from fastapi import APIRouter, Body, Depends
from openai import OpenAI
from pydantic import BaseModel

from api.dependencies import get_llm_client

router = APIRouter()


class ChatRequest(BaseModel):
    message: str
    session_id: str | None = None


def run_agent(client: OpenAI, message: str, session_id: str | None = None) -> str:
    response = client.chat.completions.create(
        model="deepseek-chat",
        messages=[
            {"role": "system", "content": "You are a helpful agent."},
            {"role": "user", "content": message},
        ],
    )
    return response.choices[0].message.content


@router.get("/")
def root():
    return {"status": "ok"}


@router.post("/chat")
def chat(req: ChatRequest, client: OpenAI = Depends(get_llm_client)):
    response = run_agent(client, req.message, req.session_id)
    return {"response": response, "session_id": req.session_id}


@router.get("/models")
def list_models():
    return {
        "object": "list",
        "data": [
            {
                "id": "agent-model",
                "object": "model",
                "created": 0,
                "owned_by": "local-agent",
            }
        ],
    }


@router.post("/chat/completions")
def chat_completions(
    payload: dict = Body(...),
    client: OpenAI = Depends(get_llm_client),
):
    messages = payload["messages"]
    user_message = messages[-1]["content"]
    response = run_agent(client, user_message)

    return {
        "id": "chatcmpl-local",
        "object": "chat.completion",
        "choices": [
            {
                "index": 0,
                "message": {"role": "assistant", "content": response},
            }
        ],
    }