Update app.py

app.py

@@ -9,12 +9,13 @@ import gradio as gr
 
 pd.options.mode.chained_assignment = None
 
-# Load precomputed embeddings
+# Load precomputed embeddings from your dataset repo
 embeddings = pickle.load(open(
-    hf_hub_download("bhavyagiri/semantic-memes", repo_type="dataset", filename="meme-embeddings.pkl"), "rb"))
+    hf_hub_download("Go-Raw/semantic-memes", repo_type="dataset", filename="meme-embeddings.pkl"), "rb"))
 
-# Load meme metadata
-df = pd.read_csv(hf_hub_download("bhavyagiri/semantic-memes", repo_type="dataset", filename="input.csv"))
+# Load meme metadata from your dataset repo
+df = pd.read_csv(
+    hf_hub_download("Go-Raw/semantic-memes", repo_type="dataset", filename="semantic_memes.csv"))
 
 # Load model
 model = SentenceTransformer('sentence-transformers/all-mpnet-base-v2')
@@ -37,15 +38,15 @@ def generate_memes(prompt):
             print(f"Error loading image {url}: {e}")
     return images
 
-# UI components
-input_textbox = gr.Textbox(lines=1, label="Search something cool")
-output_gallery = gr.Gallery(label="Retrieved Memes", columns=3, rows=2, height="auto")
+# Gradio UI
+input_textbox = gr.Textbox(lines=1, label="Type your vibe here 🧠")
+output_gallery = gr.Gallery(label="Your Meme Results", columns=3, rows=2, height="auto")
 
-title = "Semantic Search for Memes"
-description = "Search memes from a dataset of ~6k memes using semantic similarity. [GitHub Repo](https://github.com/bhavya-giri/retrieving-memes)"
-examples = ["Get Shreked", "Going Crazy", "Spiderman is my teacher"]
+title = "🧠 Meme Lord"
+description = "Search Indian memes from a custom dataset using semantic similarity. Built using Sentence Transformers & Hugging Face. [Dataset](https://huggingface.co/datasets/Go-Raw/semantic-memes)"
+examples = ["When the professor says 'open book exam'", "Shaktimaan saves the day", "Tu janta nahi mera baap kaun hai"]
 
-# Interface
+# Launch app
 iface = gr.Interface(
     fn=generate_memes,
     inputs=input_textbox,