import gradio as gr from huggingface_hub import InferenceClient import sys import io import traceback model_name = "Qwen/Qwen2.5-72B-Instruct" client = InferenceClient(model_name) def llm_inference(user_sample): eos_token = "<|endoftext|>" output = client.chat.completions.create( messages=[ {"role": "system", "content": "You are a Python language guide. Write code on the user topic. Make sure that the code is runnable and doesn't close the shell window, so end with input() if the user request is simple. If the input is code, correct it for mistakes."}, {"role": "user", "content": f"Write only python code without any explanation: {user_sample}"}, ], stream=False, temperature=0.7, top_p=0.1, max_tokens=412, stop=[eos_token] ) response = '' for choice in output.choices: response += choice['message']['content'] return response def chat(user_input, history): response = llm_inference(user_input) history.append((user_input, response)) return history, history def execute_code(code): old_stdout = sys.stdout redirected_output = sys.stdout = io.StringIO() try: exec(code, {}) output = redirected_output.getvalue() except Exception as e: output = f"Error: {e}\n{traceback.format_exc()}" finally: sys.stdout = old_stdout return output with gr.Blocks() as demo: gr.Markdown("# 🐍 Python Helper Chatbot") with gr.Tab("Chat"): chatbot = gr.Chatbot() msg = gr.Textbox(placeholder="Type your message here...") msg.submit(chat, inputs=[msg, chatbot], outputs=[chatbot, chatbot]) with gr.Tab("Interpreter"): gr.Markdown("### 🖥️ Test Your Code") code_input = gr.Code(language="python") run_button = gr.Button("Run Code") code_output = gr.Textbox(label="Output") run_button.click(execute_code, inputs=code_input, outputs=code_output) with gr.Tab("Logs"): gr.Markdown("### 📜 Logs") log_output = gr.Textbox(label="Logs", lines=10, interactive=False) demo.launch()