Live2DフィーちゃんとChatGPTを組み合わせるまで（と必要な技術について）

import openai
openai.api_key = "APIキー"
model_engine = "gpt-3.5-turbo"

input = "入力"
prompt = [{"role": "user", "content": input}]
completion = openai.ChatCompletion.create(model=model_engine,
                                              messages=prompt)

message = completion.choices[0].message.content.replace("\n", "")

import win32com.client

cevio = win32com.client.Dispatch(
    "CeVIO.Talk.RemoteService2.ServiceControl2")
cevio.StartHost(False)
talker = win32com.client.Dispatch(
    "CeVIO.Talk.RemoteService2.Talker2V40")
talker.Cast = "フィーちゃん"
talker.components.At(1).Value = 90  # ふつう
talker.components.At(4).Value = 10  # 落ち着き
temppath = 'Temp/'
hash = hashlib.md5(message.encode()).hexdigest()
path = hash + ".wav"
state = talker.OutputWaveToFile(message, temppath + path)
analyzed = emotion_analyzer.analyze(message)

from mlask import MLAsk

emotion_analyzer = MLAsk()
emotion = emotion_analyzer.analyze(message)

{
    'message': "こんにちは！私はAIチャットボットです。何かお困りのことがあればお気軽にお聞きください。",
    'path': "90d4553dbbc093e7b10420ef06cb04d2.wav",
    'emotion': "iya"
}

from fastapi import FastAPI
from fastapi.responses import FileResponse
from starlette.middleware.cors import CORSMiddleware

# GPTへの入力から感情分析、音声合成までの関数を
# chatgpt_emotion_buildin.gpt_to_voiceemotion(input)としている。
import chatgpt_emotion_buildin


app = FastAPI()

# Access-Control-Allow-Originを返す
app.add_middleware(CORSMiddleware,
                   allow_origins=["*"],
                   allow_credentials=True,
                   allow_methods=["*"],
                   allow_headers=["*"])


@app.get("/chat/{input}")
def gpt_to_voiceemotion(input: str):
    print("input: " + input)
    return chatgpt_emotion_buildin.gpt_to_voiceemotion(input)


@app.get("/voice/{path}")
def ret_voice(path: str):
    print("audio_output: " + path)
    return FileResponse("Temp/" + path)

{
	"Type": "Live2D Expression",
	"Parameters": [
		{
			"Id": "ParamEyeROpen",
			"Value": -1,
			"Blend": "Add"
	},
      {
			"Id": "ParamEyeLOpen",
			"Value": -1,
			"Blend": "Add"
	},
      {
			"Id": "ParamCheek",
			"Value": 1,
			"Blend": "Add"
	}
	]
}

export class LAppLive2DManager {
    const expressionArray = [['yorokobi', 'Happy'], ['ikari', 'Rage'], ['aware', 'Tear'], ['kowagari', 'Blue'], 
                             ['haji', 'Exclamation2'], ['suki', 'Happy'], ['iya', 'Tear'], ['takaburi', 'Eye1'], 
                             ['yasuragi', 'Happy'], ['odoroki', 'Exclamation']];
    const expressionMap = new Map(expressionArray);
    public async changeEmotion(){
        let input = (<HTMLInputElement>document.getElementById('input_form')).value;
        let expression = '';
        let res = await fetch("http://127.0.0.1:8001/chat/" + input,{mode:'cors'})
            .then((response) => response.json())
            .then(function(data) {
                return data;
                });
        (<HTMLInputElement>document.getElementById('output_form')).textContent = res['message'];
        expression = expressionMap.get(res['emotion']);
        path = res['path'];
        this._model.startVoice("http://127.0.0.1:8001/voice/" + path);
        this._model.setExpression(expression);
        }
}

export class LAppModel extends CubismUserModel {
    public update(): void {
        let value = 0.0;
        this._wavFileHandler.update(deltaTimeSeconds);
        value = this._wavFileHandler.getRms();
        value = value * 10;
        this._model.addParameterValueById(this._lipSyncId, value, 0.8);
    }

    public startVoice(path : string): void {
        const voice = new Audio(path);
        voice.play();
        this._wavFileHandler.start(path);
    }
}

let res = await fetch("http://127.0.0.1:8001/chat/" + input,{mode:'cors'})
    .then((response) => response.json())
    .then(function(data) {
        return data;
        });