Update app.py

app.py

@@ -1,47 +1,45 @@
-import gradio as gr
-import requests
-from transformers import pipeline
-
-# Load NLP model
-zero_shot = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
-
-# 🎁 Web search for gift suggestions
-def search_gifts(query):
-    amazon_url = f"https://www.amazon.in/s?k={query.replace(' ', '+')}"
-    igp_url = f"https://www.igp.com/search?q={query.replace(' ', '+')}"
-    indiamart_url = f"https://dir.indiamart.com/search.mp?ss={query.replace(' ', '+')}"
-
-    return {"Amazon": amazon_url, "IGP": igp_url, "IndiaMart": indiamart_url}
-
-# 🎯 Main function for gift recommendation
-def recommend_gifts(text):
-    if not text:
-        return "Please enter a description."
-
-    # NLP Processing
-    categories = ["art", "music", "tech", "travel", "books", "fashion", "fitness", "gaming"]
-    results = zero_shot(text, categories)
-
-    # Get top interest
-    top_interest = results["labels"][0]
-
-    # Search for gifts based on interest
-    links = search_gifts(top_interest)
-
-    return {
-        "Predicted Interest": top_interest,
-        "Gift Suggestions": links
-    }
-
-# 🎨 Gradio UI for easy interaction
-demo = gr.Interface(
-    fn=recommend_gifts, 
-    inputs="text", 
-    outputs="json",
-    title="🎁 AI Gift Recommender",
-    description="Enter details about the person you are buying a gift for, and get personalized suggestions with shopping links!",
-)
-
-# 🚀 Launch Gradio App
-if __name__ == "__main__":
-    demo.launch()
+import gradio as gr
+import requests
+from transformers import pipeline
+
+# Load NLP model (lighter model for efficiency)
+zero_shot = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
+
+# 🎁 Web search for gift suggestions
+def search_gifts(query):
+    amazon_url = f"[Amazon](https://www.amazon.in/s?k={query.replace(' ', '+')})"
+    igp_url = f"[IGP](https://www.igp.com/search?q={query.replace(' ', '+')})"
+    indiamart_url = f"[IndiaMart](https://dir.indiamart.com/search.mp?ss={query.replace(' ', '+')})"
+
+    return f"🔗 **Amazon**: {amazon_url}\n🔗 **IGP**: {igp_url}\n🔗 **IndiaMart**: {indiamart_url}"
+
+# 🎯 Main function for gift recommendation
+def recommend_gifts(text):
+    if not text:
+        return "Please enter a description."
+
+    # NLP Processing
+    categories = ["art", "music", "tech", "travel", "books", "fashion", "fitness", "gaming"]
+    results = zero_shot(text, categories)
+
+    # Get top interest
+    top_interest = results["labels"][0]
+
+    # Get gift links
+    links = search_gifts(top_interest)
+
+    return f"🎯 **Predicted Interest**: `{top_interest}`\n\n🛒 **Gift Suggestions:**\n{links}"
+
+# 🎨 Gradio UI for better display
+demo = gr.Interface(
+    fn=recommend_gifts, 
+    inputs="text", 
+    outputs="markdown",  # 🔹 Changes output format to Markdown for better UI
+    title="🎁 AI Gift Recommender",
+    description="Enter details about the person you are buying a gift for, and get personalized suggestions with shopping links!",
+)
+
+# 🚀 Launch Gradio App
+if __name__ == "__main__":
+    demo.launch()
+