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7900fe8 | 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 | import torch, gradio as gr
from pathlib import Path
import sys
sys.path.insert(0, str(Path(__file__).parent.parent))
from model.architecture import CodeLLM, CodeLLMConfig
from model.tokenizer import get_gpt2_tokenizer_for_code
DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
config = CodeLLMConfig()
model = CodeLLM(config)
WEIGHTS_PATH = Path("./checkpoints/final/pytorch_model.bin")
if WEIGHTS_PATH.exists():
model.load_state_dict(torch.load(WEIGHTS_PATH, map_location=DEVICE))
print("Loaded trained weights!")
model.to(DEVICE).eval()
tokenizer = get_gpt2_tokenizer_for_code()
def generate_code(prompt, language="Python", max_new_tokens=256, temperature=0.8, top_k=50, top_p=0.95):
lang_map = {"Python":"<|python|>","JavaScript":"<|javascript|>",
"TypeScript":"<|typescript|>","Rust":"<|rust|>","Go":"<|go|>","C++":"<|cpp|>"}
full_prompt = f"{lang_map.get(language,'')}{prompt}"
input_ids = tokenizer.encode(full_prompt, return_tensors="pt").to(DEVICE)
with torch.no_grad():
out = model.generate(input_ids, max_new_tokens=max_new_tokens,
temperature=temperature, top_k=top_k, top_p=top_p)
return tokenizer.decode(out[0][input_ids.shape[1]:], skip_special_tokens=True)
with gr.Blocks(title="CodeLLM", theme=gr.themes.Soft()) as demo:
gr.Markdown("# CodeLLM — Custom Coding AI\n125M param transformer built from scratch")
with gr.Row():
with gr.Column():
prompt = gr.Textbox(label="Code prompt", lines=5, placeholder="def fibonacci(n):")
lang = gr.Dropdown(["Python","JavaScript","TypeScript","Rust","Go","C++"], value="Python", label="Language")
with gr.Row():
btn = gr.Button("Generate ⚡", variant="primary")
clear = gr.Button("Clear")
output = gr.Code(label="Output", language="python", lines=20)
with gr.Accordion("Settings", open=False):
with gr.Row():
max_tok = gr.Slider(32, 512, 256, step=32, label="Max tokens")
temp = gr.Slider(0.1, 2.0, 0.8, step=0.1, label="Temperature")
topk = gr.Slider(1, 100, 50, step=1, label="Top-k")
topp = gr.Slider(0.1, 1.0, 0.95, step=0.05, label="Top-p")
btn.click(generate_code, inputs=[prompt, lang, max_tok, temp, topk, topp], outputs=output)
clear.click(lambda: ("", ""), outputs=[prompt, output])
demo.launch() |