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IMMORTAL-text-to-code-ai

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IMMORTALJAY commited on Jul 16, 2025

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1 Parent(s): 65fc6ad

Update app.py

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app.py +146 -17

app.py CHANGED Viewed

@@ -1,22 +1,151 @@
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import torch
-model_id = "replit/replit-code-v1-3b"
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
-def generate_code(prompt):
-    inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
-    outputs = model.generate(**inputs, max_new_tokens=300)
-    code = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return code
-gr.Interface(
-    fn=generate_code,
-    inputs=gr.Textbox(label="Enter your coding prompt", lines=4),
-    outputs=gr.Code(label="Generated Code"),
-    title="IMMORTAL Text to Code AI",
-    description="Now powered by Replit Code model — real code generation!"
-).launch()

 import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import time
+import os
+from utils.zip_generator import create_zip
+from utils.code_explainer import explain_code
+# Load the AI model (using DeepSeek Coder 1.3B as default)
+MODEL_NAME = "deepseek-ai/deepseek-coder-1.3b"
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
+# Predefined prompts for common website types
+PREBUILT_PROMPTS = {
+    "Portfolio": "Create a modern portfolio website with dark mode toggle, hero section, about me, projects grid, and contact form. Use Tailwind CSS for styling.",
+    "Blog": "Build a blog homepage with responsive navbar, featured post section, article cards grid, and newsletter subscription. Make it minimalist and elegant.",
+    "Landing Page": "Design a one-page landing page for a SaaS product with hero section, features, testimonials, pricing table, and CTA button. Use bright colors.",
+    "E-commerce": "Create an e-commerce product page with image gallery, product details, add to cart button, and related products section. Make it mobile-friendly."
+}
+def generate_website(prompt, use_prebuilt=False, explain=False):
+    start_time = time.time()
+    # Use prebuilt prompt if selected
+    if use_prebuilt and prompt in PREBUILT_PROMPTS:
+        prompt = PREBUILT_PROMPTS[prompt]
+    # Construct the full prompt for the AI
+    full_prompt = f"""Create a complete, responsive website based on this description:
+{prompt}
+Requirements:
+- Use HTML, CSS, and minimal JavaScript
+- Make it mobile-friendly
+- Include all necessary UI elements
+- Add comments in the code
+Here's the complete code:
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Generated Website</title>
+    <style>"""
+    # Generate code using the AI model
+    inputs = tokenizer(full_prompt, return_tensors="pt")
+    outputs = model.generate(**inputs, max_length=1500, temperature=0.7)
+    generated_code = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    # Extract the HTML part (from the prompt onward)
+    html_start = generated_code.find("<!DOCTYPE html>")
+    if html_start == -1:
+        html_start = generated_code.find("<html")
+    if html_start != -1:
+        generated_code = generated_code[html_start:]
+    # Create explanation if requested
+    explanation = ""
+    if explain:
+        explanation = explain_code(generated_code)
+    # Generate downloadable ZIP
+    zip_path = create_zip(generated_code)
+    processing_time = time.time() - start_time
+    return generated_code, zip_path, explanation, f"Generated in {processing_time:.2f} seconds"
+# Gradio UI
+with gr.Blocks(title="AI Website Builder", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🚀 AI Website Builder")
+    gr.Markdown("Describe the website you want and we'll generate the code for you!")
+    with gr.Row():
+        with gr.Column(scale=3):
+            prompt_type = gr.Dropdown(
+                choices=list(PREBUILT_PROMPTS.keys()),
+                label="Or select a prebuilt template",
+                value="Portfolio"
+            )
+            user_prompt = gr.Textbox(
+                label="Describe your website",
+                placeholder="e.g., 'A modern portfolio with dark mode and contact form'",
+                lines=3
+            )
+            explain_checkbox = gr.Checkbox(label="Explain the generated code", value=False)
+            generate_btn = gr.Button("Generate Website", variant="primary")
+        with gr.Column(scale=2):
+            gr.Examples(
+                examples=[
+                    ["A minimalist personal blog with dark mode"],
+                    ["A restaurant homepage with menu and reservation form"],
+                    ["A tech startup landing page with animated features"]
+                ],
+                inputs=user_prompt,
+                label="Example Prompts"
+            )
+    with gr.Row():
+        code_output = gr.Code(
+            label="Generated Code",
+            language="html",
+            interactive=True
+        )
+        html_output = gr.HTML(
+            label="Live Preview",
+            interactive=False
+        )
+    with gr.Row():
+        time_output = gr.Textbox(label="Generation Time")
+        download_btn = gr.Button("Download Code as ZIP")
+        download_file = gr.File(label="Download", visible=False)
+    explanation_output = gr.Textbox(
+        label="Code Explanation",
+        visible=False,
+        lines=5
+    )
+    # Event handlers
+    generate_btn.click(
+        fn=generate_website,
+        inputs=[user_prompt, prompt_type, explain_checkbox],
+        outputs=[code_output, download_file, explanation_output, time_output]
+    )
+    code_output.change(
+        fn=lambda x: x,
+        inputs=code_output,
+        outputs=html_output
+    )
+    download_btn.click(
+        fn=lambda x: x,
+        inputs=download_file,
+        outputs=download_file
+    )
+    explain_checkbox.change(
+        fn=lambda x: gr.Textbox(visible=x),
+        inputs=explain_checkbox,
+        outputs=explanation_output
+    )
+if __name__ == "__main__":
+    demo.launch()