=["anime-block"]):
+
+                exec(f"anime{i + 1} = gr.Textbox(label='Anime {i + 1}')")
+
+                with gr.Row():  # Add Like and Dislike buttons under each anime name
+                    like_btn = gr.Button("👍 Like")
+                    dislike_btn = gr.Button("👎 Dislike")
+
+                exec(f"image{i + 1} = gr.Image(label='Image', elem_classes=['output-image', 'fixed-width'])")
+                exec(
+                    f"description{i + 1} = gr.HTML('<div class=\"anime-description\" style=\"margin-top: 10px; font-size: 14px; color: #666;\">Description for anime {i + 1}</div>')")
+
+                # anime_names.append(anime_name)  # Store the reference to use in the button's click method
+
+                # feedback_text = gr.Textbox(
+                #     label="Feedback",
+                #     interactive=False,
+                #     visible=False  # Hidden initially; becomes visible after feedback
+                # )
+                # feedback_texts.append(feedback_text)
+
+                # Link Like and Dislike buttons to feedback function
+                # like_btn.click(fn=feedback_button, inputs=["Like", anime_name], outputs=feedback_text)
+                # dislike_btn.click(fn=feedback_button, inputs=["Dislike", anime_name], outputs=feedback_text)
+
+    generate_btn.click(
+        fn=integration_warm,
+        inputs=[prompt],
+        outputs=[anime1, anime2, anime3, anime4, image1, image2, image3, image4, description1, description2, description3, description4, ]
+    )
+    # Link the "Clear" button to the clear function to clear the prompt
+    clear_btn.click(
+        fn=clear_prompt,  # The function to call
+        inputs=[],  # No input required
+        outputs=[prompt]  # Clears the prompt
+    )
+
+
+
+
+if __name__ == "__main__":
+    # integration_warm(query='I want something like Demon Slayer, but with more romance and produced by Kyoto Animation')
+    # warm user
+    demo.launch(server_name="0.0.0.0", server_port=7860)