# coding=utf-8
"""
OpenAI 兼容私域模型调用
"""
import json
from typing import Iterator, Dict, List, Optional, Any

import requests
from django.utils.translation import gettext as _

from common.config.tokenizer_manage_config import TokenizerManage
from common.exception.app_exception import AppApiException
from common.utils.logger import maxkb_logger
from langchain_core.messages import BaseMessage, get_buffer_string
from models_provider.base_model_provider import ModelInfo, ModelTypeConst, MaxKBBaseModel


class OpenAICompatibleChatModel(MaxKBBaseModel):
    """OpenAI 兼容模型调用"""

    @staticmethod
    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
        from models_provider.impl.openai_compatible_provider.openai_compatible_provider import model_info_manage
        model_info = model_info_manage.get_model_info(model_type, model_name)
        return OpenAICompatibleChatModel(model_info=model_info, model_credential=model_credential,
                                         model_name=model_name, **model_kwargs)

    def __init__(self, model_info: ModelInfo, model_credential: Dict[str, object], model_name: str = None, **kwargs):
        self.model_info = model_info
        self.model_credential = model_credential
        self.api_base = model_credential.get('api_base', '').rstrip('/')
        self.api_key = model_credential.get('api_key', '')
        self.model_name = model_name or model_info.name

    def _build_headers(self):
        return {
            'Content-Type': 'application/json',
            'Authorization': f'Bearer {self.api_key}',
        }

    @staticmethod
    def _convert_messages(messages):
        """将 langchain Message 对象转换为 OpenAI API 的 dict 格式"""
        converted = []
        for msg in messages:
            if hasattr(msg, 'content'):
                role = 'system'
                if hasattr(msg, '__class__'):
                    class_name = msg.__class__.__name__
                    if 'Human' in class_name:
                        role = 'user'
                    elif 'AI' in class_name:
                        role = 'assistant'
                    elif 'System' in class_name:
                        role = 'system'
                converted.append({'role': role, 'content': msg.content})
            elif isinstance(msg, dict):
                converted.append(msg)
            else:
                converted.append({'role': 'user', 'content': str(msg)})
        return converted

    def stream(self, messages, **kwargs):
        """流式聊天 - yield 带 content 和 additional_kwargs 属性的对象"""
        url = f"{self.api_base}/chat/completions"
        api_messages = self._convert_messages(messages)
        body = {
            'model': self.model_name,
            'messages': api_messages,
            'stream': True,
            **kwargs
        }

        try:
            response = requests.post(url, json=body, headers=self._build_headers(), stream=True, timeout=120)
            response.raise_for_status()

            for line in response.iter_lines():
                if not line:
                    continue
                line = line.decode('utf-8')
                if not line.startswith('data: '):
                    continue
                data = line[6:]
                if data.strip() == '[DONE]':
                    break
                try:
                    chunk = json.loads(data)
                    delta = chunk.get('choices', [{}])[0].get('delta', {})
                    content = delta.get('content')
                    if content:
                        yield type('StreamChunk', (), {
                            'content': content,
                            'additional_kwargs': {},
                        })()
                except json.JSONDecodeError:
                    continue
        except requests.exceptions.Timeout:
            raise AppApiException(504, _('Request timeout'))
        except requests.exceptions.ConnectionError:
            raise AppApiException(502, _('Failed to connect to API server'))
        except AppApiException:
            raise
        except Exception as e:
            maxkb_logger.error(f'OpenAI compatible stream error: {e}')
            raise AppApiException(500, str(e))

    def invoke(self, messages, **kwargs):
        """非流式聊天 - 返回带 content 和 additional_kwargs 的对象"""
        url = f"{self.api_base}/chat/completions"
        api_messages = self._convert_messages(messages)
        body = {
            'model': self.model_name,
            'messages': api_messages,
            'stream': False,
            **kwargs
        }

        try:
            response = requests.post(url, json=body, headers=self._build_headers(), timeout=120)
            response.raise_for_status()
            result = response.json()
            content = result.get('choices', [{}])[0].get('message', {}).get('content', '')
            return type('InvokeResult', (), {
                'content': content,
                'additional_kwargs': {},
            })()
        except requests.exceptions.Timeout:
            raise AppApiException(504, _('Request timeout'))
        except requests.exceptions.ConnectionError:
            raise AppApiException(502, _('Failed to connect to API server'))
        except Exception as e:
            maxkb_logger.error(f'OpenAI compatible invoke error: {e}')
            raise AppApiException(500, str(e))

    def chat(self, messages, stream=False, **kwargs):
        """聊天补全"""
        if stream:
            return self.stream(messages, **kwargs)
        return self.invoke(messages, **kwargs)

    def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
        try:
            tokenizer = TokenizerManage.get_tokenizer()
            return sum([len(tokenizer.encode(get_buffer_string([m]))) for m in messages])
        except Exception:
            return 0

    def get_num_tokens(self, text: str) -> int:
        try:
            tokenizer = TokenizerManage.get_tokenizer()
            return len(tokenizer.encode(text))
        except Exception:
            return 0

    def verify_connection(self):
        """验证连接"""
        try:
            url = f"{self.api_base}/models"
            response = requests.get(url, headers=self._build_headers(), timeout=10)
            response.raise_for_status()
            return True
        except Exception as e:
            raise AppApiException(500, _('Connection verification failed: {error}').format(error=str(e)))