# Copyright 2021 Zilliz. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import os
from typing import List
from packaging.version import Version
import openai
from towhee.operator.base import PyOperator


class OpenaiChat(PyOperator):
    '''Wrapper of OpenAI Chat API'''
    def __init__(self,
                 model_name: str = 'gpt-3.5-turbo',
                 api_key: str = None,
                 **kwargs
                 ):
        openai.api_key = api_key or os.getenv('OPENAI_API_KEY')
        self._openai_version = openai.__version__
        if Version(self._openai_version) >= Version('1.0.0'):
            from openai import OpenAI
            self.client = OpenAI(api_key=openai.api_key)
            self.openai_completion = self.client.chat.completions
        else:
            self.openai_completion = openai.ChatCompletion

        self._model = model_name
        self.stream = kwargs.pop('stream') if 'stream' in kwargs else False
        self.kwargs = kwargs

    def __call__(self, messages: List[dict]):
        messages = self.parse_inputs(messages)
        response = self.openai_completion.create(
                model=self._model,
                messages=messages,
                n=1,
                stream=self.stream,
                **self.kwargs
            )
        if Version(self._openai_version) >= Version('1.0.0'):
            if self.stream:
                response = (res.dict() for res in response)
            else:
                response = response.dict()
        if self.stream:
            return self.stream_output(response)
        else:
            answer = response['choices'][0]['message']['content']
            return answer

    def parse_inputs(self, messages: List[dict]):
        assert isinstance(messages, list), \
            'Inputs must be a list of dictionaries with keys from ["system", "question", "answer"].'
        new_messages = []
        for m in messages:
            if ('role' and 'content' in m) and (m['role'] in ['system', 'assistant', 'user']):
                new_messages.append(m)
            else:
                for k, v in m.items():
                    if k == 'question':
                        new_m = {'role': 'user', 'content': v}
                    elif k == 'answer':
                        new_m = {'role': 'assistant', 'content': v}
                    elif k == 'system':
                        new_m = {'role': 'system', 'content': v}
                    else:
                        raise KeyError('Invalid message key: only accept key value from ["system", "question", "answer"].')
                    new_messages.append(new_m)
        return new_messages
    
    def stream_output(self, response):
        for resp in response:
            yield resp['choices'][0]['delta']

    @staticmethod
    def supported_model_names():
        model_list = [
            'gpt-3.5-turbo',
            'gpt-3.5-turbo-0301'
        ]
        model_list.sort()
        return model_list