app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load the CodeGen model
model_name = "Salesforce/codegen-6B-mono"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, device_map=None)

# Function to generate code
def generate_code(prompt):
    inputs = tokenizer(prompt, return_tensors="pt").to("cuda")  # Use GPU if available
    outputs = model.generate(inputs["input_ids"], max_length=100, num_beams=5)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Create a Gradio interface
interface = gr.Interface(
    fn=generate_code,
    inputs=gr.Textbox(lines=2, placeholder="Enter your code prompt here..."),
    outputs="text",
    title="CodeGen Code Generator",
    description="Generate code from text prompts using Salesforce CodeGen-6B-mono model."
)

# Launch the app
interface.launch()