Update app.py

app.py

@@ -1,35 +1,53 @@
 import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
+import requests
 
 # Load DeepSeek-R1 model and tokenizer
 model_name = "deepseek-ai/DeepSeek-R1"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto", trust_remote_code=True)
 
-# Function to generate gift recommendations
+# 🎁 Web search function to get gift suggestions from various e-commerce sites
+def search_gifts(query):
+    search_query = query.replace(" ", "+")
+    return {
+        "Amazon": f"https://www.amazon.in/s?k={search_query}",
+        "Flipkart": f"https://www.flipkart.com/search?q={search_query}",
+        "IGP": f"https://www.igp.com/search?q={search_query}",
+        "IndiaMart": f"https://dir.indiamart.com/search.mp?ss={search_query}",
+    }
+
+# 🎯 Generate gift recommendations using AI
 def recommend_gifts(text):
     if not text:
         return "Please enter a description."
 
     # Prepare input prompt for the model
-    prompt = f"Based on the following description, suggest suitable gifts: '{text}'"
+    prompt = f"Suggest the best gifts for: '{text}'"
 
-    # Tokenize input and generate response
+    # Generate response using the model
     inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
     outputs = model.generate(inputs.input_ids, max_length=200, do_sample=True)
     recommendation = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
-    return {"Recommendation": recommendation}
+    # Search for gifts on shopping websites
+    product_links = search_gifts(recommendation)
+
+    return {
+        "Predicted Gift": recommendation,
+        "Gift Suggestions": product_links
+    }
 
-# Gradio interface
+# 🎨 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!",
+    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()