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2c07d60 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 | #!/usr/bin/env python3
"""
WebICoder v3 — Quick Start Example
Generate HTML websites from natural language prompts using MLX on Apple Silicon.
⚠️ MANDATORY: This script implements all 5 required rules for correct output.
See README.md for full documentation.
Usage:
python example.py "Create a landing page for a coffee shop"
python example.py --interactive
"""
import sys
import re
from mlx_lm import load, stream_generate
from mlx_lm.sample_utils import make_sampler, make_logits_processors
# ─── Configuration ──────────────────────────────────────────────────────────
MODEL_PATH = "." # Current directory (the model repo)
# RULE 1: System prompt + Alpaca format (### Instruction / ### Response)
SYSTEM_PROMPT = (
"You are WebICoder, an expert frontend web developer specializing in premium, "
"Apple-inspired design. You create stunning websites using only HTML, CSS, and "
"vanilla JavaScript. Your designs feature: minimalist layouts, elegant typography, "
"smooth animations, glassmorphism effects, generous whitespace, and a refined "
"color palette. You always produce complete, production-ready code."
)
# RULE 2: Stop sequences — MANDATORY to prevent infinite loops
STOP_SEQUENCES = ["</html>", "### Instruction:", "You are Deepcoder", "You are WebICoder"]
# RULE 4: Low temperature — MANDATORY for coherent HTML
DEFAULT_TEMP = 0.4
DEFAULT_MAX_TOKENS = 4096
# ─── RULE 1: Prompt Formatting (MANDATORY) ──────────────────────────────────
def format_prompt(user_input: str) -> str:
"""
MANDATORY: Format user input into the model's training prompt format.
The model was trained with Alpaca-style prompts. Sending raw text
without this formatting will produce garbage output.
"""
return f"{SYSTEM_PROMPT}\n\n### Instruction:\n{user_input}\n\n### Response:\n"
# ─── RULE 5: Post-Processing (MANDATORY) ────────────────────────────────────
def clean_html(text: str) -> str:
"""
MANDATORY: Extract clean HTML from model output.
The model may leak training artifacts (system prompt, instruction markers).
This function strips them and returns only valid HTML.
"""
# Remove system prompt leaks
for pattern in [
r"You are (?:Deep|Web[iI])coder.*?production-ready code\.\n*",
r"### Instruction:.*",
r"### Response:\s*",
]:
text = re.sub(pattern, "", text, flags=re.DOTALL)
# Extract complete HTML document
html_match = re.search(r"(<(?:!DOCTYPE\s+html|html)[\s\S]*?</html>)", text, re.IGNORECASE)
if html_match:
return html_match.group(1).strip()
# Fallback: find any HTML content and wrap it
html_start = re.search(r"<(?:!DOCTYPE|html|head|body|link)", text, re.IGNORECASE)
if html_start:
html = text[html_start.start():].strip()
if not html.lower().startswith("<!doctype"):
html = "<!DOCTYPE html>\n<html>\n" + html
if "</html>" not in html.lower():
html += "\n</html>"
return html
return text.strip()
# ─── Generation ─────────────────────────────────────────────────────────────
def generate_html(prompt: str, temperature: float = DEFAULT_TEMP, max_tokens: int = DEFAULT_MAX_TOKENS) -> str:
"""
Generate HTML from a natural language prompt.
Implements all 5 mandatory rules:
1. Prompt formatting (### Instruction / ### Response)
2. Stop at </html>
3. Repetition penalty (1.2, context=256)
4. Low temperature (0.4)
5. Post-processing (clean_html)
"""
print(f"[INFO] Loading model from: {MODEL_PATH}")
model, tokenizer = load(MODEL_PATH)
# RULE 1: Format the prompt
formatted_prompt = format_prompt(prompt)
# RULE 4: Low temperature sampler
sampler = make_sampler(temp=temperature)
# RULE 3: Repetition penalty — MANDATORY
logits_processors = make_logits_processors(
repetition_penalty=1.2,
repetition_context_size=256,
)
print(f"[INFO] Generating (temp={temperature}, max_tokens={max_tokens}, rep_penalty=1.2)...")
print("─" * 60)
full_text = ""
last_response = None
for response in stream_generate(
model, tokenizer,
prompt=formatted_prompt,
max_tokens=max_tokens,
sampler=sampler,
logits_processors=logits_processors, # RULE 3
):
last_response = response
token_str = response.text
full_text += token_str
print(token_str, end="", flush=True)
# RULE 2: Stop at </html> — MANDATORY
should_stop = False
for stop_seq in STOP_SEQUENCES:
if stop_seq in full_text:
idx = full_text.find(stop_seq)
if stop_seq == "</html>":
full_text = full_text[:idx + len(stop_seq)]
else:
full_text = full_text[:idx]
should_stop = True
break
if should_stop or response.finish_reason is not None:
break
print("\n" + "─" * 60)
if last_response:
print(f"[INFO] Generated {last_response.generation_tokens} tokens at {last_response.generation_tps:.1f} tok/s")
print(f"[INFO] Peak memory: {last_response.peak_memory:.2f} GB")
# RULE 5: Clean the output — MANDATORY
return clean_html(full_text)
# ─── Main ────────────────────────────────────────────────────────────────────
def main():
if len(sys.argv) > 1 and sys.argv[1] != "--interactive":
# Single prompt mode
prompt = " ".join(sys.argv[1:])
html = generate_html(prompt)
output_file = "output.html"
with open(output_file, "w") as f:
f.write(html)
print(f"\n[INFO] Saved to {output_file} ({len(html)} chars)")
else:
# Interactive mode
print("=" * 60)
print(" ⚡ WebICoder v3 — Interactive Mode")
print(" Type a website description, press Enter to generate.")
print(" Type 'quit' to exit.")
print("=" * 60)
while True:
try:
prompt = input("\n🌐 Describe your website: ").strip()
if not prompt or prompt.lower() in ("quit", "exit", "q"):
break
html = generate_html(prompt)
output_file = "output.html"
with open(output_file, "w") as f:
f.write(html)
print(f"\n[INFO] Saved to {output_file} ({len(html)} chars)")
except KeyboardInterrupt:
print("\n[INFO] Bye!")
break
if __name__ == "__main__":
main()
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