Update app.py

app.py

@@ -46,6 +46,10 @@ if selected_brand != "Select":
         watch_data = next((item for item in data if item["sku"] == selected_sku), None)
 
     if watch_data:
+        # Generation parameters
+        max_length = st.slider("Max Length", min_value=50, max_value=300, value=150)
+        temperature = st.slider("Temperature", min_value=0.1, max_value=1.0, value=0.7, step=0.1)
+        
         # Generate description based on attributes
         if st.button("Generate Description"):
             attributes = {
@@ -57,11 +61,30 @@ if selected_brand != "Select":
                 "movement": watch_data.get("movement", "Unknown Movement"),
                 "gender": watch_data.get("gender", "Unknown Gender"),
             }
-            input_text = f"Brand: {attributes['brand']}, Watch Name: {attributes['name']}, SKU: {attributes['sku']}, Features: {attributes['features']}, Case Size: {attributes['casesize']}, Movement: {attributes['movement']}, Gender: {attributes['gender']}"
+            
+            # Format input similar to training data (adjust this based on your training data format)
+            input_text = f"""Generate a detailed description for the following watch:
+Brand: {attributes['brand']}
+Name: {attributes['name']}
+SKU: {attributes['sku']}
+Features: {attributes['features']}
+Case Size: {attributes['casesize']}
+Movement: {attributes['movement']}
+Gender: {attributes['gender']}
+
+Description:"""
             
             # Tokenize input and generate description
             inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True)
-            outputs = model.generate(**inputs, max_length=150, num_return_sequences=1)
+            outputs = model.generate(
+                **inputs, 
+                max_length=max_length, 
+                num_return_sequences=1,
+                temperature=temperature,
+                top_k=50,
+                top_p=0.95,
+                do_sample=True
+            )
             
             # Decode generated text
             description = tokenizer.decode(outputs[0], skip_special_tokens=True)
@@ -73,6 +96,10 @@ if selected_brand != "Select":
             # Display watch details
             st.write("### Watch Details")
             st.json(json.dumps(watch_data, indent=2))
+
+            # Display input text for debugging
+            st.write("### Input Text (for debugging)")
+            st.text(input_text)
 else:
     st.warning("Please select a brand.")
 
@@ -99,7 +126,7 @@ st.markdown(
     }
     </style>
     <div class="footer">
-        <p>Developed with ❤️ by Your Name</p>
+        <p>Developed with ❤️ by Shreyansh Jha</p>
     </div>
     """,
     unsafe_allow_html=True