"""LLM 어댑터 — openai SDK 직접 호출 (langchain 미사용).

provider 로 OpenAI / Azure OpenAI 분기. 무거운 import 는 호출 시점에 한다.
chat_complete: messages → 응답 텍스트. json_mode 면 JSON 객체 강제(response_format).
"""

import json
from typing import List, Optional

from negotiation.profiling.config import LlmCredentials


def _client(creds: LlmCredentials):
    if creds.provider == "azure":
        from openai import AzureOpenAI
        return AzureOpenAI(api_key=creds.api_key, azure_endpoint=creds.azure_endpoint,
                           api_version=creds.api_version or "2024-06-01")
    from openai import OpenAI
    kwargs = {"api_key": creds.api_key}
    if creds.base_url:
        kwargs["base_url"] = creds.base_url
    return OpenAI(**kwargs)


def chat_complete(messages: List[dict], creds: Optional[LlmCredentials] = None,
                  json_mode: bool = False, temperature: float = 0.7, max_tokens: int = 1024) -> str:
    """OpenAI(또는 Azure) chat completion 호출 → 응답 텍스트.

    Args:
        messages: [{"role": "system"|"user"|"assistant", "content": "..."}]
        creds: 자격증명(없으면 OpenAIConfig 전역값).
        json_mode: True 면 JSON 객체 응답 강제.
    """
    if creds is None:
        creds = LlmCredentials.from_config()
    if not creds.is_configured():
        raise RuntimeError("LLM 미설정 (OpenAIConfig.api_key/model 확인)")

    client = _client(creds)
    kwargs = {"model": creds.model, "messages": messages,
              "temperature": temperature, "max_tokens": max_tokens}
    if json_mode:
        kwargs["response_format"] = {"type": "json_object"}
    resp = client.chat.completions.create(**kwargs)
    return resp.choices[0].message.content or ""


def chat_json(messages: List[dict], creds: Optional[LlmCredentials] = None, **kw) -> dict:
    """JSON 응답을 파싱해 dict 로 반환."""
    text = chat_complete(messages, creds=creds, json_mode=True, **kw)
    return json.loads(text)