| 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() |
