Update app.py

app.py

@@ -2,27 +2,24 @@ import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 
-# Load Starcoder model (code generation)
-model_name = "bigcode/starcoder"
+# ✅ Use open-access model
+model_name = "deepseek-ai/deepseek-coder-6.7b-instruct"
+
 tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32)
 
 def generate_html(prompt):
-    input_text = f"Generate only HTML/CSS/JS code for this website idea:\n{prompt}"
-    inputs = tokenizer.encode(input_text, return_tensors="pt", truncation=True, max_length=1024)
+    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)
-    code = tokenizer.decode(outputs[0], skip_special_tokens=True)
-
-    # Keep only the HTML part from the output
-    first_html_index = code.find('<')
-    if first_html_index != -1:
-        return code[first_html_index:]
-    return code
+    decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    first_tag = decoded.find('<')
+    return decoded[first_tag:] if first_tag != -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"),
+    outputs=gr.Code(label="Generated HTML/CSS/JS Code"),
     title="SKORD AI Website Generator",
-    description="Get only HTML/CSS/JS code from your idea using AI. Works in English and Hindi."
+    description="Type your website idea and receive full HTML/CSS/JS code (pure code output only)."
 ).launch()