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| import gradio as gr | |
| import torch | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| # Load CodeT5+ model and tokenizer | |
| model_id = "Salesforce/codet5p-770m" | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| model = AutoModelForSeq2SeqLM.from_pretrained(model_id, torch_dtype=torch.float32) | |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| model.to(device) | |
| # Prompt templates for supported languages | |
| language_prompts = { | |
| "Python": "Fix the following Python code:\n", | |
| "C": "Fix the following C code:\n", | |
| "C++": "Fix the following C++ code:\n", | |
| "JavaScript": "Fix the following JavaScript code:\n" | |
| } | |
| # Debug function | |
| def eternos_debugger(code, error, language): | |
| if not code.strip(): | |
| return "β Please enter some code to debug." | |
| prompt = language_prompts[language] + code + "\nError:\n" + error + "\nFixed Code:\n" | |
| inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512).to(device) | |
| with torch.no_grad(): | |
| outputs = model.generate( | |
| **inputs, | |
| max_new_tokens=256, | |
| temperature=0.3, | |
| top_p=0.9, | |
| do_sample=True | |
| ) | |
| result = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| return result.strip() | |
| # Gradio Interface | |
| with gr.Blocks(theme=gr.themes.Soft()) as demo: | |
| gr.Markdown("## π οΈ Eternos β AI Code Debugger") | |
| gr.Markdown("Supports Python, C, C++, JavaScript β Powered by CodeT5+") | |
| with gr.Row(): | |
| code_input = gr.Textbox(label="π¨βπ» Your Code", lines=14, placeholder="Paste your buggy code here...") | |
| error_input = gr.Textbox(label="β οΈ Error Message (optional)", lines=4) | |
| language_input = gr.Dropdown(["Python", "C", "C++", "JavaScript"], label="π Language", value="Python") | |
| output_code = gr.Code(label="β Suggested Fix") | |
| run_btn = gr.Button("π Debug Code") | |
| run_btn.click(fn=eternos_debugger, inputs=[code_input, error_input, language_input], outputs=output_code) | |
| demo.launch() | |