| import gradio as gr |
| import subprocess |
| import threading |
|
|
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| import torch |
|
|
| MODEL_NAME = "Qwen/Qwen2.5-1.5B-Instruct" |
|
|
| print("Loading model...") |
|
|
| tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME) |
|
|
| model = AutoModelForCausalLM.from_pretrained( |
| MODEL_NAME, |
| torch_dtype="auto", |
| device_map="cpu" |
| ) |
|
|
| print("Model loaded") |
|
|
|
|
| def ask_ai(prompt): |
|
|
| try: |
| messages = [ |
| { |
| "role": "user", |
| "content": prompt |
| } |
| ] |
|
|
| text = tokenizer.apply_chat_template( |
| messages, |
| tokenize=False, |
| add_generation_prompt=True |
| ) |
|
|
| inputs = tokenizer( |
| text, |
| return_tensors="pt" |
| ) |
|
|
| output = model.generate( |
| **inputs, |
| max_new_tokens=512, |
| temperature=0.7, |
| do_sample=True |
| ) |
|
|
| result = tokenizer.decode( |
| output[0], |
| skip_special_tokens=True |
| ) |
|
|
| return result |
|
|
| except Exception as e: |
| return str(e) |
|
|
|
|
| def execute_code(code): |
|
|
| try: |
|
|
| proc = subprocess.run( |
| ["python3", "-c", code], |
| capture_output=True, |
| text=True, |
| timeout=30 |
| ) |
|
|
| if proc.returncode == 0: |
| return proc.stdout or "Done" |
|
|
| return proc.stderr |
|
|
| except Exception as e: |
| return str(e) |
|
|
|
|
| def ai_and_run(prompt): |
|
|
| ai_response = ask_ai( |
| prompt + |
| "\nReturn only executable Python code." |
| ) |
|
|
| result = execute_code(ai_response) |
|
|
| return ( |
| "AI RESPONSE:\n\n" |
| + ai_response |
| + "\n\nOUTPUT:\n\n" |
| + result |
| ) |
|
|
|
|
| with gr.Blocks(theme=gr.themes.Soft()) as demo: |
|
|
| gr.Markdown("# Qwen AI + Sandbox") |
|
|
| with gr.Tab("Chat"): |
|
|
| prompt = gr.Textbox( |
| label="Message", |
| lines=4 |
| ) |
|
|
| output = gr.Textbox( |
| label="Response", |
| lines=15 |
| ) |
|
|
| btn = gr.Button("Send") |
|
|
| btn.click( |
| ask_ai, |
| prompt, |
| output |
| ) |
|
|
| with gr.Tab("Python Sandbox"): |
|
|
| code = gr.Textbox( |
| label="Python Code", |
| lines=12 |
| ) |
|
|
| result = gr.Textbox( |
| label="Output", |
| lines=12 |
| ) |
|
|
| run = gr.Button("Run") |
|
|
| run.click( |
| execute_code, |
| code, |
| result |
| ) |
|
|
| with gr.Tab("AI Generate & Run"): |
|
|
| p = gr.Textbox( |
| label="Instruction", |
| lines=4 |
| ) |
|
|
| r = gr.Textbox( |
| label="Result", |
| lines=20 |
| ) |
|
|
| b = gr.Button("Generate & Run") |
|
|
| b.click( |
| ai_and_run, |
| p, |
| r |
| ) |
|
|
| demo.launch( |
| server_name="0.0.0.0", |
| server_port=7860 |
| ) |
