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. 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()