Update app.py

app.py

@@ -2,24 +2,23 @@ import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 
-# ✅ Use open-access model
-model_name = "deepseek-ai/deepseek-coder-6.7b-instruct"
+model_name = "Salesforce/codegen-350M-mono"
 
 tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
-def generate_html(prompt):
-    input_prompt = f"Generate only HTML, CSS, and JS website code from this idea:\n\n{prompt}\n\nOnly return code output:"
-    inputs = tokenizer.encode(input_prompt, return_tensors="pt", truncation=True, max_length=1024)
-    outputs = model.generate(inputs, max_length=1500, temperature=0.7, do_sample=True)
+def generate_code(prompt):
+    full_prompt = f"# HTML/CSS/JS website code for:\n# {prompt}\n"
+    inputs = tokenizer(full_prompt, return_tensors="pt").input_ids
+    outputs = model.generate(inputs, max_length=1024, temperature=0.7)
     decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    first_tag = decoded.find('<')
-    return decoded[first_tag:] if first_tag != -1 else decoded
+    html_start = decoded.find('<')
+    return decoded[html_start:] if html_start != -1 else decoded
 
 gr.Interface(
-    fn=generate_html,
-    inputs=gr.Textbox(lines=6, label="Describe your website idea (English or Hindi)"),
-    outputs=gr.Code(label="Generated HTML/CSS/JS Code"),
+    fn=generate_code,
+    inputs=gr.Textbox(lines=6, label="Describe your website idea"),
+    outputs=gr.Code(label="Generated HTML/CSS/JS"),
     title="SKORD AI Website Generator",
-    description="Type your website idea and receive full HTML/CSS/JS code (pure code output only)."
+    description="Describe your idea in English or Hindi. This will return only HTML/CSS/JS."
 ).launch()