import sys
from fastchat.conversation import Conversation
from server.model_workers.base import *
from fastchat import conversation as conv
import sys
from server.model_workers.base import ApiEmbeddingsParams
from typing import List, Literal, Dict


# MODEL_VERSIONS = {
#     "ernie-bot": "completions",
#     "ernie-bot-turbo": "eb-instant",
#     "bloomz-7b": "bloomz_7b1",
#     "qianfan-bloomz-7b-c": "qianfan_bloomz_7b_compressed",
#     "llama2-7b-chat": "llama_2_7b",
#     "llama2-13b-chat": "llama_2_13b",
#     "llama2-70b-chat": "llama_2_70b",
#     "qianfan-llama2-ch-7b": "qianfan_chinese_llama_2_7b",
#     "chatglm2-6b-32k": "chatglm2_6b_32k",
#     "aquilachat-7b": "aquilachat_7b",
#     # "linly-llama2-ch-7b": "", # 暂未发布
#     # "linly-llama2-ch-13b": "", # 暂未发布
#     # "chatglm2-6b": "", # 暂未发布
#     # "chatglm2-6b-int4": "", # 暂未发布
#     # "falcon-7b": "", # 暂未发布
#     # "falcon-180b-chat": "", # 暂未发布
#     # "falcon-40b": "", # 暂未发布
#     # "rwkv4-world": "", # 暂未发布
#     # "rwkv5-world": "", # 暂未发布
#     # "rwkv4-pile-14b": "", # 暂未发布
#     # "rwkv4-raven-14b": "", # 暂未发布
#     # "open-llama-7b": "", # 暂未发布
#     # "dolly-12b": "", # 暂未发布
#     # "mpt-7b-instruct": "", # 暂未发布
#     # "mpt-30b-instruct": "", # 暂未发布
#     # "OA-Pythia-12B-SFT-4": "", # 暂未发布
#     # "xverse-13b": "", # 暂未发布

#     # # 以下为企业测试，需要单独申请
#     # "flan-ul2": "",
#     # "Cerebras-GPT-6.7B": ""
#     # "Pythia-6.9B": ""
# }


# @cached(TTLCache(1, 1800)) # 经过测试，缓存的token可以使用，目前每30分钟刷新一次
# def get_baidu_access_token(api_key: str, secret_key: str) -> str:
#     """
#     使用 AK，SK 生成鉴权签名（Access Token）
#     :return: access_token，或是None(如果错误)
#     """
#     url = "https://aip.baidubce.com/oauth/2.0/token"
#     params = {"grant_type": "client_credentials", "client_id": api_key, "client_secret": secret_key}
#     try:
#         with get_httpx_client() as client:
#             return client.get(url, params=params).json().get("access_token")
#     except Exception as e:
#         print(f"failed to get token from baidu: {e}")


class QianFanWorker(ApiModelWorker):
    """
    百度千帆
    """
    DEFAULT_EMBED_MODEL = "bge-large-zh"

    def __init__(
        self,
        *,
        version: Literal["ernie-bot", "ernie-bot-turbo"] = "ernie-bot",
        model_names: List[str] = ["qianfan-api"],
        controller_addr: str = None,
        worker_addr: str = None,
        **kwargs,
    ):
        kwargs.update(model_names=model_names, controller_addr=controller_addr, worker_addr=worker_addr)
        kwargs.setdefault("context_len", 16384)
        super().__init__(**kwargs)
        self.version = version

    def do_chat(self, params: ApiChatParams) -> Dict:
        params.load_config(self.model_names[0])
        import qianfan

        comp = qianfan.ChatCompletion(model=params.version,
                                      endpoint=params.version_url,
                                      ak=params.api_key,
                                      sk=params.secret_key,)
        text = ""
        for resp in comp.do(messages=params.messages,
                            temperature=params.temperature,
                            top_p=params.top_p,
                            stream=True):
            if resp.code == 200:
                if chunk := resp.body.get("result"):
                    text += chunk
                    yield {
                        "error_code": 0,
                        "text": text
                    }
            else:
                yield {
                    "error_code": resp.code,
                    "text": str(resp.body),
                }

        # BASE_URL = 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat'\
        #         '/{model_version}?access_token={access_token}'

        # access_token = get_baidu_access_token(params.api_key, params.secret_key)
        # if not access_token:
        #     yield {
        #         "error_code": 403,
        #         "text": f"failed to get access token. have you set the correct api_key and secret key?",
        #     }

        # url = BASE_URL.format(
        #     model_version=params.version_url or MODEL_VERSIONS[params.version],
        #     access_token=access_token,
        # )
        # payload = {
        #     "messages": params.messages,
        #     "temperature": params.temperature,
        #     "stream": True
        # }
        # headers = {
        #     'Content-Type': 'application/json',
        #     'Accept': 'application/json',
        # }
        
        # text = ""
        # with get_httpx_client() as client:
        #     with client.stream("POST", url, headers=headers, json=payload) as response:
        #         for line in response.iter_lines():
        #             if not line.strip():
        #                 continue
        #             if line.startswith("data: "):
        #                 line = line[6:]
        #             resp = json.loads(line)

        #             if "result" in resp.keys():
        #                 text += resp["result"]
        #                 yield {
        #                     "error_code": 0,
        #                     "text": text
        #                 }
        #             else:
        #                 yield {
        #                     "error_code": resp["error_code"],
        #                     "text": resp["error_msg"]
        #                 }

    def do_embeddings(self, params: ApiEmbeddingsParams) -> Dict:
        import qianfan
        params.load_config(self.model_names[0])

        embed = qianfan.Embedding(ak=params.api_key, sk=params.secret_key)
        resp = embed.do(texts = params.texts, model=params.embed_model or self.DEFAULT_EMBED_MODEL)
        if resp.code == 200:
            embeddings = [x.embedding for x in resp.body.get("data", [])]
            return {"code": 200, "embeddings": embeddings}
        else:
            return {"code": resp.code, "msg": str(resp.body)}


    # TODO: qianfan支持续写模型
    def get_embeddings(self, params):
        # TODO: 支持embeddings
        print("embedding")
        print(params)

    def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
        # TODO: 确认模板是否需要修改
        return conv.Conversation(
            name=self.model_names[0],
            system_message="你是一个聪明的助手，请根据用户的提示来完成任务",
            messages=[],
            roles=["user", "assistant"],
            sep="\n### ",
            stop_str="###",
        )


if __name__ == "__main__":
    import uvicorn
    from server.utils import MakeFastAPIOffline
    from fastchat.serve.model_worker import app

    worker = QianFanWorker(
        controller_addr="http://127.0.0.1:20001",
        worker_addr="http://127.0.0.1:21004"
    )
    sys.modules["fastchat.serve.model_worker"].worker = worker
    MakeFastAPIOffline(app)
    uvicorn.run(app, port=21004)