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MINEOGO commited on 9 days ago

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853d569

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1 Parent(s): 5f4f3c1

Update app.py

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app.py +43 -54

app.py CHANGED Viewed

@@ -2,83 +2,72 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 import re
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-def clean_code_blocks(raw_response):
     """
-    Extract code for each file from a structured LLM response
-    Expected format:
     index.html
     <code>
-    static/style.css
     <code>
     """
-    parts = re.split(r"(?:\n|^)([^\n\/\\<>:\"|?*]+(?:\.[a-z]+)?(?:\/[^\n]+)?)\n", raw_response)
-    file_blocks = {}
-    for i in range(1, len(parts), 2):
-        filename = parts[i].strip()
-        code = parts[i + 1].strip()
-        if filename and code:
-            file_blocks[filename] = code
-    return file_blocks
 def generate_code(prompt, system_message, max_tokens, temperature, top_p, backend):
-    full_system_prompt = f"""
-You are a code-generation AI. You MUST generate a full website including an index.html file.
-Use ONLY the {backend} backend structure.
-Output all code for each file separately using this format:
-filename.ext
-<code without backticks>
-Do NOT add commentary, do NOT use markdown. Output raw code only.
-""".strip() + "\n\n" + system_message
     messages = [
-        {"role": "system", "content": full_system_prompt},
         {"role": "user", "content": prompt}
     ]
-    response = ""
-    for chunk in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p
-    ):
-        token = chunk.choices[0].delta.content
-        if token:
-            response += token
-    # Parse and display each file in its own tab
     files = clean_code_blocks(response)
-    tabs = []
-    for filename, code in files.items():
-        tabs.append(gr.TabItem(label=filename, elem_id=filename))
-        tabs.append(gr.Code(value=code, language="html" if filename.endswith(".html") else "python" if filename.endswith(".py") else "javascript" if filename.endswith(".js") else "css", label=filename))
-    return tabs
 with gr.Blocks() as demo:
-    gr.Markdown("## WebGen AI — One Prompt → Multi-File Website Generator")
     with gr.Row():
-        prompt = gr.Textbox(label="Enter Prompt", placeholder="Describe the website you want...")
-        backend = gr.Dropdown(["Flask", "Static", "Node.js"], value="Static", label="Select Backend")
-    system_msg = gr.Textbox(value="You are a helpful assistant.", label="System Message")
-    max_tokens = gr.Slider(1, 2048, value=1024, label="Max Tokens")
-    temperature = gr.Slider(0.1, 4.0, value=0.7, step=0.1, label="Temperature")
-    top_p = gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-p")
-    run_btn = gr.Button("Generate Code")
-    tabs_output = gr.Group()
-    def wrapper(*args):
-        return generate_code(*args)
-    run_btn.click(wrapper, inputs=[prompt, system_msg, max_tokens, temperature, top_p, backend], outputs=tabs_output)
 if __name__ == "__main__":
     demo.launch()

 from huggingface_hub import InferenceClient
 import re
+client = InferenceClient("http://localhost:5000")  # change this if needed
+def clean_code_blocks(response):
     """
+    Parses AI response to extract file blocks like:
     index.html
     <code>
+    style.css
     <code>
     """
+    pattern = re.compile(r"^([^\s\/\\]+\.?[a-zA-Z0-9]*)\n([\s\S]+?)(?=\n\S|$)", re.MULTILINE)
+    return pattern.findall(response)
 def generate_code(prompt, system_message, max_tokens, temperature, top_p, backend):
+    system_prompt = f"""
+You are a code-generation assistant.
+Respond ONLY with raw code for a website with multiple files (like index.html, style.css, script.js, app.py, etc.).
+Use the {backend} backend ONLY.
+Do NOT use markdown formatting. Do NOT add backticks. Do NOT add any explanations. Just output file names followed by their code, like:
+index.html
+<html>...
+style.css
+body {{...}}
+app.py
+from flask import Flask...
+""".strip()
     messages = [
+        {"role": "system", "content": system_prompt + "\n\n" + system_message},
         {"role": "user", "content": prompt}
     ]
+    # Single non-streaming call since we're parsing files
+    completion = client.chat_completion(messages, max_tokens=max_tokens, temperature=temperature, top_p=top_p)
+    response = completion.choices[0].message.content
     files = clean_code_blocks(response)
+    with gr.Tabs() as tabset:
+        for filename, code in files:
+            with gr.Tab(label=filename.strip()):
+                gr.Code(value=code.strip(), language="html" if filename.endswith(".html") else "css" if filename.endswith(".css") else "javascript" if filename.endswith(".js") else "python" if filename.endswith(".py") else "text")
+    return tabset
 with gr.Blocks() as demo:
+    gr.Markdown("### WebGen: Prompt → Multi-File Website (with Flask, Node.js, Static support)")
     with gr.Row():
+        prompt = gr.Textbox(label="Prompt", lines=2)
+        backend = gr.Dropdown(["Flask", "Static", "Node.js"], value="Static", label="Backend")
+    with gr.Accordion("Advanced Settings", open=False):
+        system_msg = gr.Textbox(value="", label="System Message")
+        max_tokens = gr.Slider(128, 2048, value=1024, step=1, label="Max Tokens")
+        temperature = gr.Slider(0.1, 2.0, value=0.7, step=0.1, label="Temperature")
+        top_p = gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-p")
+    output = gr.Column()
+    run_btn = gr.Button("Generate")
+    run_btn.click(generate_code, inputs=[prompt, system_msg, max_tokens, temperature, top_p, backend], outputs=output)
 if __name__ == "__main__":
     demo.launch()