import time
import os
from typing import TYPE_CHECKING
if TYPE_CHECKING:
    from avatars.base_avatar import BaseAvatar
from utils.logger import logger

# Built-in LLM providers. Each exposes an OpenAI-compatible chat completions
# endpoint; the active one is selected with --llm_provider (default: dashscope).
LLM_PROVIDERS = {
    "dashscope": {
        "api_key_env": "DASHSCOPE_API_KEY",
        "base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1",
        "default_model": "qwen-plus",
    },
    "orcarouter": {
        "api_key_env": "ORCAROUTER_API_KEY",
        "base_url": "https://api.orcarouter.ai/v1",
        "default_model": "orcarouter/auto",
    },
}


def _llm_provider(opt) -> str:
    """Return the configured provider name, defaulting to dashscope."""
    return getattr(opt, 'llm_provider', 'dashscope') or 'dashscope'


def _llm_client(opt):
    """Create the OpenAI-compatible client for the configured provider."""
    from openai import OpenAI
    cfg = LLM_PROVIDERS.get(_llm_provider(opt), LLM_PROVIDERS['dashscope'])
    return OpenAI(
        api_key=os.getenv(cfg['api_key_env']),
        base_url=cfg['base_url'],
    )


def _llm_model(opt) -> str:
    """Resolve the model name, falling back to the provider default."""
    cfg = LLM_PROVIDERS.get(_llm_provider(opt), LLM_PROVIDERS['dashscope'])
    return getattr(opt, 'llm_model', '') or cfg['default_model']


def llm_response(message,avatar_session:'BaseAvatar',datainfo:dict={}):
    try:
        opt = avatar_session.opt
        start = time.perf_counter()
        client = _llm_client(opt)
        model = _llm_model(opt)
        end = time.perf_counter()
        logger.info(f"llm Time init: {end-start}s,{message}")
        completion = client.chat.completions.create(
            model=model,
            messages=[{'role': 'system', 'content': '你是一个知识助手，尽量以简短、口语化的方式输出'},
                    {'role': 'user', 'content': message}],
            stream=True,
            # Display token usage in the last line of the streamed response.
            stream_options={"include_usage": True}
        )
        result=""
        first = True
        for chunk in completion:
            if len(chunk.choices)>0:
                #print(chunk.choices[0].delta.content)
                if first:
                    end = time.perf_counter()
                    logger.info(f"llm Time to first chunk: {end-start}s")
                    first = False
                msg = chunk.choices[0].delta.content
                if msg is None:
                    continue
                lastpos=0
                #msglist = re.split('[,.!;:，。！?]',msg)
                for i, char in enumerate(msg):
                    if char in ",.!;:，。！？：；" :
                        result = result+msg[lastpos:i+1]
                        lastpos = i+1
                        if len(result)>10:
                            logger.info(result)
                            avatar_session.put_msg_txt(result,datainfo)
                            result=""
                result = result+msg[lastpos:]
        end = time.perf_counter()
        logger.info(f"llm Time to last chunk: {end-start}s")
        if result:
            avatar_session.put_msg_txt(result,datainfo)

    except Exception as e:
        logger.exception('llm exceptiopn:')
        return