Update app.py

app.py

@@ -1,27 +1,16 @@
 import gradio as gr
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
-import torch
-import requests
-
-# Load Qwen-2.5 model (Better compatibility)
-model_name = "qwen/Qwen2.5-7B-Chat"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-device = "cuda" if torch.cuda.is_available() else "cpu"
-
-model = AutoModelForCausalLM.from_pretrained(
-    model_name,
-    torch_dtype=torch.float16 if device == "cuda" else torch.float32,
-    device_map="auto"
-)
+from transformers import pipeline
 
-# Text-generation pipeline
-generator = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if torch.cuda.is_available() else -1)
+# 🔹 Load Qwen2.5-14B-Instruct-1M with a pipeline
+pipe = pipeline("text-generation", model="Qwen/Qwen2.5-14B-Instruct-1M")
 
-# 🎯 Extract interests from user input
+# 🎯 Function to extract interests from user input
 def extract_interests(text):
     prompt = f"Extract 3-5 relevant interests from this request: '{text}'. Focus on hobbies and product preferences."
-    response = generator(prompt, max_length=50, num_return_sequences=1)
+    
+    response = pipe(prompt, max_length=50, num_return_sequences=1)
     interests = response[0]["generated_text"].replace(prompt, "").strip()
+
     return interests.split(", ")
 
 # 🎁 Web search for gift suggestions
@@ -43,14 +32,19 @@ def search_gifts(interests):
 def recommend_gifts(text):
     if not text:
         return "Please enter a description."
+
     interests = extract_interests(text)
     links = search_gifts(interests)
-    return {"Predicted Interests": interests, "Gift Suggestions": links}
 
-# 🎨 Gradio UI
+    return {
+        "Predicted Interests": interests,
+        "Gift Suggestions": links
+    }
+
+# 🎨 Gradio UI for easy interaction
 demo = gr.Interface(
-    fn=recommend_gifts,
-    inputs="text",
+    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!",
@@ -59,4 +53,3 @@ demo = gr.Interface(
 # 🚀 Launch Gradio App
 if __name__ == "__main__":
     demo.launch()
-