import socket
import subprocess
import gradio as gr
from openai import OpenAI


subprocess.Popen("bash /home/user/app/start.sh", shell=True)

client = OpenAI(base_url="http://0.0.0.0:8000/v1", api_key="sk-local", timeout=600)


def respond(
    message,
    history: list[tuple[str, str]],
    system_message=None,
    max_tokens=None,
    temperature=0.7
):
    messages = []
    if system_message:
        messages = [{"role": "system", "content": system_message}]

    for user, assistant in history:
        if user:
            messages.append({"role": "user", "content": user})
        if assistant:
            messages.append({"role": "assistant", "content": assistant})

    messages.append({"role": "user", "content": message})

    try:
        stream = client.chat.completions.create(
            model="Deepseek-R1-0528-Qwen3-8B",
            messages=messages,
            max_tokens=max_tokens,
            temperature=temperature,
            top_p=top_p,
            stream=True,
            tools=[
                {
                    "type": "function",
                    "function": {
                        "name": "browser_search",
                        "description": (
                            "Search the web for a given query and return the most relevant results."
                        ),
                        "parameters": {
                            "type": "object",
                            "properties": {
                                "query": {
                                    "type": "string",
                                    "description": "The search query string.",
                                },
                                "max_results": {
                                    "type": "integer",
                                    "description": (
                                        "Maximum number of search results to return. "
                                        "If omitted the service will use its default."
                                    ),
                                    "default": 5,
                                },
                            },
                            "required": ["query"],
                        },
                    },
                },
                {"type": "code_interpreter"},
            ],
        )

        print("messages", messages)
        output = ""
        for chunk in stream:
            delta = chunk.choices[0].delta

            try:
                output += delta.reasoning_content
            except:
                output += delta.content or ""

            yield output

    except Exception as e:
        print(f"[Error] {e}")
        yield "⚠️ Llama.cpp server error"


demo = gr.ChatInterface(respond)

if __name__ == "__main__":
    demo.launch(show_api=False)