Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from fpdf import FPDF
+import torch
+import spaces
+
+# 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
+@spaces.GPU
+def generate_documentation(code_input):
+    prompt = f"Generate README and documentation 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=512)
+    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]
+    
+    return documentation
+
+# Function to generate and download PDF
+def create_pdf(documentation):
+    pdf = FPDF()
+    pdf.set_auto_page_break(auto=True, margin=15)
+    pdf.add_page()
+    pdf.set_font("Arial", size=12)
+    pdf.multi_cell(200, 10, documentation)
+    
+    file_name = "/mnt/data/Generated_Documentation.pdf"
+    pdf.output(file_name)
+    
+    return file_name
+
+# Gradio interface
+def process_code(code_input):
+    documentation = generate_documentation(code_input)
+    pdf_path = create_pdf(documentation)
+    return documentation, pdf_path
+
+# 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("""
+    # :notebook_with_decorative_cover: Code Documentation Generator
+    
+    Paste your code below, and the app will generate the README and detailed documentation for you.
+    The output will also be available for download as a PDF.
+    """)
+    
+    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(":sparkles: Generate Documentation", elem_classes="btn btn-primary")
+    
+    with gr.Row():
+        output_text = gr.Textbox(label="Generated Documentation", lines=20, interactive=False)
+        download_pdf = gr.File(label="Download PDF", file_types=[".pdf"])
+    
+    # Bind function to button click
+    generate_button.click(process_code, inputs=code_input, outputs=[output_text, download_pdf])
+
+# Launch the Gradio app
+app.launch()