app.py

from transformers import AutoModelForCausalLM, AutoTokenizer
import gradio as gr

# Load the DeepSeek-Coder model
model_name = "deepseek-ai/deepseek-coder-6.7b-instruct"  # You can use any LLaMA-based model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Function to generate comments
def generate_code_comments(code_snippet):
    prompt = f"### Code:\n{code_snippet}\n### Add meaningful comments to this code:\n"
    inputs = tokenizer(prompt, return_tensors="pt", padding=True, truncation=True, max_length=512)
    outputs = model.generate(**inputs, max_length=512)
    commented_code = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return commented_code

# Create Gradio interface
iface = gr.Interface(
    fn=generate_code_comments,
    inputs="text",
    outputs="text",
    title="AI Code Comment Generator",
    description="Enter a code snippet, and the AI will add meaningful comments.",
)

iface.launch()