Spaces:
Running
on
Zero
Running
on
Zero
import gradio as gr | |
from transformers import AutoModelForCausalLM, AutoTokenizer | |
import torch | |
import spaces | |
import io | |
# Initialize the Qwen model and tokenizer | |
model_name = "Qwen/Qwen2.5-Coder-7B-Instruct" | |
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto") | |
tokenizer = AutoTokenizer.from_pretrained(model_name) | |
# Function to generate README and documentation | |
def generate_documentation(code_input): | |
prompt = f"Generate README for the following code:\n\n{code_input}" | |
messages = [ | |
{"role": "system", "content": "You are CodeDocify, a highly efficient and intelligent assistant designed to analyze code and generate comprehensive, clear, and concise documentation. Your purpose is to help developers by producing well-structured README files and detailed explanations of their code. You aim to simplify complex code into easily understandable documentation, ensuring that your responses are accurate, professional, and easy to follow."}, | |
{"role": "user", "content": prompt} | |
] | |
# Prepare inputs for the model | |
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) | |
model_inputs = tokenizer([text], return_tensors="pt").to(model.device) | |
# Generate the documentation | |
generated_ids = model.generate(**model_inputs, max_new_tokens=4000) | |
generated_ids = [output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)] | |
documentation = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] | |
print(documentation) | |
return documentation | |
# Gradio interface | |
def process_code(code_input): | |
documentation = generate_documentation(code_input) | |
readme_file = io.BytesIO() | |
readme_file.write(documentation.encode('utf-8')) | |
readme_file.seek(0) | |
return documentation, readme_file | |
# Set up the Gradio app with Bootstrap, icons, and smiley | |
with gr.Blocks(css=".container { font-family: 'Roboto', sans-serif; } .btn-primary { background-color: #007bff; } .icon { margin-right: 10px; }") as app: | |
gr.Markdown(""" | |
#Code Documentation Generator | |
Paste your code below, and the app will generate the Documentation for you. | |
""") | |
with gr.Row(): | |
code_input = gr.Textbox(lines=10, label="Paste your code here", placeholder="Enter your code...", show_label=False, elem_classes="form-control") | |
with gr.Row(): | |
generate_button = gr.Button("Generate Documentation", elem_classes="btn btn-primary") | |
with gr.Row(): | |
output_text = gr.Markdown(label="Generated Documentation") | |
download_button = gr.File(label="Download README.md") | |
# Bind function to button click | |
generate_button.click(process_code, inputs=code_input, outputs=[output_text, download_button]) | |
# Launch the Gradio app | |
app.launch() | |