import openai
import os
import time
import requests
from langchain import OpenAI
from langchain.chains import ConversationChain
from langchain.memory import ConversationSummaryBufferMemory
from langchain.chat_models import ChatOpenAI
from transformers import pipeline


openai.api_key = os.environ["OPENAI_API_KEY"]
did_api_key = os.environ.get('DID_API_KEY')

memory = ConversationSummaryBufferMemory(
    llm=ChatOpenAI(),
    max_token_limit=2048
)

conversation = ConversationChain(
    llm=OpenAI(max_tokens=2048, temperature=0.5),
    memory=memory,
)

avatar_url = "https://cdn.discordapp.com/attachments/1065596492796153856/1095617463112187984/John_Carmack_Potrait_668a7a8d-1bb0-427d-8655-d32517f6583d.png"


# 请求D-ID创建一段小视频
def generate_talk(input, avatar_url, voice_type="microsoft", voice_id="zh-CN-YunyeNeural", api_key=did_api_key):
    url = "https://api.d-id.com/talks"
    payload = {
        "script": {
            "type": "text",
            "provider": {
                "type": voice_type,
                "voice_id": voice_id
            },
            "ssml": "false",
            "input": input
        },
        "config": {
            "fluent": "false",
            "pad_audio": "0.0"
        },
        "source_url": avatar_url
    }
    headers = {
        "accept": "application/json",
        "content-type": "application/json",
        "authorization": "Basic " + api_key
    }

    response = requests.post(url, json=payload, headers=headers)
    return response.json()


# 获取生成的 Talk 视频
def get_a_talk(id, api_key=did_api_key):
    url = "https://api.d-id.com/talks/" + id
    headers = {
        "accept": "application/json",
        "authorization": "Basic "+api_key
    }
    response = requests.get(url, headers=headers)
    return response.json()


# 播放视频
def get_mp4_video(input, avatar_url=avatar_url):
    response = generate_talk(input=input, avatar_url=avatar_url)
    talk = get_a_talk(response['id'])
    video_url = ""
    index = 0
    while index < 30:
        index += 1
        if 'result_url' in talk:
            video_url = talk['result_url']
            return video_url
        else:
            time.sleep(1)
            talk = get_a_talk(response['id'])
    return video_url


# 获取gpt res，发给did获取视频
def predict(input, history=[]):
    if input is not None:
        history.append(input)
        response = conversation.predict(input=input)

        video_url = get_mp4_video(input=response, avatar_url=avatar_url)
        video_html = f"""<video width="320" height="240" controls autoplay><source src="{video_url}" type="video/mp4"></video>"""

        history.append(response)
        # ['用户输入1', '聊天机器人回复1', ...] ==> [('用户输入1', '聊天机器人回复1'), ...]
        responses = [(u, b) for u, b in zip(history[::2], history[1::2])]
        return responses, video_html, history
    else:
        video_html = f'<img src="{avatar_url}" width="320" height="240" alt="John Carmack">'
        responses = [(u, b) for u, b in zip(history[::2], history[1::2])]
        return responses, video_html, history


# 通过openai whisper 语音识别
def transcribe(audio):
    os.rename(audio, audio + '.wav')
    audio_file = open(audio + '.wav', "rb")
    transcript = openai.Audio.transcribe(
        "whisper-1", audio_file, prompt="这是一段简体中文的问题。")
    return transcript['text']


# 通过openai whisper 语音识别
# def transcribe(audio):
#     os.rename(audio, audio + '.wav')
#     audio_file = open(audio + '.wav', "rb")
#     transcriber = pipeline(model="openai/whisper-medium", device=0)
#     result = transcriber(audio_file)
#     return result['text']


def process_audio(audio, history=[]):
    if audio is not None:
        text = transcribe(audio)
        return predict(text, history)
    else:
        text = None
        return predict(text, history)